From c0e6fbf8c380718102bd25fcb8d2e55f8f9480d1 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 8 May 2024 09:14:50 +0300 Subject: [PATCH 01/64] metal : fix unused warning --- ggml-metal.metal | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ggml-metal.metal b/ggml-metal.metal index 3d4276ae02b9e..46c7d503930a4 100644 --- a/ggml-metal.metal +++ b/ggml-metal.metal @@ -2175,7 +2175,7 @@ kernel void kernel_flash_attn_ext_f16( const short D4 = D/4; const short D8 = D/8; - const short Q8 = Q/8; + //const short Q8 = Q/8; const short NW = N_SIMDWIDTH; const short SH = (C + Q); // shared memory per simdgroup in (half) From 3855416027cb25d9a708ffa5581cf503a87856a6 Mon Sep 17 00:00:00 2001 From: Justine Tunney Date: Wed, 8 May 2024 02:30:09 -0400 Subject: [PATCH 02/64] ggml : introduce bfloat16 support (#6412) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Introduce bfloat16 support Many models on Hugging Face (e.g. Mistral, TinyLLaMA) use bfloat16 as their canonical floating point format. ┌sign │ │ ┌exponent │ │ │ │ ┌mantissa │ │ │ │┌──┴───┐┌─┴───┐ 0b0000000000000000 brain16 This encoding has the same number of exponent bits as float32. That makes conversion relatively straightforward, even in the absence of hardware support. For example, converting brain16 to binary32 means simply shifting 16 bits to the left. ┌sign │ │ ┌exponent │ │ │ │ ┌mantissa │ │ │ │┌──┴───┐┌─┴───────────────────┐ 0b00000000000000000000000000000000 IEEE binary32 The issue is that converting bf16 to fp16 can result in information loss. Only 13% of bf16 numbers can be precisely represented in fp16 which in practice ends up being 99.71% of Mistral 7b v0.2's weights however there is currently no way other than fp32 to get the others ┌sign │ │ ┌exponent │ │ │ │ ┌mantissa │ │ │ │┌─┴─┐┌─┴──────┐ 0b0000000000000000 IEEE binary16 This change fixes that, by adding a bf16 data type to GGML. Support for CPU inference has been implemented along with optimizations for the AVX2, AVX512, and AVX512BF16 ISAs. Perplexity on Mistral 7b 0.2 improves somewhere around -0.0024 to -0.0046 compared to using fp16 * Remove GGML code that's not needed * Minimize the GGML API surface area for BF16 * Remove bf16 luts * Make the GGML header look nicer * Fix documentation * Apply ggerganov's fixes for test-backend-ops * Add BF16 code for new ggml_validate_row_data() function --- examples/finetune/finetune.cpp | 2 +- examples/quantize/quantize.cpp | 3 +- ggml-impl.h | 77 +++ ggml-metal.m | 2 +- ggml-quants.c | 18 + ggml.c | 1177 +++++++++++++++++++++++++++++--- ggml.h | 22 +- gguf-py/gguf/constants.py | 2 + llama.cpp | 20 +- llama.h | 1 + tests/test-backend-ops.cpp | 6 +- 11 files changed, 1228 insertions(+), 102 deletions(-) diff --git a/examples/finetune/finetune.cpp b/examples/finetune/finetune.cpp index 3da5317b3d910..22743b1bf02fd 100644 --- a/examples/finetune/finetune.cpp +++ b/examples/finetune/finetune.cpp @@ -575,7 +575,7 @@ static struct ggml_tensor * llama_build_lora_finetune_graphs( GGML_ASSERT(tokens_input->type == GGML_TYPE_I32); auto add_to_f32 = [] (struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b) { - if (ggml_is_quantized(a->type) || a->type == GGML_TYPE_F16) { + if (ggml_is_quantized(a->type) || a->type == GGML_TYPE_F16 || a->type == GGML_TYPE_BF16) { return ggml_add_cast(ctx, a, b, GGML_TYPE_F32); } else if (a->type == GGML_TYPE_F32) { return ggml_add(ctx, a, b); diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 432cc2b4feadf..909eab283ee6e 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -46,7 +46,8 @@ static const std::vector QUANT_OPTIONS = { { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 4.45G, +0.0122 ppl @ LLaMA-v1-7B", }, { "Q6_K", LLAMA_FTYPE_MOSTLY_Q6_K, " 5.15G, +0.0008 ppl @ LLaMA-v1-7B", }, { "Q8_0", LLAMA_FTYPE_MOSTLY_Q8_0, " 6.70G, +0.0004 ppl @ LLaMA-v1-7B", }, - { "F16", LLAMA_FTYPE_MOSTLY_F16, "13.00G @ 7B", }, + { "F16", LLAMA_FTYPE_MOSTLY_F16, "14.00G, -0.0020 ppl @ Mistral-7B", }, + { "BF16", LLAMA_FTYPE_MOSTLY_BF16, "14.00G, -0.0050 ppl @ Mistral-7B", }, { "F32", LLAMA_FTYPE_ALL_F32, "26.00G @ 7B", }, // Note: Ensure COPY comes after F32 to avoid ftype 0 from matching. { "COPY", LLAMA_FTYPE_ALL_F32, "only copy tensors, no quantizing", }, diff --git a/ggml-impl.h b/ggml-impl.h index 94a1cc66854f4..d85b152bf16ea 100644 --- a/ggml-impl.h +++ b/ggml-impl.h @@ -17,6 +17,83 @@ #define MIN(a, b) ((a) < (b) ? (a) : (b)) #define MAX(a, b) ((a) > (b) ? (a) : (b)) +/** + * Converts brain16 to float32. + * + * The bfloat16 floating point format has the following structure: + * + * ┌sign + * │ + * │ ┌exponent + * │ │ + * │ │ ┌mantissa + * │ │ │ + * │┌──┴───┐┌─┴───┐ + * 0b0000000000000000 brain16 + * + * Since bf16 has the same number of exponent bits as a 32bit float, + * encoding and decoding numbers becomes relatively straightforward. + * + * ┌sign + * │ + * │ ┌exponent + * │ │ + * │ │ ┌mantissa + * │ │ │ + * │┌──┴───┐┌─┴───────────────────┐ + * 0b00000000000000000000000000000000 IEEE binary32 + * + * For comparison, the standard fp16 format has fewer exponent bits. + * + * ┌sign + * │ + * │ ┌exponent + * │ │ + * │ │ ┌mantissa + * │ │ │ + * │┌─┴─┐┌─┴──────┐ + * 0b0000000000000000 IEEE binary16 + * + * @see IEEE 754-2008 + */ +static inline float ggml_compute_bf16_to_fp32(ggml_bf16_t h) { + union { + float f; + uint32_t i; + } u; + u.i = (uint32_t)h.bits << 16; + return u.f; +} + +/** + * Converts float32 to brain16. + * + * This function is binary identical to AMD Zen4 VCVTNEPS2BF16. + * Subnormals shall be flushed to zero, and NANs will be quiet. + * This code should vectorize nicely if using modern compilers. + */ +static inline ggml_bf16_t ggml_compute_fp32_to_bf16(float s) { + ggml_bf16_t h; + union { + float f; + uint32_t i; + } u; + u.f = s; + if ((u.i & 0x7fffffff) > 0x7f800000) { /* nan */ + h.bits = (u.i >> 16) | 64; /* force to quiet */ + return h; + } + if (!(u.i & 0x7f800000)) { /* subnormal */ + h.bits = (u.i & 0x80000000) >> 16; /* flush to zero */ + return h; + } + h.bits = (u.i + (0x7fff + ((u.i >> 16) & 1))) >> 16; + return h; +} + +#define GGML_FP32_TO_BF16(x) ggml_compute_fp32_to_bf16(x) +#define GGML_BF16_TO_FP32(x) ggml_compute_bf16_to_fp32(x) + #ifdef __cplusplus extern "C" { #endif diff --git a/ggml-metal.m b/ggml-metal.m index 017b72ce94383..78cac5041d360 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -803,7 +803,7 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const case GGML_OP_DIAG_MASK_INF: case GGML_OP_GET_ROWS: { - return op->ne[3] == 1; + return op->src[0]->type != GGML_TYPE_BF16 && op->ne[3] == 1; } default: return false; diff --git a/ggml-quants.c b/ggml-quants.c index 444d1e55ebd54..9883b6f8cabbb 100644 --- a/ggml-quants.c +++ b/ggml-quants.c @@ -12450,6 +12450,24 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte const size_t nb = nbytes/ggml_type_size(type); switch (type) { + case GGML_TYPE_BF16: + { + int nans = 0; + int infs = 0; + const unsigned short * f = (const unsigned short *) data; + for (size_t i = 0; i < nb; ++i) { + nans += (f[i] & 0x7fff) > 0x7f80; + infs += (f[i] & 0x7fff) == 0x7f80; + } + if (nans) { + fprintf(stderr, "%s: found %d NaNs in row of %zu BF16 values\n", __func__, nans, nb); + return false; + } + if (infs) { + fprintf(stderr, "%s: found %d infinities in row of %zu BF16 values\n", __func__, infs, nb); + return false; + } + } break; case GGML_TYPE_F16: { const ggml_fp16_t * f = (const ggml_fp16_t *) data; diff --git a/ggml.c b/ggml.c index 82179a1257f30..093d38d00ae35 100644 --- a/ggml.c +++ b/ggml.c @@ -322,7 +322,7 @@ static ggml_fp16_t ggml_table_exp_f16[1 << 16]; // precomputed f32 table for f16 (256 KB) (ggml-impl.h) float ggml_table_f32_f16[1 << 16]; -const char * ggml_status_to_string(enum ggml_status status) { +GGML_CALL const char * ggml_status_to_string(enum ggml_status status) { switch (status) { case GGML_STATUS_ALLOC_FAILED: return "GGML status: error (failed to allocate memory)"; case GGML_STATUS_FAILED: return "GGML status: error (operation failed)"; @@ -333,16 +333,26 @@ const char * ggml_status_to_string(enum ggml_status status) { return "GGML status: unknown"; } -// note: do not use these inside ggml.c -// these are meant to be used via the ggml.h API float ggml_fp16_to_fp32(ggml_fp16_t x) { +#define ggml_fp16_to_fp32 do_not_use__ggml_fp16_to_fp32__in_ggml return GGML_FP16_TO_FP32(x); } ggml_fp16_t ggml_fp32_to_fp16(float x) { +#define ggml_fp32_to_fp16 do_not_use__ggml_fp32_to_fp16__in_ggml return GGML_FP32_TO_FP16(x); } +float ggml_bf16_to_fp32(ggml_bf16_t x) { +#define ggml_bf16_to_fp32 do_not_use__ggml_bf16_to_fp32__in_ggml + return GGML_BF16_TO_FP32(x); // it just left shifts +} + +ggml_bf16_t ggml_fp32_to_bf16(float x) { +#define ggml_fp32_to_bf16 do_not_use__ggml_fp32_to_bf16__in_ggml + return GGML_FP32_TO_BF16(x); +} + void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int64_t n) { for (int64_t i = 0; i < n; i++) { y[i] = GGML_FP16_TO_FP32(x[i]); @@ -368,6 +378,49 @@ void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int64_t n) { } } +void ggml_bf16_to_fp32_row(const ggml_bf16_t * x, float * y, int64_t n) { + int64_t i = 0; +#if defined(__AVX512F__) + for (; i + 16 <= n; i += 16) { + _mm512_storeu_ps(y + i, + _mm512_castsi512_ps( + _mm512_slli_epi32( + _mm512_cvtepu16_epi32( + _mm256_loadu_si256( + (const __m256i *)(x + i))), + 16))); + } +#elif defined(__AVX2__) + for (; i + 8 <= n; i += 8) { + _mm256_storeu_ps(y + i, + _mm256_castsi256_ps( + _mm256_slli_epi32( + _mm256_cvtepu16_epi32( + _mm_loadu_si128( + (const __m128i *)(x + i))), + 16))); + } +#endif + for (; i < n; i++) { + y[i] = GGML_BF16_TO_FP32(x[i]); + } +} + +void ggml_fp32_to_bf16_row(const float * x, ggml_bf16_t * y, int64_t n) { + int i = 0; +#if defined(__AVX512BF16__) + for (; i + 32 <= n; i += 32) { + _mm512_storeu_ps( + (__m512 *)(y + i), + (__m512)_mm512_cvtne2ps_pbh(_mm512_loadu_ps(x + i + 16), + _mm512_loadu_ps(x + i))); + } +#endif + for (; i < n; i++) { + y[i] = GGML_FP32_TO_BF16(x[i]); + } +} + bool ggml_guid_matches(ggml_guid_t guid_a, ggml_guid_t guid_b) { return memcmp(guid_a, guid_b, sizeof(ggml_guid)) == 0; } @@ -503,6 +556,7 @@ static const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float); static void ggml_vec_dot_f32(int n, float * restrict s, size_t bs, const float * restrict x, size_t bx, const float * restrict y, size_t by, int nrc); static void ggml_vec_dot_f16(int n, float * restrict s, size_t bs, ggml_fp16_t * restrict x, size_t bx, ggml_fp16_t * restrict y, size_t by, int nrc); +static void ggml_vec_dot_bf16(int n, float * restrict s, size_t bs, ggml_bf16_t * restrict x, size_t bx, ggml_bf16_t * restrict y, size_t by, int nrc); static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = { [GGML_TYPE_I8] = { @@ -845,6 +899,18 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = { .type_size = sizeof(block_q8_K), .is_quantized = true, .from_float = quantize_row_q8_K, + }, + [GGML_TYPE_BF16] = { + .type_name = "bf16", + .blck_size = 1, + .type_size = sizeof(ggml_bf16_t), + .is_quantized = false, + .to_float = (ggml_to_float_t) ggml_bf16_to_fp32_row, + .from_float = (ggml_from_float_t) ggml_fp32_to_bf16_row, + .from_float_reference = (ggml_from_float_t) ggml_fp32_to_bf16_row, + .vec_dot = (ggml_vec_dot_t) ggml_vec_dot_bf16, + .vec_dot_type = GGML_TYPE_BF16, + .nrows = 1, } }; @@ -1480,6 +1546,8 @@ inline static void ggml_vec_set_i32(const int n, int32_t * x, const int32_t v) { inline static void ggml_vec_set_f16(const int n, ggml_fp16_t * x, const int32_t v) { for (int i = 0; i < n; ++i) x[i] = v; } +inline static void ggml_vec_set_bf16(const int n, ggml_bf16_t * x, const ggml_bf16_t v) { for (int i = 0; i < n; ++i) x[i] = v; } + inline static void ggml_vec_add_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] + y[i]; } inline static void ggml_vec_add1_f32(const int n, float * z, const float * x, const float v) { for (int i = 0; i < n; ++i) z[i] = x[i] + v; } inline static void ggml_vec_acc_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] += x[i]; } @@ -1498,7 +1566,7 @@ static void ggml_vec_dot_f32(int n, float * restrict s, size_t bs, const float * UNUSED(by); UNUSED(bs); -#ifdef GGML_SIMD +#if defined(GGML_SIMD) float sumf = 0.0f; const int np = (n & ~(GGML_F32_STEP - 1)); @@ -1534,6 +1602,70 @@ static void ggml_vec_dot_f32(int n, float * restrict s, size_t bs, const float * *s = sumf; } +static void ggml_vec_dot_bf16(int n, float * restrict s, size_t bs, ggml_bf16_t * restrict x, size_t bx, ggml_bf16_t * restrict y, size_t by, int nrc) { + assert(nrc == 1); + UNUSED(nrc); + UNUSED(bx); + UNUSED(by); + UNUSED(bs); + int i = 0; + ggml_float sumf = 0; + +#if defined(__AVX512BF16__) + __m512 c1 = _mm512_setzero_ps(); + __m512 c2 = _mm512_setzero_ps(); + for (; i + 64 <= n; i += 64) { + c1 = _mm512_dpbf16_ps(c1, (__m512bh)_mm512_loadu_ps((const float *)(x + i)), + (__m512bh)_mm512_loadu_ps((const float *)(y + i))); + c2 = _mm512_dpbf16_ps(c2, (__m512bh)_mm512_loadu_ps((const float *)(x + i + 32)), + (__m512bh)_mm512_loadu_ps((const float *)(y + i + 32))); + } + sumf += (ggml_float)_mm512_reduce_add_ps(c1); + sumf += (ggml_float)_mm512_reduce_add_ps(c2); + +#elif defined(__AVX512F__) +#define LOAD(p) _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)(p))), 16)) + __m512 c1 = _mm512_setzero_ps(); + __m512 c2 = _mm512_setzero_ps(); + for (; i + 32 <= n; i += 32) { + c1 = _mm512_add_ps(_mm512_mul_ps(LOAD(x + i), LOAD(y + i)), c1); + c2 = _mm512_add_ps(_mm512_mul_ps(LOAD(x + i + 16), LOAD(y + i + 16)), c2); + } + sumf += (ggml_float)_mm512_reduce_add_ps(c1); + sumf += (ggml_float)_mm512_reduce_add_ps(c2); + +#undef LOAD +#elif defined(__AVX2__) +#define LOAD(p) _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)(p))), 16)) + __m256 c1 = _mm256_setzero_ps(); + __m256 c2 = _mm256_setzero_ps(); + __m256 c3 = _mm256_setzero_ps(); + __m256 c4 = _mm256_setzero_ps(); + for (; i + 32 <= n; i += 32) { + c1 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i), LOAD(y + i)), c1); + c2 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 8), LOAD(y + i + 8)), c2); + c3 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 16), LOAD(y + i + 16)), c3); + c4 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 24), LOAD(y + i + 24)), c4); + } + __m128 g; + c1 = _mm256_add_ps(_mm256_add_ps(c1, c3), + _mm256_add_ps(c2, c4)); + g = _mm_add_ps(_mm256_extractf128_ps(c1, 1), + _mm256_castps256_ps128(c1)); + g = _mm_add_ps(g, _mm_movehl_ps(g, g)); + g = _mm_add_ss(g, _mm_movehdup_ps(g)); + sumf += (ggml_float)_mm_cvtss_f32(g); + +#undef LOAD +#endif + + for (; i < n; ++i) { + sumf += (ggml_float)(GGML_BF16_TO_FP32(x[i]) * + GGML_BF16_TO_FP32(y[i])); + } + *s = sumf; +} + static void ggml_vec_dot_f16(int n, float * restrict s, size_t bs, ggml_fp16_t * restrict x, size_t bx, ggml_fp16_t * restrict y, size_t by, int nrc) { assert(nrc == 1); UNUSED(nrc); @@ -1967,6 +2099,14 @@ inline static void ggml_vec_sum_f16_ggf(const int n, float * s, const ggml_fp16_ *s = sum; } +inline static void ggml_vec_sum_bf16_ggf(const int n, float * s, const ggml_bf16_t * x) { + float sum = 0.0f; + for (int i = 0; i < n; ++i) { + sum += GGML_BF16_TO_FP32(x[i]); + } + *s = sum; +} + inline static void ggml_vec_max_f32(const int n, float * s, const float * x) { #ifndef GGML_USE_ACCELERATE float max = -INFINITY; @@ -2377,7 +2517,7 @@ void ggml_numa_init(enum ggml_numa_strategy numa_flag) { // figure out which node we're on uint current_cpu; int getcpu_ret = 0; -#if __GLIBC__ > 2 || (__GLIBC__ == 2 && __GLIBC_MINOR__ > 28) +#if __GLIBC__ > 2 || (__GLIBC__ == 2 && __GLIBC_MINOR__ > 28) || defined(__COSMOPOLITAN__) getcpu_ret = getcpu(¤t_cpu, &g_state.numa.current_node); #else // old glibc doesn't have a wrapper for this call. Fall back on direct syscall @@ -2588,6 +2728,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { switch (ftype) { case GGML_FTYPE_ALL_F32: wtype = GGML_TYPE_F32; break; case GGML_FTYPE_MOSTLY_F16: wtype = GGML_TYPE_F16; break; + case GGML_FTYPE_MOSTLY_BF16: wtype = GGML_TYPE_BF16; break; case GGML_FTYPE_MOSTLY_Q4_0: wtype = GGML_TYPE_Q4_0; break; case GGML_FTYPE_MOSTLY_Q4_1: wtype = GGML_TYPE_Q4_1; break; case GGML_FTYPE_MOSTLY_Q5_0: wtype = GGML_TYPE_Q5_0; break; @@ -2729,15 +2870,16 @@ struct ggml_context * ggml_init(struct ggml_init_params params) { { const uint64_t t_start = ggml_time_us(); UNUSED(t_start); - ggml_fp16_t ii; for (int i = 0; i < (1 << 16); ++i) { - uint16_t ui = i; - memcpy(&ii, &ui, sizeof(ii)); - const float f = ggml_table_f32_f16[i] = GGML_COMPUTE_FP16_TO_FP32(ii); + union { + uint16_t u16; + ggml_fp16_t fp16; + } u = {i}; + float f = ggml_table_f32_f16[i] = GGML_COMPUTE_FP16_TO_FP32(u.fp16); ggml_table_gelu_f16[i] = GGML_FP32_TO_FP16(ggml_gelu_f32(f)); ggml_table_gelu_quick_f16[i] = GGML_FP32_TO_FP16(ggml_gelu_quick_f32(f)); ggml_table_silu_f16[i] = GGML_FP32_TO_FP16(ggml_silu_f32(f)); - ggml_table_exp_f16[i] = GGML_FP32_TO_FP16(expf(f)); + ggml_table_exp_f16[i] = GGML_FP32_TO_FP16(expf(f)); } const uint64_t t_end = ggml_time_us(); UNUSED(t_end); @@ -3201,6 +3343,13 @@ struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value) { ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_FP32_TO_FP16(value)); } } break; + case GGML_TYPE_BF16: + { + assert(tensor->nb[0] == sizeof(ggml_fp16_t)); + for (int i = 0; i < n; i++) { + ggml_vec_set_bf16(nc, (ggml_bf16_t *)(data + i*n1), GGML_FP32_TO_BF16(value)); + } + } break; case GGML_TYPE_F32: { assert(tensor->nb[0] == sizeof(float)); @@ -3253,6 +3402,13 @@ struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value) { ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_FP32_TO_FP16(value)); } } break; + case GGML_TYPE_BF16: + { + assert(tensor->nb[0] == sizeof(ggml_bf16_t)); + for (int i = 0; i < n; i++) { + ggml_vec_set_bf16(nc, (ggml_bf16_t *)(data + i*n1), GGML_FP32_TO_BF16(value)); + } + } break; case GGML_TYPE_F32: { assert(tensor->nb[0] == sizeof(float)); @@ -3320,6 +3476,11 @@ int32_t ggml_get_i32_1d(const struct ggml_tensor * tensor, int i) { GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t)); return GGML_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]); } + case GGML_TYPE_BF16: + { + GGML_ASSERT(tensor->nb[0] == sizeof(ggml_bf16_t)); + return GGML_BF16_TO_FP32(((ggml_bf16_t *)(tensor->data))[i]); + } case GGML_TYPE_F32: { GGML_ASSERT(tensor->nb[0] == sizeof(float)); @@ -3362,6 +3523,11 @@ void ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value) { GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t)); ((ggml_fp16_t *)(tensor->data))[i] = GGML_FP32_TO_FP16(value); } break; + case GGML_TYPE_BF16: + { + GGML_ASSERT(tensor->nb[0] == sizeof(ggml_bf16_t)); + ((ggml_bf16_t *)(tensor->data))[i] = GGML_FP32_TO_BF16(value); + } break; case GGML_TYPE_F32: { GGML_ASSERT(tensor->nb[0] == sizeof(float)); @@ -3385,6 +3551,8 @@ int32_t ggml_get_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i return ((int32_t *) data)[0]; case GGML_TYPE_F16: return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]); + case GGML_TYPE_BF16: + return GGML_BF16_TO_FP32(((ggml_bf16_t *) data)[0]); case GGML_TYPE_F32: return ((float *) data)[0]; default: @@ -3413,6 +3581,10 @@ void ggml_set_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, { ((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value); } break; + case GGML_TYPE_BF16: + { + ((ggml_bf16_t *)(data))[0] = GGML_FP32_TO_BF16(value); + } break; case GGML_TYPE_F32: { ((float *)(data))[0] = value; @@ -3451,6 +3623,11 @@ float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i) { GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t)); return GGML_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]); } + case GGML_TYPE_BF16: + { + GGML_ASSERT(tensor->nb[0] == sizeof(ggml_bf16_t)); + return GGML_BF16_TO_FP32(((ggml_bf16_t *)(tensor->data))[i]); + } case GGML_TYPE_F32: { GGML_ASSERT(tensor->nb[0] == sizeof(float)); @@ -3493,6 +3670,11 @@ void ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value) { GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t)); ((ggml_fp16_t *)(tensor->data))[i] = GGML_FP32_TO_FP16(value); } break; + case GGML_TYPE_BF16: + { + GGML_ASSERT(tensor->nb[0] == sizeof(ggml_bf16_t)); + ((ggml_bf16_t *)(tensor->data))[i] = GGML_FP32_TO_BF16(value); + } break; case GGML_TYPE_F32: { GGML_ASSERT(tensor->nb[0] == sizeof(float)); @@ -3516,6 +3698,8 @@ float ggml_get_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, return ((int32_t *) data)[0]; case GGML_TYPE_F16: return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]); + case GGML_TYPE_BF16: + return GGML_BF16_TO_FP32(((ggml_bf16_t *) data)[0]); case GGML_TYPE_F32: return ((float *) data)[0]; default: @@ -3544,6 +3728,10 @@ void ggml_set_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, { ((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value); } break; + case GGML_TYPE_BF16: + { + ((ggml_bf16_t *)(data))[0] = GGML_FP32_TO_BF16(value); + } break; case GGML_TYPE_F32: { ((float *)(data))[0] = value; @@ -3738,7 +3926,11 @@ static struct ggml_tensor * ggml_add_cast_impl( // TODO: support less-strict constraint // GGML_ASSERT(ggml_can_repeat(b, a)); GGML_ASSERT(ggml_can_repeat_rows(b, a)); - GGML_ASSERT(ggml_is_quantized(a->type) || a->type == GGML_TYPE_F16); // currently only supported for quantized input and f16 + + // currently only supported for quantized input and f16 + GGML_ASSERT(ggml_is_quantized(a->type) || + a->type == GGML_TYPE_F16 || + a->type == GGML_TYPE_BF16); bool is_node = false; @@ -7215,8 +7407,8 @@ static void ggml_compute_forward_dup_same_cont( ((char *) src0->data + ie0*nb00), (ie1 - ie0) * ggml_type_size(src0->type)); } - } + static void ggml_compute_forward_dup_f16( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -7490,7 +7682,7 @@ static void ggml_compute_forward_dup_f16( } } -static void ggml_compute_forward_dup_f32( +static void ggml_compute_forward_dup_bf16( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -7538,10 +7730,11 @@ static void ggml_compute_forward_dup_f32( return; } + // TODO: add more special-case implementations for tensor shapes/strides that can benefit from memcpy + if (ggml_is_contiguous(dst)) { - // TODO: simplify - if (nb00 == sizeof(float)) { - if (dst->type == GGML_TYPE_F32) { + if (nb00 == sizeof(ggml_bf16_t)) { + if (dst->type == GGML_TYPE_BF16) { size_t id = 0; const size_t rs = ne00 * nb00; char * dst_ptr = (char *) dst->data; @@ -7557,8 +7750,43 @@ static void ggml_compute_forward_dup_f32( id += rs * (ne01 - ir1); } } + } else if (dst->type == GGML_TYPE_F16) { + size_t id = 0; + ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); + for (int i00 = 0; i00 < ne00; i00++) { + dst_ptr[id] = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(src0_ptr[i00])); + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } + } else if (dst->type == GGML_TYPE_F32) { + size_t id = 0; + float * dst_ptr = (float *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); + for (int i00 = 0; i00 < ne00; i00++) { + dst_ptr[id] = GGML_BF16_TO_FP32(src0_ptr[i00]); + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } } else if (type_traits[dst->type].from_float) { ggml_from_float_t const quantize_row_q = type_traits[dst->type].from_float; + float * src0_f32 = (float *) params->wdata + (ne00 + CACHE_LINE_SIZE_F32) * ith; size_t id = 0; size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); @@ -7568,8 +7796,13 @@ static void ggml_compute_forward_dup_f32( for (int i02 = 0; i02 < ne02; i02++) { id += rs * ir0; for (int i01 = ir0; i01 < ir1; i01++) { - const float * src0_ptr = (float *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); - quantize_row_q(src0_ptr, dst_ptr + id, ne00); + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); + + for (int i00 = 0; i00 < ne00; i00++) { + src0_f32[i00] = GGML_BF16_TO_FP32(src0_ptr[i00]); + } + + quantize_row_q(src0_f32, dst_ptr + id, ne00); id += rs; } id += rs * (ne01 - ir1); @@ -7590,7 +7823,25 @@ static void ggml_compute_forward_dup_f32( id += ne00 * ir0; for (int i01 = ir0; i01 < ir1; i01++) { for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + + dst_ptr[id] = GGML_BF16_TO_FP32(*src0_ptr); + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } + } else if (dst->type == GGML_TYPE_BF16) { + size_t id = 0; + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + for (int i00 = 0; i00 < ne00; i00++) { + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); dst_ptr[id] = *src0_ptr; id++; @@ -7608,9 +7859,9 @@ static void ggml_compute_forward_dup_f32( id += ne00 * ir0; for (int i01 = ir0; i01 < ir1; i01++) { for (int i00 = 0; i00 < ne00; i00++) { - const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); - dst_ptr[id] = GGML_FP32_TO_FP16(*src0_ptr); + dst_ptr[id] = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(*src0_ptr)); id++; } } @@ -7621,18 +7872,16 @@ static void ggml_compute_forward_dup_f32( GGML_ASSERT(false); // TODO: implement } } - return; } // dst counters - int64_t i10 = 0; int64_t i11 = 0; int64_t i12 = 0; int64_t i13 = 0; - if (dst->type == GGML_TYPE_F32) { + if (dst->type == GGML_TYPE_BF16) { for (int64_t i03 = 0; i03 < ne03; i03++) { for (int64_t i02 = 0; i02 < ne02; i02++) { i10 += ne00 * ir0; @@ -7653,7 +7902,59 @@ static void ggml_compute_forward_dup_f32( const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - memcpy(dst_ptr, src0_ptr, sizeof(float)); + memcpy(dst_ptr, src0_ptr, sizeof(ggml_bf16_t)); + + if (++i10 == ne00) { + i10 = 0; + if (++i11 == ne01) { + i11 = 0; + if (++i12 == ne02) { + i12 = 0; + if (++i13 == ne03) { + i13 = 0; + } + } + } + } + } + } + i10 += ne00 * (ne01 - ir1); + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + } else if (dst->type == GGML_TYPE_F16) { + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + i10 += ne00 * ir0; + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + for (int64_t i01 = ir0; i01 < ir1; i01++) { + for (int64_t i00 = 0; i00 < ne00; i00++) { + const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); + + *(ggml_fp16_t *) dst_ptr = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr)); if (++i10 == ne0) { i10 = 0; @@ -7684,7 +7985,7 @@ static void ggml_compute_forward_dup_f32( } } } - } else if (dst->type == GGML_TYPE_F16) { + } else if (dst->type == GGML_TYPE_F32) { for (int64_t i03 = 0; i03 < ne03; i03++) { for (int64_t i02 = 0; i02 < ne02; i02++) { i10 += ne00 * ir0; @@ -7705,7 +8006,7 @@ static void ggml_compute_forward_dup_f32( const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); - *(ggml_fp16_t *) dst_ptr = GGML_FP32_TO_FP16(*(const float *) src0_ptr); + *(float *) dst_ptr = GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr); if (++i10 == ne0) { i10 = 0; @@ -7741,31 +8042,27 @@ static void ggml_compute_forward_dup_f32( } } -// A simplified version of ggml_compute_forward_dup that doesn't do float upcasting, and just plain old memcpy. -static void ggml_compute_forward_dup_bytes( +static void ggml_compute_forward_dup_f32( const struct ggml_compute_params * params, struct ggml_tensor * dst) { const struct ggml_tensor * src0 = dst->src[0]; GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); - GGML_ASSERT(src0->type == dst->type); if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { return; } - if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst)) { - ggml_compute_forward_dup_same_cont(params, dst); - return; - } - - GGML_TENSOR_UNARY_OP_LOCALS; + GGML_TENSOR_UNARY_OP_LOCALS - const size_t type_size = ggml_type_size(src0->type); const int ith = params->ith; // thread index const int nth = params->nth; // number of threads + if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst) && src0->type == dst->type) { + ggml_compute_forward_dup_same_cont(params, dst); + return; + } // parallelize by rows const int nr = ne01; @@ -7777,9 +8074,9 @@ static void ggml_compute_forward_dup_bytes( if (src0->type == dst->type && ne00 == ne0 && - nb00 == type_size && nb0 == type_size) { + nb00 == ggml_type_size(src0->type) && nb0 == ggml_type_size(dst->type)) { // copy by rows - const size_t rs = ne00 * type_size; + const size_t rs = ne00*nb00; for (int64_t i03 = 0; i03 < ne03; i03++) { for (int64_t i02 = 0; i02 < ne02; i02++) { for (int64_t i01 = ir0; i01 < ir1; i01++) { @@ -7794,41 +8091,366 @@ static void ggml_compute_forward_dup_bytes( } if (ggml_is_contiguous(dst)) { - size_t id = 0; - char * dst_ptr = (char *) dst->data; - const size_t rs = ne00 * type_size; - - if (nb00 == type_size) { - // src0 is contigous on first dimension, copy by rows - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int64_t i01 = ir0; i01 < ir1; i01++) { - const char * src0_ptr = (char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03; - memcpy(dst_ptr + id, src0_ptr, rs); - id += rs; - } - id += rs * (ne01 - ir1); - } - } - } else { - //printf("%s: this is not optimal - fix me\n", __func__); - - for (int64_t i03 = 0; i03 < ne03; i03++) { - for (int64_t i02 = 0; i02 < ne02; i02++) { - id += rs * ir0; - for (int64_t i01 = ir0; i01 < ir1; i01++) { - for (int64_t i00 = 0; i00 < ne00; i00++) { - const char * src0_ptr = (char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03; - memcpy(dst_ptr + id, src0_ptr, type_size); + // TODO: simplify + if (nb00 == sizeof(float)) { + if (dst->type == GGML_TYPE_F32) { + size_t id = 0; + const size_t rs = ne00 * nb00; + char * dst_ptr = (char *) dst->data; - id += type_size; + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += rs * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + const char * src0_ptr = (char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03; + memcpy(dst_ptr + id, src0_ptr, rs); + id += rs; } + id += rs * (ne01 - ir1); } - id += rs * (ne01 - ir1); } - } - } + } else if (type_traits[dst->type].from_float) { + ggml_from_float_t const quantize_row_q = type_traits[dst->type].from_float; + + size_t id = 0; + size_t rs = nb0 * (ne00 / ggml_blck_size(dst->type)); + char * dst_ptr = (char *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += rs * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + const float * src0_ptr = (float *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03); + quantize_row_q(src0_ptr, dst_ptr + id, ne00); + id += rs; + } + id += rs * (ne01 - ir1); + } + } + } else { + GGML_ASSERT(false); // TODO: implement + } + } else { + //printf("%s: this is not optimal - fix me\n", __func__); + + if (dst->type == GGML_TYPE_F32) { + size_t id = 0; + float * dst_ptr = (float *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + for (int i00 = 0; i00 < ne00; i00++) { + const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + + dst_ptr[id] = *src0_ptr; + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } + } else if (dst->type == GGML_TYPE_F16) { + size_t id = 0; + ggml_fp16_t * dst_ptr = (ggml_fp16_t *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + for (int i00 = 0; i00 < ne00; i00++) { + const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + + dst_ptr[id] = GGML_FP32_TO_FP16(*src0_ptr); + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } + } else if (dst->type == GGML_TYPE_BF16) { + size_t id = 0; + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) dst->data; + + for (int i03 = 0; i03 < ne03; i03++) { + for (int i02 = 0; i02 < ne02; i02++) { + id += ne00 * ir0; + for (int i01 = ir0; i01 < ir1; i01++) { + for (int i00 = 0; i00 < ne00; i00++) { + const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + + dst_ptr[id] = GGML_FP32_TO_BF16(*src0_ptr); + id++; + } + } + id += ne00 * (ne01 - ir1); + } + } + } else { + GGML_ASSERT(false); // TODO: implement + } + } + + return; + } + + // dst counters + + int64_t i10 = 0; + int64_t i11 = 0; + int64_t i12 = 0; + int64_t i13 = 0; + + if (dst->type == GGML_TYPE_F32) { + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + i10 += ne00 * ir0; + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + for (int64_t i01 = ir0; i01 < ir1; i01++) { + for (int64_t i00 = 0; i00 < ne00; i00++) { + const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); + + memcpy(dst_ptr, src0_ptr, sizeof(float)); + + if (++i10 == ne0) { + i10 = 0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + i10 += ne00 * (ne01 - ir1); + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + } else if (dst->type == GGML_TYPE_F16) { + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + i10 += ne00 * ir0; + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + for (int64_t i01 = ir0; i01 < ir1; i01++) { + for (int64_t i00 = 0; i00 < ne00; i00++) { + const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); + + *(ggml_fp16_t *) dst_ptr = GGML_FP32_TO_FP16(*(const float *) src0_ptr); + + if (++i10 == ne0) { + i10 = 0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + i10 += ne00 * (ne01 - ir1); + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + } else if (dst->type == GGML_TYPE_BF16) { + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + i10 += ne00 * ir0; + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + for (int64_t i01 = ir0; i01 < ir1; i01++) { + for (int64_t i00 = 0; i00 < ne00; i00++) { + const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03); + char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3); + + *(ggml_bf16_t *) dst_ptr = GGML_FP32_TO_BF16(*(const float *) src0_ptr); + + if (++i10 == ne0) { + i10 = 0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + i10 += ne00 * (ne01 - ir1); + while (i10 >= ne0) { + i10 -= ne0; + if (++i11 == ne1) { + i11 = 0; + if (++i12 == ne2) { + i12 = 0; + if (++i13 == ne3) { + i13 = 0; + } + } + } + } + } + } + } else { + GGML_ASSERT(false); // TODO: implement + } +} + +// A simplified version of ggml_compute_forward_dup that doesn't do float upcasting, and just plain old memcpy. +static void ggml_compute_forward_dup_bytes( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + + GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0)); + GGML_ASSERT(src0->type == dst->type); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst)) { + ggml_compute_forward_dup_same_cont(params, dst); + return; + } + + GGML_TENSOR_UNARY_OP_LOCALS; + + const size_t type_size = ggml_type_size(src0->type); + const int ith = params->ith; // thread index + const int nth = params->nth; // number of threads + + + // parallelize by rows + const int nr = ne01; + // number of rows per thread + const int dr = (nr + nth - 1) / nth; + // row range for this thread + const int ir0 = dr * ith; + const int ir1 = MIN(ir0 + dr, nr); + + if (src0->type == dst->type && + ne00 == ne0 && + nb00 == type_size && nb0 == type_size) { + // copy by rows + const size_t rs = ne00 * type_size; + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + for (int64_t i01 = ir0; i01 < ir1; i01++) { + memcpy( + ((char *) dst->data + i01*nb1 + i02*nb2 + i03*nb3), + ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03), + rs); + } + } + } + return; + } + + if (ggml_is_contiguous(dst)) { + size_t id = 0; + char * dst_ptr = (char *) dst->data; + const size_t rs = ne00 * type_size; + + if (nb00 == type_size) { + // src0 is contigous on first dimension, copy by rows + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + id += rs * ir0; + for (int64_t i01 = ir0; i01 < ir1; i01++) { + const char * src0_ptr = (char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03; + memcpy(dst_ptr + id, src0_ptr, rs); + id += rs; + } + id += rs * (ne01 - ir1); + } + } + } else { + //printf("%s: this is not optimal - fix me\n", __func__); + + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + id += rs * ir0; + for (int64_t i01 = ir0; i01 < ir1; i01++) { + for (int64_t i00 = 0; i00 < ne00; i00++) { + const char * src0_ptr = (char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03; + memcpy(dst_ptr + id, src0_ptr, type_size); + + id += type_size; + } + } + id += rs * (ne01 - ir1); + } + } + } return; } @@ -7909,6 +8531,10 @@ static void ggml_compute_forward_dup( { ggml_compute_forward_dup_f16(params, dst); } break; + case GGML_TYPE_BF16: + { + ggml_compute_forward_dup_bf16(params, dst); + } break; case GGML_TYPE_F32: { ggml_compute_forward_dup_f32(params, dst); @@ -8002,17 +8628,96 @@ static void ggml_compute_forward_add_f32( float * dst_ptr = (float *) ((char *) dst->data + i03*nb3 + i02*nb2 + i01*nb1 ); float * src0_ptr = (float *) ((char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01); - for (int64_t i0 = 0; i0 < ne0; ++i0) { - const int64_t i10 = i0 % ne10; - float * src1_ptr = (float *) ((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + i10*nb10); + for (int64_t i0 = 0; i0 < ne0; ++i0) { + const int64_t i10 = i0 % ne10; + float * src1_ptr = (float *) ((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + i10*nb10); + + dst_ptr[i0] = src0_ptr[i0] + *src1_ptr; + } + } + } +} + +static void ggml_compute_forward_add_f16_f32( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + + GGML_ASSERT(ggml_are_same_shape(src0, src1) && ggml_are_same_shape(src0, dst)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + const int ith = params->ith; + const int nth = params->nth; + + const int nr = ggml_nrows(src0); + + GGML_TENSOR_BINARY_OP_LOCALS + + GGML_ASSERT(src0->type == GGML_TYPE_F16); + GGML_ASSERT(src1->type == GGML_TYPE_F32); + + if (dst->type == GGML_TYPE_F32) { + GGML_ASSERT( nb0 == sizeof(float)); + } + else { + GGML_ASSERT(dst->type == GGML_TYPE_F16); + GGML_ASSERT( nb0 == sizeof(ggml_fp16_t)); + } + + GGML_ASSERT(nb00 == sizeof(ggml_fp16_t)); + + // rows per thread + const int dr = (nr + nth - 1)/nth; + + // row range for this thread + const int ir0 = dr*ith; + const int ir1 = MIN(ir0 + dr, nr); + + if (nb10 == sizeof(float)) { + if (dst->type == GGML_TYPE_F16) { + for (int ir = ir0; ir < ir1; ++ir) { + // src0, src1 and dst are same shape => same indices + const int i3 = ir/(ne2*ne1); + const int i2 = (ir - i3*ne2*ne1)/ne1; + const int i1 = (ir - i3*ne2*ne1 - i2*ne1); + + ggml_fp16_t * dst_ptr = (ggml_fp16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); + ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + float * src1_ptr = (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11); + + for (int i = 0; i < ne0; i++) { + dst_ptr[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(src0_ptr[i]) + src1_ptr[i]); + } + } + } else { + for (int ir = ir0; ir < ir1; ++ir) { + // src0, src1 and dst are same shape => same indices + const int i3 = ir/(ne2*ne1); + const int i2 = (ir - i3*ne2*ne1)/ne1; + const int i1 = (ir - i3*ne2*ne1 - i2*ne1); + + float * dst_ptr = (float *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); + ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + float * src1_ptr = (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11); - dst_ptr[i0] = src0_ptr[i0] + *src1_ptr; + for (int i = 0; i < ne0; i++) { + dst_ptr[i] = GGML_FP16_TO_FP32(src0_ptr[i]) + src1_ptr[i]; + } } } } + else { + // src1 is not contiguous + GGML_ASSERT(false); + } } -static void ggml_compute_forward_add_f16_f32( +static void ggml_compute_forward_add_bf16_f32( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -8032,18 +8737,18 @@ static void ggml_compute_forward_add_f16_f32( GGML_TENSOR_BINARY_OP_LOCALS - GGML_ASSERT(src0->type == GGML_TYPE_F16); + GGML_ASSERT(src0->type == GGML_TYPE_BF16); GGML_ASSERT(src1->type == GGML_TYPE_F32); if (dst->type == GGML_TYPE_F32) { GGML_ASSERT( nb0 == sizeof(float)); } else { - GGML_ASSERT(dst->type == GGML_TYPE_F16); - GGML_ASSERT( nb0 == sizeof(ggml_fp16_t)); + GGML_ASSERT(dst->type == GGML_TYPE_BF16); + GGML_ASSERT( nb0 == sizeof(ggml_bf16_t)); } - GGML_ASSERT(nb00 == sizeof(ggml_fp16_t)); + GGML_ASSERT(nb00 == sizeof(ggml_bf16_t)); // rows per thread const int dr = (nr + nth - 1)/nth; @@ -8053,19 +8758,19 @@ static void ggml_compute_forward_add_f16_f32( const int ir1 = MIN(ir0 + dr, nr); if (nb10 == sizeof(float)) { - if (dst->type == GGML_TYPE_F16) { + if (dst->type == GGML_TYPE_BF16) { for (int ir = ir0; ir < ir1; ++ir) { // src0, src1 and dst are same shape => same indices const int i3 = ir/(ne2*ne1); const int i2 = (ir - i3*ne2*ne1)/ne1; const int i1 = (ir - i3*ne2*ne1 - i2*ne1); - ggml_fp16_t * dst_ptr = (ggml_fp16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); - ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); + ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); float * src1_ptr = (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11); for (int i = 0; i < ne0; i++) { - dst_ptr[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(src0_ptr[i]) + src1_ptr[i]); + dst_ptr[i] = GGML_FP32_TO_BF16(GGML_BF16_TO_FP32(src0_ptr[i]) + src1_ptr[i]); } } } else { @@ -8076,11 +8781,11 @@ static void ggml_compute_forward_add_f16_f32( const int i1 = (ir - i3*ne2*ne1 - i2*ne1); float * dst_ptr = (float *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); - ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); float * src1_ptr = (float *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11); for (int i = 0; i < ne0; i++) { - dst_ptr[i] = GGML_FP16_TO_FP32(src0_ptr[i]) + src1_ptr[i]; + dst_ptr[i] = GGML_BF16_TO_FP32(src0_ptr[i]) + src1_ptr[i]; } } } @@ -8147,6 +8852,62 @@ static void ggml_compute_forward_add_f16_f16( } } +static void ggml_compute_forward_add_bf16_bf16( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + + GGML_ASSERT(ggml_are_same_shape(src0, src1) && ggml_are_same_shape(src0, dst)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + const int ith = params->ith; + const int nth = params->nth; + + const int nr = ggml_nrows(src0); + + GGML_TENSOR_BINARY_OP_LOCALS + + GGML_ASSERT(src0->type == GGML_TYPE_BF16); + GGML_ASSERT(src1->type == GGML_TYPE_BF16); + GGML_ASSERT(dst->type == GGML_TYPE_BF16); + + GGML_ASSERT( nb0 == sizeof(ggml_bf16_t)); + GGML_ASSERT(nb00 == sizeof(ggml_bf16_t)); + + // rows per thread + const int dr = (nr + nth - 1)/nth; + + // row range for this thread + const int ir0 = dr*ith; + const int ir1 = MIN(ir0 + dr, nr); + + if (nb10 == sizeof(ggml_bf16_t)) { + for (int ir = ir0; ir < ir1; ++ir) { + // src0, src1 and dst are same shape => same indices + const int i3 = ir/(ne2*ne1); + const int i2 = (ir - i3*ne2*ne1)/ne1; + const int i1 = (ir - i3*ne2*ne1 - i2*ne1); + + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1); + ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + ggml_bf16_t * src1_ptr = (ggml_bf16_t *) ((char *) src1->data + i3*nb13 + i2*nb12 + i1*nb11); + + for (int i = 0; i < ne0; i++) { + dst_ptr[i] = GGML_FP32_TO_BF16(GGML_BF16_TO_FP32(src0_ptr[i]) + GGML_BF16_TO_FP32(src1_ptr[i])); + } + } + } + else { + // src1 is not contiguous + GGML_ASSERT(false); + } +} + static void ggml_compute_forward_add_q_f32( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -8256,6 +9017,18 @@ static void ggml_compute_forward_add( GGML_ASSERT(false); } } break; + case GGML_TYPE_BF16: + { + if (src1->type == GGML_TYPE_BF16) { + ggml_compute_forward_add_bf16_bf16(params, dst); + } + else if (src1->type == GGML_TYPE_F32) { + ggml_compute_forward_add_bf16_f32(params, dst); + } + else { + GGML_ASSERT(false); + } + } break; case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -8514,6 +9287,110 @@ static void ggml_compute_forward_add1_q_f32( } } +static void ggml_compute_forward_add1_bf16_f32( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + + GGML_ASSERT(ggml_are_same_shape(src0, dst)); + GGML_ASSERT(ggml_is_scalar(src1)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + // scalar to add + const float v = *(float *) src1->data; + + const int ith = params->ith; + const int nth = params->nth; + + const int nr = ggml_nrows(src0); + + GGML_TENSOR_UNARY_OP_LOCALS + + GGML_ASSERT(src0->type == GGML_TYPE_BF16); + GGML_ASSERT(src1->type == GGML_TYPE_F32); + GGML_ASSERT(dst->type == GGML_TYPE_BF16); + + GGML_ASSERT( nb0 == sizeof(ggml_bf16_t)); + GGML_ASSERT(nb00 == sizeof(ggml_bf16_t)); + + // rows per thread + const int dr = (nr + nth - 1)/nth; + + // row range for this thread + const int ir0 = dr*ith; + const int ir1 = MIN(ir0 + dr, nr); + + for (int ir = ir0; ir < ir1; ++ir) { + // src0 and dst are same shape => same indices + const int i3 = ir/(ne2*ne1); + const int i2 = (ir - i3*ne2*ne1)/ne1; + const int i1 = (ir - i3*ne2*ne1 - i2*ne1); + + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 ); + ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + for (int i = 0; i < ne0; i++) { + dst_ptr[i] = GGML_FP32_TO_BF16(GGML_BF16_TO_FP32(src0_ptr[i]) + v); + } + } +} + +static void ggml_compute_forward_add1_bf16_bf16( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + + GGML_ASSERT(ggml_are_same_shape(src0, dst)); + GGML_ASSERT(ggml_is_scalar(src1)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + // scalar to add + const float v = GGML_BF16_TO_FP32(*(ggml_bf16_t *) src1->data); + + const int ith = params->ith; + const int nth = params->nth; + + const int nr = ggml_nrows(src0); + + GGML_TENSOR_UNARY_OP_LOCALS + + GGML_ASSERT(src0->type == GGML_TYPE_BF16); + GGML_ASSERT(src1->type == GGML_TYPE_BF16); + GGML_ASSERT(dst->type == GGML_TYPE_BF16); + + GGML_ASSERT( nb0 == sizeof(ggml_bf16_t)); + GGML_ASSERT(nb00 == sizeof(ggml_bf16_t)); + + // rows per thread + const int dr = (nr + nth - 1)/nth; + + // row range for this thread + const int ir0 = dr*ith; + const int ir1 = MIN(ir0 + dr, nr); + + for (int ir = ir0; ir < ir1; ++ir) { + // src0 and dst are same shape => same indices + const int i3 = ir/(ne2*ne1); + const int i2 = (ir - i3*ne2*ne1)/ne1; + const int i1 = (ir - i3*ne2*ne1 - i2*ne1); + + ggml_bf16_t * dst_ptr = (ggml_bf16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 ); + ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01); + for (int i = 0; i < ne0; i++) { + dst_ptr[i] = GGML_FP32_TO_BF16(GGML_BF16_TO_FP32(src0_ptr[i]) + v); + } + } +} + static void ggml_compute_forward_add1( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -8538,6 +9415,18 @@ static void ggml_compute_forward_add1( GGML_ASSERT(false); } } break; + case GGML_TYPE_BF16: + { + if (src1->type == GGML_TYPE_BF16) { + ggml_compute_forward_add1_bf16_bf16(params, dst); + } + else if (src1->type == GGML_TYPE_F32) { + ggml_compute_forward_add1_bf16_f32(params, dst); + } + else { + GGML_ASSERT(false); + } + } break; case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -8666,6 +9555,7 @@ static void ggml_compute_forward_acc( ggml_compute_forward_acc_f32(params, dst); } break; case GGML_TYPE_F16: + case GGML_TYPE_BF16: case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -9187,6 +10077,40 @@ static void ggml_compute_forward_sum_f16( ((ggml_fp16_t *) dst->data)[0] = GGML_FP32_TO_FP16(sum); } +static void ggml_compute_forward_sum_bf16( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + + assert(params->ith == 0); + assert(ggml_is_scalar(dst)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + assert(src0->nb[0] == sizeof(ggml_bf16_t)); + + GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne) + GGML_TENSOR_LOCALS(size_t, nb0, src0, nb) + + float sum = 0; + float row_sum = 0; + + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + for (int64_t i01 = 0; i01 < ne01; i01++) { + ggml_vec_sum_bf16_ggf(ne00, + &row_sum, + (ggml_bf16_t *) ((char *) src0->data + i01 * nb01 + i02 * nb02 + i03 * nb03)); + sum += row_sum; + } + } + } + ((ggml_bf16_t *) dst->data)[0] = GGML_FP32_TO_BF16(sum); +} + static void ggml_compute_forward_sum( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -9202,6 +10126,10 @@ static void ggml_compute_forward_sum( { ggml_compute_forward_sum_f16(params, dst); } break; + case GGML_TYPE_BF16: + { + ggml_compute_forward_sum_bf16(params, dst); + } break; default: { GGML_ASSERT(false); @@ -9476,6 +10404,7 @@ static void ggml_compute_forward_repeat( switch (src0->type) { case GGML_TYPE_F16: + case GGML_TYPE_BF16: case GGML_TYPE_I16: { ggml_compute_forward_repeat_f16(params, dst); @@ -11793,6 +12722,7 @@ static void ggml_compute_forward_set( ggml_compute_forward_set_f32(params, dst); } break; case GGML_TYPE_F16: + case GGML_TYPE_BF16: case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -11967,6 +12897,49 @@ static void ggml_compute_forward_get_rows_f16( } } +static void ggml_compute_forward_get_rows_bf16( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + GGML_TENSOR_BINARY_OP_LOCALS + + const int64_t nc = ne00; + const int64_t nr = ggml_nelements(src1); + + assert(ne0 == nc); + assert(ne02 == ne11); + assert(nb00 == sizeof(ggml_bf16_t)); + assert(ggml_nrows(dst) == nr); + + const int ith = params->ith; + const int nth = params->nth; + + // rows per thread + const int dr = (nr + nth - 1)/nth; + + // row range for this thread + const int ir0 = dr*ith; + const int ir1 = MIN(ir0 + dr, nr); + + for (int64_t i = ir0; i < ir1; ++i) { + const int64_t i12 = i/(ne11*ne10); + const int64_t i11 = (i - i12*ne11*ne10)/ne10; + const int64_t i10 = (i - i12*ne11*ne10 - i11*ne10); + const int64_t i01 = *(int32_t *) ((char *) src1->data + i10*nb10 + i11*nb11 + i12*nb12); + + ggml_bf16_to_fp32_row( + (const void *) ((char *) src0->data + i01*nb01 + i11*nb02 + i12*nb03), + (float *) ((char *) dst->data + i10*nb1 + i11*nb2 + i12*nb3), nc); + } +} + static void ggml_compute_forward_get_rows_f32( const struct ggml_compute_params * params, struct ggml_tensor * dst) { @@ -12044,6 +13017,10 @@ static void ggml_compute_forward_get_rows( { ggml_compute_forward_get_rows_f16(params, dst); } break; + case GGML_TYPE_BF16: + { + ggml_compute_forward_get_rows_bf16(params, dst); + } break; case GGML_TYPE_F32: case GGML_TYPE_I32: { @@ -12739,6 +13716,7 @@ static void ggml_compute_forward_alibi( { ggml_compute_forward_alibi_f32(params, dst); } break; + case GGML_TYPE_BF16: case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -12828,6 +13806,7 @@ static void ggml_compute_forward_clamp( ggml_compute_forward_clamp_f32(params, dst); } break; case GGML_TYPE_F16: + case GGML_TYPE_BF16: case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: @@ -15921,6 +16900,7 @@ static void ggml_compute_forward_get_rel_pos( switch (src0->type) { case GGML_TYPE_F16: + case GGML_TYPE_BF16: { ggml_compute_forward_get_rel_pos_f16(params, dst); } break; @@ -18785,7 +19765,10 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa case GGML_OP_CPY: case GGML_OP_DUP: { - if (ggml_is_quantized(node->type)) { + if (ggml_is_quantized(node->type) || + // F16 -> BF16 and BF16 -> F16 copies go through intermediate F32 + (node->src[0]->type == GGML_TYPE_F16 && node->src[1] && node->src[1]->type == GGML_TYPE_BF16) || + (node->src[0]->type == GGML_TYPE_BF16 && node->src[1] && node->src[1]->type == GGML_TYPE_F16)) { cur = ggml_type_size(GGML_TYPE_F32) * node->ne[0] * n_tasks; } } break; @@ -18864,7 +19847,8 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa const int64_t ne10 = node->src[1]->ne[0]; // L const int64_t ne11 = node->src[1]->ne[1]; // Cin - if (node->src[0]->type == GGML_TYPE_F16 && + if ((node->src[0]->type == GGML_TYPE_F16 || + node->src[0]->type == GGML_TYPE_BF16) && node->src[1]->type == GGML_TYPE_F32) { cur += sizeof(ggml_fp16_t)*ne00*ne01*ne02; cur += sizeof(ggml_fp16_t)*ne10*ne11; @@ -18900,6 +19884,9 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa } else if (node->src[1]->type == GGML_TYPE_F16) { cur = sizeof(float)*ne11*n_tasks; // TODO: this can become (n_tasks-1) cur += sizeof(float)*ne11*n_tasks; // this is overestimated by x2 + } else if (node->src[1]->type == GGML_TYPE_BF16) { + cur = sizeof(float)*ne11*n_tasks; // TODO: this can become (n_tasks-1) + cur += sizeof(float)*ne11*n_tasks; // this is overestimated by x2 } } break; case GGML_OP_FLASH_ATTN_EXT: @@ -18916,6 +19903,9 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa } else if (node->src[1]->type == GGML_TYPE_F16) { cur = sizeof(float)*node->src[1]->ne[1]*n_tasks; // TODO: this can become (n_tasks-1) cur += sizeof(float)*node->src[1]->ne[1]*n_tasks; // this is overestimated by x2 + } else if (node->src[1]->type == GGML_TYPE_BF16) { + cur = sizeof(float)*node->src[1]->ne[1]*n_tasks; // TODO: this can become (n_tasks-1) + cur += sizeof(float)*node->src[1]->ne[1]*n_tasks; // this is overestimated by x2 } } break; case GGML_OP_FLASH_ATTN_BACK: @@ -18929,6 +19919,9 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa } else if (node->src[1]->type == GGML_TYPE_F16) { cur = sizeof(float)*mxDn*n_tasks; // TODO: this can become (n_tasks-1) cur += sizeof(float)*mxDn*n_tasks; // this is overestimated by x2 + } else if (node->src[1]->type == GGML_TYPE_BF16) { + cur = sizeof(float)*mxDn*n_tasks; // TODO: this can become (n_tasks-1) + cur += sizeof(float)*mxDn*n_tasks; // this is overestimated by x2 } } break; @@ -19705,7 +20698,9 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph if (node->type == GGML_TYPE_I8 || node->type == GGML_TYPE_I16 || node->type == GGML_TYPE_I32) { fprintf(fp, "%d", ggml_get_i32_1d(node, j)); } - else if (node->type == GGML_TYPE_F32 || node->type == GGML_TYPE_F16) { + else if (node->type == GGML_TYPE_F32 || + node->type == GGML_TYPE_F16 || + node->type == GGML_TYPE_BF16) { fprintf(fp, "%.1e", (double)ggml_get_f32_1d(node, j)); } else { @@ -20763,6 +21758,12 @@ size_t ggml_quantize_chunk( ggml_fp32_to_fp16_row(src + start, (ggml_fp16_t *)dst + start, n); result = n * elemsize; } break; + case GGML_TYPE_BF16: + { + size_t elemsize = sizeof(ggml_bf16_t); + ggml_fp32_to_bf16_row(src + start, (ggml_bf16_t *)dst + start, n); + result = n * elemsize; + } break; case GGML_TYPE_F32: { size_t elemsize = sizeof(float); diff --git a/ggml.h b/ggml.h index a11795973ca3f..fe60538220680 100644 --- a/ggml.h +++ b/ggml.h @@ -326,14 +326,20 @@ extern "C" { // get ggml_status name string GGML_API GGML_CALL const char * ggml_status_to_string(enum ggml_status status); + // ieee 754-2008 half-precision float16 + // todo: make this not an integral type typedef uint16_t ggml_fp16_t; - - // convert FP16 <-> FP32 - GGML_API float ggml_fp16_to_fp32(ggml_fp16_t x); - GGML_API ggml_fp16_t ggml_fp32_to_fp16(float x); - - GGML_API void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int64_t n); - GGML_API void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int64_t n); + GGML_API float ggml_fp16_to_fp32(ggml_fp16_t); + GGML_API ggml_fp16_t ggml_fp32_to_fp16(float); + GGML_API void ggml_fp16_to_fp32_row(const ggml_fp16_t *, float *, int64_t); + GGML_API void ggml_fp32_to_fp16_row(const float *, ggml_fp16_t *, int64_t); + + // google brain half-precision bfloat16 + typedef struct { uint16_t bits; } ggml_bf16_t; + GGML_API ggml_bf16_t ggml_fp32_to_bf16(float); + GGML_API float ggml_bf16_to_fp32(ggml_bf16_t); // consider just doing << 16 + GGML_API void ggml_bf16_to_fp32_row(const ggml_bf16_t *, float *, int64_t); + GGML_API void ggml_fp32_to_bf16_row(const float *, ggml_bf16_t *, int64_t); struct ggml_object; struct ggml_context; @@ -370,6 +376,7 @@ extern "C" { GGML_TYPE_I64 = 27, GGML_TYPE_F64 = 28, GGML_TYPE_IQ1_M = 29, + GGML_TYPE_BF16 = 30, GGML_TYPE_COUNT, }; @@ -410,6 +417,7 @@ extern "C" { GGML_FTYPE_MOSTLY_IQ2_S = 21, // except 1d tensors GGML_FTYPE_MOSTLY_IQ4_XS = 22, // except 1d tensors GGML_FTYPE_MOSTLY_IQ1_M = 23, // except 1d tensors + GGML_FTYPE_MOSTLY_BF16 = 24, // except 1d tensors }; // available tensor operations: diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 4f232e18d9691..6e968fc4e598f 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -817,6 +817,7 @@ class GGMLQuantizationType(IntEnum): I64 = 27 F64 = 28 IQ1_M = 29 + BF16 = 30 class GGUFEndian(IntEnum): @@ -888,6 +889,7 @@ def get_type(val: Any) -> GGUFValueType: GGMLQuantizationType.I64: (1, 8), GGMLQuantizationType.F64: (1, 8), GGMLQuantizationType.IQ1_M: (256, QK_K // 8 + QK_K // 16 + QK_K // 32), + GGMLQuantizationType.BF16: (1, 2), } diff --git a/llama.cpp b/llama.cpp index 07fde36195170..26e7a33918372 100644 --- a/llama.cpp +++ b/llama.cpp @@ -3175,6 +3175,7 @@ struct llama_model_loader { switch (type_max) { case GGML_TYPE_F32: ftype = LLAMA_FTYPE_ALL_F32; break; case GGML_TYPE_F16: ftype = LLAMA_FTYPE_MOSTLY_F16; break; + case GGML_TYPE_BF16: ftype = LLAMA_FTYPE_MOSTLY_BF16; break; case GGML_TYPE_Q4_0: ftype = LLAMA_FTYPE_MOSTLY_Q4_0; break; case GGML_TYPE_Q4_1: ftype = LLAMA_FTYPE_MOSTLY_Q4_1; break; case GGML_TYPE_Q5_0: ftype = LLAMA_FTYPE_MOSTLY_Q5_0; break; @@ -3666,6 +3667,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) { switch (ftype) { case LLAMA_FTYPE_ALL_F32: return "all F32"; case LLAMA_FTYPE_MOSTLY_F16: return "F16"; + case LLAMA_FTYPE_MOSTLY_BF16: return "BF16"; case LLAMA_FTYPE_MOSTLY_Q4_0: return "Q4_0"; case LLAMA_FTYPE_MOSTLY_Q4_1: return "Q4_1"; case LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16: @@ -6129,6 +6131,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam || !( model.ftype == LLAMA_FTYPE_ALL_F32 || model.ftype == LLAMA_FTYPE_MOSTLY_F16 || + model.ftype == LLAMA_FTYPE_MOSTLY_BF16 || model.ftype == LLAMA_FTYPE_MOSTLY_Q4_0 || model.ftype == LLAMA_FTYPE_MOSTLY_Q4_1 ) @@ -14158,13 +14161,16 @@ static void llama_tensor_dequantize_internal( if (qtype.to_float == NULL) { throw std::runtime_error(format("type %s unsupported for integer quantization: no dequantization available", ggml_type_name(tensor->type))); } - } else if (tensor->type != GGML_TYPE_F16) { + } else if (tensor->type != GGML_TYPE_F16 && + tensor->type != GGML_TYPE_BF16) { throw std::runtime_error(format("cannot dequantize/convert tensor type %s", ggml_type_name(tensor->type))); } if (nthread < 2) { if (tensor->type == GGML_TYPE_F16) { ggml_fp16_to_fp32_row((ggml_fp16_t *)tensor->data, f32_output, nelements); + } else if (tensor->type == GGML_TYPE_BF16) { + ggml_bf16_to_fp32_row((ggml_bf16_t *)tensor->data, f32_output, nelements); } else if (ggml_is_quantized(tensor->type)) { qtype.to_float(tensor->data, f32_output, nelements); } else { @@ -14173,7 +14179,14 @@ static void llama_tensor_dequantize_internal( return; } - size_t block_size = tensor->type == GGML_TYPE_F16 ? 1 : (size_t)ggml_blck_size(tensor->type); + size_t block_size; + if (tensor->type == GGML_TYPE_F16 || + tensor->type == GGML_TYPE_BF16) { + block_size = 1; + } else { + block_size = (size_t)ggml_blck_size(tensor->type); + } + size_t block_size_bytes = ggml_type_size(tensor->type); GGML_ASSERT(nelements % block_size == 0); @@ -14192,6 +14205,8 @@ static void llama_tensor_dequantize_internal( auto compute = [qtype] (ggml_type typ, uint8_t * inbuf, float * outbuf, int nels) { if (typ == GGML_TYPE_F16) { ggml_fp16_to_fp32_row((ggml_fp16_t *)inbuf, outbuf, nels); + } else if (typ == GGML_TYPE_BF16) { + ggml_bf16_to_fp32_row((ggml_bf16_t *)inbuf, outbuf, nels); } else { qtype.to_float(inbuf, outbuf, nels); } @@ -14552,6 +14567,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s case LLAMA_FTYPE_MOSTLY_Q5_1: default_type = GGML_TYPE_Q5_1; break; case LLAMA_FTYPE_MOSTLY_Q8_0: default_type = GGML_TYPE_Q8_0; break; case LLAMA_FTYPE_MOSTLY_F16: default_type = GGML_TYPE_F16; break; + case LLAMA_FTYPE_MOSTLY_BF16: default_type = GGML_TYPE_BF16; break; case LLAMA_FTYPE_ALL_F32: default_type = GGML_TYPE_F32; break; // K-quants diff --git a/llama.h b/llama.h index d7f4bf8ea90d2..5761cacf4d7f4 100644 --- a/llama.h +++ b/llama.h @@ -137,6 +137,7 @@ extern "C" { LLAMA_FTYPE_MOSTLY_IQ2_M = 29, // except 1d tensors LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors LLAMA_FTYPE_MOSTLY_IQ1_M = 31, // except 1d tensors + LLAMA_FTYPE_MOSTLY_BF16 = 32, // except 1d tensors LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file }; diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index b27c1291e4088..41718e00172bf 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -50,7 +50,7 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m if (tensor->type == GGML_TYPE_F32 || tensor->type == GGML_TYPE_I32) { ggml_backend_tensor_set(tensor, data.data(), 0, size * sizeof(float)); - } else if (ggml_is_quantized(tensor->type) || tensor->type == GGML_TYPE_F16) { + } else if (ggml_is_quantized(tensor->type) || tensor->type == GGML_TYPE_F16 || tensor->type == GGML_TYPE_BF16) { GGML_ASSERT(size % ggml_blck_size(tensor->type) == 0); std::vector dataq(ggml_row_size(tensor->type, size)); std::vector imatrix(tensor->ne[0], 1.0f); // dummy importance matrix @@ -92,6 +92,8 @@ static std::vector tensor_to_float(const ggml_tensor * t) { size_t i = i3*t->nb[3] + i2*t->nb[2] + i1*t->nb[1] + i0/bs*t->nb[0]; if (t->type == GGML_TYPE_F16) { tv.push_back(ggml_fp16_to_fp32(*(ggml_fp16_t*)&buf[i])); + } else if (t->type == GGML_TYPE_BF16) { + tv.push_back(ggml_bf16_to_fp32(*(ggml_bf16_t*)&buf[i])); } else if (t->type == GGML_TYPE_F32) { tv.push_back(*(float *) &buf[i]); } else if (t->type == GGML_TYPE_I32) { @@ -1898,7 +1900,7 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op std::default_random_engine rng(0); const ggml_type all_types[] = { - GGML_TYPE_F32, GGML_TYPE_F16, + GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_Q4_0, GGML_TYPE_Q4_1, GGML_TYPE_Q5_0, GGML_TYPE_Q5_1, GGML_TYPE_Q8_0, From acdce3cdef6fc2f0b7b5623231fd7762c0884d1c Mon Sep 17 00:00:00 2001 From: Brian Date: Wed, 8 May 2024 18:54:39 +1000 Subject: [PATCH 03/64] compare-llama-bench.py: add missing basicConfig (#7138) * compare-llama-bench.py: add missing basicConfig * compare-llama-bench.py: Add line break between error message and print_help() * Add regular print() markdown table --- scripts/compare-llama-bench.py | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/scripts/compare-llama-bench.py b/scripts/compare-llama-bench.py index 3892fd25cf3bf..fed3c1ee3d298 100755 --- a/scripts/compare-llama-bench.py +++ b/scripts/compare-llama-bench.py @@ -93,11 +93,14 @@ "specified values are averaged WITHOUT weighing by the --repetitions parameter of llama-bench." ) parser.add_argument("-s", "--show", help=help_s) +parser.add_argument("--verbose", action="store_true", help="increase output verbosity") known_args, unknown_args = parser.parse_known_args() +logging.basicConfig(level=logging.DEBUG if known_args.verbose else logging.INFO) + if unknown_args: - logger.error(f"Received unknown args: {unknown_args}.") + logger.error(f"Received unknown args: {unknown_args}.\n") parser.print_help() sys.exit(1) @@ -110,7 +113,7 @@ input_file = sqlite_files[0] if input_file is None: - logger.error("Cannot find a suitable input file, please provide one.") + logger.error("Cannot find a suitable input file, please provide one.\n") parser.print_help() sys.exit(1) @@ -202,12 +205,12 @@ def get_commit_hexsha8(name): hexsha8_baseline = find_parent_in_data(repo.heads.master.commit) if hexsha8_baseline is None: - logger.error("No baseline was provided and did not find data for any master branch commits.") + logger.error("No baseline was provided and did not find data for any master branch commits.\n") parser.print_help() sys.exit(1) else: logger.error("No baseline was provided and the current working directory " - "is not part of a git repository from which a baseline could be inferred.") + "is not part of a git repository from which a baseline could be inferred.\n") parser.print_help() sys.exit(1) @@ -238,7 +241,7 @@ def get_commit_hexsha8(name): break if hexsha8_compare is None: - logger.error("No compare target was provided and did not find data for any non-master commits.") + logger.error("No compare target was provided and did not find data for any non-master commits.\n") parser.print_help() sys.exit(1) else: @@ -361,7 +364,7 @@ def get_rows(properties): headers = [PRETTY_NAMES[p] for p in show] headers += ["Test", f"t/s {name_baseline}", f"t/s {name_compare}", "Speedup"] -logger.info(tabulate( +print(tabulate( # noqa: NP100 table, headers=headers, floatfmt=".2f", From 7e0b6a7b3ba94ff624dc27c1e0e735fded8819b8 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Wed, 8 May 2024 12:47:07 +0300 Subject: [PATCH 04/64] py : also print the normalizers --- convert-hf-to-gguf-update.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index ae901e24c9a17..a3fe67ee7de9c 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -151,6 +151,8 @@ def download_file_with_auth(url, token, save_path): # print the "pre_tokenizer" content from the tokenizer.json with open(f"models/tokenizers/{name}/tokenizer.json", "r", encoding="utf-8") as f: cfg = json.load(f) + normalizer = cfg["normalizer"] + logger.info("normalizer: " + json.dumps(normalizer, indent=4)) pre_tokenizer = cfg["pre_tokenizer"] logger.info("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4)) From 4cd621c26de2095cd7c4464bdec5fe2e696ef3f3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?DAN=E2=84=A2?= Date: Wed, 8 May 2024 06:43:23 -0400 Subject: [PATCH 05/64] convert : add BPE pre-tokenization for DBRX (#7132) * Add BPE pre-tokenization for DBRX. * Add vocab GGUFs. * Remove test. * Remove GGUFs. --- convert-hf-to-gguf-update.py | 1 + convert-hf-to-gguf.py | 3 +++ llama.cpp | 4 ++++ llama.h | 1 + 4 files changed, 9 insertions(+) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index a3fe67ee7de9c..b51010983ab46 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -68,6 +68,7 @@ class TOKENIZER_TYPE(IntEnum): {"name": "refact", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/smallcloudai/Refact-1_6-base", }, {"name": "command-r", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/CohereForAI/c4ai-command-r-v01", }, {"name": "olmo", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", }, + {"name": "dbrx", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", }, ] # make directory "models/tokenizers" if it doesn't exist diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index f65d9320e9a1b..8b89575d5a2fc 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -317,6 +317,9 @@ def get_vocab_base_pre(self, tokenizer) -> str: if chkhsh == "b6dc8df998e1cfbdc4eac8243701a65afe638679230920b50d6f17d81c098166": # ref: https://huggingface.co/allenai/OLMo-1.7-7B-hf res = "olmo" + if chkhsh == "a8594e3edff7c29c003940395316294b2c623e09894deebbc65f33f1515df79e": + # ref: https://huggingface.co/databricks/dbrx-instruct + res = "dbrx" if res is None: logger.warning("\n") diff --git a/llama.cpp b/llama.cpp index 26e7a33918372..331c9d47243b3 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4394,6 +4394,9 @@ static void llm_load_vocab( } else if ( tokenizer_pre == "olmo") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_OLMO; + } else if ( + tokenizer_pre == "dbrx") { + vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DBRX; } else { throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str())); } @@ -12200,6 +12203,7 @@ struct llm_tokenizer_bpe { case LLAMA_VOCAB_TYPE_BPE: switch (vocab.type_pre) { case LLAMA_VOCAB_PRE_TYPE_LLAMA3: + case LLAMA_VOCAB_PRE_TYPE_DBRX: word_collection = unicode_regex_split(text, { // original regex from tokenizer.json //"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", diff --git a/llama.h b/llama.h index 5761cacf4d7f4..388839f3995e1 100644 --- a/llama.h +++ b/llama.h @@ -82,6 +82,7 @@ extern "C" { LLAMA_VOCAB_PRE_TYPE_REFACT = 8, LLAMA_VOCAB_PRE_TYPE_COMMAND_R = 9, LLAMA_VOCAB_PRE_TYPE_OLMO = 10, + LLAMA_VOCAB_PRE_TYPE_DBRX = 11, }; // note: these values should be synchronized with ggml_rope From 1fd9c1741d864d01cd7ec6d67227b92d7bfabf22 Mon Sep 17 00:00:00 2001 From: Xuan Son Nguyen Date: Wed, 8 May 2024 13:24:14 +0200 Subject: [PATCH 06/64] clean up json_value & server_log (#7142) --- examples/server/utils.hpp | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index 1a22125028204..af12f497d327d 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -49,18 +49,18 @@ extern bool server_log_json; #define LOG_WARNING(MSG, ...) server_log("WARN", __func__, __LINE__, MSG, __VA_ARGS__) #define LOG_INFO( MSG, ...) server_log("INFO", __func__, __LINE__, MSG, __VA_ARGS__) -static inline void server_log(const char *level, const char *function, int line, const char *message, const nlohmann::ordered_json &extra); +static inline void server_log(const char * level, const char * function, int line, const char * message, const json & extra); template -static T json_value(const json &body, const std::string &key, const T &default_value) { +static T json_value(const json & body, const std::string & key, const T & default_value) { // Fallback null to default value - if (body.contains(key) && !body.at(key).is_null()){ + if (body.contains(key) && !body.at(key).is_null()) { try { - return body.value(key, default_value); - } - catch (nlohmann::json_abi_v3_11_3::detail::type_error const&){ - std::string message = "Wrong type supplied for parameter '" + key + "'. Expected '" + typeid(default_value).name() + "', using default value."; - server_log("WARN", __func__, __LINE__, message.c_str(), body); + return body.at(key); + } catch (NLOHMANN_JSON_NAMESPACE::detail::type_error const &) { + std::stringstream ss; + ss << "Wrong type supplied for parameter '" << key << "'. Expected '" << json(default_value).type_name() << "', using default value."; + LOG_WARNING(ss.str().c_str(), body); return default_value; } } else { @@ -68,16 +68,16 @@ static T json_value(const json &body, const std::string &key, const T &default_v } } -static inline void server_log(const char *level, const char *function, int line, const char *message, const nlohmann::ordered_json &extra) { +static inline void server_log(const char * level, const char * function, int line, const char * message, const json & extra) { std::stringstream ss_tid; ss_tid << std::this_thread::get_id(); - json log = nlohmann::ordered_json{ + json log = json{ {"tid", ss_tid.str()}, {"timestamp", time(nullptr)}, }; if (server_log_json) { - log.merge_patch( { + log.merge_patch({ {"level", level}, {"function", function}, {"line", line}, @@ -98,7 +98,7 @@ static inline void server_log(const char *level, const char *function, int line, } std::stringstream ss; ss << buf << " |"; - for (const auto& el : log.items()) + for (const auto & el : log.items()) { const std::string value = el.value().dump(-1, ' ', false, json::error_handler_t::replace); ss << " " << el.key() << "=" << value; From 229ffff872f8ad0d21c997d18ee7a23692ae60a0 Mon Sep 17 00:00:00 2001 From: Ren Xuancheng Date: Wed, 8 May 2024 20:06:43 +0800 Subject: [PATCH 07/64] llama : add BPE pre-tokenization for Qwen2 (#7114) * Add BPE pre-tokenization for Qwen2. * minor : fixes --------- Co-authored-by: Ren Xuancheng <17811943+jklj077@users.noreply.github.com> Co-authored-by: Georgi Gerganov --- convert-hf-to-gguf-update.py | 1 + convert-hf-to-gguf.py | 3 + llama.cpp | 10 +++ llama.h | 5 +- models/ggml-vocab-qwen2.gguf | Bin 0 -> 5928681 bytes models/ggml-vocab-qwen2.gguf.inp | 106 +++++++++++++++++++++++++++++++ models/ggml-vocab-qwen2.gguf.out | 43 +++++++++++++ tests/CMakeLists.txt | 1 + 8 files changed, 167 insertions(+), 2 deletions(-) create mode 100644 models/ggml-vocab-qwen2.gguf create mode 100644 models/ggml-vocab-qwen2.gguf.inp create mode 100644 models/ggml-vocab-qwen2.gguf.out diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index b51010983ab46..a26f45a5fb1d0 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -67,6 +67,7 @@ class TOKENIZER_TYPE(IntEnum): {"name": "gpt-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/openai-community/gpt2", }, {"name": "refact", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/smallcloudai/Refact-1_6-base", }, {"name": "command-r", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/CohereForAI/c4ai-command-r-v01", }, + {"name": "qwen2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", }, {"name": "olmo", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", }, {"name": "dbrx", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", }, ] diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 8b89575d5a2fc..454e9fcdd784e 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -314,6 +314,9 @@ def get_vocab_base_pre(self, tokenizer) -> str: if chkhsh == "9c2227e4dd922002fb81bde4fc02b0483ca4f12911410dee2255e4987644e3f8": # ref: https://huggingface.co/CohereForAI/c4ai-command-r-v01 res = "command-r" + if chkhsh == "e636dc30a262dcc0d8c323492e32ae2b70728f4df7dfe9737d9f920a282b8aea": + # ref: https://huggingface.co/Qwen/Qwen1.5-7B + res = "qwen2" if chkhsh == "b6dc8df998e1cfbdc4eac8243701a65afe638679230920b50d6f17d81c098166": # ref: https://huggingface.co/allenai/OLMo-1.7-7B-hf res = "olmo" diff --git a/llama.cpp b/llama.cpp index 331c9d47243b3..9c72d118f2db2 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4391,6 +4391,9 @@ static void llm_load_vocab( } else if ( tokenizer_pre == "command-r") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_COMMAND_R; + } else if ( + tokenizer_pre == "qwen2") { + vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_QWEN2; } else if ( tokenizer_pre == "olmo") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_OLMO; @@ -12263,6 +12266,13 @@ struct llm_tokenizer_bpe { "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)", }); break; + case LLAMA_VOCAB_PRE_TYPE_QWEN2: + word_collection = unicode_regex_split(text, { + // original regex from tokenizer.json + // "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+" + "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", + }); + break; default: // default regex for BPE tokenization pre-processing word_collection = unicode_regex_split(text, { diff --git a/llama.h b/llama.h index 388839f3995e1..0b2e708d06dea 100644 --- a/llama.h +++ b/llama.h @@ -81,8 +81,9 @@ extern "C" { LLAMA_VOCAB_PRE_TYPE_GPT2 = 7, LLAMA_VOCAB_PRE_TYPE_REFACT = 8, LLAMA_VOCAB_PRE_TYPE_COMMAND_R = 9, - LLAMA_VOCAB_PRE_TYPE_OLMO = 10, - 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zV-t!fce+a0TwLh@bC_F7CTw)wZ#gJz;lPqEuyhV=uW}|;()nx%+9O9r<$k>MFh;j? zi8~YTXrAEd2nZS z@95~kYj+NgPfl0+hqrh6Z+!pFH};N??ydLUTz&6{tG$z-pQwR7|Lon>-Vfe8xPR;9 zbpQDDz1O!nFaPA|oz?#FdbPiLdwuW0op zu2I$A>ec5R*fsv@YEQpH`ddebr|ZL0^-Ec;+GSModG#Ll^C61lx9+YF*T?&(2S Date: Wed, 8 May 2024 13:22:32 +0100 Subject: [PATCH 08/64] convert.py : --vocab-only generates false but valid params (#7027) An example of how this might be used in the style of baby-llama will be attached with this PR. --- convert.py | 51 ++++++++++++++++++++++++++++++++------------------- 1 file changed, 32 insertions(+), 19 deletions(-) diff --git a/convert.py b/convert.py index 7f0b6b7498e10..aebfc50f3b028 100755 --- a/convert.py +++ b/convert.py @@ -1508,25 +1508,27 @@ def main(args_in: list[str] | None = None) -> None: if args.big_endian: endianess = gguf.GGUFEndian.BIG - params = Params.load(model_plus) - if params.n_ctx == -1: - if args.ctx is None: - msg = """\ - The model doesn't have a context size, and you didn't specify one with --ctx - Please specify one with --ctx: - - LLaMA v1: --ctx 2048 - - LLaMA v2: --ctx 4096""" - parser.error(textwrap.dedent(msg)) - params.n_ctx = args.ctx - - if args.outtype: - params.ftype = { - "f32": GGMLFileType.AllF32, - "f16": GGMLFileType.MostlyF16, - "q8_0": GGMLFileType.MostlyQ8_0, - }[args.outtype] - - logger.info(f"params = {params}") + params = None + if args.pad_vocab or not args.vocab_only: + params = Params.load(model_plus) + if params.n_ctx == -1: + if args.ctx is None: + msg = """\ + The model doesn't have a context size, and you didn't specify one with --ctx + Please specify one with --ctx: + - LLaMA v1: --ctx 2048 + - LLaMA v2: --ctx 4096""" + parser.error(textwrap.dedent(msg)) + params.n_ctx = args.ctx + + if args.outtype: + params.ftype = { + "f32": GGMLFileType.AllF32, + "f16": GGMLFileType.MostlyF16, + "q8_0": GGMLFileType.MostlyQ8_0, + }[args.outtype] + + logger.info(f"params = {params}") model_parent_path = model_plus.paths[0].parent vocab_path = Path(args.vocab_dir or args.model or model_parent_path) @@ -1539,6 +1541,17 @@ def main(args_in: list[str] | None = None) -> None: if not args.outfile: raise ValueError("need --outfile if using --vocab-only") outfile = args.outfile + if params is None: + params = Params( + n_vocab = vocab.vocab_size, + n_embd = 1, + n_layer = 1, + n_ctx = 1, + n_ff = 1, + n_head = 1, + n_head_kv = 1, + f_norm_eps = 1e-5, + ) OutputFile.write_vocab_only(outfile, params, vocab, special_vocab, endianess=endianess, pad_vocab=args.pad_vocab) logger.info(f"Wrote {outfile}") From 911b3900dded9a1cfe0f0e41b82c7a29baf3a217 Mon Sep 17 00:00:00 2001 From: Johan Date: Wed, 8 May 2024 14:27:58 +0200 Subject: [PATCH 09/64] server : add_special option for tokenize endpoint (#7059) --- examples/server/README.md | 2 +- examples/server/server.cpp | 3 +- examples/server/tests/features/server.feature | 14 +++++++- examples/server/tests/features/steps/steps.py | 36 ++++++++++++++++--- 4 files changed, 48 insertions(+), 7 deletions(-) diff --git a/examples/server/README.md b/examples/server/README.md index a7c3f0b5fc129..6503179914da0 100644 --- a/examples/server/README.md +++ b/examples/server/README.md @@ -331,7 +331,7 @@ Notice that each `probs` is an array of length `n_probs`. `content`: Set the text to tokenize. - Note that a special `BOS` token is never inserted. + `add_special`: Boolean indicating if special tokens, i.e. `BOS`, should be inserted. Default: `false` - **POST** `/detokenize`: Convert tokens to text. diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 85ae1ad9617eb..06c0be56749ab 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -3647,7 +3647,8 @@ int main(int argc, char ** argv) { std::vector tokens; if (body.count("content") != 0) { - tokens = ctx_server.tokenize(body["content"], false); + const bool add_special = json_value(body, "add_special", false); + tokens = ctx_server.tokenize(body["content"], add_special); } const json data = format_tokenizer_response(tokens); return res.set_content(data.dump(), "application/json; charset=utf-8"); diff --git a/examples/server/tests/features/server.feature b/examples/server/tests/features/server.feature index 646a4e49d0d56..d21c09135243a 100644 --- a/examples/server/tests/features/server.feature +++ b/examples/server/tests/features/server.feature @@ -7,6 +7,7 @@ Feature: llama.cpp server And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models And a model file test-model.gguf And a model alias tinyllama-2 + And BOS token is 1 And 42 as server seed # KV Cache corresponds to the total amount of tokens # that can be stored across all independent sequences: #4130 @@ -91,7 +92,18 @@ Feature: llama.cpp server """ What is the capital of France ? """ - Then tokens can be detokenize + Then tokens can be detokenized + And tokens do not begin with BOS + + Scenario: Tokenize w/ BOS + Given adding special tokens + When tokenizing: + """ + What is the capital of Germany? + """ + Then tokens begin with BOS + Given first token is removed + Then tokens can be detokenized Scenario: Models available Given available models diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py index b8dbef21d1b76..0882a5d36193b 100644 --- a/examples/server/tests/features/steps/steps.py +++ b/examples/server/tests/features/steps/steps.py @@ -376,6 +376,11 @@ def step_seed(context, seed): context.seed.append(seed) +@step('BOS token is {bos:d}') +def step_bos_token(context, bos): + context.bos = bos + + @step('a prefix prompt') def step_prompt_prefix(context): context.prompt_prefix = context_text(context) @@ -656,21 +661,29 @@ async def all_embeddings_are_generated(context): assert_embeddings(context.tasks_result.pop().pop()) +@step('adding special tokens') +def step_tokenize_set_add_special(context): + context.tokenize_add_special = True + + @step('tokenizing') @async_run_until_complete async def step_tokenize(context): context.tokenized_text = context_text(context) async with aiohttp.ClientSession() as session: + tokenize_args = { + "content": context.tokenized_text, + } + if getattr(context, 'tokenize_add_special', None) is not None: + tokenize_args['add_special'] = context.tokenize_add_special async with session.post(f'{context.base_url}/tokenize', - json={ - "content": context.tokenized_text, - }) as response: + json=tokenize_args) as response: assert response.status == 200 tokenize_json = await response.json() context.tokens = tokenize_json['tokens'] -@step('tokens can be detokenize') +@step('tokens can be detokenized') @async_run_until_complete async def step_detokenize(context): assert len(context.tokens) > 0 @@ -685,6 +698,21 @@ async def step_detokenize(context): assert context.tokenized_text == detokenize_json['content'].strip() +@step('tokens begin with BOS') +def step_strings_for_tokenization(context): + assert context.tokens[0] == context.bos + + +@step('tokens do not begin with BOS') +def step_strings_for_tokenization(context): + assert context.tokens[0] != context.bos + + +@step('first token is removed') +def step_strings_for_tokenization(context): + context.tokens = context.tokens[1:] + + @step('an OPTIONS request is sent from {origin}') @async_run_until_complete async def step_options_request(context, origin): From 465263d0cf1e8f8bc41948332dbd009d27a68590 Mon Sep 17 00:00:00 2001 From: Eve <139727413+netrunnereve@users.noreply.github.com> Date: Wed, 8 May 2024 14:29:23 +0000 Subject: [PATCH 10/64] sgemm : AVX Q4_0 and Q8_0 (#6891) * basic avx implementation * style * combine denibble with load * reduce 256 to 128 (and back!) conversions * sse load * Update sgemm.cpp * oops oops --- sgemm.cpp | 77 ++++++++++++++++++++++++++++++++++++++++--------------- 1 file changed, 56 insertions(+), 21 deletions(-) diff --git a/sgemm.cpp b/sgemm.cpp index 4e0159804e816..40ba9d7e9a7b7 100644 --- a/sgemm.cpp +++ b/sgemm.cpp @@ -1,6 +1,3 @@ -// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;coding:utf-8 -*- -// vi: set et ft=c++ ts=4 sts=4 sw=4 fenc=utf-8 :vi -// // Copyright 2024 Mozilla Foundation // // Permission is hereby granted, free of charge, to any person obtaining @@ -585,15 +582,15 @@ class tinyBLAS_Q0_ARM { }; #endif // __ARM_FEATURE_DOTPROD -#if defined(__AVX2__) || defined(__AVX512F__) +#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__) template -class tinyBLAS_Q0_AVX2 { +class tinyBLAS_Q0_AVX { public: - tinyBLAS_Q0_AVX2(int64_t k, - const TA *A, int64_t lda, - const TB *B, int64_t ldb, - TC *C, int64_t ldc, - int ith, int nth) + tinyBLAS_Q0_AVX(int64_t k, + const TA *A, int64_t lda, + const TB *B, int64_t ldb, + TC *C, int64_t ldc, + int ith, int nth) : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) { } @@ -728,14 +725,34 @@ class tinyBLAS_Q0_AVX2 { __m256 Cv[RN][RM] = {}; for (int64_t l = 0; l < k; ++l) for (int64_t j = 0; j < RN; ++j) - for (int64_t i = 0; i < RM; ++i) + for (int64_t i = 0; i < RM; ++i) { +#if defined(__AVX2__) + __m256 udTmp = updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l), + load(A + lda * (ii + i) + l)), + _mm256_sign_epi8(load(B + ldb * (jj + j) + l), + load(A + lda * (ii + i) + l))); +#else + __m128i ali0 = load0(A + lda * (ii + i) + l); + __m128i ali1 = load1(A + lda * (ii + i) + l); + __m128i blj0 = load0(B + ldb * (jj + j) + l); + __m128i blj1 = load1(B + ldb * (jj + j) + l); + + __m128i sepAA0 = _mm_sign_epi8(ali0, ali0); + __m128i sepAA1 = _mm_sign_epi8(ali1, ali1); + __m128i sepBA0 = _mm_sign_epi8(blj0, ali0); + __m128i sepBA1 = _mm_sign_epi8(blj1, ali1); + + // updot + const __m128i oneFill = _mm_set1_epi16(1); + __m128i mad0 = _mm_maddubs_epi16(sepAA0, sepBA0); + __m128i mad1 = _mm_maddubs_epi16(sepAA1, sepBA1); + __m256 udTmp = _mm256_cvtepi32_ps(MM256_SET_M128I(_mm_madd_epi16(oneFill, mad1), _mm_madd_epi16(oneFill, mad0))); +#endif Cv[j][i] = madd(_mm256_set1_ps(unhalf(A[lda * (ii + i) + l].d) * unhalf(B[ldb * (jj + j) + l].d)), - updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l), - load(A + lda * (ii + i) + l)), - _mm256_sign_epi8(load(B + ldb * (jj + j) + l), - load(A + lda * (ii + i) + l))), - Cv[j][i]); + udTmp, + Cv[j][i]); + } for (int64_t j = 0; j < RN; ++j) for (int64_t i = 0; i < RM; ++i) C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]); @@ -746,10 +763,28 @@ class tinyBLAS_Q0_AVX2 { return _mm256_loadu_si256((const __m256i *)b->qs); } + inline __m128i load0(const block_q8_0 *b) { + return _mm_loadu_si128((const __m128i *)b->qs); + } + + inline __m128i load1(const block_q8_0 *b) { + return _mm_loadu_si128(((const __m128i *)b->qs) + 1); + } + inline __m256i load(const block_q4_0 *b) { return _mm256_sub_epi8(denibble(b->qs), _mm256_set1_epi8(8)); } + inline __m128i load0(const block_q4_0 *b) { + const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs)); + return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), x), _mm_set1_epi8(8)); + } + + inline __m128i load1(const block_q4_0 *b) { + const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs)); + return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4)), _mm_set1_epi8(8)); + } + inline __m256 updot(__m256i u, __m256i s) { __m256i res; #if defined(__AVXVNNI__) || (defined(__AVX512VNNI__) && defined(__AVX512VL__)) @@ -777,7 +812,7 @@ class tinyBLAS_Q0_AVX2 { const int ith; const int nth; }; -#endif // __AVX2__ +#endif // __AVX__ } // namespace @@ -928,8 +963,8 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda case GGML_TYPE_Q8_0: { if (Btype != GGML_TYPE_Q8_0) return false; -#if defined(__AVX2__) || defined(__AVX512F__) - tinyBLAS_Q0_AVX2 tb{ +#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__) + tinyBLAS_Q0_AVX tb{ k, (const block_q8_0 *)A, lda, (const block_q8_0 *)B, ldb, (float *)C, ldc, @@ -952,8 +987,8 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda case GGML_TYPE_Q4_0: { if (Btype != GGML_TYPE_Q8_0) return false; -#if defined(__AVX2__) || defined(__AVX512F__) - tinyBLAS_Q0_AVX2 tb{ +#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__) + tinyBLAS_Q0_AVX tb{ k, (const block_q4_0 *)A, lda, (const block_q8_0 *)B, ldb, (float *)C, ldc, From 83330d8cd6491e53e1aca4c5dfc47e039b3c04ff Mon Sep 17 00:00:00 2001 From: Dawid Potocki Date: Thu, 9 May 2024 02:32:32 +1200 Subject: [PATCH 11/64] main : add --conversation / -cnv flag (#7108) --- common/common.cpp | 5 +++++ common/common.h | 1 + examples/main/main.cpp | 11 +++++++---- 3 files changed, 13 insertions(+), 4 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 467fb014eedb0..4a9da284e7ec9 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -911,6 +911,10 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa params.instruct = true; return true; } + if (arg == "-cnv" || arg == "--conversation") { + params.conversation = true; + return true; + } if (arg == "-cml" || arg == "--chatml") { params.chatml = true; return true; @@ -1417,6 +1421,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { printf(" --version show version and build info\n"); printf(" -i, --interactive run in interactive mode\n"); printf(" --interactive-first run in interactive mode and wait for input right away\n"); + printf(" -cnv, --conversation run in conversation mode (does not print special tokens and suffix/prefix)\n"); printf(" -ins, --instruct run in instruction mode (use with Alpaca models)\n"); printf(" -cml, --chatml run in chatml mode (use with ChatML-compatible models)\n"); printf(" --multiline-input allows you to write or paste multiple lines without ending each in '\\'\n"); diff --git a/common/common.h b/common/common.h index 9252a4b63889b..6f00a2cca8883 100644 --- a/common/common.h +++ b/common/common.h @@ -140,6 +140,7 @@ struct gpt_params { bool random_prompt = false; // do not randomize prompt if none provided bool use_color = false; // use color to distinguish generations and inputs bool interactive = false; // interactive mode + bool conversation = false; // conversation mode (does not print special tokens and suffix/prefix) bool chatml = false; // chatml mode (used for models trained on chatml syntax) bool prompt_cache_all = false; // save user input and generations to prompt cache bool prompt_cache_ro = false; // open the prompt cache read-only and do not update it diff --git a/examples/main/main.cpp b/examples/main/main.cpp index f676ea1ba8a13..49acd6bab4074 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -362,6 +362,9 @@ int main(int argc, char ** argv) { params.interactive_first = true; params.antiprompt.emplace_back("<|im_start|>user\n"); } + else if (params.conversation) { + params.interactive_first = true; + } // enable interactive mode if interactive start is specified if (params.interactive_first) { @@ -733,7 +736,7 @@ int main(int argc, char ** argv) { // display text if (input_echo && display) { for (auto id : embd) { - const std::string token_str = llama_token_to_piece(ctx, id); + const std::string token_str = llama_token_to_piece(ctx, id, !params.conversation); printf("%s", token_str.c_str()); if (embd.size() > 1) { @@ -816,7 +819,7 @@ int main(int argc, char ** argv) { if (n_past > 0 && is_interacting) { LOG("waiting for user input\n"); - if (params.instruct || params.chatml) { + if (params.conversation || params.instruct || params.chatml) { printf("\n> "); } @@ -826,7 +829,7 @@ int main(int argc, char ** argv) { } std::string buffer; - if (!params.input_prefix.empty()) { + if (!params.input_prefix.empty() && !params.conversation) { LOG("appending input prefix: '%s'\n", params.input_prefix.c_str()); printf("%s", params.input_prefix.c_str()); } @@ -850,7 +853,7 @@ int main(int argc, char ** argv) { // Entering a empty line lets the user pass control back if (buffer.length() > 1) { // append input suffix if any - if (!params.input_suffix.empty()) { + if (!params.input_suffix.empty() && !params.conversation) { LOG("appending input suffix: '%s'\n", params.input_suffix.c_str()); printf("%s", params.input_suffix.c_str()); } From 26458af1d63c85195cd96cd1673051e332d06d30 Mon Sep 17 00:00:00 2001 From: Gilad S Date: Wed, 8 May 2024 22:08:10 +0300 Subject: [PATCH 12/64] metal : use `vm_allocate` instead of `posix_memalign` on macOS (#7078) * fix: use `malloc` instead of `posix_memalign` in `ggml-metal.m` to make it not crash Electron proccesses * fix: typo * fix: use `vm_allocate` instead of `posix_memalign` * fix: don't call `newBufferWithBytesNoCopy` with `NULL` when `ggml_metal_host_malloc` returns `NULL` * fix: use `vm_allocate` only on macOS --- ggml-metal.m | 29 ++++++++++++++++++++++------- 1 file changed, 22 insertions(+), 7 deletions(-) diff --git a/ggml-metal.m b/ggml-metal.m index 78cac5041d360..c6817f01f2bdb 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -265,11 +265,20 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){ static void * ggml_metal_host_malloc(size_t n) { void * data = NULL; + +#if TARGET_OS_OSX + kern_return_t err = vm_allocate((vm_map_t) mach_task_self(), (void *) &data, n, VM_FLAGS_ANYWHERE); + if (err != KERN_SUCCESS) { + GGML_METAL_LOG_ERROR("%s: error: vm_allocate failed\n", __func__); + return NULL; + } +#else const int result = posix_memalign((void **) &data, sysconf(_SC_PAGESIZE), n); if (result != 0) { GGML_METAL_LOG_ERROR("%s: error: posix_memalign failed\n", __func__); return NULL; } +#endif return data; } @@ -2840,7 +2849,11 @@ GGML_CALL static void ggml_backend_metal_buffer_free_buffer(ggml_backend_buffer_ ggml_backend_metal_free_device(); if (ctx->owned) { +#if TARGET_OS_OSX + vm_deallocate((vm_map_t)mach_task_self(), (vm_address_t)ctx->all_data, ctx->all_size); +#else free(ctx->all_data); +#endif } free(ctx); @@ -2944,14 +2957,16 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buff ctx->owned = true; ctx->n_buffers = 1; - ctx->buffers[0].data = ctx->all_data; - ctx->buffers[0].size = size; - ctx->buffers[0].metal = [device newBufferWithBytesNoCopy:ctx->all_data - length:size_aligned - options:MTLResourceStorageModeShared - deallocator:nil]; + if (ctx->all_data != NULL) { + ctx->buffers[0].data = ctx->all_data; + ctx->buffers[0].size = size; + ctx->buffers[0].metal = [device newBufferWithBytesNoCopy:ctx->all_data + length:size_aligned + options:MTLResourceStorageModeShared + deallocator:nil]; + } - if (ctx->buffers[0].metal == nil) { + if (ctx->all_data == NULL || ctx->buffers[0].metal == nil) { GGML_METAL_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); free(ctx); ggml_backend_metal_free_device(); From bd1871fa2b1bf8a081b43ba9bc85f8ffd46fac46 Mon Sep 17 00:00:00 2001 From: JohnnyB Date: Wed, 8 May 2024 20:12:06 +0100 Subject: [PATCH 13/64] server : add themes + favicon (#6848) * Added themes support with two sample themes and a favicon. * Newline * Newline * Newline * Trailing whitespace * Increased opacity for contrast * Increase opacity. Check actions cancelled for some other priority job and I can't seem to manually re-run them, so MOAR OPACITY * Opacity action trigger. Trying to re-trigger the cancelled action. * One more opacity adjustment This Actions pipeline is failing for random issues. * Delete examples/server/themes/buttons_top/completion.js This will be served from the static string built-in to server. * Delete examples/server/themes/buttons_top/index.js This will be served from the static string built-in to server. * Delete examples/server/themes/wild/completion.js This will be served from the static string built-in to server. * Delete examples/server/themes/buttons_top/json-schema-to-grammar.mjs This will be served from the static string built-in to server. * Delete examples/server/themes/wild/index.js This will be served from the static string built-in to server. * Delete examples/server/themes/wild/json-schema-to-grammar.mjs This will be served from the static string built-in to server. * Replaced underscore. --- examples/server/public/favicon.ico | Bin 0 -> 4122 bytes examples/server/themes/README.md | 5 + examples/server/themes/buttons-top/README.md | 7 + .../server/themes/buttons-top/buttons_top.png | Bin 0 -> 119747 bytes .../server/themes/buttons-top/favicon.ico | Bin 0 -> 4122 bytes examples/server/themes/buttons-top/index.html | 1057 ++++++++++++++++ examples/server/themes/wild/README.md | 5 + examples/server/themes/wild/favicon.ico | Bin 0 -> 4122 bytes examples/server/themes/wild/index.html | 1061 +++++++++++++++++ examples/server/themes/wild/llama_cpp.png | Bin 0 -> 76484 bytes examples/server/themes/wild/llamapattern.png | Bin 0 -> 259586 bytes examples/server/themes/wild/wild.png | Bin 0 -> 496463 bytes 12 files changed, 2135 insertions(+) create mode 100644 examples/server/public/favicon.ico create mode 100644 examples/server/themes/README.md create mode 100644 examples/server/themes/buttons-top/README.md create mode 100644 examples/server/themes/buttons-top/buttons_top.png create mode 100644 examples/server/themes/buttons-top/favicon.ico create mode 100644 examples/server/themes/buttons-top/index.html create mode 100644 examples/server/themes/wild/README.md create mode 100644 examples/server/themes/wild/favicon.ico create mode 100644 examples/server/themes/wild/index.html create mode 100644 examples/server/themes/wild/llama_cpp.png create mode 100644 examples/server/themes/wild/llamapattern.png create mode 100644 examples/server/themes/wild/wild.png diff --git a/examples/server/public/favicon.ico b/examples/server/public/favicon.ico new file mode 100644 index 0000000000000000000000000000000000000000..89e154a0a7525ecd19379e8e200e36851c325d31 GIT binary patch literal 4122 zcmV+#5asUx0096206;(h0096X00a;K02TlM0EtjeM-2)Z3IG5A4M|8uQUCw|KmY&$ zKnMl^0063Kaozv`56ekJK~#90#hZDQRMnlwKli=by1TlndI5R?*;+s#g0#D%Q4nxX z#3hqsJQ+MDax^A6nK|fWl8Hy>M1v-R-1SmHQ!vN3#58wlufO=pE*b8(6 z@slxksSxE}gkcyOPzziHTnj7!nt>`H2DAac0$uy0}R9P0^b7e0wyJ&YeL|6YSdNg^hazuO$#X{ zz<%IzA;exOr3QF`Iuwy45C?)l$mjD(P1DM<&fyq02P96-3;Z)`^A!N6)wo!FQ6sI* zUMBn9_}vZ$V;1*pILt4%_Sl-H9gfH2Q7Pp_;7Z^+U`}Ez8^syBfJgiK`ZfUO$>4@^ zh=3dTCa@Z)0Kt8iG_dOIM(V4whp%?)2mz=Q2KW+iCrVtLImVs}oR1>x(?FyQ>&?Qr zL?EH?E(HDvGzs9TuTJBph4naduk=!H*VC!SBgG+)I0UIoKD= zdbVs@6~DQzg(-gbi1!a05$<09S+W@hHc;l%2j#7m3@N3KI{DdvxOSG8bEkOozTXp$ z^NUR#SF-cXtI{pUUj^2GLFvUvn}5D1+NGdNc7;uPR)0H;Ie+*7Laz8H>L z{Cv~V?9N^XE9TYZeE-uEVSez}BgtkA_$9ET+}b~hu@FE*+3yJe-&z=;t}>SiS2%1$ z_@FaebiaT8BpRw+Ip2SHO9$O)OYs`;2VK|8F8fK0g#ZrVti<0ep5aF;pqu+6R<`5{ z!KE!VIp6IyEuPyMN;adwQ$Tlhb$$*TFUCTE3KR!`5KOBXX}&U1m2JwnWJ(3I>htuG z5{=(2yoJ~2_vox_osepu(U{*{YQPQi>oc2I1A$y&a=B2d z2nb*@Pz|uO#fM%<0VHtkyjr{t4X3V+5E)y7WlL;Zsfr~ne&*Muxav$`E+@eQOrlgz zP@obS4uHwN!t9?!OI-!`E^g%BH;=O~X!60)e)a}U226|YaFnjWI6jX~eT9R1uZw1% zi=DwJC^49XIw-5)BxA%_2#^xen##i6EeQvEOg0_r37`WlBt)mdo0|hHTk=uIAdhV6;MtuaqSlxdc?Ix8;AUVQDkreZFpNmK z9HX%WLrRE+z>`Cp@97%ivG+Py`+kt&uDcL|1@$gkn=4t=o(bVu#fF0A`HcCP{f{!N}OB|JPAB*7{;+cATVwdITiw_NhLTk6kx=%d2v^el`kG) zD4rHqO$aWXTFEVEPGn(Y6_fq05x&82L@b-mff)OHO#Zy9hbOl85LU!!L~+E$z`q%W z@lGHRh!+}bG>nA+sbh8MiU21DV%-1cXRO^C1ey46A-H`}Eh}3mvY@dNr(V3laqAjW z{BEZB-CR7~&-X59;?;cytJfdJh*}!(4=8c?hG7`*j)xO;kEgIFmkHA}bzm`YJ_v3* za{{)M-1@>kp52+Y)k~*U^1Br?`1UysO!m8qGL?l8sBqBQ?B#~}HE7ai%dsI))~E^i zTO<-0DrFy;7z+oa_6#a%uF?W_12K@!mFtcmm3N3o*Z9Nr)4Arfnk?N=ZhU+^%*zMD$>t$c zyf9{zq|D@1l9>5zBnt82uf;!+evtYk6zKtRdYt)yhJ5OUfXN1Zci`k_6;hFAxPPkSpf&j zPxZ01rG^Wq`3O{`iP1R_<0l(ZNzy)4rpS;|>KVb31ng2cqEsE=0=@<;2e@TH4c}~? 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To try any of these add --path to your run like `server --path=wild`. + +![image](wild/wild.png) diff --git a/examples/server/themes/buttons-top/README.md b/examples/server/themes/buttons-top/README.md new file mode 100644 index 0000000000000..808c4cf81a959 --- /dev/null +++ b/examples/server/themes/buttons-top/README.md @@ -0,0 +1,7 @@ +# LLaMA.cpp Server Buttons Top Theme + +Simple tweaks to the UI. Chat buttons at the top of the page instead of bottom so you can hit Stop instead of chasing it down the page. + +To use simply run server with `--path=themes/buttons_top` + +![image](buttons_top.png) diff --git a/examples/server/themes/buttons-top/buttons_top.png b/examples/server/themes/buttons-top/buttons_top.png new file mode 100644 index 0000000000000000000000000000000000000000..c544545196f995d9c5f0e26de14df6254324e26f GIT binary patch literal 119747 zcmXt9bx>PualnV==3P5IeKjBZep^%1@20!oJPpl_&5d){0atU^b6bO?mONoD z)z&c~ycmZ2g95?y>eO2S*|3I%aP8m1*J6aqCG>HKYy`eB%yzT+i&&1}o}KJ>!n^{! zBX_BRXjdtC@AV_SIy~uuzgPE$epkJX$WQ59#0D2q#di5M#aWMJYL`l;cV-|z#_JMW zGu7+%&yQXxdO8V2EMcbnY3>`1)SPL9hX;6Xk9>fotJP-Fw2PCQr^Ruo>Q6)3s9hQ6 z4%wzw|SPi>=BiVA8%&08Kt;y-Q3FmcNZ%RO)4A5O3q zJTZY<_j?G^l03vYxQlN|`%wF@C=j7zq0(58cEKtFRw9pYuXgTF+_GnOn?Y^UseUXj z6CV5QJU2s2aUHQ4FB(Fne&)+~RR9}w-Kst{pdJnD5}&IWur&??aej49GLq21z}YvB7%h;p~w7WkG$tRsX2Q2_`I2HFQ}SD@IK>gu 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    + +
    +
    + + + + diff --git a/examples/server/themes/wild/README.md b/examples/server/themes/wild/README.md new file mode 100644 index 0000000000000..560bcc81bfde1 --- /dev/null +++ b/examples/server/themes/wild/README.md @@ -0,0 +1,5 @@ +# LLaMA.cpp Server Wild Theme + +Simple tweaks to the UI. To use simply run server with `--path=themes/wild` + +![image](wild.png) diff --git a/examples/server/themes/wild/favicon.ico b/examples/server/themes/wild/favicon.ico new file mode 100644 index 0000000000000000000000000000000000000000..89e154a0a7525ecd19379e8e200e36851c325d31 GIT binary patch literal 4122 zcmV+#5asUx0096206;(h0096X00a;K02TlM0EtjeM-2)Z3IG5A4M|8uQUCw|KmY&$ zKnMl^0063Kaozv`56ekJK~#90#hZDQRMnlwKli=by1TlndI5R?*;+s#g0#D%Q4nxX z#3hqsJQ+MDax^A6nK|fWl8Hy>M1v-R-1SmHQ!vN3#58wlufO=pE*b8(6 z@slxksSxE}gkcyOPzziHTnj7!nt>`H2DAac0$uy0}R9P0^b7e0wyJ&YeL|6YSdNg^hazuO$#X{ zz<%IzA;exOr3QF`Iuwy45C?)l$mjD(P1DM<&fyq02P96-3;Z)`^A!N6)wo!FQ6sI* zUMBn9_}vZ$V;1*pILt4%_Sl-H9gfH2Q7Pp_;7Z^+U`}Ez8^syBfJgiK`ZfUO$>4@^ zh=3dTCa@Z)0Kt8iG_dOIM(V4whp%?)2mz=Q2KW+iCrVtLImVs}oR1>x(?FyQ>&?Qr zL?EH?E(HDvGzs9TuTJBph4naduk=!H*VC!SBgG+)I0UIoKD= zdbVs@6~DQzg(-gbi1!a05$<09S+W@hHc;l%2j#7m3@N3KI{DdvxOSG8bEkOozTXp$ z^NUR#SF-cXtI{pUUj^2GLFvUvn}5D1+NGdNc7;uPR)0H;Ie+*7Laz8H>L z{Cv~V?9N^XE9TYZeE-uEVSez}BgtkA_$9ET+}b~hu@FE*+3yJe-&z=;t}>SiS2%1$ z_@FaebiaT8BpRw+Ip2SHO9$O)OYs`;2VK|8F8fK0g#ZrVti<0ep5aF;pqu+6R<`5{ z!KE!VIp6IyEuPyMN;adwQ$Tlhb$$*TFUCTE3KR!`5KOBXX}&U1m2JwnWJ(3I>htuG z5{=(2yoJ~2_vox_osepu(U{*{YQPQi>oc2I1A$y&a=B2d z2nb*@Pz|uO#fM%<0VHtkyjr{t4X3V+5E)y7WlL;Zsfr~ne&*Muxav$`E+@eQOrlgz zP@obS4uHwN!t9?!OI-!`E^g%BH;=O~X!60)e)a}U226|YaFnjWI6jX~eT9R1uZw1% zi=DwJC^49XIw-5)BxA%_2#^xen##i6EeQvEOg0_r37`WlBt)mdo0|hHTk=uIAdhV6;MtuaqSlxdc?Ix8;AUVQDkreZFpNmK z9HX%WLrRE+z>`Cp@97%ivG+Py`+kt&uDcL|1@$gkn=4t=o(bVu#fF0A`HcCP{f{!N}OB|JPAB*7{;+cATVwdITiw_NhLTk6kx=%d2v^el`kG) zD4rHqO$aWXTFEVEPGn(Y6_fq05x&82L@b-mff)OHO#Zy9hbOl85LU!!L~+E$z`q%W z@lGHRh!+}bG>nA+sbh8MiU21DV%-1cXRO^C1ey46A-H`}Eh}3mvY@dNr(V3laqAjW z{BEZB-CR7~&-X59;?;cytJfdJh*}!(4=8c?hG7`*j)xO;kEgIFmkHA}bzm`YJ_v3* za{{)M-1@>kp52+Y)k~*U^1Br?`1UysO!m8qGL?l8sBqBQ?B#~}HE7ai%dsI))~E^i zTO<-0DrFy;7z+oa_6#a%uF?W_12K@!mFtcmm3N3o*Z9Nr)4Arfnk?N=ZhU+^%*zMD$>t$c zyf9{zq|D@1l9>5zBnt82uf;!+evtYk6zKtRdYt)yhJ5OUfXN1Zci`k_6;hFAxPPkSpf&j zPxZ01rG^Wq`3O{`iP1R_<0l(ZNzy)4rpS;|>KVb31ng2cqEsE=0=@<;2e@TH4c}~? zn5_2Xg<-~ddV42#zuJL0+$+rRmD-IM?OTI9v^7YJ-^sr(Zsx0VYw@~up82qo9l=y$ z=y{+ExRG=LRwkakYZyj%v7Tbll_A401gduT7hq<+TW9lar!lL(qF}%F?ji16caT>O z4Q4(zQ8GMgs^_xlUT$7Afm>cYOhggyGn5Z-6EJPq>q#B;FTlZKh)@&(5-jEc{sUD6 z=MWEU?o2kj zP$~EdpdWSevw#3Xuy%PfH5q#1%>#Wr^>Ht#YV$lP<*2oUVhP{?E&yf%eD}ObG*su$ z1jQ}MnvKVJ{Yc7QzXE&*IEqSfrKoq+oElo2(^;ao5BBlEJ6%badOh%Gl<2*Wsu4U3 zAcV$^U#iQ>E=S`sNdQ-34v%3NQ6Yqtj}t~EKnD9?31|q7Wv3Pvn{CGiSo2O-ve|}W zcN4f3RZUtx+Pn!|1Pq`==1i2_&n}{$6ZiotXnIFVxjqyM_2nW$u^dnjoCombW)HI` z+qVkOG~G2Q3n<$s!!_8TN4bjgCoD%!t0 zKec{iD9%;Sv~$7KO4eL9Ev?Zc)DEjiT{)+Q_UXP<`!gfL(%tt!EhX>F7SICwB)!$ zkcmm&>@>YYOL7IE6ypdKBLX7Xxl-4tt;kO^34GWwlx+3^`-&LM0uBwF1;X99ElC%4iKD0<1wz22&H;-DHy+Ir zffe)WvaZMM>J0POw%*iI2ctHR*(7uILJbD+m$^@fr6kWiO0pCrdMyJAH^0K_B(bNm8m zZA{foe5hb03j7xM3DAks!lj5r6y*|!$Z>)N5C;ZYTRQA>-gy=&#M9WZDYt|Pz?zRlzzUNHo)6O+oA zWpgZ4__D?s&0aidM`;BxEpZpv1U>;?MV$%&15ulh8BhHNqE;sRhZB8vqwWZ`IS#|t;OBblf z?We%qs03yVr5LxOqPyy=f4>)(o>^eY;?hfjhf!6bL#Vi5GjOi7Epg6cyUFOvfGVCy z6wwY-M0RM@x`1h#$w6-bywbMB_4DiU=K6(zxf3hdxZj{-&`Ksz76X11$BD#7Jir-I zTWUj=B>9VGYgqxDiVBI}Kykz#R6sP-w4})FYe^*PgN!?Ywqg<@#S$Qfx)(I3y*DOq zoLf`yVua75bIuemn+}HP9I^!JLd9ZKI_+z~*MWH`OEE$W&u;MWvt^U{ymyGB1C{`$ zpo*iNCYKDg1cxWX_uGrE?(0>xTwFamyB9 zS0E6uP1EcL-bLjKo=0VgUPR>`js*e%yVy!mDJijL)G3^yYns@;Y7VD2RE^r#vSG)G zLAD&}=k@&|-aZoMc-RI_aC)7CB{QmNZT7OL$xBPUC(F@V-)?Z(vwM@xhk(_AK)@_& zXGNlvq^JXxh5a>9aoud6`0e#A1@rjBVM&Q)s{)5h6F7B&Ll=32qk}yra~|52^gT8M zU(qxz==1sV^e7!g7e`Igv{4z^sle&GgAw6#3C=yG8f~<^cmkRb=$g7$;MCQ>3-zpW zYrMRthob{=P+sMqq?FxbErjMm(F927f(X!#N;OS*{m_7Ds&cTfxvFR)l(aY@Foxp1 zdY~UvKH?3a&ExTuEx0PFJf0vz4@%=+1l0cDzCOIVU_oP5mOU>QB5}#n9|u7x%x%DX z9*?JNmnTai0D#Bik)~-L1$LlZ-I`Yq^mCvq%)Ew5>Z_b(xzlFGZ8jb1W9>T~w5ink z5GttJ`*-7j)Z)_mUO^*$ohQViMmLUykG1=xzu6QCX+eCKGcTeB$6**)K}&I Y56YREzWcW|-v9sr07*qoM6N<$g8wb3s{jB1 literal 0 HcmV?d00001 diff --git a/examples/server/themes/wild/index.html b/examples/server/themes/wild/index.html new file mode 100644 index 0000000000000..772e716cdb2e0 --- /dev/null +++ b/examples/server/themes/wild/index.html @@ -0,0 +1,1061 @@ + + + + + + + llama.cpp - chat + + + + + + + +
    + +
    +
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support for moondream vision language model (#6899)" This reverts commit 46e12c4692a37bdd31a0432fc5153d7d22bc7f72. --- README.md | 1 - examples/llava/clip.cpp | 71 +++++++---------------------------------- 2 files changed, 11 insertions(+), 61 deletions(-) diff --git a/README.md b/README.md index 1c960b8c11ef7..15686047031c1 100644 --- a/README.md +++ b/README.md @@ -140,7 +140,6 @@ Typically finetunes of the base models below are supported as well. - [x] [MobileVLM 1.7B/3B models](https://huggingface.co/models?search=mobileVLM) - [x] [Yi-VL](https://huggingface.co/models?search=Yi-VL) - [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM) -- [x] [Moondream](https://huggingface.co/vikhyatk/moondream2) **HTTP server** diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp index e3c9bcd4364aa..f568f470c8f5c 100644 --- a/examples/llava/clip.cpp +++ b/examples/llava/clip.cpp @@ -104,7 +104,6 @@ static std::string format(const char * fmt, ...) { #define TN_POS_EMBD "%s.position_embd.weight" #define TN_CLASS_EMBD "v.class_embd" #define TN_PATCH_EMBD "v.patch_embd.weight" -#define TN_PATCH_BIAS "v.patch_embd.bias" #define TN_ATTN_K "%s.blk.%d.attn_k.%s" #define TN_ATTN_Q "%s.blk.%d.attn_q.%s" #define TN_ATTN_V "%s.blk.%d.attn_v.%s" @@ -426,7 +425,6 @@ struct clip_vision_model { // embeddings struct ggml_tensor * class_embedding; struct ggml_tensor * patch_embeddings; - struct ggml_tensor * patch_bias; struct ggml_tensor * position_embeddings; struct ggml_tensor * pre_ln_w; @@ -503,11 +501,6 @@ struct clip_ctx { bool use_gelu = false; int32_t ftype = 1; - bool has_class_embedding = true; - bool has_pre_norm = true; - bool has_post_norm = false; - bool has_patch_bias = false; - struct gguf_context * ctx_gguf; struct ggml_context * ctx_data; @@ -533,7 +526,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 const int patch_size = hparams.patch_size; const int num_patches = ((image_size / patch_size) * (image_size / patch_size)); const int num_patches_per_side = image_size / patch_size; GGML_UNUSED(num_patches_per_side); - const int num_positions = num_patches + (ctx->has_class_embedding ? 1 : 0); + const int num_positions = num_patches + 1; const int hidden_size = hparams.hidden_size; const int n_head = hparams.n_head; const int d_head = hidden_size / n_head; @@ -564,23 +557,16 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 inp = ggml_reshape_3d(ctx0, inp, num_patches, hidden_size, batch_size); inp = ggml_cont(ctx0, ggml_permute(ctx0, inp, 1, 0, 2, 3)); - if (ctx->has_patch_bias) { - // inp = ggml_add(ctx0, inp, ggml_repeat(ctx0, model.patch_bias, inp)); - inp = ggml_add(ctx0, inp, model.patch_bias); - } - // concat class_embeddings and patch_embeddings - struct ggml_tensor * embeddings = inp; - if (ctx->has_class_embedding) { - embeddings = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, hidden_size, num_positions, batch_size); - embeddings = ggml_acc(ctx0, embeddings, model.class_embedding, - embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], 0); - embeddings = ggml_acc(ctx0, embeddings, inp, - embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], model.class_embedding->nb[1]); - } + struct ggml_tensor * embeddings = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, hidden_size, num_positions, batch_size); ggml_set_name(embeddings, "embeddings"); ggml_set_input(embeddings); + embeddings = ggml_acc(ctx0, embeddings, model.class_embedding, + embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], 0); + + embeddings = ggml_acc(ctx0, embeddings, inp, + embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], model.class_embedding->nb[1]); struct ggml_tensor * positions = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions); ggml_set_name(positions, "positions"); @@ -590,7 +576,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 ggml_add(ctx0, embeddings, ggml_get_rows(ctx0, model.position_embeddings, positions)); // pre-layernorm - if (ctx->has_pre_norm) { + { embeddings = ggml_norm(ctx0, embeddings, eps); ggml_set_name(embeddings, "pre_ln"); @@ -678,14 +664,6 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 embeddings = cur; } - // post-layernorm - if (ctx->has_post_norm) { - embeddings = ggml_norm(ctx0, embeddings, eps); - ggml_set_name(embeddings, "post_ln"); - - embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.post_ln_w), model.post_ln_b); - } - // llava projector { embeddings = ggml_reshape_2d(ctx0, embeddings, embeddings->ne[0], embeddings->ne[1]); @@ -1170,39 +1148,12 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { } - try { - vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); - new_clip->has_class_embedding = true; - } catch (const std::exception& e) { - new_clip->has_class_embedding = false; - } - - try { - vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); - vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); - new_clip->has_pre_norm = true; - } catch (std::exception & e) { - new_clip->has_pre_norm = false; - } - - try { - vision_model.post_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "weight")); - vision_model.post_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "bias")); - new_clip->has_post_norm = true; - } catch (std::exception & e) { - new_clip->has_post_norm = false; - } - - try { - vision_model.patch_bias = get_tensor(new_clip->ctx_data, TN_PATCH_BIAS); - new_clip->has_patch_bias = true; - } catch (std::exception & e) { - new_clip->has_patch_bias = false; - } - try { vision_model.patch_embeddings = get_tensor(new_clip->ctx_data, TN_PATCH_EMBD); + vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); vision_model.position_embeddings = get_tensor(new_clip->ctx_data, format(TN_POS_EMBD, "v")); + vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); + vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); } catch(const std::exception& e) { LOG_TEE("%s: failed to load vision model tensors\n", __func__); } From c12452c7aec8a02264afc00196a13caa591a13ac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= <johannesg@5d6.de> Date: Wed, 8 May 2024 21:53:08 +0200 Subject: [PATCH 15/64] JSON: [key] -> .at(key), assert() -> GGML_ASSERT (#7143) --- common/common.cpp | 14 ++--- common/json-schema-to-grammar.h | 4 ++ examples/server/server.cpp | 74 ++++++++++++++------------- examples/server/utils.hpp | 8 +-- tests/test-json-schema-to-grammar.cpp | 1 + 5 files changed, 56 insertions(+), 45 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 4a9da284e7ec9..0535508ba98df 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1,4 +1,6 @@ #include "common.h" +// Change JSON_ASSERT from assert() to GGML_ASSERT: +#define JSON_ASSERT GGML_ASSERT #include "json.hpp" #include "json-schema-to-grammar.h" #include "llama.h" @@ -1969,18 +1971,18 @@ static bool llama_download_file(const std::string & url, const std::string & pat try { metadata_in >> metadata; fprintf(stderr, "%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str()); - if (metadata.contains("url") && metadata["url"].is_string()) { - auto previous_url = metadata["url"].get<std::string>(); + if (metadata.contains("url") && metadata.at("url").is_string()) { + auto previous_url = metadata.at("url").get<std::string>(); if (previous_url != url) { fprintf(stderr, "%s: Model URL mismatch: %s != %s\n", __func__, url.c_str(), previous_url.c_str()); return false; } } - if (metadata.contains("etag") && metadata["etag"].is_string()) { - etag = metadata["etag"]; + if (metadata.contains("etag") && metadata.at("etag").is_string()) { + etag = metadata.at("etag"); } - if (metadata.contains("lastModified") && metadata["lastModified"].is_string()) { - last_modified = metadata["lastModified"]; + if (metadata.contains("lastModified") && metadata.at("lastModified").is_string()) { + last_modified = metadata.at("lastModified"); } } catch (const nlohmann::json::exception & e) { fprintf(stderr, "%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what()); diff --git a/common/json-schema-to-grammar.h b/common/json-schema-to-grammar.h index e1abed3037582..41623b3464528 100644 --- a/common/json-schema-to-grammar.h +++ b/common/json-schema-to-grammar.h @@ -1,4 +1,8 @@ #pragma once + +#include "ggml.h" +// Change JSON_ASSERT from assert() to GGML_ASSERT: +#define JSON_ASSERT GGML_ASSERT #include "json.hpp" std::string json_schema_to_grammar(const nlohmann::ordered_json& schema); diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 06c0be56749ab..305f79492a055 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -12,6 +12,8 @@ // increase max payload length to allow use of larger context size #define CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 1048576 #include "httplib.h" +// Change JSON_ASSERT from assert() to GGML_ASSERT: +#define JSON_ASSERT GGML_ASSERT #include "json.hpp" // auto generated files (update with ./deps.sh) @@ -859,7 +861,7 @@ struct server_context { slot.sparams.min_keep = json_value(data, "min_keep", default_sparams.min_keep); // process "json_schema" and "grammar" - if (data.contains("json_schema") && !data["json_schema"].is_null() && data.contains("grammar") && !data["grammar"].is_null()) { + if (data.contains("json_schema") && !data.at("json_schema").is_null() && data.contains("grammar") && !data.at("grammar").is_null()) { send_error(task, "Either \"json_schema\" or \"grammar\" can be specified, but not both", ERROR_TYPE_INVALID_REQUEST); return false; } else if (data.contains("json_schema") && !data.contains("grammar")) { @@ -1512,7 +1514,7 @@ struct server_context { // add subtasks for (int i = 0; i < prompt_count; i++) { json subtask_data = multiprompt_task.data; - subtask_data["prompt"] = subtask_data["prompt"][i]; + subtask_data["prompt"] = subtask_data.at("prompt")[i]; // subtasks inherit everything else (infill mode, embedding mode, etc.) request_completion(subtask_ids[i], id_multi, subtask_data, multiprompt_task.infill, multiprompt_task.embedding); @@ -1532,7 +1534,7 @@ struct server_context { } if (task.data.contains("system_prompt")) { - system_prompt_set(task.data["system_prompt"]); + system_prompt_set(task.data.at("system_prompt")); for (server_slot & slot : slots) { slot.n_past = 0; @@ -1644,7 +1646,7 @@ struct server_context { } break; case SERVER_TASK_TYPE_SLOT_SAVE: { - int id_slot = task.data["id_slot"]; + int id_slot = task.data.at("id_slot"); server_slot * slot = get_slot(id_slot); if (slot == nullptr) { send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST); @@ -1654,8 +1656,8 @@ struct server_context { const size_t token_count = slot->cache_tokens.size(); const int64_t t_start = ggml_time_us(); - std::string filename = task.data["filename"]; - std::string filepath = task.data["filepath"]; + std::string filename = task.data.at("filename"); + std::string filepath = task.data.at("filepath"); const size_t nwrite = llama_state_seq_save_file(ctx, filepath.c_str(), slot->id + 1, slot->cache_tokens.data(), token_count); @@ -1679,7 +1681,7 @@ struct server_context { } break; case SERVER_TASK_TYPE_SLOT_RESTORE: { - int id_slot = task.data["id_slot"]; + int id_slot = task.data.at("id_slot"); server_slot * slot = get_slot(id_slot); if (slot == nullptr) { send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST); @@ -1688,8 +1690,8 @@ struct server_context { const int64_t t_start = ggml_time_us(); - std::string filename = task.data["filename"]; - std::string filepath = task.data["filepath"]; + std::string filename = task.data.at("filename"); + std::string filepath = task.data.at("filepath"); slot->cache_tokens.resize(slot->n_ctx); size_t token_count = 0; @@ -1721,7 +1723,7 @@ struct server_context { } break; case SERVER_TASK_TYPE_SLOT_ERASE: { - int id_slot = task.data["id_slot"]; + int id_slot = task.data.at("id_slot"); server_slot * slot = get_slot(id_slot); if (slot == nullptr) { send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST); @@ -3136,8 +3138,8 @@ int main(int argc, char ** argv) { server_task_result result = ctx_server.queue_results.recv(task.id); ctx_server.queue_results.remove_waiting_task_id(task.id); - const int n_idle_slots = result.data["idle"]; - const int n_processing_slots = result.data["processing"]; + const int n_idle_slots = result.data.at("idle"); + const int n_processing_slots = result.data.at("processing"); json health = { {"status", "ok"}, @@ -3147,7 +3149,7 @@ int main(int argc, char ** argv) { res.status = 200; // HTTP OK if (sparams.slots_endpoint && req.has_param("include_slots")) { - health["slots"] = result.data["slots"]; + health["slots"] = result.data.at("slots"); } if (n_idle_slots == 0) { @@ -3191,7 +3193,7 @@ int main(int argc, char ** argv) { server_task_result result = ctx_server.queue_results.recv(task.id); ctx_server.queue_results.remove_waiting_task_id(task.id); - res.set_content(result.data["slots"].dump(), "application/json"); + res.set_content(result.data.at("slots").dump(), "application/json"); res.status = 200; // HTTP OK }; @@ -3218,32 +3220,32 @@ int main(int argc, char ** argv) { json data = result.data; - const uint64_t n_prompt_tokens_processed = data["n_prompt_tokens_processed"]; - const uint64_t t_prompt_processing = data["t_prompt_processing"]; + const uint64_t n_prompt_tokens_processed = data.at("n_prompt_tokens_processed"); + const uint64_t t_prompt_processing = data.at("t_prompt_processing"); - const uint64_t n_tokens_predicted = data["n_tokens_predicted"]; - const uint64_t t_tokens_generation = data["t_tokens_generation"]; + const uint64_t n_tokens_predicted = data.at("n_tokens_predicted"); + const uint64_t t_tokens_generation = data.at("t_tokens_generation"); - const int32_t kv_cache_used_cells = data["kv_cache_used_cells"]; + const int32_t kv_cache_used_cells = data.at("kv_cache_used_cells"); // metrics definition: https://prometheus.io/docs/practices/naming/#metric-names json all_metrics_def = json { {"counter", {{ {"name", "prompt_tokens_total"}, {"help", "Number of prompt tokens processed."}, - {"value", (uint64_t) data["n_prompt_tokens_processed_total"]} + {"value", (uint64_t) data.at("n_prompt_tokens_processed_total")} }, { {"name", "prompt_seconds_total"}, {"help", "Prompt process time"}, - {"value", (uint64_t) data["t_prompt_processing_total"] / 1.e3} + {"value", (uint64_t) data.at("t_prompt_processing_total") / 1.e3} }, { {"name", "tokens_predicted_total"}, {"help", "Number of generation tokens processed."}, - {"value", (uint64_t) data["n_tokens_predicted_total"]} + {"value", (uint64_t) data.at("n_tokens_predicted_total")} }, { {"name", "tokens_predicted_seconds_total"}, {"help", "Predict process time"}, - {"value", (uint64_t) data["t_tokens_generation_total"] / 1.e3} + {"value", (uint64_t) data.at("t_tokens_generation_total") / 1.e3} }}}, {"gauge", {{ {"name", "prompt_tokens_seconds"}, @@ -3260,15 +3262,15 @@ int main(int argc, char ** argv) { },{ {"name", "kv_cache_tokens"}, {"help", "KV-cache tokens."}, - {"value", (uint64_t) data["kv_cache_tokens_count"]} + {"value", (uint64_t) data.at("kv_cache_tokens_count")} },{ {"name", "requests_processing"}, {"help", "Number of request processing."}, - {"value", (uint64_t) data["processing"]} + {"value", (uint64_t) data.at("processing")} },{ {"name", "requests_deferred"}, {"help", "Number of request deferred."}, - {"value", (uint64_t) data["deferred"]} + {"value", (uint64_t) data.at("deferred")} }}} }; @@ -3279,8 +3281,8 @@ int main(int argc, char ** argv) { const auto & metrics_def = el.value(); for (const auto & metric_def : metrics_def) { - const std::string name = metric_def["name"]; - const std::string help = metric_def["help"]; + const std::string name = metric_def.at("name"); + const std::string help = metric_def.at("help"); auto value = json_value(metric_def, "value", 0.); prometheus << "# HELP llamacpp:" << name << " " << help << "\n" @@ -3289,7 +3291,7 @@ int main(int argc, char ** argv) { } } - const int64_t t_start = data["t_start"]; + const int64_t t_start = data.at("t_start"); res.set_header("Process-Start-Time-Unix", std::to_string(t_start)); res.set_content(prometheus.str(), "text/plain; version=0.0.4"); @@ -3298,7 +3300,7 @@ int main(int argc, char ** argv) { const auto handle_slots_save = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) { json request_data = json::parse(req.body); - std::string filename = request_data["filename"]; + std::string filename = request_data.at("filename"); if (!validate_file_name(filename)) { res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST)); return; @@ -3328,7 +3330,7 @@ int main(int argc, char ** argv) { const auto handle_slots_restore = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) { json request_data = json::parse(req.body); - std::string filename = request_data["filename"]; + std::string filename = request_data.at("filename"); if (!validate_file_name(filename)) { res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST)); return; @@ -3648,7 +3650,7 @@ int main(int argc, char ** argv) { std::vector<llama_token> tokens; if (body.count("content") != 0) { const bool add_special = json_value(body, "add_special", false); - tokens = ctx_server.tokenize(body["content"], add_special); + tokens = ctx_server.tokenize(body.at("content"), add_special); } const json data = format_tokenizer_response(tokens); return res.set_content(data.dump(), "application/json; charset=utf-8"); @@ -3660,7 +3662,7 @@ int main(int argc, char ** argv) { std::string content; if (body.count("tokens") != 0) { - const std::vector<llama_token> tokens = body["tokens"]; + const std::vector<llama_token> tokens = body.at("tokens"); content = tokens_to_str(ctx_server.ctx, tokens.cbegin(), tokens.cend()); } @@ -3683,10 +3685,10 @@ int main(int argc, char ** argv) { json prompt; if (body.count("input") != 0) { is_openai = true; - prompt = body["input"]; + prompt = body.at("input"); } else if (body.count("content") != 0) { // with "content", we only support single prompt - prompt = std::vector<std::string>{body["content"]}; + prompt = std::vector<std::string>{body.at("content")}; } else { res_error(res, format_error_response("\"input\" or \"content\" must be provided", ERROR_TYPE_INVALID_REQUEST)); return; @@ -3705,7 +3707,7 @@ int main(int argc, char ** argv) { if (!result.error) { if (result.data.count("results")) { // result for multi-task - responses = result.data["results"]; + responses = result.data.at("results"); } else { // result for single task responses = std::vector<json>{result.data}; diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index af12f497d327d..d872b63f537f4 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -3,6 +3,8 @@ #include "llama.h" #include "common.h" +// Change JSON_ASSERT from assert() to GGML_ASSERT: +#define JSON_ASSERT GGML_ASSERT #include "json.hpp" #include <string> @@ -373,11 +375,11 @@ static json oaicompat_completion_params_parse( llama_params["top_p"] = json_value(body, "top_p", 1.0); // Apply chat template to the list of messages - llama_params["prompt"] = format_chat(model, chat_template, body["messages"]); + llama_params["prompt"] = format_chat(model, chat_template, body.at("messages")); // Handle "stop" field - if (body.contains("stop") && body["stop"].is_string()) { - llama_params["stop"] = json::array({body["stop"].get<std::string>()}); + if (body.contains("stop") && body.at("stop").is_string()) { + llama_params["stop"] = json::array({body.at("stop").get<std::string>()}); } else { llama_params["stop"] = json_value(body, "stop", json::array()); } diff --git a/tests/test-json-schema-to-grammar.cpp b/tests/test-json-schema-to-grammar.cpp index b2ce4d260a5a4..c5361b5b8912c 100755 --- a/tests/test-json-schema-to-grammar.cpp +++ b/tests/test-json-schema-to-grammar.cpp @@ -2,6 +2,7 @@ #undef NDEBUG #endif +#include <cassert> #include <fstream> #include <sstream> #include <regex> From bc4bba364fb96d908f2698e908648df5e6f55e02 Mon Sep 17 00:00:00 2001 From: agray3 <agray3@users.noreply.github.com> Date: Wed, 8 May 2024 21:55:49 +0100 Subject: [PATCH 16/64] Introduction of CUDA Graphs to LLama.cpp (#6766) * DRAFT: Introduction of CUDA Graphs to LLama.cpp * FIx issues raised in comments * Tidied to now only use CUDA runtime (not mixed with driver calls) * disable for multi-gpu and batch size > 1 * Disable CUDA graphs for old GPU arch and with env var * added missing CUDA_CHECKs * Addressed comments * further addressed comments * limit to GGML_ALLOW_CUDA_GRAPHS defined in llama.cpp cmake * Added more comprehensive graph node checking * With mechanism to fall back if graph capture fails * Revert "With mechanism to fall back if graph capture fails" This reverts commit eb9f15fb6fcb81384f732c4601a5b25c016a5143. * Fall back if graph capture fails and address other comments * - renamed GGML_ALLOW_CUDA_GRAPHS to GGML_CUDA_USE_GRAPHS - rename env variable to disable CUDA graphs to GGML_CUDA_DISABLE_GRAPHS - updated Makefile build to enable CUDA graphs - removed graph capture failure checking in ggml_cuda_error using a global variable to track this is not thread safe, but I am also not safistied with checking an error by string if this is necessary to workaround some issues with graph capture with eg. cuBLAS, we can pass the ggml_backend_cuda_context to the error checking macro and store the result in the context - fixed several resource leaks - fixed issue with zero node graphs - changed fixed size arrays to vectors - removed the count of number of evaluations before start capturing, and instead changed the capture mode to relaxed - removed the check for multiple devices so that it is still possible to use a single device, instead checks for split buffers to disable cuda graphs with -sm row - changed the op for checking batch size to GGML_OP_ADD, should be more reliable than GGML_OP_SOFT_MAX - code style fixes - things to look into - VRAM usage of the cudaGraphExec_t, if it is significant we may need to make it optional - possibility of using cudaStreamBeginCaptureToGraph to keep track of which ggml graph nodes correspond to which cuda graph nodes * fix build without cuda graphs * remove outdated comment * replace minimum cc value with a constant --------- Co-authored-by: slaren <slarengh@gmail.com> --- CMakeLists.txt | 1 + Makefile | 2 +- ggml-cuda.cu | 300 +++++++++++++++++++++++++++++++++++++++++-- ggml-cuda/clamp.cu | 1 - ggml-cuda/common.cuh | 40 ++++++ ggml-cuda/convert.cu | 4 +- ggml-cuda/cpy.cu | 29 +++++ ggml-cuda/cpy.cuh | 2 + ggml-cuda/mmq.cu | 30 ++--- ggml-cuda/mmvq.cu | 6 +- ggml-cuda/scale.cu | 1 - 11 files changed, 372 insertions(+), 44 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 0e22ee2301878..07b3a4388b0a6 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -405,6 +405,7 @@ if (LLAMA_CUDA) list(APPEND GGML_SOURCES_CUDA "ggml-cuda.cu") add_compile_definitions(GGML_USE_CUDA) + add_compile_definitions(GGML_CUDA_USE_GRAPHS) if (LLAMA_CUDA_FORCE_DMMV) add_compile_definitions(GGML_CUDA_FORCE_DMMV) endif() diff --git a/Makefile b/Makefile index c568dd008f350..3fa56d13a4671 100644 --- a/Makefile +++ b/Makefile @@ -433,7 +433,7 @@ ifdef LLAMA_CUDA else CUDA_PATH ?= /usr/local/cuda endif - MK_CPPFLAGS += -DGGML_USE_CUDA -I$(CUDA_PATH)/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include + MK_CPPFLAGS += -DGGML_USE_CUDA -I$(CUDA_PATH)/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include -DGGML_CUDA_USE_GRAPHS MK_LDFLAGS += -lcuda -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L$(CUDA_PATH)/lib64 -L/usr/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib -L/usr/lib/wsl/lib OBJS += ggml-cuda.o OBJS += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu)) diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 2d1742c82a265..6f89a7cc3e900 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -1647,7 +1647,7 @@ static void ggml_cuda_op_mul_mat( } } -static void ggml_cuda_mul_mat_vec_p021(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst){ +static void ggml_cuda_mul_mat_vec_p021(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { GGML_ASSERT(ggml_is_permuted(src0) && ggml_is_permuted(src1)); GGML_ASSERT(ggml_backend_buffer_is_cuda(src0->buffer)); GGML_ASSERT(src0->nb[0] <= src0->nb[1] && src0->nb[2] <= src0->nb[3]); // 0213 permutation @@ -1670,7 +1670,7 @@ static void ggml_cuda_mul_mat_vec_p021(ggml_backend_cuda_context & ctx, const gg ggml_mul_mat_p021_f16_f32_cuda(src0_ddq, src1_ddf, dst_ddf, ne00, ne01, ne02, ne12, main_stream); } -static void ggml_cuda_mul_mat_vec_nc(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst){ +static void ggml_cuda_mul_mat_vec_nc(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { GGML_ASSERT(!ggml_is_transposed(src0)); GGML_ASSERT(!ggml_is_transposed(src1)); GGML_ASSERT(!ggml_is_permuted(src0)); @@ -2410,32 +2410,304 @@ GGML_CALL static void ggml_backend_cuda_synchronize(ggml_backend_t backend) { GGML_UNUSED(backend); } +static void set_ggml_graph_node_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) { + graph_node_properties->node_address = node->data; + graph_node_properties->node_op = node->op; + for (int i = 0; i < GGML_MAX_DIMS; i++) { + graph_node_properties->ne[i] = node->ne[i]; + graph_node_properties->nb[i] = node->nb[i]; + } + for (int i = 0; i < GGML_MAX_SRC; i++) { + graph_node_properties->src_address[i] = node->src[i] ? node->src[i]->data : nullptr; + } +} + +static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) { + if (node->data != graph_node_properties->node_address && + node->op != GGML_OP_CPY && + node->op != GGML_OP_VIEW) { + return false; + } + + if (node->op != graph_node_properties->node_op) { + return false; + } + + for (int i = 0; i < GGML_MAX_DIMS; i++) { + if (node->ne[i] != graph_node_properties->ne[i]) { + return false; + } + if (node->nb[i] != graph_node_properties->nb[i]) { + return false; + } + } + + for (int i = 0; i < GGML_MAX_SRC; i++) { + if (node->src[i] && + node->src[i]->data != graph_node_properties->src_address[i] && + node->op != GGML_OP_CPY && + node->op != GGML_OP_VIEW + ) { + return false; + } + } + return true; +} + GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) { ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context; ggml_cuda_set_device(cuda_ctx->device); - for (int i = 0; i < cgraph->n_nodes; i++) { - ggml_tensor * node = cgraph->nodes[i]; +#ifdef USE_CUDA_GRAPH + static const bool disable_cuda_graphs_due_to_env = (getenv("GGML_CUDA_DISABLE_GRAPHS") != nullptr); - if (ggml_is_empty(node) || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE || node->op == GGML_OP_NONE) { - continue; + // Objects required for CUDA Graph + if (cuda_ctx->cuda_graph == nullptr) { + cuda_ctx->cuda_graph.reset(new ggml_cuda_graph()); + } + + bool use_cuda_graph = true; + bool cuda_graph_update_required = false; + // pointer to CUDA cpy kernel, which is required to identify + // kernel parameters which need updated in the graph for each token + void * ggml_cuda_cpy_fn_ptr = nullptr; + + if (cuda_ctx->cuda_graph->graph == nullptr) { + if (ggml_cuda_info().devices[cuda_ctx->device].cc < CC_AMPERE) { + cuda_ctx->cuda_graph->disable_due_to_gpu_arch = true; +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to GPU architecture\n", __func__); +#endif + } + } + + // Disable CUDA graphs in presence of env var, old GPU, use-case which is changing too rapidly, + // or previous graph capture failure. + // Also disable for multi-gpu for now. TO DO investigate + if (disable_cuda_graphs_due_to_env + || cuda_ctx->cuda_graph->disable_due_to_gpu_arch + || cuda_ctx->cuda_graph->disable_due_to_too_many_updates + || cuda_ctx->cuda_graph->disable_due_to_failed_graph_capture) { + use_cuda_graph = false; + } + + if (use_cuda_graph) { + if (cuda_ctx->cuda_graph->instance == nullptr) { + cuda_graph_update_required = true; + } + + // Check if the graph size has changed + if (cuda_ctx->cuda_graph->ggml_graph_properties.size() != (size_t)cgraph->n_nodes) { + cuda_graph_update_required = true; + cuda_ctx->cuda_graph->ggml_graph_properties.resize(cgraph->n_nodes); + } + + // Loop over nodes in GGML graph to determine if CUDA graph update is required + // and store properties to allow this comparison for the next token + for (int i = 0; i < cgraph->n_nodes; i++) { + bool has_matching_properties = true; + if (!cuda_graph_update_required) { + has_matching_properties = ggml_graph_node_has_matching_properties(cgraph->nodes[i], &cuda_ctx->cuda_graph->ggml_graph_properties[i]); + } + if (!has_matching_properties) { + cuda_graph_update_required = true; + } + set_ggml_graph_node_properties(cgraph->nodes[i], &cuda_ctx->cuda_graph->ggml_graph_properties[i]); + } + + // Loop over nodes in GGML graph to obtain info needed for CUDA graph + cuda_ctx->cuda_graph->updated_kernel_arg.clear(); + for (int i = 0; i < cgraph->n_nodes; i++) { + ggml_tensor * node = cgraph->nodes[i]; + + if (node->src[0] && ggml_backend_buffer_is_cuda_split(node->src[0]->buffer)) { + use_cuda_graph = false; // Split buffers are not supported by CUDA graph capture +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to split buffer\n", __func__); +#endif + } + + if (node->op == GGML_OP_MUL_MAT_ID) { + use_cuda_graph = false; // This node type is not supported by CUDA graph capture +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to mul_mat_id\n", __func__); +#endif + } + + if (node->op == GGML_OP_ADD && node->src[1] && node->src[1]->ne[1] > 1) { + // disable CUDA graphs for batch size > 1 for now. + // Changes in batch size or context size can cause changes to the grid size of some kernels. + use_cuda_graph = false; +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to batch size > 1 [%s] [%ld %ld %ld %ld]\n", __func__, node->name, node->ne[0], node->ne[1], node->ne[2], node->ne[3]); +#endif + } + + if (node->op == GGML_OP_CPY) { + // store the copy op parameter which changes with each token. + cuda_ctx->cuda_graph->updated_kernel_arg.push_back((char **) &(node->src[1]->data)); + if (ggml_cuda_cpy_fn_ptr == nullptr) { + // store a pointer to the copy op CUDA kernel to identify it later + ggml_cuda_cpy_fn_ptr = ggml_cuda_cpy_fn(node->src[0], node->src[1]); + } + } + + if (!use_cuda_graph) { + break; + } + } + + // Disable CUDA graphs (from the next token) if the use-case is demanding too many consecutive graph updates. + if (cuda_graph_update_required) { + cuda_ctx->cuda_graph->number_consecutive_updates++; + } else { + cuda_ctx->cuda_graph->number_consecutive_updates = 0; } + if (cuda_ctx->cuda_graph->number_consecutive_updates >= 4) { + cuda_ctx->cuda_graph->disable_due_to_too_many_updates = true; +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to too many consecutive updates\n", __func__); +#endif + } + } + + if (use_cuda_graph && cuda_graph_update_required) { // Start CUDA graph capture + CUDA_CHECK(cudaStreamBeginCapture(cuda_ctx->stream(), cudaStreamCaptureModeRelaxed)); + } + +#else + bool use_cuda_graph = false; + bool cuda_graph_update_required = false; +#endif // USE_CUDA_GRAPH + + bool graph_evaluated_or_captured = false; + + while (!graph_evaluated_or_captured) { + // Only perform the graph execution if CUDA graphs are not enabled, or we are capturing the graph. + // With the use of CUDA graphs, the execution will be performed by the graph launch. + if (!use_cuda_graph || cuda_graph_update_required) { + for (int i = 0; i < cgraph->n_nodes; i++) { + ggml_tensor * node = cgraph->nodes[i]; + + if (ggml_is_empty(node) || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE || node->op == GGML_OP_NONE) { + continue; + } + #ifndef NDEBUG - assert(node->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device)); - for (int j = 0; j < GGML_MAX_SRC; j++) { - if (node->src[j] != nullptr) { - assert(node->src[j]->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) || ggml_backend_buffer_is_cuda_split(node->src[j]->buffer)); + assert(node->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device)); + for (int j = 0; j < GGML_MAX_SRC; j++) { + if (node->src[j] != nullptr) { + assert(node->src[j]->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) || ggml_backend_buffer_is_cuda_split(node->src[j]->buffer)); + } + } +#endif + + bool ok = ggml_cuda_compute_forward(*cuda_ctx, node); + if (!ok) { + fprintf(stderr, "%s: error: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); + } + GGML_ASSERT(ok); } } + +#ifdef USE_CUDA_GRAPH + if (use_cuda_graph && cuda_graph_update_required) { // End CUDA graph capture + if (cuda_ctx->cuda_graph->graph != nullptr) { + CUDA_CHECK(cudaGraphDestroy(cuda_ctx->cuda_graph->graph)); + cuda_ctx->cuda_graph->graph = nullptr; + } + CUDA_CHECK(cudaStreamEndCapture(cuda_ctx->stream(), &cuda_ctx->cuda_graph->graph)); + +#if 0 + if (disable_cuda_graphs_due_to_failed_capture) { + use_cuda_graph = false; + cuda_ctx->cuda_graph->disable_due_to_failed_graph_capture = true; +#ifndef NDEBUG + fprintf(stderr, "%s: disabling CUDA graphs due to failed graph capture\n", __func__); #endif + } else { + graph_evaluated_or_captured = true; // CUDA graph has been captured + } +#endif + graph_evaluated_or_captured = true; // CUDA graph has been captured + } else { + graph_evaluated_or_captured = true; // ggml graph has been directly evaluated + } + } - bool ok = ggml_cuda_compute_forward(*cuda_ctx, node); - if (!ok) { - fprintf(stderr, "%s: error: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); + if (use_cuda_graph) { + if (cuda_ctx->cuda_graph->instance == nullptr) { // Create executable graph from captured graph. + CUDA_CHECK(cudaGraphInstantiate(&cuda_ctx->cuda_graph->instance, cuda_ctx->cuda_graph->graph, NULL, NULL, 0)); } - GGML_ASSERT(ok); + + // Perform update to graph (if required for this token), and change copy parameter (required for every token) + + if (cuda_graph_update_required) { + // Extract nodes from graph + if (cuda_ctx->cuda_graph->num_nodes == 0) { + // First call with null argument gets number of nodes in graph + CUDA_CHECK(cudaGraphGetNodes(cuda_ctx->cuda_graph->graph, nullptr, &cuda_ctx->cuda_graph->num_nodes)); + } + // Subsequent call with non-null argument gets nodes + cuda_ctx->cuda_graph->nodes.resize(cuda_ctx->cuda_graph->num_nodes); + cuda_ctx->cuda_graph->params.resize(cuda_ctx->cuda_graph->num_nodes); + if (cuda_ctx->cuda_graph->num_nodes > 0) { + CUDA_CHECK(cudaGraphGetNodes(cuda_ctx->cuda_graph->graph, cuda_ctx->cuda_graph->nodes.data(), &cuda_ctx->cuda_graph->num_nodes)); + + // Loop over nodes, and extract kernel parameters from each node + for (size_t i = 0; i < cuda_ctx->cuda_graph->num_nodes; i++) { + cudaGraphNodeType node_type; + CUDA_CHECK(cudaGraphNodeGetType(cuda_ctx->cuda_graph->nodes[i], &node_type)); + if (node_type == cudaGraphNodeTypeKernel) { + cudaError_t stat = cudaGraphKernelNodeGetParams(cuda_ctx->cuda_graph->nodes[i], &cuda_ctx->cuda_graph->params[i]); // Get params using runtime + if (stat == cudaErrorInvalidDeviceFunction) { + // Fails due to incorrect handling by CUDA runtime of CUDA BLAS node. + // We don't need to update blas nodes, so clear error and move on. + cudaGetLastError(); + } else { + GGML_ASSERT(stat == cudaSuccess); + } + } + } + } + } + + // One of the arguments to the copy kernel is updated for each token, hence we need to + // replace that argument with the updated value in the CUDA graph + if (!cuda_graph_update_required) { // on update steps, the live parameters will already be captured + int k = 0; + for (size_t i = 0; i < cuda_ctx->cuda_graph->num_nodes; i++) { + if (cuda_ctx->cuda_graph->params[i].func == ggml_cuda_cpy_fn_ptr) { + char ** updated_kernel_arg_ptr = cuda_ctx->cuda_graph->updated_kernel_arg.at(k++); + cuda_ctx->cuda_graph->params[i].kernelParams[1] = updated_kernel_arg_ptr; + CUDA_CHECK(cudaGraphKernelNodeSetParams(cuda_ctx->cuda_graph->nodes[i], &cuda_ctx->cuda_graph->params[i])); + } + } + } + + // Update graph executable + cudaGraphExecUpdateResultInfo result_info; + cudaError_t stat = cudaGraphExecUpdate(cuda_ctx->cuda_graph->instance, cuda_ctx->cuda_graph->graph, &result_info); + if (stat == cudaErrorGraphExecUpdateFailure) { +#ifndef NDEBUG + fprintf(stderr, "%s: CUDA graph update failed\n", __func__); +#endif + // The pre-existing graph exec cannot be updated due to violated constraints + // so instead clear error and re-instantiate + cudaGetLastError(); + CUDA_CHECK(cudaGraphExecDestroy(cuda_ctx->cuda_graph->instance)); + cuda_ctx->cuda_graph->instance = nullptr; + CUDA_CHECK(cudaGraphInstantiate(&cuda_ctx->cuda_graph->instance, cuda_ctx->cuda_graph->graph, NULL, NULL, 0)); + } else { + GGML_ASSERT(stat == cudaSuccess); + } + // Launch graph + CUDA_CHECK(cudaGraphLaunch(cuda_ctx->cuda_graph->instance, cuda_ctx->stream())); +#else + graph_evaluated_or_captured = true; +#endif // USE_CUDA_GRAPH } return GGML_STATUS_SUCCESS; diff --git a/ggml-cuda/clamp.cu b/ggml-cuda/clamp.cu index 379ded042d897..8009a3e3d8607 100644 --- a/ggml-cuda/clamp.cu +++ b/ggml-cuda/clamp.cu @@ -31,5 +31,4 @@ void ggml_cuda_op_clamp(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { memcpy(&max, (float *) dst->op_params + 1, sizeof(float)); clamp_f32_cuda(src0_d, dst_d, min, max, ggml_nelements(src0), stream); - CUDA_CHECK(cudaGetLastError()); } diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh index b2627b7b4b77f..a4197f11ba779 100644 --- a/ggml-cuda/common.cuh +++ b/ggml-cuda/common.cuh @@ -19,6 +19,7 @@ #include <cassert> #include <cfloat> #include <string> +#include <vector> #if defined(GGML_USE_HIPBLAS) #include <hip/hip_runtime.h> @@ -526,6 +527,43 @@ struct ggml_tensor_extra_gpu { cudaEvent_t events[GGML_CUDA_MAX_DEVICES][GGML_CUDA_MAX_STREAMS]; // events for synchronizing multiple GPUs }; + +#if (CUDART_VERSION >= 12000) && defined(GGML_CUDA_USE_GRAPHS) +#define USE_CUDA_GRAPH +#endif + +struct ggml_graph_node_properties { + void * node_address; + ggml_op node_op; + int64_t ne[GGML_MAX_DIMS]; + size_t nb[GGML_MAX_DIMS]; + void * src_address[GGML_MAX_SRC]; +}; + +struct ggml_cuda_graph { +#ifdef USE_CUDA_GRAPH + ~ggml_cuda_graph() { + if (instance != nullptr) { + CUDA_CHECK(cudaGraphExecDestroy(instance)); + } + if (graph != nullptr) { + CUDA_CHECK(cudaGraphDestroy(graph)); + } + } + cudaGraph_t graph = nullptr; + cudaGraphExec_t instance = nullptr; + size_t num_nodes = 0; + std::vector<cudaGraphNode_t> nodes; + std::vector<cudaKernelNodeParams> params; + bool disable_due_to_gpu_arch = false; + bool disable_due_to_too_many_updates = false; + bool disable_due_to_failed_graph_capture = false; + int number_consecutive_updates = 0; + std::vector<ggml_graph_node_properties> ggml_graph_properties; + std::vector<char **> updated_kernel_arg; +#endif +}; + struct ggml_backend_cuda_context { int device; std::string name; @@ -534,6 +572,8 @@ struct ggml_backend_cuda_context { cudaStream_t streams[GGML_CUDA_MAX_DEVICES][GGML_CUDA_MAX_STREAMS] = { { nullptr } }; cublasHandle_t cublas_handles[GGML_CUDA_MAX_DEVICES] = {nullptr}; + std::unique_ptr<ggml_cuda_graph> cuda_graph; + explicit ggml_backend_cuda_context(int device) : device(device), name(GGML_CUDA_NAME + std::to_string(device)) { diff --git a/ggml-cuda/convert.cu b/ggml-cuda/convert.cu index 75e50c9856123..830e2d7566162 100644 --- a/ggml-cuda/convert.cu +++ b/ggml-cuda/convert.cu @@ -727,7 +727,6 @@ static void convert_unary_cuda(const void * __restrict__ vx, dst_t * __restrict_ } to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) { - int id; switch (type) { case GGML_TYPE_Q4_0: return dequantize_row_q4_0_cuda; @@ -738,8 +737,7 @@ to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) { case GGML_TYPE_Q5_1: return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; case GGML_TYPE_Q8_0: - CUDA_CHECK(cudaGetDevice(&id)); - if (ggml_cuda_info().devices[id].cc >= CC_PASCAL) { + if (ggml_cuda_info().devices[ggml_cuda_get_device()].cc >= CC_PASCAL) { return dequantize_block_q8_0_f16_cuda; } return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; diff --git a/ggml-cuda/cpy.cu b/ggml-cuda/cpy.cu index 16d9c8fffb4b3..12d741f017d3b 100644 --- a/ggml-cuda/cpy.cu +++ b/ggml-cuda/cpy.cu @@ -459,3 +459,32 @@ void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; ggml_cuda_cpy(ctx, src0, dst); } + +void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) { + if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32) { + return (void*) cpy_f32_f16<cpy_1_f32_f32>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16) { + return (void*) cpy_f32_f16<cpy_1_f32_f16>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) { + return (void*) cpy_f32_q<cpy_blck_f32_q8_0, QK8_0>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) { + return (void*) cpy_f32_q<cpy_blck_f32_q4_0, QK4_0>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) { + return (void*) cpy_f32_q<cpy_blck_f32_q4_1, QK4_1>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) { + return (void*) cpy_f32_q<cpy_blck_f32_q5_0, QK5_0>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) { + return (void*) cpy_f32_q<cpy_blck_f32_iq4_nl, QK4_NL>; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) { + return (void*) cpy_f32_q<cpy_blck_f32_q5_1, QK5_1>; + } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) { + return (void*) cpy_f32_f16<cpy_1_f32_f16>; + } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) { + return (void*) cpy_f32_f16<cpy_1_f16_f32>; + } else { + fprintf(stderr, "%s: unsupported type combination (%s to %s)\n", __func__, + ggml_type_name(src0->type), ggml_type_name(src1->type)); + GGML_ASSERT(false); + } +} + diff --git a/ggml-cuda/cpy.cuh b/ggml-cuda/cpy.cuh index f0b2c453bfe6a..7961674266ee1 100644 --- a/ggml-cuda/cpy.cuh +++ b/ggml-cuda/cpy.cuh @@ -5,3 +5,5 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1); void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst); + +void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1); diff --git a/ggml-cuda/mmq.cu b/ggml-cuda/mmq.cu index 60d6616a860f7..7948f1b1237fa 100644 --- a/ggml-cuda/mmq.cu +++ b/ggml-cuda/mmq.cu @@ -1735,8 +1735,7 @@ static void ggml_mul_mat_q4_0_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -1780,8 +1779,7 @@ static void ggml_mul_mat_q4_1_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -1825,8 +1823,7 @@ static void ggml_mul_mat_q5_0_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -1870,8 +1867,7 @@ static void ggml_mul_mat_q5_1_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -1915,8 +1911,7 @@ static void ggml_mul_mat_q8_0_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -1960,8 +1955,7 @@ static void ggml_mul_mat_q2_K_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -2007,8 +2001,7 @@ static void ggml_mul_mat_q3_K_q8_1_cuda( #if QK_K == 256 - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -2053,8 +2046,7 @@ static void ggml_mul_mat_q4_K_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -2098,8 +2090,7 @@ static void ggml_mul_mat_q5_K_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; @@ -2143,8 +2134,7 @@ static void ggml_mul_mat_q6_K_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); const int compute_capability = ggml_cuda_info().devices[id].cc; int mmq_x, mmq_y, nwarps; diff --git a/ggml-cuda/mmvq.cu b/ggml-cuda/mmvq.cu index 3965590017b95..65cc1bcaad697 100644 --- a/ggml-cuda/mmvq.cu +++ b/ggml-cuda/mmvq.cu @@ -89,8 +89,7 @@ static void mul_mat_vec_q_cuda( GGML_ASSERT(ncols_x % qk == 0); GGML_ASSERT(ncols_y <= MMVQ_MAX_BATCH_SIZE); - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); int64_t nwarps = 1; int64_t rows_per_cuda_block = 1; @@ -328,8 +327,7 @@ void ggml_cuda_op_mul_mat_vec_q( const int64_t ne0 = dst->ne[0]; - int id; - CUDA_CHECK(cudaGetDevice(&id)); + int id = ggml_cuda_get_device(); // the main device has a larger memory buffer to hold the results from all GPUs // nrows_dst == nrows of the matrix that the kernel writes into diff --git a/ggml-cuda/scale.cu b/ggml-cuda/scale.cu index 6e3617d1cdbd5..1405e066e86a2 100644 --- a/ggml-cuda/scale.cu +++ b/ggml-cuda/scale.cu @@ -28,5 +28,4 @@ void ggml_cuda_op_scale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { memcpy(&scale, dst->op_params, sizeof(float)); scale_f32_cuda(src0_d, dst_d, scale, ggml_nelements(src0), stream); - CUDA_CHECK(cudaGetLastError()); } From f98eb31c517c95960df1d0abc48002787f145f3b Mon Sep 17 00:00:00 2001 From: compilade <git@compilade.net> Date: Wed, 8 May 2024 18:16:38 -0400 Subject: [PATCH 17/64] convert-hf : save memory with lazy evaluation (#7075) * convert-hf : begin refactoring write_tensor * convert : upgrade to sentencepiece v0.2.0 * convert-hf : remove unused n_dims in extra_*_tensors * convert-hf : simplify MoE weights stacking * convert-hf : flake8 linter doesn't like semicolons * convert-hf : allow unusual model part names For example, loading `model-00001-of-00001.safetensors` now works. * convert-hf : fix stacking MoE expert tensors `torch.stack` and `torch.cat` don't do the same thing. * convert-hf : fix Mamba conversion Tested to work even with a SentencePiece-based tokenizer. * convert : use a string for the SentencePiece tokenizer path * convert-hf : display tensor shape * convert-hf : convert norms to f32 by default * convert-hf : sort model part names `os.listdir` is said to list files in arbitrary order. Sorting the file names should let "model-00009-of-00042.safetensors" be loaded before "model-00010-of-00042.safetensors". * convert-hf : use an ABC for Model again It seems Protocol can't be used as a statically type-checked ABC, because its subclasses also can't be instantiated. (why did it seem to work?) At least there's still a way to throw an error when forgetting to define the `model_arch` property of any registered Model subclasses. * convert-hf : use a plain class for Model, and forbid direct instantiation There are no abstract methods used anyway, so using ABC isn't really necessary. * convert-hf : more consistent formatting of cmdline args * convert-hf : align the message logged for converted tensors * convert-hf : fix Refact conversion * convert-hf : save memory with lazy evaluation * convert-hf : flake8 doesn't like lowercase L as a variable name * convert-hf : remove einops requirement for InternLM2 * convert-hf : faster model parts loading Instead of pre-loading them all into a dict, iterate on the tensors in the model parts progressively as needed in Model.write_tensors Conversion for some architectures relies on checking for the presence of specific tensor names, so for multi-part models, the weight map is read from the relevant json file to quickly get these names up-front. * convert-hf : minor changes for consistency * gguf-py : add tqdm as a dependency It's small, and used for a progress bar in GGUFWriter.write_tensors_to_file --- convert-hf-to-gguf.py | 1969 +++++++---------- convert.py | 20 +- examples/server/tests/features/steps/steps.py | 2 +- gguf-py/gguf/constants.py | 2 +- gguf-py/gguf/gguf_reader.py | 8 +- gguf-py/gguf/gguf_writer.py | 77 +- gguf-py/gguf/vocab.py | 6 +- gguf-py/pyproject.toml | 1 + gguf-py/scripts/gguf-dump.py | 2 +- gguf-py/scripts/gguf-new-metadata.py | 12 +- pyrightconfig.json | 3 + ...requirements-convert-hf-to-gguf-update.txt | 1 - .../requirements-convert-hf-to-gguf.txt | 1 - requirements/requirements-convert.txt | 2 +- 14 files changed, 847 insertions(+), 1259 deletions(-) create mode 100644 pyrightconfig.json diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 454e9fcdd784e..1dc18b2a57721 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -9,11 +9,10 @@ import os import re import sys -from abc import ABC, abstractmethod from enum import IntEnum from pathlib import Path from hashlib import sha256 -from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterator, Sequence, TypeVar, cast +from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Sequence, TypeVar, cast, overload import numpy as np import torch @@ -25,7 +24,7 @@ sys.path.insert(1, str(Path(__file__).parent / 'gguf-py')) import gguf -from convert import LlamaHfVocab, permute +from convert import LlamaHfVocab logger = logging.getLogger("hf-to-gguf") @@ -44,29 +43,55 @@ class SentencePieceTokenTypes(IntEnum): AnyModel = TypeVar("AnyModel", bound="type[Model]") -class Model(ABC): +class Model: _model_classes: dict[str, type[Model]] = {} - def __init__(self, dir_model: Path, ftype: int, fname_out: Path, is_big_endian: bool, use_temp_file: bool): + dir_model: Path + ftype: int + fname_out: Path + is_big_endian: bool + endianess: gguf.GGUFEndian + use_temp_file: bool + lazy: bool + part_names: list[str] + is_safetensors: bool + hparams: dict[str, Any] + gguf_writer: gguf.GGUFWriter + block_count: int + tensor_map: gguf.TensorNameMap + tensor_names: set[str] | None + + # subclasses should define this! + model_arch: gguf.MODEL_ARCH + + def __init__(self, dir_model: Path, ftype: int, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool): + if self.__class__ == Model: + raise TypeError(f"{self.__class__.__name__!r} should not be directly instantiated") self.dir_model = dir_model self.ftype = ftype self.fname_out = fname_out self.is_big_endian = is_big_endian self.endianess = gguf.GGUFEndian.BIG if is_big_endian else gguf.GGUFEndian.LITTLE self.use_temp_file = use_temp_file - self.is_safetensors = self._is_model_safetensors() - self.num_parts = Model.count_model_parts(self.dir_model, ".safetensors" if self.is_safetensors else ".bin") - self.part_names = self._get_part_names() + self.lazy = not eager + self.part_names = Model.get_model_part_names(self.dir_model, ".safetensors") + self.is_safetensors = len(self.part_names) > 0 + if not self.is_safetensors: + self.part_names = Model.get_model_part_names(self.dir_model, ".bin") self.hparams = Model.load_hparams(self.dir_model) self.gguf_writer = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file) self.block_count = self.find_hparam(["n_layers", "num_hidden_layers", "n_layer"]) + self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count) + self.tensor_names = None - @property - @abstractmethod - def model_arch(self) -> gguf.MODEL_ARCH: - pass + @classmethod + def __init_subclass__(cls): + # can't use an abstract property, because overriding it without type errors + # would require using decorated functions instead of simply defining the property + if "model_arch" not in cls.__dict__: + raise TypeError(f"Missing property 'model_arch' for {cls.__name__!r}") - def find_hparam(self, keys: Sequence[str], optional: bool = False) -> Any: + def find_hparam(self, keys: Iterable[str], optional: bool = False) -> Any: key = next((k for k in keys if k in self.hparams), None) if key is not None: return self.hparams[key] @@ -78,6 +103,22 @@ def set_vocab(self): self._set_vocab_gpt2() def get_tensors(self) -> Iterator[tuple[str, Tensor]]: + tensor_names_from_parts: set[str] = set() + + if len(self.part_names) > 1: + self.tensor_names = set() + index_name = "model.safetensors" if self.is_safetensors else "pytorch_model.bin" + index_name += ".index.json" + logger.info(f"gguf: loading model weight map from '{index_name}'") + with open(self.dir_model / index_name, "r", encoding="utf-8") as f: + index: dict[str, Any] = json.load(f) + weight_map = index.get("weight_map") + if weight_map is None or not isinstance(weight_map, dict): + raise ValueError(f"Can't load 'weight_map' from {index_name!r}") + self.tensor_names.update(weight_map.keys()) + else: + self.tensor_names = tensor_names_from_parts + for part_name in self.part_names: logger.info(f"gguf: loading model part '{part_name}'") ctx: ContextManager[Any] @@ -88,10 +129,33 @@ def get_tensors(self) -> Iterator[tuple[str, Tensor]]: ctx = contextlib.nullcontext(torch.load(str(self.dir_model / part_name), map_location="cpu", mmap=True, weights_only=True)) with ctx as model_part: + tensor_names_from_parts.update(model_part.keys()) + for name in model_part.keys(): data = model_part.get_tensor(name) if self.is_safetensors else model_part[name] + if self.lazy: + data = LazyTorchTensor.from_eager(data) yield name, data + # only verify tensor name presence; it doesn't matter if they are not in the right files + if len(sym_diff := tensor_names_from_parts.symmetric_difference(self.tensor_names)) > 0: + raise ValueError(f"Mismatch between weight map and model parts for tensor names: {sym_diff}") + + def format_tensor_name(self, key: gguf.MODEL_TENSOR, bid: int | None = None, suffix: str = ".weight") -> str: + name: str = gguf.TENSOR_NAMES[key] + if key not in gguf.MODEL_TENSORS[self.model_arch]: + raise ValueError(f"Missing {key!r} for MODEL_TENSORS of {self.model_arch!r}") + if "{bid}" in name: + assert bid is not None + name = name.format(bid=bid) + return name + suffix + + def map_tensor_name(self, name: str, try_suffixes: Sequence[str] = (".weight", ".bias")) -> str: + new_name = self.tensor_map.get_name(key=name, try_suffixes=try_suffixes) + if new_name is None: + raise ValueError(f"Can not map tensor {name!r}") + return new_name + def set_gguf_parameters(self): self.gguf_writer.add_name(self.dir_model.name) self.gguf_writer.add_block_count(self.block_count) @@ -135,12 +199,27 @@ def set_gguf_parameters(self): self.gguf_writer.add_file_type(self.ftype) logger.info(f"gguf: file type = {self.ftype}") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + + return [(self.map_tensor_name(name), data_torch)] + + def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del name, new_name, bid, n_dims # unused + + return False + + def extra_f16_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del name, new_name, bid, n_dims # unused + + return False + def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) + max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,") + for name, data_torch in self.get_tensors(): # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): + if name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")): continue old_dtype = data_torch.dtype @@ -149,37 +228,52 @@ def write_tensors(self): if data_torch.dtype not in (torch.float16, torch.float32): data_torch = data_torch.to(torch.float32) - data = data_torch.squeeze().numpy() + # use the first number-like part of the tensor name as the block id + bid = None + for part in name.split("."): + if part.isdecimal(): + bid = int(part) + break + + for new_name, data in ((n, d.squeeze().numpy()) for n, d in self.modify_tensors(data_torch, name, bid)): + data: np.ndarray = data # type hint + n_dims = len(data.shape) + data_dtype = data.dtype - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + # if f32 desired, convert any float16 to float32 + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) - n_dims = len(data.shape) - data_dtype = data.dtype + # when both are True, f32 should win + extra_f32 = self.extra_f32_tensors(name, new_name, bid, n_dims) + extra_f16 = self.extra_f16_tensors(name, new_name, bid, n_dims) + + # Most of the codebase that takes in 1D tensors or norms only handles F32 tensors + extra_f32 = extra_f32 or n_dims == 1 or new_name.endswith("_norm.weight") + + # if f16 desired, convert any float32 2-dim weight tensors to float16 + extra_f16 = extra_f16 or (name.endswith(".weight") and n_dims >= 2) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + # when both extra_f32 and extra_f16 are False, convert to float32 by default + if self.ftype == 1 and data_dtype == np.float16 and (extra_f32 or not extra_f16): + data = data.astype(np.float32) - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")): - data = data.astype(np.float32) + if self.ftype == 1 and data_dtype == np.float32 and extra_f16 and not extra_f32: + data = data.astype(np.float16) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + # reverse shape to make it similar to the internal ggml dimension order + shape_str = f"{{{', '.join(str(n) for n in reversed(data.shape))}}}" - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + # n_dims is implicit in the shape + logger.info(f"{f'%-{max_name_len}s' % f'{new_name},'} {old_dtype} --> {data.dtype}, shape = {shape_str}") - self.gguf_writer.add_tensor(new_name, data) + self.gguf_writer.add_tensor(new_name, data) def write(self): self.write_tensors() self.gguf_writer.write_header_to_file() self.gguf_writer.write_kv_data_to_file() - self.gguf_writer.write_tensors_to_file() + self.gguf_writer.write_tensors_to_file(progress=True) self.gguf_writer.close() def write_vocab(self): @@ -188,16 +282,18 @@ def write_vocab(self): self.gguf_writer.close() @staticmethod - def count_model_parts(dir_model: Path, prefix: str) -> int: - num_parts = 0 + def get_model_part_names(dir_model: Path, suffix: str) -> list[str]: + part_names: list[str] = [] for filename in os.listdir(dir_model): - if filename.endswith(prefix): - num_parts += 1 + if filename.endswith(suffix): + part_names.append(filename) - return num_parts + part_names.sort() + + return part_names @staticmethod - def load_hparams(dir_model): + def load_hparams(dir_model: Path): with open(dir_model / "config.json", "r", encoding="utf-8") as f: return json.load(f) @@ -205,32 +301,19 @@ def load_hparams(dir_model): def register(cls, *names: str) -> Callable[[AnyModel], AnyModel]: assert names - def func(modelcls: type[Model]): + def func(modelcls: AnyModel) -> AnyModel: for name in names: cls._model_classes[name] = modelcls return modelcls return func @classmethod - def from_model_architecture(cls, arch): + def from_model_architecture(cls, arch: str) -> type[Model]: try: return cls._model_classes[arch] except KeyError: raise NotImplementedError(f'Architecture {arch!r} not supported!') from None - def _is_model_safetensors(self) -> bool: - return Model.count_model_parts(self.dir_model, ".safetensors") > 0 - - def _get_part_names(self): - if self.is_safetensors: - if self.num_parts == 1: # there's only one .safetensors file - return ("model.safetensors",) - return (f"model-{n:05}-of-{self.num_parts:05}.safetensors" for n in range(1, self.num_parts + 1)) - - if self.num_parts == 1: # there's only one .bin file - return ("pytorch_model.bin",) - return (f"pytorch_model-{n:05}-of-{self.num_parts:05}.bin" for n in range(1, self.num_parts + 1)) - # used for GPT-2 BPE and WordPiece vocabs def get_vocab_base(self) -> tuple[list[str], list[int], str]: tokens: list[str] = [] @@ -420,22 +503,24 @@ def _set_vocab_sentencepiece(self): if not tokenizer_path.is_file(): raise FileNotFoundError(f"File not found: {tokenizer_path}") - tokenizer = SentencePieceProcessor(str(tokenizer_path)) + tokenizer = SentencePieceProcessor() + tokenizer.LoadFromFile(str(tokenizer_path)) + vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size()) for token_id in range(tokenizer.vocab_size()): - piece = tokenizer.id_to_piece(token_id) + piece = tokenizer.IdToPiece(token_id) text = piece.encode("utf-8") - score = tokenizer.get_score(token_id) + score = tokenizer.GetScore(token_id) toktype = SentencePieceTokenTypes.NORMAL - if tokenizer.is_unknown(token_id): + if tokenizer.IsUnknown(token_id): toktype = SentencePieceTokenTypes.UNKNOWN - elif tokenizer.is_control(token_id): + elif tokenizer.IsControl(token_id): toktype = SentencePieceTokenTypes.CONTROL - elif tokenizer.is_unused(token_id): + elif tokenizer.IsUnused(token_id): toktype = SentencePieceTokenTypes.UNUSED - elif tokenizer.is_byte(token_id): + elif tokenizer.IsByte(token_id): toktype = SentencePieceTokenTypes.BYTE tokens.append(text) @@ -458,7 +543,7 @@ def _set_vocab_sentencepiece(self): pad_count = vocab_size - len(tokens) logger.debug(f"Padding vocab with {pad_count} token(s) - [PAD1] through [PAD{pad_count}]") for i in range(1, pad_count + 1): - tokens.append(f"[PAD{i}]") + tokens.append(bytes(f"[PAD{i}]", encoding="utf-8")) scores.append(-1000.0) toktypes.append(SentencePieceTokenTypes.UNUSED) @@ -533,81 +618,52 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"]) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): - block_count = self.hparams["n_layer"] - tensors = dict(self.get_tensors()) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - has_lm_head = True + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads")) n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed")) - for name, data_torch in tensors.items(): - if "lm_head.weight" not in tensors.keys() and "output.weight" not in tensors.keys(): - has_lm_head = False + name = re.sub(r'transformer\.', '', name) + + tensors: list[tuple[str, Tensor]] = [] + + if re.match(r"h\.\d+\.self_attention\.query_key_value\.weight", name): + # Map bloom-style qkv_linear to gpt-style qkv_linear + # bloom: https://github.com/huggingface/transformers/blob/main/src/transformers/models/bloom/modeling_bloom.py#L238-L252 # noqa + # gpt-2: https://github.com/huggingface/transformers/blob/main/src/transformers/models/gpt2/modeling_gpt2.py#L312 # noqa + qkv_weights = data_torch.reshape((n_head, 3, n_embed // n_head, n_embed)) + data_torch = torch.cat( + ( + qkv_weights[:, 0, :, :].reshape((-1, n_embed)), + qkv_weights[:, 1, :, :].reshape((-1, n_embed)), + qkv_weights[:, 2, :, :].reshape((-1, n_embed)), + ), + dim=0, + ) + logger.info("re-format attention.linear_qkv.weight") + elif re.match(r"h\.\d+\.self_attention\.query_key_value\.bias", name): + qkv_bias = data_torch.reshape((n_head, 3, n_embed // n_head)) + data_torch = torch.cat( + ( + qkv_bias[:, 0, :].reshape((n_embed,)), + qkv_bias[:, 1, :].reshape((n_embed,)), + qkv_bias[:, 2, :].reshape((n_embed,)), + ), + dim=0, + ) + logger.info("re-format attention.linear_qkv.bias") - name = re.sub(r'transformer\.', '', name) + tensors.append((self.map_tensor_name(name), data_torch)) - old_dtype = data_torch.dtype + if name == "word_embeddings.weight": + assert self.tensor_names is not None - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + # TODO: tie them at runtime, don't duplicate in the model file + if all(s not in self.tensor_names for s in ("lm_head.weight", "output.weight")): + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT), data_torch)) - data = data_torch.squeeze().numpy() - - if re.match(r"h\.\d+\.self_attention\.query_key_value\.weight", name): - # Map bloom-style qkv_linear to gpt-style qkv_linear - # bloom: https://github.com/huggingface/transformers/blob/main/src/transformers/models/bloom/modeling_bloom.py#L238-L252 # noqa - # gpt-2: https://github.com/huggingface/transformers/blob/main/src/transformers/models/gpt2/modeling_gpt2.py#L312 # noqa - qkv_weights = data.reshape((n_head, 3, n_embed // n_head, n_embed)) - data = np.concatenate( - ( - qkv_weights[:, 0, :, :].reshape((-1, n_embed)), - qkv_weights[:, 1, :, :].reshape((-1, n_embed)), - qkv_weights[:, 2, :, :].reshape((-1, n_embed)), - ), - axis=0, - ) - logger.info("re-format attention.linear_qkv.weight") - elif re.match(r"h\.\d+\.self_attention\.query_key_value\.bias", name): - qkv_bias = data.reshape((n_head, 3, n_embed // n_head)) - data = np.concatenate( - ( - qkv_bias[:, 0, :].reshape((n_embed,)), - qkv_bias[:, 1, :].reshape((n_embed,)), - qkv_bias[:, 2, :].reshape((n_embed,)), - ), - axis=0, - ) - logger.info("re-format attention.linear_qkv.bias") - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"=> {new_name}, shape = {data.shape}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) - - if not has_lm_head and name == "word_embeddings.weight": - self.gguf_writer.add_tensor("output.weight", data) - logger.info(name, f"=> output.weight, shape = {data.shape}, {old_dtype} --> {data.dtype}") + return tensors @Model.register("MPTForCausalLM") @@ -643,50 +699,16 @@ def set_gguf_parameters(self): else: self.gguf_writer.add_max_alibi_bias(0.0) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers")) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): - continue + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - if "scales" in name: - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias", ".scales")) - if new_name is not None: - new_name = new_name.replace("scales", "act.scales") - else: - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + if "scales" in name: + new_name = self.map_tensor_name(name, try_suffixes=(".weight", ".bias", ".scales")) + new_name = new_name.replace("scales", "act.scales") + else: + new_name = self.map_tensor_name(name, try_suffixes=(".weight", ".bias")) - self.gguf_writer.add_tensor(new_name, data) + return [(new_name, data_torch)] @Model.register("OrionForCausalLM") @@ -726,48 +748,6 @@ def set_gguf_parameters(self): # ref: https://huggingface.co/OrionStarAI/Orion-14B-Chat/blob/276a17221ce42beb45f66fac657a41540e71f4f5/modeling_orion.py#L570-L571 self.gguf_writer.add_layer_norm_eps(self.hparams["rms_norm_eps"]) - def write_tensors(self): - # Collect tensors from generator object - model_kv = dict(self.get_tensors()) - block_count = self.hparams["num_hidden_layers"] - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - for name, data_torch in model_kv.items(): - # we don't need these - if name.endswith(".rotary_emb.inv_freq"): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{name} -> {new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) - @Model.register("BaichuanForCausalLM", "BaiChuanForCausalLM") class BaichuanModel(Model): @@ -809,60 +789,26 @@ def set_gguf_parameters(self): self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"]) - def write_tensors(self): - # Collect tensors from generator object - model_kv = dict(self.get_tensors()) - block_count = self.hparams["num_hidden_layers"] + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: head_count = self.hparams["num_attention_heads"] - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) head_count_kv = self.hparams.get("num_key_value_heads", head_count) - for i in range(block_count): - if (w := model_kv.get(f"model.layers.{i}.self_attn.W_pack.weight")) is not None: - logger.info(f"Unpacking and permuting layer {i}") - model_kv[f"model.layers.{i}.self_attn.q_proj.weight"] = \ - self._reverse_hf_permute_part(w, 0, head_count, head_count) - model_kv[f"model.layers.{i}.self_attn.k_proj.weight"] = \ - self._reverse_hf_permute_part(w, 1, head_count, head_count_kv) - model_kv[f"model.layers.{i}.self_attn.v_proj.weight"] = \ - self._reverse_hf_part(w, 2) - del model_kv[f"model.layers.{i}.self_attn.W_pack.weight"] - - for name, data_torch in model_kv.items(): - # we don't need these - if name.endswith(".rotary_emb.inv_freq"): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + tensors: list[tuple[str, Tensor]] = [] + + if bid is not None and name == f"model.layers.{bid}.self_attn.W_pack.weight": + logger.info(f"Unpacking and permuting layer {bid}") + tensors = [ + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid), + self._reverse_hf_permute_part(data_torch, 0, head_count, head_count)), + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid), + self._reverse_hf_permute_part(data_torch, 1, head_count, head_count_kv)), + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid), + self._reverse_hf_part(data_torch, 2)), + ] + else: + tensors = [(self.map_tensor_name(name), data_torch)] - logger.info(f"{name} -> {new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) + return tensors def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor: if n_kv_head is not None and n_head != n_kv_head: @@ -894,7 +840,7 @@ def set_vocab(self): dir_model = self.dir_model hparams = self.hparams - tokens: list[bytearray] = [] + tokens: list[bytes] = [] toktypes: list[int] = [] from transformers import AutoTokenizer @@ -902,7 +848,7 @@ def set_vocab(self): vocab_size = hparams.get("vocab_size", len(tokenizer.vocab)) assert max(tokenizer.vocab.values()) < vocab_size - reverse_vocab = {id_: encoded_tok for encoded_tok, id_ in tokenizer.vocab.items()} + reverse_vocab: dict[int, str] = {id_: encoded_tok for encoded_tok, id_ in tokenizer.vocab.items()} added_vocab = tokenizer.get_added_vocab() for token_id in range(vocab_size): @@ -965,55 +911,19 @@ def set_gguf_parameters(self): self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"]) - def write_tensors(self): - # Collect tensors from generator object - model_kv = dict(self.get_tensors()) - block_count = self.hparams["num_hidden_layers"] + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + head_count = self.hparams["num_attention_heads"] - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) head_count_kv = self.hparams.get("num_key_value_heads", head_count) - for name, data_torch in model_kv.items(): - # we don't need these - if name.endswith(".rotary_emb.inv_freq"): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - # HF models permute some of the tensors, so we need to undo that - if name.endswith(("q_proj.weight")): - data_torch = self._reverse_hf_permute(data_torch, head_count, head_count) - if name.endswith(("k_proj.weight")): - data_torch = self._reverse_hf_permute(data_torch, head_count, head_count_kv) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype + # HF models permute some of the tensors, so we need to undo that + if name.endswith("q_proj.weight"): + data_torch = self._reverse_hf_permute(data_torch, head_count, head_count) + if name.endswith("k_proj.weight"): + data_torch = self._reverse_hf_permute(data_torch, head_count, head_count_kv) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{name} -> {new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor: if n_kv_head is not None and n_head != n_kv_head: @@ -1054,71 +964,31 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"]) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): - block_count = self.hparams.get("num_hidden_layers") - if block_count is None: - block_count = self.hparams["n_layer"] # old name - - n_head = self.hparams.get("num_attention_heads") - if n_head is None: - n_head = self.hparams["n_head"] # old name - - n_head_kv = self.hparams.get("num_kv_heads") - if n_head_kv is None: - n_head_kv = self.hparams.get("n_head_kv", 1) # old name - - head_dim = self.hparams["hidden_size"] // n_head - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - for name, data_torch in self.get_tensors(): - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - # QKV tensor transform - # The original query_key_value tensor contains n_head_kv "kv groups", - # each consisting of n_head/n_head_kv query weights followed by one key - # and one value weight (shared by all query heads in the kv group). - # This layout makes it a big pain to work with in GGML. - # So we rearrange them here,, so that we have n_head query weights - # followed by n_head_kv key weights followed by n_head_kv value weights, - # in contiguous fashion. - # ref: https://github.com/jploski/ggml/blob/falcon40b/examples/falcon/convert-hf-to-ggml.py - - if "query_key_value" in name: - qkv = data_torch.view(n_head_kv, n_head // n_head_kv + 2, head_dim, head_dim * n_head) - q = qkv[:, :-2].reshape(n_head * head_dim, head_dim * n_head) - k = qkv[:, [-2]].reshape(n_head_kv * head_dim, head_dim * n_head) - v = qkv[:, [-1]].reshape(n_head_kv * head_dim, head_dim * n_head) - data_torch = torch.cat((q, k, v)).reshape_as(data_torch) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - n_dims = len(data.shape) - data_dtype = data.dtype + # QKV tensor transform + # The original query_key_value tensor contains n_head_kv "kv groups", + # each consisting of n_head/n_head_kv query weights followed by one key + # and one value weight (shared by all query heads in the kv group). + # This layout makes it a big pain to work with in GGML. + # So we rearrange them here,, so that we have n_head query weights + # followed by n_head_kv key weights followed by n_head_kv value weights, + # in contiguous fashion. + # ref: https://github.com/jploski/ggml/blob/falcon40b/examples/falcon/convert-hf-to-ggml.py - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + if "query_key_value" in name: + n_head = self.find_hparam(["num_attention_heads", "n_head"]) + n_head_kv = self.find_hparam(["num_kv_heads", "n_head_kv"], optional=True) or 1 + head_dim = self.hparams["hidden_size"] // n_head - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + qkv = data_torch.view(n_head_kv, n_head // n_head_kv + 2, head_dim, head_dim * n_head) + q = qkv[:, :-2].reshape(n_head * head_dim, head_dim * n_head) + k = qkv[:, [-2]].reshape(n_head_kv * head_dim, head_dim * n_head) + v = qkv[:, [-1]].reshape(n_head_kv * head_dim, head_dim * n_head) + data_torch = torch.cat((q, k, v)).reshape_as(data_torch) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] @Model.register("GPTBigCodeForCausalLM") @@ -1164,7 +1034,7 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layer_norm_epsilon"]) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: hidden_dim = self.hparams["n_embd"] inner_dim = 4 * hidden_dim hidden_dim = int(2 * inner_dim / 3) @@ -1173,56 +1043,23 @@ def write_tensors(self): n_head = self.hparams["n_head"] n_head_kv = 1 head_dim = self.hparams["n_embd"] // n_head - block_count = self.hparams["n_layer"] - - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - tensors = dict(self.get_tensors()) - for i in range(block_count): - if (w := tensors.get(f"transformer.h.{i}.attn.kv.weight")) is not None: - tensors[f"model.layers.{i}.self_attn.k_proj.weight"] = w[:n_head_kv * head_dim] - tensors[f"model.layers.{i}.self_attn.v_proj.weight"] = w[n_head_kv * head_dim:] - del tensors[f"transformer.h.{i}.attn.kv.weight"] - if (w := tensors.get(f"transformer.h.{i}.attn.q.weight")) is not None: - tensors[f"model.layers.{i}.self_attn.q_proj.weight"] = w - del tensors[f"transformer.h.{i}.attn.q.weight"] - if (w := tensors.get(f"transformer.h.{i}.mlp.gate_up_proj.weight")) is not None: - tensors[f"model.layers.{i}.mlp.gate_proj.weight"] = w[:ff_dim] - tensors[f"model.layers.{i}.mlp.up_proj.weight"] = w[ff_dim:] - del tensors[f"transformer.h.{i}.mlp.gate_up_proj.weight"] - - for name, data_torch in tensors.items(): - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight",)) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + tensors: list[tuple[str, Tensor]] = [] - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + if bid is not None: + if name == f"transformer.h.{bid}.attn.kv.weight": + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid), data_torch[:n_head_kv * head_dim])) + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid), data_torch[n_head_kv * head_dim:])) + elif name == f"transformer.h.{bid}.attn.q.weight": + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid), data_torch)) + elif name == f"transformer.h.{bid}.mlp.gate_up_proj.weight": + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.FFN_GATE, bid), data_torch[:ff_dim])) + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.FFN_UP, bid), data_torch[ff_dim:])) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + if len(tensors) == 0: + tensors.append((self.map_tensor_name(name), data_torch)) - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) + return tensors @Model.register("PersimmonForCausalLM") @@ -1257,22 +1094,11 @@ def set_vocab(self): # self.gguf_writer.add_bos_token_id(71013) # self.gguf_writer.add_eos_token_id(71013) - def write_tensors(self): - block_count = self.hparams.get("num_layers", self.hparams.get("num_hidden_layers")) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) + def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del name, new_name, bid, n_dims # unused - for name, data_torch in self.get_tensors(): - if name.endswith(".self_attention.rotary_emb.inv_freq"): - continue - old_dtype = data_torch.dtype - # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?) - data = data_torch.to(torch.float32).squeeze().numpy() - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - n_dims = len(data.shape) - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) + # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?) + return True @Model.register("StableLmForCausalLM", "StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM") @@ -1302,84 +1128,67 @@ def set_gguf_parameters(self): self.gguf_writer.add_parallel_residual(hparams["use_parallel_residual"] if "use_parallel_residual" in hparams else True) self.gguf_writer.add_layer_norm_eps(self.find_hparam(["layer_norm_eps", "norm_eps"])) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_head = self.hparams.get("num_attention_heads") - n_kv_head = self.hparams.get("num_key_value_heads") - q_norms = dict() - k_norms = dict() - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): - continue + _q_norms: list[dict[str, Tensor]] | None = None + _k_norms: list[dict[str, Tensor]] | None = None - old_dtype = data_torch.dtype + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + n_head = self.hparams["num_attention_heads"] + n_kv_head = self.hparams["num_key_value_heads"] - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + if name.find("q_layernorm.norms") != -1: + assert bid is not None - data = data_torch.squeeze().numpy() - n_dims = len(data.shape) - if name.find("q_layernorm.norms") != -1: - q_norms[name] = data - if len(q_norms) >= (block_count * n_head): - self._stack_qk_norm(block_count, name, tensor_map, n_head, q_norms, n_dims, layer_name="q_layernorm") - continue - if name.find("k_layernorm.norms") != -1: - k_norms[name] = data - if len(k_norms) >= (block_count * n_kv_head): - self._stack_qk_norm(block_count, name, tensor_map, n_kv_head, k_norms, n_dims, layer_name="k_layernorm") - continue + if self._q_norms is None: + self._q_norms = [{} for _ in range(self.block_count)] - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + self._q_norms[bid][name] = data_torch - n_dims = len(data.shape) - data_dtype = data.dtype + if len(self._q_norms[bid]) >= n_head: + return self._stack_qk_norm(bid, n_head, self._q_norms[bid], "q_layernorm") + else: + return [] - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + if name.find("k_layernorm.norms") != -1: + assert bid is not None - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")): - data = data.astype(np.float32) + if self._k_norms is None: + self._k_norms = [{} for _ in range(self.block_count)] - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and not new_name.endswith("_norm.weight") and n_dims == 2: - data = data.astype(np.float16) + self._k_norms[bid][name] = data_torch - logger.debug(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + if len(self._k_norms[bid]) >= n_kv_head: + return self._stack_qk_norm(bid, n_kv_head, self._k_norms[bid], "k_layernorm") + else: + return [] - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] - def _stack_qk_norm(self, block_count, name, tensor_map, n_head, norms, n_dims, layer_name="q_layernorm"): - for bid in range(block_count): - datas = [] - for xid in range(n_head): - ename = f"model.layers.{bid}.self_attn.{layer_name}.norms.{xid}.weight" - datas.append(norms[ename]) - del norms[ename] - data = np.stack(datas, axis=0) - data_dtype = data.dtype - merged_name = f"model.layers.{bid}.self_attn.{layer_name}.weight" - new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")): - data = data.astype(np.float32) + def _stack_qk_norm(self, bid: int, n_head: int, norms: dict[str, Tensor], layer_name: str = "q_layernorm"): + datas: list[Tensor] = [] + # extract the norms in order + for xid in range(n_head): + ename = f"model.layers.{bid}.self_attn.{layer_name}.norms.{xid}.weight" + datas.append(norms[ename]) + del norms[ename] + data_torch = torch.stack(datas, dim=0) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and not new_name.endswith("_norm.weight") and n_dims == 2: - data = data.astype(np.float16) + merged_name = f"model.layers.{bid}.self_attn.{layer_name}.weight" + new_name = self.map_tensor_name(merged_name) - logger.debug(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") + return [(new_name, data_torch)] - self.gguf_writer.add_tensor(new_name, data) + def write_tensors(self): + super().write_tensors() + + if self._q_norms is not None or self._k_norms is not None: + # flatten two `list[dict[str, Tensor]]` into a single `list[str]` + norms = ( + [k for d in self._q_norms for k in d.keys()] if self._q_norms is not None else [] + ) + ( + [k for d in self._k_norms for k in d.keys()] if self._k_norms is not None else [] + ) + if len(norms) > 0: + raise ValueError(f"Unprocessed norms: {norms}") @Model.register("LlamaForCausalLM", "MistralForCausalLM", "MixtralForCausalLM") @@ -1419,102 +1228,69 @@ def set_gguf_parameters(self): self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"]) - # Same as super class, but permuting q_proj, k_proj - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_head = self.hparams.get("num_attention_heads") - n_kv_head = self.hparams.get("num_key_value_heads") - n_experts = self.hparams.get("num_local_experts") - experts = dict() - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.numpy() - - if name.endswith("q_proj.weight"): - data = permute(data, n_head, n_head) - if name.endswith("k_proj.weight"): - data = permute(data, n_head, n_kv_head) - - data = data.squeeze() + @staticmethod + def permute(weights: Tensor, n_head: int, n_head_kv: int | None): + if n_head_kv is not None and n_head != n_head_kv: + n_head = n_head_kv + return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:]) + .swapaxes(1, 2) + .reshape(weights.shape)) - # process the experts separately - if name.find("block_sparse_moe.experts") != -1: - experts[name] = data - if len(experts) >= n_experts: - # merge the experts into a single 3d tensor - for bid in range(block_count): - for wid in range(1, 4): - full = True - for xid in range(n_experts): - ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.w{wid}.weight" - if ename not in experts: - full = False - break - if not full: - continue + _experts: list[dict[str, Tensor]] | None = None - datas = [] - for xid in range(n_experts): - ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.w{wid}.weight" - datas.append(experts[ename]) - del experts[ename] + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + n_head = self.hparams["num_attention_heads"] + n_kv_head = self.hparams.get("num_key_value_heads") - data = np.stack(datas, axis=0) - data_dtype = data.dtype + if name.endswith("q_proj.weight"): + data_torch = LlamaModel.permute(data_torch, n_head, n_head) + if name.endswith("k_proj.weight"): + data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head) - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + # process the experts separately + if name.find("block_sparse_moe.experts") != -1: + n_experts = self.hparams["num_local_experts"] - if self.ftype == 1 and data_dtype == np.float32: - data = data.astype(np.float16) + assert bid is not None - merged_name = f"layers.{bid}.feed_forward.experts.w{wid}.weight" + if self._experts is None: + self._experts = [{} for _ in range(self.block_count)] - new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + self._experts[bid][name] = data_torch - logger.info(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") + if len(self._experts[bid]) >= n_experts * 3: + tensors: list[tuple[str, Tensor]] = [] - self.gguf_writer.add_tensor(new_name, data) - continue + # merge the experts into a single 3d tensor + for wid in ["w1", "w2", "w3"]: + datas: list[Tensor] = [] - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + for xid in range(n_experts): + ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.{wid}.weight" + datas.append(self._experts[bid][ename]) + del self._experts[bid][ename] - n_dims = len(data.shape) - data_dtype = data.dtype + data_torch = torch.stack(datas, dim=0) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + merged_name = f"layers.{bid}.feed_forward.experts.{wid}.weight" - # 1d tensors need to be converted to float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + new_name = self.map_tensor_name(merged_name) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + tensors.append((new_name, data_torch)) + return tensors + else: + return [] - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + return [(self.map_tensor_name(name), data_torch)] - self.gguf_writer.add_tensor(new_name, data) + def write_tensors(self): + super().write_tensors() - if len(experts) > 0: - raise ValueError(f"Unprocessed experts: {experts.keys()}") + if self._experts is not None: + # flatten `list[dict[str, Tensor]]` into `list[str]` + experts = [k for d in self._experts for k in d.keys()] + if len(experts) > 0: + raise ValueError(f"Unprocessed experts: {experts}") @Model.register("GrokForCausalLM") @@ -1531,89 +1307,44 @@ def set_gguf_parameters(self): super().set_gguf_parameters() self.gguf_writer.add_name("Grok") - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_experts = self.hparams.get("num_local_experts") - experts = dict() - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): - continue - - old_dtype = data_torch.dtype + _experts: list[dict[str, Tensor]] | None = None - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + # process the experts separately + if name.find(".moe.") != -1: + n_experts = self.hparams["num_local_experts"] - # process the experts separately - if name.find(".moe.") != -1: - experts[name] = data - if len(experts) >= n_experts: - # merge the experts into a single 3d tensor - for bid in range(block_count): - for wid in ["linear", "linear_1", "linear_v"]: - full = True - for xid in range(n_experts): - ename = f"transformer.decoder_layer.{bid}.moe.{xid}.{wid}.weight" - if ename not in experts: - full = False - break - if not full: - continue + assert bid is not None - datas = [] - for xid in range(n_experts): - ename = f"transformer.decoder_layer.{bid}.moe.{xid}.{wid}.weight" - datas.append(experts[ename]) - del experts[ename] + if self._experts is None: + self._experts = [{} for _ in range(self.block_count)] - data = np.stack(datas, axis=0) - data_dtype = data.dtype + self._experts[bid][name] = data_torch - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + if len(self._experts[bid]) >= n_experts * 3: + tensors: list[tuple[str, Tensor]] = [] - if self.ftype == 1 and data_dtype == np.float32: - data = data.astype(np.float16) + # merge the experts into a single 3d tensor + for wid in ["linear", "linear_1", "linear_v"]: + datas: list[Tensor] = [] - merged_name = f"transformer.decoder_layer.{bid}.moe.{wid}.weight" + for xid in range(n_experts): + ename = f"transformer.decoder_layer.{bid}.moe.{xid}.{wid}.weight" + datas.append(self._experts[bid][ename]) + del self._experts[bid][ename] - new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + data_torch = torch.stack(datas, dim=0) - logger.info(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") + merged_name = f"transformer.decoder_layer.{bid}.moe.{wid}.weight" - self.gguf_writer.add_tensor(new_name, data) - continue + new_name = self.map_tensor_name(merged_name) - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + tensors.append((new_name, data_torch)) + return tensors + else: + return [] - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] @Model.register("DbrxForCausalLM") @@ -1646,68 +1377,45 @@ def set_gguf_parameters(self): self.gguf_writer.add_file_type(self.ftype) logger.info(f"gguf: file type = {self.ftype}") - def write_tensors(self): - block_count = self.hparams.get("n_layers") - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - for name, data_torch in self.get_tensors(): - n_expert = self.hparams["ffn_config"]["moe_num_experts"] - n_ff = self.hparams["ffn_config"]["ffn_hidden_size"] - n_embd = self.hparams["d_model"] - - # Specific behavior for experts tensors: suffix .weight, view as 3D and transpose - # original implementation expects (n_expert, n_ff, n_embd) for all experts weights - # But llama.cpp moe graph works differently - # AND the dimensions in ggml are typically in the reverse order of the pytorch dimensions - # so (n_expert, n_ff, n_embd) in pytorch is {n_embd, n_ff, n_expert} in ggml_tensor - exp_tensor_names = {"ffn.experts.mlp.w1": None, # LLM_TENSOR_FFN_GATE_EXPS ggml_tensor->ne{n_embd, n_ff, n_expert} - "ffn.experts.mlp.w2": (0, 2, 1), # LLM_TENSOR_FFN_DOWN_EXPS ggml_tensor->ne{n_ff, n_embd, n_expert} - "ffn.experts.mlp.v1": None} # LLM_TENSOR_FFN_UP_EXPS ggml_tensor->ne{n_embd, n_ff, n_expert} - experts = False - for exp_tensor_name in exp_tensor_names.keys(): - if name.find(exp_tensor_name) != -1 and name.find(".weight") == -1: - experts = True - data_torch = data_torch.view(n_expert, n_ff, n_embd) - if (permute_tensor := exp_tensor_names[exp_tensor_name]) is not None: - data_torch = data_torch.permute(*permute_tensor) - break - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - # In MoE models the ffn tensors are typically most of the model weights, - # and need to be quantizable. Quantize expects tensor names to be suffixed by .weight. - # Every other model has the weight names ending in .weight, - # let's assume that is the convention which is not the case for dbrx: - # https://huggingface.co/databricks/dbrx-instruct/blob/main/model.safetensors.index.json#L15 - new_name = tensor_map.get_name(name if not experts else name + ".weight", try_suffixes=(".weight",)) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # Most of the codebase that takes in 1D tensors only handles F32 tensors - # and most of the outputs tensors are F32. - if data_dtype != np.float32 and n_dims == 1: - raise ValueError(f"Can not map tensor {name!r}: all 1D tensors must be F32") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + + n_expert = self.hparams["ffn_config"]["moe_num_experts"] + n_ff = self.hparams["ffn_config"]["ffn_hidden_size"] + n_embd = self.hparams["d_model"] + + # Specific behavior for experts tensors: suffix .weight, view as 3D and transpose + # original implementation expects (n_expert, n_ff, n_embd) for all experts weights + # But llama.cpp moe graph works differently + # AND the dimensions in ggml are typically in the reverse order of the pytorch dimensions + # so (n_expert, n_ff, n_embd) in pytorch is {n_embd, n_ff, n_expert} in ggml_tensor + exp_tensor_names = {"ffn.experts.mlp.w1": None, # LLM_TENSOR_FFN_GATE_EXPS ggml_tensor->ne{n_embd, n_ff, n_expert} + "ffn.experts.mlp.w2": (0, 2, 1), # LLM_TENSOR_FFN_DOWN_EXPS ggml_tensor->ne{n_ff, n_embd, n_expert} + "ffn.experts.mlp.v1": None} # LLM_TENSOR_FFN_UP_EXPS ggml_tensor->ne{n_embd, n_ff, n_expert} + experts = False + + for exp_tensor_name in exp_tensor_names.keys(): + if name.find(exp_tensor_name) != -1 and name.find(".weight") == -1: + experts = True + data_torch = data_torch.view(n_expert, n_ff, n_embd) + if (permute_tensor := exp_tensor_names[exp_tensor_name]) is not None: + data_torch = data_torch.permute(*permute_tensor) + break - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + # map tensor names + # In MoE models the ffn tensors are typically most of the model weights, + # and need to be quantizable. Quantize expects tensor names to be suffixed by .weight. + # Every other model has the weight names ending in .weight, + # let's assume that is the convention which is not the case for dbrx: + # https://huggingface.co/databricks/dbrx-instruct/blob/main/model.safetensors.index.json#L15 + new_name = self.map_tensor_name(name if not experts else name + ".weight", try_suffixes=(".weight",)) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and n_dims > 1: - data = data.astype(np.float16) + return [(new_name, data_torch)] - logger.debug(f"{new_name}, n_dims = {n_dims}, shape = {data.shape}, {old_dtype} --> {data.dtype}") + def extra_f16_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del name, new_name, bid # unused - self.gguf_writer.add_tensor(new_name, data) + return n_dims > 1 @Model.register("MiniCPMForCausalLM") @@ -1740,53 +1448,19 @@ def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | Non .reshape(weights.shape) ) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_head = self.hparams.get("num_attention_heads") - n_kv_head = self.hparams.get("num_key_value_heads") - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - # HF models permute some of the tensors, so we need to undo that - if name.endswith(("q_proj.weight")): - data_torch = self._reverse_hf_permute(data_torch, n_head, n_head) - if name.endswith(("k_proj.weight")): - data_torch = self._reverse_hf_permute(data_torch, n_head, n_kv_head) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + n_head = self.hparams["num_attention_heads"] + n_kv_head = self.hparams.get("num_key_value_heads") - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + # HF models permute some of the tensors, so we need to undo that + if name.endswith(("q_proj.weight")): + data_torch = self._reverse_hf_permute(data_torch, n_head, n_head) + if name.endswith(("k_proj.weight")): + data_torch = self._reverse_hf_permute(data_torch, n_head, n_kv_head) - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] @Model.register("QWenLMHeadModel") @@ -1830,46 +1504,6 @@ def set_gguf_parameters(self): self.gguf_writer.add_head_count(self.hparams["num_attention_heads"]) self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layer_norm_epsilon"]) - def write_tensors(self): - block_count = self.hparams["num_hidden_layers"] - model_kv = dict(self.get_tensors()) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - for name, data_torch in model_kv.items(): - # we don't need these - if name.endswith(".rotary_emb.inv_freq"): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) - @Model.register("Qwen2ForCausalLM") class Qwen2Model(Model): @@ -1891,92 +1525,52 @@ def set_gguf_parameters(self): if (n_experts := self.hparams.get("num_experts")) is not None: self.gguf_writer.add_expert_count(n_experts) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_experts = self.hparams.get("num_experts") - experts = dict() - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # process the experts separately - if name.find("experts") != -1: - experts[name] = data - if len(experts) >= n_experts * 3: - # merge the experts into a single 3d tensor - for bid in range(block_count): - for w_name in ["down_proj", "gate_proj", "up_proj"]: - full = True - for xid in range(n_experts): - ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight" - if ename not in experts: - full = False - break - if not full: - continue - - datas = [] - for xid in range(n_experts): - ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight" - datas.append(experts[ename]) - del experts[ename] + _experts: list[dict[str, Tensor]] | None = None - data = np.stack(datas, axis=0) - data_dtype = data.dtype + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + # process the experts separately + if name.find("experts") != -1: + n_experts = self.hparams["num_experts"] + assert bid is not None - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + if self._experts is None: + self._experts = [{} for _ in range(self.block_count)] - if self.ftype == 1 and data_dtype == np.float32: - data = data.astype(np.float16) + self._experts[bid][name] = data_torch - merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight" + if len(self._experts[bid]) >= n_experts * 3: + tensors: list[tuple[str, Tensor]] = [] - new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - logger.debug(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) - continue + # merge the experts into a single 3d tensor + for w_name in ["down_proj", "gate_proj", "up_proj"]: + datas: list[Tensor] = [] - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + for xid in range(n_experts): + ename = f"model.layers.{bid}.mlp.experts.{xid}.{w_name}.weight" + datas.append(self._experts[bid][ename]) + del self._experts[bid][ename] - n_dims = len(data.shape) - data_dtype = data.dtype + data_torch = torch.stack(datas, dim=0) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + merged_name = f"model.layers.{bid}.mlp.experts.{w_name}.weight" - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")): - data = data.astype(np.float32) + new_name = self.map_tensor_name(merged_name) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + tensors.append((new_name, data_torch)) + return tensors + else: + return [] - logger.debug(f"{new_name}, n_dims = {n_dims}, shape = {data.shape}, {old_dtype} --> {data.dtype}") + return [(self.map_tensor_name(name), data_torch)] - self.gguf_writer.add_tensor(new_name, data) + def write_tensors(self): + super().write_tensors() - if len(experts) > 0: - raise ValueError(f"Unprocessed experts: {experts.keys()}") + if self._experts is not None: + # flatten `list[dict[str, Tensor]]` into `list[str]` + experts = [k for d in self._experts for k in d.keys()] + if len(experts) > 0: + raise ValueError(f"Unprocessed experts: {experts}") @Model.register("GPT2LMHeadModel") @@ -1993,54 +1587,27 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_epsilon"]) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - for name, data_torch in self.get_tensors(): - # we don't need these - if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq", ".attn.bias", ".attn.masked_bias")): - continue + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - if name.endswith((".c_attn.weight", ".c_proj.weight", ".c_fc.weight", ".c_proj.weight")): - data_torch = data_torch.transpose(1, 0) - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + tensors: list[tuple[str, Tensor]] = [] - data = data_torch.squeeze().numpy() + # we don't need these + if name.endswith((".attn.bias", ".attn.masked_bias")): + return tensors - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + if name.endswith((".c_attn.weight", ".c_proj.weight", ".c_fc.weight", ".c_proj.weight")): + data_torch = data_torch.transpose(1, 0) - n_dims = len(data.shape) - data_dtype = data.dtype + new_name = self.map_tensor_name(name) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + tensors.append((new_name, data_torch)) - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + # note: GPT2 output is tied to (same as) wte in original model + if new_name == self.format_tensor_name(gguf.MODEL_TENSOR.TOKEN_EMBD): + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT), data_torch)) - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) - - # note: GPT2 output is tied to (same as) wte in original model - if new_name == "token_embd.weight": - logger.info(f"output.weight, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor("output.weight", data) + return tensors @Model.register("PhiForCausalLM") @@ -2080,7 +1647,8 @@ def set_vocab(self): if not tokenizer_path.is_file(): raise ValueError(f'Error: Missing {tokenizer_path}') - tokenizer = SentencePieceProcessor(str(tokenizer_path)) + tokenizer = SentencePieceProcessor() + tokenizer.LoadFromFile(str(tokenizer_path)) vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size()) @@ -2090,18 +1658,18 @@ def set_vocab(self): for token_id in range(tokenizer.vocab_size()): - piece = tokenizer.id_to_piece(token_id) + piece = tokenizer.IdToPiece(token_id) text = piece.encode("utf-8") - score = tokenizer.get_score(token_id) + score = tokenizer.GetScore(token_id) toktype = SentencePieceTokenTypes.NORMAL - if tokenizer.is_unknown(token_id): + if tokenizer.IsUnknown(token_id): toktype = SentencePieceTokenTypes.UNKNOWN - elif tokenizer.is_control(token_id): + elif tokenizer.IsControl(token_id): toktype = SentencePieceTokenTypes.CONTROL - elif tokenizer.is_unused(token_id): + elif tokenizer.IsUnused(token_id): toktype = SentencePieceTokenTypes.UNUSED - elif tokenizer.is_byte(token_id): + elif tokenizer.IsByte(token_id): toktype = SentencePieceTokenTypes.BYTE tokens[token_id] = text @@ -2187,51 +1755,18 @@ def shuffle_attn_output_weight(self, data_torch): data_torch = torch.reshape(data_torch, (5120, 5120)) return data_torch - def write_tensors(self): - block_count = self.hparams.get("num_layers", self.hparams.get("num_hidden_layers")) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - for name, data_torch in self.get_tensors(): - if "self_attn.rotary_emb.inv_freq" in name: - continue - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - # shuffle for broadcasting of gqa in ggml_mul_mat - if new_name.endswith("attn_q.weight"): - data_torch = self.shuffle_attn_q_weight(data_torch) - elif new_name.endswith("attn_output.weight"): - data_torch = self.shuffle_attn_output_weight(data_torch) - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + new_name = self.map_tensor_name(name) - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + # shuffle for broadcasting of gqa in ggml_mul_mat + if new_name.endswith("attn_q.weight"): + data_torch = self.shuffle_attn_q_weight(data_torch) + elif new_name.endswith("attn_output.weight"): + data_torch = self.shuffle_attn_output_weight(data_torch) - self.gguf_writer.add_tensor(new_name, data) + return [(new_name, data_torch)] @Model.register("CodeShellForCausalLM") @@ -2254,51 +1789,21 @@ def set_gguf_parameters(self): self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) self.gguf_writer.add_rope_scaling_factor(1.0) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - tensors = dict(self.get_tensors()) - has_lm_head = "lm_head.weight" in tensors.keys() or "output.weight" in tensors.keys() - for name, data_torch in tensors.items(): - # we don't need these - if name.endswith((".attn.rotary_emb.inv_freq")): - continue + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - old_dtype = data_torch.dtype + new_name = self.map_tensor_name(name) - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) + tensors: list[tuple[str, Tensor]] = [(new_name, data_torch)] - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + if new_name == self.format_tensor_name(gguf.MODEL_TENSOR.TOKEN_EMBD): + assert self.tensor_names is not None - self.gguf_writer.add_tensor(new_name, data) + if all(s not in self.tensor_names for s in ("lm_head.weight", "output.weight")): + # copy tok_embd.weight to output.weight + tensors.append((self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT), data_torch)) - if not has_lm_head and name == "transformer.wte.weight": - self.gguf_writer.add_tensor("output.weight", data) - logger.info(name, f"=> output.weight, shape = {data.shape}, {old_dtype} --> {data.dtype}") + return tensors @Model.register("InternLM2ForCausalLM") @@ -2327,27 +1832,29 @@ def set_vocab(self): sentencepiece_model.ParseFromString(open(tokenizer_path, "rb").read()) add_prefix = sentencepiece_model.normalizer_spec.add_dummy_prefix - tokenizer = SentencePieceProcessor(str(tokenizer_path)) + tokenizer = SentencePieceProcessor() + tokenizer.LoadFromFile(str(tokenizer_path)) + vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size()) for token_id in range(vocab_size): - piece = tokenizer.id_to_piece(token_id) + piece = tokenizer.IdToPiece(token_id) text = piece.encode("utf-8") - score = tokenizer.get_score(token_id) + score = tokenizer.GetScore(token_id) if text == b"\x00": # (TODO): fixme # Hack here and replace the \x00 characters. - logger.debug(f"InternLM2 convert token '{text}' to '🐉'!") - text = "🐉" + logger.warning(f"InternLM2 convert token '{text}' to '🐉'!") + text = "🐉".encode("utf-8") toktype = SentencePieceTokenTypes.NORMAL - if tokenizer.is_unknown(token_id): + if tokenizer.IsUnknown(token_id): toktype = SentencePieceTokenTypes.UNKNOWN - elif tokenizer.is_control(token_id): + elif tokenizer.IsControl(token_id): toktype = SentencePieceTokenTypes.CONTROL - elif tokenizer.is_unused(token_id): + elif tokenizer.IsUnused(token_id): toktype = SentencePieceTokenTypes.UNUSED - elif tokenizer.is_byte(token_id): + elif tokenizer.IsByte(token_id): toktype = SentencePieceTokenTypes.BYTE tokens.append(text) @@ -2384,13 +1891,15 @@ def set_vocab(self): special_vocab.add_to_gguf(self.gguf_writer) def _try_get_sft_eos(self, tokenizer): - unused_145_list = tokenizer.encode('[UNUSED_TOKEN_145]') - im_end_list = tokenizer.encode('<|im_end|>') + unused_145_list = tokenizer.Encode('[UNUSED_TOKEN_145]') + im_end_list = tokenizer.Encode('<|im_end|>') + eos_token = None assert (len(unused_145_list) == 1) ^ (len(im_end_list) == 1) if len(unused_145_list) == 1: eos_token = unused_145_list[0] if len(im_end_list) == 1: eos_token = im_end_list[0] + assert eos_token return eos_token def _hf_permute_qk(self, weights, n_head: int, n_head_kv: int): @@ -2411,71 +1920,36 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"]) self.gguf_writer.add_head_count_kv(self.hparams["num_key_value_heads"]) - def post_write_tensors(self, tensor_map, name, data_torch): - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - data = data_torch.squeeze().numpy() - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - - n_dims = len(data.shape) - data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) - - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - self.gguf_writer.add_tensor(new_name, data) - - def write_tensors(self): - from einops import rearrange - - num_heads = self.hparams.get("num_attention_heads") - num_kv_heads = self.hparams.get("num_key_value_heads") - hidden_size = self.hparams.get("hidden_size") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + num_heads = self.hparams["num_attention_heads"] + num_kv_heads = self.hparams["num_key_value_heads"] + hidden_size = self.hparams["hidden_size"] q_per_kv = num_heads // num_kv_heads head_dim = hidden_size // num_heads num_groups = num_heads // q_per_kv - block_count = self.hparams["num_hidden_layers"] - model_kv = dict(self.get_tensors()) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) qkv_pattern = r"model\.layers\.(\d+)\.attention\.wqkv" - for name, data_torch in model_kv.items(): - # we don't need these - if name.endswith(".rotary_emb.inv_freq"): - continue - if re.match(qkv_pattern, name): - bid = re.findall(qkv_pattern, name)[0] - qkv = data_torch - qkv = rearrange(qkv.T, " o (g n i) ->o g n i", g=num_groups, n=q_per_kv + 2, i=head_dim) - q, k, v = qkv[..., : q_per_kv, :], qkv[..., q_per_kv: q_per_kv + 1, :], qkv[..., q_per_kv + 1: q_per_kv + 2, :] - # The model weights of q and k equire additional reshape. - q = self._hf_permute_qk(rearrange(q, " o g n i -> o (g n i)").T, num_heads, num_heads) - k = self._hf_permute_qk(rearrange(k, " o g n i -> o (g n i)").T, num_heads, num_kv_heads) - v = rearrange(v, " o g n i -> o (g n i)").T - self.post_write_tensors(tensor_map, f"model.layers.{bid}.attention.wq.weight", q) - self.post_write_tensors(tensor_map, f"model.layers.{bid}.attention.wk.weight", k) - self.post_write_tensors(tensor_map, f"model.layers.{bid}.attention.wv.weight", v) - else: - self.post_write_tensors(tensor_map, name, data_torch) + if re.match(qkv_pattern, name): + bid = re.findall(qkv_pattern, name)[0] + qkv = data_torch + # qkv = rearrange(qkv.T, " o (g n i) ->o g n i", g=num_groups, n=q_per_kv + 2, i=head_dim) + qkv = qkv.T.reshape((-1, num_groups, q_per_kv + 2, head_dim)) + q, k, v = qkv[..., : q_per_kv, :], qkv[..., q_per_kv: q_per_kv + 1, :], qkv[..., q_per_kv + 1: q_per_kv + 2, :] + # The model weights of q and k equire additional reshape. + # q = self._hf_permute_qk(rearrange(q, " o g n i -> o (g n i)").T, num_heads, num_heads) + q = self._hf_permute_qk(q.reshape((q.shape[0], -1)).T, num_heads, num_heads) + # k = self._hf_permute_qk(rearrange(k, " o g n i -> o (g n i)").T, num_heads, num_kv_heads) + k = self._hf_permute_qk(k.reshape((k.shape[0], -1)).T, num_heads, num_kv_heads) + # v = rearrange(v, " o g n i -> o (g n i)").T + v = v.reshape((v.shape[0], -1)).T + return [ + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid), q), + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid), k), + (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid), v), + ] + else: + return [(self.map_tensor_name(name), data_torch)] @Model.register("BertModel", "CamembertModel") @@ -2540,43 +2014,20 @@ def phantom(tok): special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens)) special_vocab.add_to_gguf(self.gguf_writer) - def write_tensors(self): - tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count) - tensors = dict(self.get_tensors()) - for name, data_torch in tensors.items(): - # we are only using BERT for embeddings so we don't need the pooling layer - if name in ("embeddings.position_ids", "pooler.dense.weight", "pooler.dense.bias"): - continue # we don't need these - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + # we are only using BERT for embeddings so we don't need the pooling layer + if name in ("embeddings.position_ids", "pooler.dense.weight", "pooler.dense.bias"): + return [] # we don't need these - data = data_torch.squeeze().numpy() - n_dims = len(data.shape) - new_dtype: type[np.floating[Any]] + return [(self.map_tensor_name(name), data_torch)] - if ( - self.ftype == 1 and name.endswith(".weight") and n_dims == 2 - and name != "embeddings.token_type_embeddings.weight" # not used with get_rows, must be F32 - ): - # if f16 desired, convert any float32 2-dim weight tensors to float16 - new_dtype = np.float16 - else: - # if f32 desired, convert any float16 to float32 - new_dtype = np.float32 - - logger.info(f"{new_name}, n_dims = {n_dims}, {data_torch.dtype} --> {new_dtype}") - - if data.dtype != new_dtype: - data = data.astype(new_dtype) + def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del new_name, bid, n_dims # unused - self.gguf_writer.add_tensor(new_name, data) + # not used with get_rows, must be F32 + return name == "embeddings.token_type_embeddings.weight" @Model.register("NomicBertModel") @@ -2642,45 +2093,20 @@ def set_gguf_parameters(self): self.gguf_writer.add_value_length(hparams["head_dim"]) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - for name, data_torch in self.get_tensors(): - # lm_head is not used in llama.cpp, while autoawq will include this tensor in model - # To prevent errors, skip loading lm_head.weight. - if name == "lm_head.weight": - logger.debug(f"Skipping get tensor {name!r} in safetensors so that convert can end normally.") - continue - - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - # ref: https://github.com/huggingface/transformers/blob/fc37f38915372c15992b540dfcbbe00a916d4fc6/src/transformers/models/gemma/modeling_gemma.py#L89 - if name.endswith("norm.weight"): - data_torch = data_torch + 1 - data = data_torch.squeeze().numpy() + # lm_head is not used in llama.cpp, while autoawq will include this tensor in model + # To prevent errors, skip loading lm_head.weight. + if name == "lm_head.weight": + logger.debug(f"Skipping get tensor {name!r} in safetensors so that convert can end normally.") + return [] - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + # ref: https://github.com/huggingface/transformers/blob/fc37f38915372c15992b540dfcbbe00a916d4fc6/src/transformers/models/gemma/modeling_gemma.py#L89 + if name.endswith("norm.weight"): + data_torch = data_torch + 1 - n_dims = len(data.shape) - data_dtype = data.dtype - - data = data.astype(np.float32) - - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: - data = data.astype(np.float16) - - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) + return [(self.map_tensor_name(name), data_torch)] @Model.register("Starcoder2ForCausalLM") @@ -2703,6 +2129,8 @@ def set_vocab(self): if (self.dir_model / "tokenizer.json").is_file(): self._set_vocab_gpt2() + elif (self.dir_model / "tokenizer.model").is_file(): + self._set_vocab_sentencepiece() else: # Use the GPT-NeoX tokenizer when no tokenizer files are present tokenizer_path = Path(sys.path[0]) / "models" / "ggml-vocab-gpt-neox.gguf" @@ -2710,28 +2138,34 @@ def set_vocab(self): neox_reader = gguf.GGUFReader(tokenizer_path, "r") field = neox_reader.get_field(gguf.Keys.Tokenizer.MODEL) - self.gguf_writer.add_tokenizer_model(bytes(field.parts[-1])) + self.gguf_writer.add_tokenizer_model(bytes(field.parts[-1]).decode("utf-8") if field else "gpt2") field = neox_reader.get_field(gguf.Keys.Tokenizer.PRE) - self.gguf_writer.add_tokenizer_pre(bytes(field.parts[-1])) + self.gguf_writer.add_tokenizer_pre(bytes(field.parts[-1]).decode("utf-8") if field else "mpt") field = neox_reader.get_field(gguf.Keys.Tokenizer.LIST) + assert field self.gguf_writer.add_token_list([bytes(field.parts[i]) for i in field.data][:vocab_size]) field = neox_reader.get_field(gguf.Keys.Tokenizer.TOKEN_TYPE) + assert field self.gguf_writer.add_token_types([field.parts[i].tolist()[0] for i in field.data][:vocab_size]) field = neox_reader.get_field(gguf.Keys.Tokenizer.MERGES) + assert field self.gguf_writer.add_token_merges([bytes(field.parts[i]) for i in field.data]) field = neox_reader.get_field(gguf.Keys.Tokenizer.BOS_ID) - self.gguf_writer.add_bos_token_id(field.parts[-1].tolist()[0]) + self.gguf_writer.add_bos_token_id(field.parts[-1].tolist()[0] if field else 1) field = neox_reader.get_field(gguf.Keys.Tokenizer.EOS_ID) - self.gguf_writer.add_eos_token_id(field.parts[-1].tolist()[0]) + self.gguf_writer.add_eos_token_id(field.parts[-1].tolist()[0] if field else 0) field = neox_reader.get_field(gguf.Keys.Tokenizer.UNK_ID) - self.gguf_writer.add_unk_token_id(field.parts[-1].tolist()[0]) + self.gguf_writer.add_unk_token_id(field.parts[-1].tolist()[0] if field else 0) + + field = neox_reader.get_field(gguf.Keys.Tokenizer.PAD_ID) + self.gguf_writer.add_pad_token_id(field.parts[-1].tolist()[0] if field else 0) def set_gguf_parameters(self): d_model = self.find_hparam(["hidden_size", "d_model"]) @@ -2760,59 +2194,42 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_rms_eps(rms_norm_eps) self.gguf_writer.add_file_type(self.ftype) - def write_tensors(self): - block_count = self.hparams["n_layer"] - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - - tok_embd = None - tok_embd_name = gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.TOKEN_EMBD] + ".weight" - output_name = gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.OUTPUT] + ".weight" - - for name, data_torch in self.get_tensors(): - old_dtype = data_torch.dtype - - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) - - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") + _tok_embd = None - if name.endswith(".A_log"): - logger.debug("A_log --> A ==> " + new_name) - data_torch = -torch.exp(data_torch) + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused - # assuming token_embd.weight is seen before output.weight - if tok_embd is not None and new_name == output_name: - if torch.equal(tok_embd, data_torch): - logger.debug(f"{output_name} is equivalent to {tok_embd_name}, omitting") - continue - if new_name == tok_embd_name: - tok_embd = data_torch + output_name = self.format_tensor_name(gguf.MODEL_TENSOR.OUTPUT) + tok_embd_name = self.format_tensor_name(gguf.MODEL_TENSOR.TOKEN_EMBD) - data = data_torch.squeeze().numpy() + new_name = self.map_tensor_name(name) - n_dims = len(data.shape) - data_dtype = data.dtype + if name.endswith(".A_log"): + logger.debug("A_log --> A ==> " + new_name) + data_torch = -torch.exp(data_torch) - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + # assuming token_embd.weight is seen before output.weight + if self._tok_embd is not None and new_name == output_name: + if torch.equal(self._tok_embd, data_torch): + logger.debug(f"{output_name} is equivalent to {tok_embd_name}, omitting") + return [] + elif new_name == tok_embd_name: + self._tok_embd = data_torch - # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + return [(new_name, data_torch)] - # if f16 desired, convert big float32 2-dim weight tensors to float16 - new_weight_name = new_name[:-len(".weight")] if new_name.endswith(".weight") else "" - if self.ftype == 1 and data_dtype == np.float32 and new_weight_name.endswith((".ssm_in", ".ssm_out", "token_embd", "output")) and n_dims == 2: - data = data.astype(np.float16) + def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: + del n_dims # unused - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") - - self.gguf_writer.add_tensor(new_name, data) + return bid is not None and new_name in ( + self.format_tensor_name(n, bid, ".weight" if name.endswith(".weight") else "") for n in [ + gguf.MODEL_TENSOR.SSM_CONV1D, + gguf.MODEL_TENSOR.SSM_X, + gguf.MODEL_TENSOR.SSM_DT, + gguf.MODEL_TENSOR.SSM_A, + gguf.MODEL_TENSOR.SSM_D, + ] + ) @Model.register("CohereForCausalLM") @@ -2846,53 +2263,142 @@ def set_gguf_parameters(self): # Same as super class, but permuting q_proj, k_proj # Copied from: LlamaModel - def write_tensors(self): - block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) - tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) - n_head = self.hparams.get("num_attention_heads") + def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: + del bid # unused + + n_head = self.hparams["num_attention_heads"] n_kv_head = self.hparams.get("num_key_value_heads") - for name, data_torch in self.get_tensors(): - old_dtype = data_torch.dtype - # convert any unsupported data types to float32 - if data_torch.dtype not in (torch.float16, torch.float32): - data_torch = data_torch.to(torch.float32) + if name.endswith("q_proj.weight"): + data_torch = LlamaModel.permute(data_torch, n_head, n_head) + if name.endswith("k_proj.weight"): + data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head) - data = data_torch.numpy() + return [(self.map_tensor_name(name), data_torch)] - if name.endswith("q_proj.weight"): - data = permute(data, n_head, n_head) - if name.endswith("k_proj.weight"): - data = permute(data, n_head, n_kv_head) - data = data.squeeze() +###### CONVERSION LOGIC ###### - # map tensor names - new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) - if new_name is None: - raise ValueError(f"Can not map tensor {name!r}") - n_dims = len(data.shape) - data_dtype = data.dtype +# tree of lazy tensors +class LazyTorchTensor: + _meta: Tensor + _data: Tensor | None + _args: tuple + _func: Callable[[tuple], Tensor] | None - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + def __init__(self, *, meta: Tensor, data: Tensor | None = None, args: tuple = (), func: Callable[[tuple], Tensor] | None = None): + self._meta = meta + self._data = data + self._args = args + self._func = func - # 1d tensors need to be converted to float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: - data = data.astype(np.float32) + @staticmethod + def _recurse_apply(o: Any, fn: Callable[[Any], Any]) -> Any: + # TODO: dict and set + if isinstance(o, (list, tuple)): + L = [] + for item in o: + L.append(LazyTorchTensor._recurse_apply(item, fn)) + if isinstance(o, tuple): + L = tuple(L) + return L + elif isinstance(o, LazyTorchTensor): + return fn(o) + else: + return o + + def _wrap_fn(self, fn: Callable, use_self: bool = False) -> Callable[[Any], LazyTorchTensor]: + def wrapped_fn(*args, **kwargs): + if kwargs is None: + kwargs = {} + args = ((self,) if use_self else ()) + args + + meta_args = LazyTorchTensor._recurse_apply(args, lambda t: t._meta) + + return LazyTorchTensor(meta=fn(*meta_args, **kwargs), args=args, func=lambda a: fn(*a, **kwargs)) + return wrapped_fn + + def __getattr__(self, __name: str) -> Any: + meta_attr = getattr(self._meta, __name) + if callable(meta_attr): + return self._wrap_fn(getattr(torch.Tensor, __name), use_self=True) + elif isinstance(meta_attr, torch.Tensor): + # for things like self.T + return self._wrap_fn(lambda s: getattr(s, __name))(self) + else: + return meta_attr - # if f16 desired, convert any float32 2-dim weight tensors to float16 - if self.ftype == 1 and data_dtype == np.float32 and n_dims == 2: - data = data.astype(np.float16) + _dtype_map: dict[torch.dtype, type] = { + torch.float16: np.float16, + torch.float32: np.float32, + } - logger.info(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + def numpy(self) -> gguf.LazyTensor: + dtype = self._dtype_map[self.dtype] + return gguf.LazyTensor(lambda: LazyTorchTensor.to_eager(self).numpy(), dtype=dtype, shape=self.shape) - self.gguf_writer.add_tensor(new_name, data) + @overload + @staticmethod + def to_eager(t: Tensor | LazyTorchTensor) -> Tensor: ... + @overload + @staticmethod + def to_eager(t: tuple) -> tuple: ... -###### CONVERSION LOGIC ###### + @staticmethod + def to_eager(t: Any) -> Any: + def simple_to_eager(_t: LazyTorchTensor) -> Tensor: + # wake up the lazy tensor + if _t._data is None and _t._func is not None: + # recurse into its arguments + _t._args = LazyTorchTensor.to_eager(_t._args) + _t._data = _t._func(_t._args) + if _t._data is not None: + return _t._data + else: + raise ValueError(f"Could not compute lazy tensor {_t!r} with args {_t._args!r}") + + # recurse into lists and/or tuples, keeping their structure + return LazyTorchTensor._recurse_apply(t, simple_to_eager) + + @staticmethod + def from_eager(t: Tensor) -> Tensor: + if (t.__class__ == LazyTorchTensor): + return t + return LazyTorchTensor(meta=t.detach().to("meta"), data=t) # type: ignore + + @classmethod + def __torch_function__(cls, func, types, args=(), kwargs=None): + del types # unused + + if kwargs is None: + kwargs = {} + + if func is torch.Tensor.numpy: + return args[0].numpy() + if func is torch.equal: + eager_args = LazyTorchTensor.to_eager(args) + return func(*eager_args, **kwargs) + + return LazyTorchTensor._wrap_fn(args[0], func)(*args, **kwargs) + + # special methods bypass __getattr__, so they need to be added manually + # ref: https://docs.python.org/3/reference/datamodel.html#special-lookup + # NOTE: LazyTorchTensor can't be a subclass of Tensor (and then be used + # as self._meta is currently used), because then the following + # operations would by default not be wrapped, and so not propagated + # when the tensor is made eager. + # It's better to get non-silent errors for not-yet-supported operators. + # TODO: add more when needed to avoid clutter, or find a more concise way + def __neg__(self, *args): # mamba + return self._wrap_fn(torch.Tensor.__neg__)(self, *args) + + def __add__(self, *args): # gemma + return self._wrap_fn(torch.Tensor.__add__)(self, *args) + + def __getitem__(self, *args): # bloom falcon refact internlm2 + return self._wrap_fn(torch.Tensor.__getitem__)(self, *args) def parse_args() -> argparse.Namespace: @@ -2904,7 +2410,8 @@ def parse_args() -> argparse.Namespace: ) parser.add_argument( "--awq-path", type=Path, default=None, - help="Path to scale awq cache file") + help="Path to scale awq cache file", + ) parser.add_argument( "--outfile", type=Path, help="path to write to; default: based on input", @@ -2913,14 +2420,30 @@ def parse_args() -> argparse.Namespace: "--outtype", type=str, choices=["f32", "f16"], default="f16", help="output format - use f32 for float32, f16 for float16", ) - parser.add_argument("--bigendian", action="store_true", help="model is executed on big endian machine") + parser.add_argument( + "--bigendian", action="store_true", + help="model is executed on big endian machine", + ) parser.add_argument( "model", type=Path, help="directory containing model file", ) - parser.add_argument("--use-temp-file", action="store_true", help="use the tempfile library while processing (helpful when running out of memory, process killed)") - parser.add_argument("--model-name", type=str, default=None, help="name of the model") - parser.add_argument("--verbose", action="store_true", help="increase output verbosity") + parser.add_argument( + "--use-temp-file", action="store_true", + help="use the tempfile library while processing (helpful when running out of memory, process killed)", + ) + parser.add_argument( + "--no-lazy", action="store_true", + help="use more RAM by computing all outputs before writing (use in case lazy evaluation is broken)", + ) + parser.add_argument( + "--model-name", type=str, default=None, + help="name of the model", + ) + parser.add_argument( + "--verbose", action="store_true", + help="increase output verbosity", + ) return parser.parse_args() @@ -2966,7 +2489,7 @@ def main() -> None: with torch.inference_mode(): model_class = Model.from_model_architecture(hparams["architectures"][0]) - model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian, args.use_temp_file) + model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian, args.use_temp_file, args.no_lazy) logger.info("Set model parameters") model_instance.set_gguf_parameters() diff --git a/convert.py b/convert.py index aebfc50f3b028..148bfd66ad65b 100755 --- a/convert.py +++ b/convert.py @@ -284,6 +284,7 @@ def loadOriginalParamsJson(model: LazyModel, config_path: Path) -> Params: n_experts = None n_experts_used = None f_rope_freq_base = None + n_ff = None # hack to determine LLaMA v1 vs v2 vs CodeLlama if config.get("moe"): @@ -308,6 +309,8 @@ def loadOriginalParamsJson(model: LazyModel, config_path: Path) -> Params: n_experts_used = config["moe"]["num_experts_per_tok"] f_rope_freq_base = 1e6 + assert n_ff is not None + return Params( n_vocab = model["tok_embeddings.weight"].shape[0], n_embd = config["dim"], @@ -462,7 +465,8 @@ def __init__(self, base_path: Path): # not found in alternate location either raise FileNotFoundError('Cannot find tokenizer.model') - self.sentencepiece_tokenizer = SentencePieceProcessor(str(fname_tokenizer)) + self.sentencepiece_tokenizer = SentencePieceProcessor() + self.sentencepiece_tokenizer.LoadFromFile(str(fname_tokenizer)) vocab_size = self.sentencepiece_tokenizer.vocab_size() new_tokens = {id: piece for piece, id in added_tokens.items() if id >= vocab_size} @@ -482,23 +486,23 @@ def __init__(self, base_path: Path): def sentencepiece_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: tokenizer = self.sentencepiece_tokenizer for i in range(tokenizer.vocab_size()): - piece = tokenizer.id_to_piece(i) + piece = tokenizer.IdToPiece(i) text = piece.encode("utf-8") - score: float = tokenizer.get_score(i) + score: float = tokenizer.GetScore(i) toktype = gguf.TokenType.NORMAL - if tokenizer.is_unknown(i): + if tokenizer.IsUnknown(i): toktype = gguf.TokenType.UNKNOWN - if tokenizer.is_control(i): + if tokenizer.IsControl(i): toktype = gguf.TokenType.CONTROL # NOTE: I think added_tokens are user defined. # ref: https://github.com/google/sentencepiece/blob/master/src/sentencepiece_model.proto # if tokenizer.is_user_defined(i): toktype = gguf.TokenType.USER_DEFINED - if tokenizer.is_unused(i): + if tokenizer.IsUnused(i): toktype = gguf.TokenType.UNUSED - if tokenizer.is_byte(i): + if tokenizer.IsByte(i): toktype = gguf.TokenType.BYTE yield text, score, toktype @@ -906,7 +910,7 @@ def load() -> UnquantizedTensor: def rebuild_from_type_v2(func, new_type, args, state): return func(*args) - CLASSES = { + CLASSES: dict[tuple[str, str], type[LazyTensor] | LazyStorageKind] = { # getattr used here as a workaround for mypy not being smart enough to determine # the staticmethods have a __func__ attribute. ('torch._tensor', '_rebuild_from_type_v2'): getattr(rebuild_from_type_v2, '__func__'), diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py index 0882a5d36193b..f4b1ac1d71840 100644 --- a/examples/server/tests/features/steps/steps.py +++ b/examples/server/tests/features/steps/steps.py @@ -939,7 +939,7 @@ async def oai_chat_completions(user_prompt, while event_received: event_received = False async for line_in_bytes in response.content: - line = line_in_bytes.decode('utf8') + line = line_in_bytes.decode('utf-8') line = line.rstrip('\n').rstrip('\r') if line == '': continue diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 6e968fc4e598f..5951c0bb0fb5e 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -860,7 +860,7 @@ def get_type(val: Any) -> GGUFValueType: # Note: Does not support GGML_QKK_64 QK_K = 256 # Items here are (block size, type size) -GGML_QUANT_SIZES = { +GGML_QUANT_SIZES: dict[GGMLQuantizationType, tuple[int, int]] = { GGMLQuantizationType.F32: (1, 4), GGMLQuantizationType.F16: (1, 2), GGMLQuantizationType.Q4_0: (32, 2 + 16), diff --git a/gguf-py/gguf/gguf_reader.py b/gguf-py/gguf/gguf_reader.py index db8525d85b450..21b089f8a2937 100644 --- a/gguf-py/gguf/gguf_reader.py +++ b/gguf-py/gguf/gguf_reader.py @@ -65,7 +65,7 @@ class ReaderTensor(NamedTuple): class GGUFReader: # I - same as host, S - swapped - byte_order: Literal['I' | 'S'] = 'I' + byte_order: Literal['I'] | Literal['S'] = 'I' alignment: int = GGUF_DEFAULT_ALIGNMENT # Note: Internal helper, API may change. @@ -83,7 +83,7 @@ class GGUFReader: GGUFValueType.BOOL: np.bool_, } - def __init__(self, path: os.PathLike[str] | str, mode: Literal['r' | 'r+' | 'c'] = 'r'): + def __init__(self, path: os.PathLike[str] | str, mode: Literal['r'] | Literal['r+'] | Literal['c'] = 'r'): self.data = np.memmap(path, mode = mode) offs = 0 if self._get(offs, np.uint32, override_order = '<')[0] != GGUF_MAGIC: @@ -128,7 +128,7 @@ def get_tensor(self, idx: int) -> ReaderTensor: return self.tensors[idx] def _get( - self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I' | 'S' | '<'] = None, + self, offset: int, dtype: npt.DTypeLike, count: int = 1, override_order: None | Literal['I'] | Literal['S'] | Literal['<'] = None, ) -> npt.NDArray[Any]: count = int(count) itemsize = int(np.empty([], dtype = dtype).itemsize) @@ -250,7 +250,7 @@ def _build_tensors(self, start_offs: int, fields: list[ReaderField]) -> None: raise ValueError(f'Found duplicated tensor with name {tensor_name}') tensor_names.add(tensor_name) ggml_type = GGMLQuantizationType(raw_dtype[0]) - n_elems = np.prod(dims) + n_elems = int(np.prod(dims)) block_size, type_size = GGML_QUANT_SIZES[ggml_type] n_bytes = n_elems * type_size // block_size data_offs = int(start_offs + offset_tensor[0]) diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py index d9cfbf71160d3..8dcf9330b076f 100644 --- a/gguf-py/gguf/gguf_writer.py +++ b/gguf-py/gguf/gguf_writer.py @@ -7,7 +7,7 @@ import tempfile from enum import Enum, auto from io import BufferedWriter -from typing import IO, Any, Sequence, Mapping +from typing import IO, Any, Callable, Sequence, Mapping from string import ascii_letters, digits import numpy as np @@ -28,6 +28,47 @@ logger = logging.getLogger(__name__) +class LazyTensor: + data: Callable[[], np.ndarray[Any, Any]] + # to avoid too deep recursion + functions: list[Callable[[np.ndarray[Any, Any]], np.ndarray[Any, Any]]] + dtype: np.dtype[Any] + shape: tuple[int, ...] + + def __init__(self, data: Callable[[], np.ndarray[Any, Any]], *, dtype: type, shape: tuple[int, ...]): + self.data = data + self.functions = [] + self.dtype = np.dtype(dtype) + self.shape = shape + + def astype(self, dtype: type, **kwargs) -> LazyTensor: + self.functions.append(lambda n: n.astype(dtype, **kwargs)) + self.dtype = np.dtype(dtype) + return self + + @property + def nbytes(self) -> int: + size = 1 + for n in self.shape: + size *= n + return size * self.dtype.itemsize + + def tofile(self, *args, **kwargs) -> None: + data = self.data() + for f in self.functions: + data = f(data) + assert data.shape == self.shape + assert data.dtype == self.dtype + assert data.nbytes == self.nbytes + self.functions = [] + self.data = lambda: data + data.tofile(*args, **kwargs) + + def byteswap(self, *args, **kwargs) -> LazyTensor: + self.functions.append(lambda n: n.byteswap(*args, **kwargs)) + return self + + class WriterState(Enum): EMPTY = auto() HEADER = auto() @@ -38,7 +79,7 @@ class WriterState(Enum): class GGUFWriter: fout: BufferedWriter temp_file: tempfile.SpooledTemporaryFile[bytes] | None - tensors: list[np.ndarray[Any, Any]] + tensors: list[np.ndarray[Any, Any] | LazyTensor] _simple_value_packing = { GGUFValueType.UINT8: "B", GGUFValueType.INT8: "b", @@ -176,7 +217,7 @@ def add_val(self, val: Any, vtype: GGUFValueType | None = None, add_vtype: bool if pack_fmt is not None: self.kv_data += self._pack(pack_fmt, val, skip_pack_prefix = vtype == GGUFValueType.BOOL) elif vtype == GGUFValueType.STRING: - encoded_val = val.encode("utf8") if isinstance(val, str) else val + encoded_val = val.encode("utf-8") if isinstance(val, str) else val self.kv_data += self._pack("Q", len(encoded_val)) self.kv_data += encoded_val elif vtype == GGUFValueType.ARRAY and isinstance(val, Sequence) and val: @@ -205,7 +246,7 @@ def add_tensor_info( raise ValueError(f'Duplicated tensor name {name}') self.ti_names.add(name) - encoded_name = name.encode("utf8") + encoded_name = name.encode("utf-8") self.ti_data += self._pack("Q", len(encoded_name)) self.ti_data += encoded_name n_dims = len(tensor_shape) @@ -237,7 +278,7 @@ def add_tensor_info( self.ti_data_count += 1 def add_tensor( - self, name: str, tensor: np.ndarray[Any, Any], raw_shape: Sequence[int] | None = None, + self, name: str, tensor: np.ndarray[Any, Any] | LazyTensor, raw_shape: Sequence[int] | None = None, raw_dtype: GGMLQuantizationType | None = None, ) -> None: if self.endianess == GGUFEndian.BIG: @@ -262,7 +303,7 @@ def write_padding(self, fp: IO[bytes], n: int, align: int | None = None) -> None if pad != 0: fp.write(bytes([0] * pad)) - def write_tensor_data(self, tensor: np.ndarray[Any, Any]) -> None: + def write_tensor_data(self, tensor: np.ndarray[Any, Any] | LazyTensor) -> None: if self.state is not WriterState.TI_DATA: raise ValueError(f'Expected output file to contain tensor info, got {self.state}') @@ -272,15 +313,33 @@ def write_tensor_data(self, tensor: np.ndarray[Any, Any]) -> None: tensor.tofile(self.fout) self.write_padding(self.fout, tensor.nbytes) - def write_tensors_to_file(self) -> None: + def write_tensors_to_file(self, *, progress: bool = False) -> None: self.write_ti_data_to_file() self.write_padding(self.fout, self.fout.tell()) if self.temp_file is None: + self.tensors.reverse() # to pop from the "beginning" in constant time + + if progress: + from tqdm import tqdm + + total_bytes = sum(t.nbytes for t in self.tensors) + + bar = tqdm(desc="Writing", total=total_bytes, unit="byte", unit_scale=True) + + while True: + try: + tensor = self.tensors.pop() + except IndexError: + break + tensor.tofile(self.fout) + bar.update(tensor.nbytes) + self.write_padding(self.fout, tensor.nbytes) + return while True: try: - tensor = self.tensors.pop(0) + tensor = self.tensors.pop() except IndexError: break tensor.tofile(self.fout) @@ -479,7 +538,7 @@ def add_add_space_prefix(self, value: bool) -> None: self.add_bool(Keys.Tokenizer.ADD_PREFIX, value) def add_chat_template(self, value: str | Sequence[Mapping[str, str]]) -> None: - if isinstance(value, list): + if not isinstance(value, str): template_default = None template_names = set() diff --git a/gguf-py/gguf/vocab.py b/gguf-py/gguf/vocab.py index c97a78f3944f4..3ba99be4f4489 100644 --- a/gguf-py/gguf/vocab.py +++ b/gguf-py/gguf/vocab.py @@ -4,7 +4,7 @@ import json import os from pathlib import Path -from typing import Any, Callable +from typing import Any, Callable, Sequence, Mapping, Iterable from .gguf_writer import GGUFWriter @@ -15,11 +15,11 @@ class SpecialVocab: merges: list[str] add_special_token: dict[str, bool] special_token_ids: dict[str, int] - chat_template: str | None + chat_template: str | Sequence[Mapping[str, str]] | None def __init__( self, path: str | os.PathLike[str], load_merges: bool = False, - special_token_types: tuple[str, ...] | None = None, + special_token_types: Iterable[str] | None = None, n_vocab: int | None = None, ): self.special_token_ids = {} diff --git a/gguf-py/pyproject.toml b/gguf-py/pyproject.toml index d1d876d6dffa6..36e63ee3b7cd6 100644 --- a/gguf-py/pyproject.toml +++ b/gguf-py/pyproject.toml @@ -21,6 +21,7 @@ classifiers = [ [tool.poetry.dependencies] python = ">=3.8" numpy = ">=1.17" +tqdm = ">=4.27" [tool.poetry.dev-dependencies] pytest = "^5.2" diff --git a/gguf-py/scripts/gguf-dump.py b/gguf-py/scripts/gguf-dump.py index 2d3c3943f64cd..1a37a7b91409d 100755 --- a/gguf-py/scripts/gguf-dump.py +++ b/gguf-py/scripts/gguf-dump.py @@ -47,7 +47,7 @@ def dump_metadata(reader: GGUFReader, args: argparse.Namespace) -> None: if len(field.types) == 1: curr_type = field.types[0] if curr_type == GGUFValueType.STRING: - log_message += ' = {0}'.format(repr(str(bytes(field.parts[-1]), encoding='utf8')[:60])) + log_message += ' = {0}'.format(repr(str(bytes(field.parts[-1]), encoding='utf-8')[:60])) elif field.types[0] in reader.gguf_scalar_to_np: log_message += ' = {0}'.format(field.parts[-1][0]) print(log_message) # noqa: NP100 diff --git a/gguf-py/scripts/gguf-new-metadata.py b/gguf-py/scripts/gguf-new-metadata.py index 3444ab41802c5..c8e3a83dfbd78 100644 --- a/gguf-py/scripts/gguf-new-metadata.py +++ b/gguf-py/scripts/gguf-new-metadata.py @@ -7,7 +7,7 @@ from pathlib import Path import numpy as np -from typing import Any, Mapping, Sequence +from typing import Any, Sequence # Necessary to load the local gguf package if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists(): @@ -34,7 +34,7 @@ def get_byteorder(reader: gguf.GGUFReader) -> gguf.GGUFEndian: return host_endian -def decode_field(field: gguf.ReaderField) -> Any: +def decode_field(field: gguf.ReaderField | None) -> Any: if field and field.types: main_type = field.types[0] @@ -42,11 +42,11 @@ def decode_field(field: gguf.ReaderField) -> Any: sub_type = field.types[-1] if sub_type == gguf.GGUFValueType.STRING: - return [str(bytes(field.parts[idx]), encoding='utf8') for idx in field.data] + return [str(bytes(field.parts[idx]), encoding='utf-8') for idx in field.data] else: return [pv for idx in field.data for pv in field.parts[idx].tolist()] if main_type == gguf.GGUFValueType.STRING: - return str(bytes(field.parts[-1]), encoding='utf8') + return str(bytes(field.parts[-1]), encoding='utf-8') else: return field.parts[-1][0] @@ -59,7 +59,7 @@ def get_field_data(reader: gguf.GGUFReader, key: str) -> Any: return decode_field(field) -def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new_metadata: Mapping[str, str], remove_metadata: Sequence[str]) -> None: +def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new_metadata: dict[str, str], remove_metadata: Sequence[str]) -> None: for field in reader.fields.values(): # Suppress virtual fields and fields written by GGUFWriter if field.name == gguf.Keys.General.ARCHITECTURE or field.name.startswith('GGUF.'): @@ -101,7 +101,7 @@ def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new for tensor in reader.tensors: # Dimensions are written in reverse order, so flip them first - shape = np.flipud(tensor.shape) + shape = np.flipud(tensor.shape).tolist() writer.add_tensor_info(tensor.name, shape, tensor.data.dtype, tensor.data.nbytes, tensor.tensor_type) writer.write_header_to_file() diff --git a/pyrightconfig.json b/pyrightconfig.json new file mode 100644 index 0000000000000..020a71a4ec214 --- /dev/null +++ b/pyrightconfig.json @@ -0,0 +1,3 @@ +{ + "extraPaths": ["gguf-py"], +} diff --git a/requirements/requirements-convert-hf-to-gguf-update.txt b/requirements/requirements-convert-hf-to-gguf-update.txt index 6ce840d73cb73..6ac4026107fbe 100644 --- a/requirements/requirements-convert-hf-to-gguf-update.txt +++ b/requirements/requirements-convert-hf-to-gguf-update.txt @@ -1,3 +1,2 @@ -r ./requirements-convert.txt torch~=2.1.1 -einops~=0.7.0 diff --git a/requirements/requirements-convert-hf-to-gguf.txt b/requirements/requirements-convert-hf-to-gguf.txt index 6ce840d73cb73..6ac4026107fbe 100644 --- a/requirements/requirements-convert-hf-to-gguf.txt +++ b/requirements/requirements-convert-hf-to-gguf.txt @@ -1,3 +1,2 @@ -r ./requirements-convert.txt torch~=2.1.1 -einops~=0.7.0 diff --git a/requirements/requirements-convert.txt b/requirements/requirements-convert.txt index 5520ba732ffca..7ab1228cb33ff 100644 --- a/requirements/requirements-convert.txt +++ b/requirements/requirements-convert.txt @@ -1,5 +1,5 @@ numpy~=1.24.4 -sentencepiece~=0.1.98 +sentencepiece~=0.2.0 transformers>=4.40.1,<5.0.0 gguf>=0.1.0 protobuf>=4.21.0,<5.0.0 From 4426e2987b566f09c7aa96ada9706cc778637620 Mon Sep 17 00:00:00 2001 From: Jared Van Bortel <jared@nomic.ai> Date: Wed, 8 May 2024 19:55:32 -0400 Subject: [PATCH 18/64] cmake : fix typo (#7151) --- CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 07b3a4388b0a6..aa65b0d6c3d04 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -431,7 +431,7 @@ if (LLAMA_CUDA) if (LLAMA_STATIC) if (WIN32) - # As of 12.3.1 CUDA Tookit for Windows does not offer a static cublas library + # As of 12.3.1 CUDA Toolkit for Windows does not offer a static cublas library set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas CUDA::cublasLt) else () set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static) From 07cd41d0965829463eff73eda3348aedbfd3a444 Mon Sep 17 00:00:00 2001 From: Ahmet Zeer <ahmed.zeer@std.yildiz.edu.tr> Date: Thu, 9 May 2024 11:16:45 +0300 Subject: [PATCH 19/64] TypoFix (#7162) --- examples/convert-llama2c-to-ggml/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/convert-llama2c-to-ggml/README.md b/examples/convert-llama2c-to-ggml/README.md index 6da2d7e1809a9..742dcf7a35b50 100644 --- a/examples/convert-llama2c-to-ggml/README.md +++ b/examples/convert-llama2c-to-ggml/README.md @@ -2,7 +2,7 @@ This example reads weights from project [llama2.c](https://github.com/karpathy/llama2.c) and saves them in ggml compatible format. The vocab that is available in `models/ggml-vocab.bin` is used by default. -To convert the model first download the models from the [llma2.c](https://github.com/karpathy/llama2.c) repository: +To convert the model first download the models from the [llama2.c](https://github.com/karpathy/llama2.c) repository: `$ make -j` From 47345248827f426038098d016ed11975021b4919 Mon Sep 17 00:00:00 2001 From: Albert Jin <albert.jin@gmail.com> Date: Thu, 9 May 2024 17:34:37 +0800 Subject: [PATCH 20/64] opencl : alignment size converted from bits to bytes (#7090) * opencl alignment size should be converted from bits to bytes Reference: https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_API.html#CL_DEVICE_MEM_BASE_ADDR_ALIGN > Alignment requirement (in bits) for sub-buffer offsets. * Update ggml-opencl.cpp for readability using division instead of shift Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> --- ggml-opencl.cpp | 1 + 1 file changed, 1 insertion(+) diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp index b3f8b7eaf0a3b..880a14958cec5 100644 --- a/ggml-opencl.cpp +++ b/ggml-opencl.cpp @@ -2119,6 +2119,7 @@ static size_t ggml_backend_opencl_buffer_type_get_alignment(ggml_backend_buffer_ if (alignment == (cl_uint)-1) { ggml_cl_init(); clGetDeviceInfo(device, CL_DEVICE_MEM_BASE_ADDR_ALIGN, sizeof(cl_uint), &alignment, NULL); + alignment /= 8; // bits to bytes } return alignment; From 22842164bcae3251b81ad9e497a16ef66833cb9e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sigbj=C3=B8rn=20Skj=C3=A6ret?= <sigbjorn.skjaeret@scala.com> Date: Thu, 9 May 2024 12:56:00 +0200 Subject: [PATCH 21/64] gguf-py : add special token modification capability (#7166) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add special token modification capability To be able to fix/amend special tokens in a GGUF let's add two new arguments: * `--special-token <name> <value>` where `<name>` can be bos, eos, prefix, middle, etc. while `<value>` is the token value, f.ex. `"<｜fim▁begin｜>"` * `--special-token-by-id <name> <id>` where `<id>` is the ID of the token, f.ex. 32006 So, in order to f.ex. add fill-in-middle tokens to a GGUF you would do the following: ```bash python3 gguf-new-metadata.py input.gguf output.gguf --special-token prefix "<｜fim▁begin｜>" --special-token middle "<｜fim▁hole｜>" --special-token suffix "<｜fim▁end｜>" ``` * improve help text * flake-- * fix multiple tokens warning * make script executable * switch to namedtuple, no need to dataclass * typing++ * add progress bar * Add special token modification capability To be able to fix/amend special tokens in a GGUF let's add two new arguments: * `--special-token <name> <value>` where `<name>` can be bos, eos, prefix, middle, etc. while `<value>` is the token value, f.ex. `"<｜fim▁begin｜>"` * `--special-token-by-id <name> <id>` where `<id>` is the ID of the token, f.ex. 32006 So, in order to f.ex. add fill-in-middle tokens to a GGUF you would do the following: ```bash gguf-new-metadata.py input.gguf output.gguf --special-token prefix "<｜fim▁begin｜>" --special-token middle "<｜fim▁end｜>" --special-token suffix "<｜fim▁hole｜>" ``` (yes, fim_end is the `middle` token, because completion is a `prefix`/`suffix`/`middle` sequence (where `middle` is unfilled)) or ```bash gguf-new-metadata.py input.gguf output.gguf --special-token prefix "<fim_prefix>" --special-token middle "<fim_middle>" --special-token suffix "<fim_suffix>" ``` etc... NB: The tokens have to exist already, trying to add non-existent token name/IDs will be ignored (with a warning), while non-existent values will fail (with an error). * improve help text * flake-- * fix multiple tokens warning * make script executable * switch to namedtuple, no need to dataclass * typing++ * add progress bar * fail on invalid token id --- gguf-py/scripts/gguf-new-metadata.py | 92 ++++++++++++++++++++++------ 1 file changed, 72 insertions(+), 20 deletions(-) mode change 100644 => 100755 gguf-py/scripts/gguf-new-metadata.py diff --git a/gguf-py/scripts/gguf-new-metadata.py b/gguf-py/scripts/gguf-new-metadata.py old mode 100644 new mode 100755 index c8e3a83dfbd78..63d3c5d8fdcf4 --- a/gguf-py/scripts/gguf-new-metadata.py +++ b/gguf-py/scripts/gguf-new-metadata.py @@ -7,7 +7,8 @@ from pathlib import Path import numpy as np -from typing import Any, Sequence +from tqdm import tqdm +from typing import Any, Sequence, NamedTuple # Necessary to load the local gguf package if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists(): @@ -18,6 +19,12 @@ logger = logging.getLogger("gguf-new-metadata") +class MetadataDetails(NamedTuple): + type: gguf.GGUFValueType + value: Any + description: str = '' + + def get_byteorder(reader: gguf.GGUFReader) -> gguf.GGUFEndian: if np.uint32(1) == np.uint32(1).newbyteorder("<"): # Host is little endian @@ -59,7 +66,16 @@ def get_field_data(reader: gguf.GGUFReader, key: str) -> Any: return decode_field(field) -def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new_metadata: dict[str, str], remove_metadata: Sequence[str]) -> None: +def find_token(token_list: Sequence[int], token: str) -> Sequence[int]: + token_ids = [index for index, value in enumerate(token_list) if value == token] + + if len(token_ids) == 0: + raise LookupError(f'Unable to find "{token}" in token list!') + + return token_ids + + +def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new_metadata: dict[str, MetadataDetails], remove_metadata: Sequence[str]) -> None: for field in reader.fields.values(): # Suppress virtual fields and fields written by GGUFWriter if field.name == gguf.Keys.General.ARCHITECTURE or field.name.startswith('GGUF.'): @@ -75,54 +91,64 @@ def copy_with_new_metadata(reader: gguf.GGUFReader, writer: gguf.GGUFWriter, new logger.debug(f'Removing {field.name}') continue - old_val = decode_field(field) + old_val = MetadataDetails(field.types[0], decode_field(field)) val = new_metadata.get(field.name, old_val) if field.name in new_metadata: - logger.debug(f'Modifying {field.name}: "{old_val}" -> "{val}"') + logger.debug(f'Modifying {field.name}: "{old_val.value}" -> "{val.value}" {val.description}') del new_metadata[field.name] - elif val is not None: + elif val.value is not None: logger.debug(f'Copying {field.name}') - if val is not None: + if val.value is not None: writer.add_key(field.name) - writer.add_val(val, field.types[0]) + writer.add_val(val.value, val.type) if gguf.Keys.Tokenizer.CHAT_TEMPLATE in new_metadata: logger.debug('Adding chat template(s)') - writer.add_chat_template(new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE]) + writer.add_chat_template(new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE].value) del new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE] - # TODO: Support other types than string? for key, val in new_metadata.items(): - logger.debug(f'Adding {key}: {val}') + logger.debug(f'Adding {key}: "{val.value}" {val.description}') writer.add_key(key) - writer.add_val(val, gguf.GGUFValueType.STRING) + writer.add_val(val.value, val.type) + + total_bytes = 0 for tensor in reader.tensors: + total_bytes += tensor.n_bytes # Dimensions are written in reverse order, so flip them first shape = np.flipud(tensor.shape).tolist() writer.add_tensor_info(tensor.name, shape, tensor.data.dtype, tensor.data.nbytes, tensor.tensor_type) + bar = tqdm(desc="Writing", total=total_bytes, unit="byte", unit_scale=True) + writer.write_header_to_file() writer.write_kv_data_to_file() writer.write_ti_data_to_file() for tensor in reader.tensors: writer.write_tensor_data(tensor.data) + bar.update(tensor.n_bytes) writer.close() def main() -> None: + tokenizer_metadata = (getattr(gguf.Keys.Tokenizer, n) for n in gguf.Keys.Tokenizer.__dict__.keys() if not n.startswith('_')) + token_names = dict((n.split('.')[-1][:-len('_token_id')], n) for n in tokenizer_metadata if n.endswith('_token_id')) + parser = argparse.ArgumentParser(description="Make a copy of a GGUF file with new metadata") parser.add_argument("input", type=Path, help="GGUF format model input filename") parser.add_argument("output", type=Path, help="GGUF format model output filename") - parser.add_argument("--general-name", type=str, help="The models general.name") - parser.add_argument("--general-description", type=str, help="The models general.description") - parser.add_argument("--chat-template", type=str, help="Chat template string (or JSON string containing templates)") - parser.add_argument("--chat-template-config", type=Path, help="Config file (tokenizer_config.json) containing chat template(s)") - parser.add_argument("--remove-metadata", action="append", type=str, help="Remove metadata (by key name) from output model") + parser.add_argument("--general-name", type=str, help="The models general.name", metavar='"name"') + parser.add_argument("--general-description", type=str, help="The models general.description", metavar='"Description ..."') + parser.add_argument("--chat-template", type=str, help="Chat template string (or JSON string containing templates)", metavar='"{% ... %} ..."') + parser.add_argument("--chat-template-config", type=Path, help="Config file containing chat template(s)", metavar='tokenizer_config.json') + parser.add_argument("--remove-metadata", action="append", type=str, help="Remove metadata (by key name) from output model", metavar='general.url') + parser.add_argument("--special-token", action="append", type=str, help="Special token by value", nargs=2, metavar=(' | '.join(token_names.keys()), '"<token>"')) + parser.add_argument("--special-token-by-id", action="append", type=str, help="Special token by id", nargs=2, metavar=(' | '.join(token_names.keys()), '0')) parser.add_argument("--force", action="store_true", help="Bypass warnings without confirmation") parser.add_argument("--verbose", action="store_true", help="Increase output verbosity") args = parser.parse_args(None if len(sys.argv) > 2 else ["--help"]) @@ -133,20 +159,20 @@ def main() -> None: remove_metadata = args.remove_metadata or [] if args.general_name: - new_metadata[gguf.Keys.General.NAME] = args.general_name + new_metadata[gguf.Keys.General.NAME] = MetadataDetails(gguf.GGUFValueType.STRING, args.general_name) if args.general_description: - new_metadata[gguf.Keys.General.DESCRIPTION] = args.general_description + new_metadata[gguf.Keys.General.DESCRIPTION] = MetadataDetails(gguf.GGUFValueType.STRING, args.general_description) if args.chat_template: - new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE] = json.loads(args.chat_template) if args.chat_template.startswith('[') else args.chat_template + new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE] = MetadataDetails(gguf.GGUFValueType.STRING, json.loads(args.chat_template) if args.chat_template.startswith('[') else args.chat_template) if args.chat_template_config: with open(args.chat_template_config, 'r') as fp: config = json.load(fp) template = config.get('chat_template') if template: - new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE] = template + new_metadata[gguf.Keys.Tokenizer.CHAT_TEMPLATE] = MetadataDetails(gguf.GGUFValueType.STRING, template) if remove_metadata: logger.warning('*** Warning *** Warning *** Warning **') @@ -166,6 +192,32 @@ def main() -> None: arch = get_field_data(reader, gguf.Keys.General.ARCHITECTURE) endianess = get_byteorder(reader) + token_list = get_field_data(reader, gguf.Keys.Tokenizer.LIST) or [] + + for name, token in args.special_token or []: + if name not in token_names: + logger.warning(f'Unknown special token "{name}", ignoring...') + else: + ids = find_token(token_list, token) + new_metadata[token_names[name]] = MetadataDetails(gguf.GGUFValueType.UINT32, ids[0], f'= {token}') + + if len(ids) > 1: + logger.warning(f'Multiple "{token}" tokens found, choosing ID {ids[0]}, use --special-token-by-id if you want another:') + logger.warning(', '.join(str(i) for i in ids)) + + for name, id_string in args.special_token_by_id or []: + if name not in token_names: + logger.warning(f'Unknown special token "{name}", ignoring...') + elif not id_string.isdecimal(): + raise LookupError(f'Token ID "{id_string}" is not a valid ID!') + else: + id_int = int(id_string) + + if id_int >= 0 and id_int < len(token_list): + new_metadata[token_names[name]] = MetadataDetails(gguf.GGUFValueType.UINT32, id_int, f'= {token_list[id_int]}') + else: + raise LookupError(f'Token ID {id_int} is not within token list!') + if os.path.isfile(args.output) and not args.force: logger.warning('*** Warning *** Warning *** Warning **') logger.warning(f'* The "{args.output}" GGUF file already exists, it will be overwritten!') From fd9f92b154850014146f61717cd292a59a5cee5a Mon Sep 17 00:00:00 2001 From: Daniel Bevenius <daniel.bevenius@gmail.com> Date: Thu, 9 May 2024 13:03:29 +0200 Subject: [PATCH 22/64] llama : update llama_timings.n_p_eval setting (#7160) This commit changes the value assigned to llama_timings.n_p_eval when ctx->n_p_eval is 0 to be 1 instead of 1 which is the current value. The motivation for this change is that if session caching is enabled, for example using the `--prompt-cache main-session.txt` command line argument for the main example, and if the same prompt is used then on subsequent runs, the prompt tokens will not actually be passed to llama_decode, and n_p_eval will not be updated by llama_synchoronize. But the value of n_p_eval will be set 1 by llama_get_timings because ctx->n_p_eval will be 0. This could be interpreted as 1 token was evaluated for the prompt which could be misleading for applications using this value. Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com> --- llama.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama.cpp b/llama.cpp index 9c72d118f2db2..806c2093262b1 100644 --- a/llama.cpp +++ b/llama.cpp @@ -17879,7 +17879,7 @@ struct llama_timings llama_get_timings(struct llama_context * ctx) { /*.t_eval_ms =*/ 1e-3 * ctx->t_eval_us, /*.n_sample =*/ std::max(1, ctx->n_sample), - /*.n_p_eval =*/ std::max(1, ctx->n_p_eval), + /*.n_p_eval =*/ std::max(0, ctx->n_p_eval), /*.n_eval =*/ std::max(1, ctx->n_eval), }; From f31ec120bc36c6270e4948e6a065a7c4cfa0c404 Mon Sep 17 00:00:00 2001 From: Galunid <karolek1231456@gmail.com> Date: Thu, 9 May 2024 14:13:05 +0200 Subject: [PATCH 23/64] Add warning if token is invalid (#7173) --- convert-hf-to-gguf-update.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index a26f45a5fb1d0..6fdb502f90c6e 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -49,6 +49,10 @@ class TOKENIZER_TYPE(IntEnum): if len(sys.argv) == 2: token = sys.argv[1] + if not token.startswith("hf_"): + logger.info("Huggingface token seems invalid") + logger.info("Usage: python convert-hf-to-gguf-update.py <huggingface_token>") + sys.exit(1) else: logger.info("Usage: python convert-hf-to-gguf-update.py <huggingface_token>") sys.exit(1) From a743d76a01f23038b2c85af1e9048ee836767b44 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= <johannesg@5d6.de> Date: Thu, 9 May 2024 14:32:02 +0200 Subject: [PATCH 24/64] CUDA: generalize FP16 fattn vec kernel (#7061) * CUDA: generalize FP16 fattn vec kernel * disable unsupported head sizes for AMD in test * try AMD fix * fix batch size 2-8 * partially revert changes --- ggml-cuda/common.cuh | 232 +++++++++++++++------------- ggml-cuda/fattn.cu | 305 +++++++++++++++++++++++++++---------- llama.cpp | 7 - tests/test-backend-ops.cpp | 4 + 4 files changed, 351 insertions(+), 197 deletions(-) diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh index a4197f11ba779..44e67e040e16a 100644 --- a/ggml-cuda/common.cuh +++ b/ggml-cuda/common.cuh @@ -234,6 +234,97 @@ typedef float dfloat; // dequantize float typedef float2 dfloat2; #endif //GGML_CUDA_F16 +#if defined(GGML_USE_HIPBLAS) +#define __CUDA_ARCH__ 1300 + +#if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \ + defined(__gfx1150__) || defined(__gfx1151__) +#define RDNA3 +#endif + +#if defined(__gfx1030__) || defined(__gfx1031__) || defined(__gfx1032__) || defined(__gfx1033__) || \ + defined(__gfx1034__) || defined(__gfx1035__) || defined(__gfx1036__) || defined(__gfx1037__) +#define RDNA2 +#endif + +#ifndef __has_builtin + #define __has_builtin(x) 0 +#endif + +typedef int8_t int8x4_t __attribute__((ext_vector_type(4))); +typedef uint8_t uint8x4_t __attribute__((ext_vector_type(4))); +static __device__ __forceinline__ int __vsubss4(const int a, const int b) { + const int8x4_t va = reinterpret_cast<const int8x4_t&>(a); + const int8x4_t vb = reinterpret_cast<const int8x4_t&>(b); +#if __has_builtin(__builtin_elementwise_sub_sat) + const int8x4_t c = __builtin_elementwise_sub_sat(va, vb); + return reinterpret_cast<const int &>(c); +#else + int8x4_t c; + int16_t tmp; +#pragma unroll + for (int i = 0; i < 4; i++) { + tmp = va[i] - vb[i]; + if(tmp > std::numeric_limits<int8_t>::max()) tmp = std::numeric_limits<int8_t>::max(); + if(tmp < std::numeric_limits<int8_t>::min()) tmp = std::numeric_limits<int8_t>::min(); + c[i] = tmp; + } + return reinterpret_cast<int &>(c); +#endif // __has_builtin(__builtin_elementwise_sub_sat) +} + +static __device__ __forceinline__ int __vsub4(const int a, const int b) { + return __vsubss4(a, b); +} + +static __device__ __forceinline__ unsigned int __vcmpeq4(unsigned int a, unsigned int b) { + const uint8x4_t& va = reinterpret_cast<const uint8x4_t&>(a); + const uint8x4_t& vb = reinterpret_cast<const uint8x4_t&>(b); + unsigned int c; + uint8x4_t& vc = reinterpret_cast<uint8x4_t&>(c); +#pragma unroll + for (int i = 0; i < 4; ++i) { + vc[i] = va[i] == vb[i] ? 0xff : 0x00; + } + return c; +} + +static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) { +#if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(__gfx1030__) + c = __builtin_amdgcn_sdot4(a, b, c, false); +#elif defined(RDNA3) + c = __builtin_amdgcn_sudot4( true, a, true, b, c, false); +#elif defined(__gfx1010__) || defined(__gfx900__) + int tmp1; + int tmp2; + asm("\n \ + v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_0 src1_sel:BYTE_0 \n \ + v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_1 src1_sel:BYTE_1 \n \ + v_add3_u32 %0, %1, %2, %0 \n \ + v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_2 src1_sel:BYTE_2 \n \ + v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_3 src1_sel:BYTE_3 \n \ + v_add3_u32 %0, %1, %2, %0 \n \ + " + : "+v"(c), "=&v"(tmp1), "=&v"(tmp2) + : "v"(a), "v"(b) + ); +#else + const int8x4_t va = reinterpret_cast<const int8x4_t&>(a); + const int8x4_t vb = reinterpret_cast<const int8x4_t&>(b); + c += va[0] * vb[0] + va[1] * vb[1] + va[2] * vb[2] + va[3] * vb[3]; +#endif + return c; +} +#endif // defined(GGML_USE_HIPBLAS) + +#define FP16_AVAILABLE (defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) || __CUDA_ARCH__ >= CC_PASCAL + +#define FP16_MMA_AVAILABLE !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_VOLTA + +static bool fp16_mma_available(const int cc) { + return cc < CC_OFFSET_AMD && cc >= CC_VOLTA; +} + [[noreturn]] static __device__ void no_device_code( const char * file_name, const int line, const char * function_name, const int arch, const char * arch_list) { @@ -275,16 +366,28 @@ static __device__ __forceinline__ float2 warp_reduce_sum(float2 a) { } static __device__ __forceinline__ half2 warp_reduce_sum(half2 a) { -#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_PASCAL +#if FP16_AVAILABLE + +#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) #pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - a = __hadd2(a, __shfl_xor_sync(0xffffffff, a, mask, 32)); - } - return a; + for (int mask = 16; mask > 0; mask >>= 1) { + const half2 a_other = __shfl_xor_sync(0xffffffff, a, mask, 32); + reinterpret_cast<half&>(a.x) += __low2half(a_other); + reinterpret_cast<half&>(a.y) += __high2half(a_other); + } + return a; #else - GGML_UNUSED(a); - NO_DEVICE_CODE; -#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_PASCAL +#pragma unroll + for (int mask = 16; mask > 0; mask >>= 1) { + a = __hadd2(a, __shfl_xor_sync(0xffffffff, a, mask, 32)); + } + return a; +#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) + +#else + NO_DEVICE_CODE; + return a; +#endif // FP16_AVAILABLE } static __device__ __forceinline__ float warp_reduce_max(float x) { @@ -296,20 +399,21 @@ static __device__ __forceinline__ float warp_reduce_max(float x) { } static __device__ __forceinline__ half ggml_cuda_hmax(const half a, const half b) { -#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +#if FP16_AVAILABLE -#if CUDART_VERSION >= CUDART_HMAX - return __hmax(a, b); +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && CUDART_VERSION < CUDART_HMAX + return __float2half(fmaxf(__half2float(a), __half2float(b))); #else - return __half2float(a) > __half2float(b) ? a : b; -#endif // CUDART_VERSION >= CUDART_HMAX + return __hmax(a, b); +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && CUDART_VERSION < CUDART_HMAX #else - GGML_UNUSED(a); - GGML_UNUSED(b); - NO_DEVICE_CODE; -#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && CUDART_VERSION < CUDART_HMAX + NO_DEVICE_CODE; + GGML_UNUSED(b); + return a; +#endif // FP16_AVAILABLE } + static __device__ __forceinline__ half2 ggml_cuda_hmax2(const half2 a, const half2 b) { #if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) @@ -317,8 +421,8 @@ static __device__ __forceinline__ half2 ggml_cuda_hmax2(const half2 a, const hal return __hmax2(a, b); #else half2 ret; - reinterpret_cast<half&>(ret.x) = __low2float(a) > __low2float(b) ? __low2half(a) : __low2half(b); - reinterpret_cast<half&>(ret.y) = __high2float(a) > __high2float(b) ? __high2half(a) : __high2half(b); + reinterpret_cast<half&>(ret.x) = __float2half(fmaxf( __low2float(a), __low2float(b))); + reinterpret_cast<half&>(ret.y) = __float2half(fmaxf(__high2float(a), __high2float(b))); return ret; #endif // CUDART_VERSION >= CUDART_HMAX @@ -326,7 +430,7 @@ static __device__ __forceinline__ half2 ggml_cuda_hmax2(const half2 a, const hal GGML_UNUSED(a); GGML_UNUSED(b); NO_DEVICE_CODE; -#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && CUDART_VERSION < CUDART_HMAX +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) } static __device__ __forceinline__ half2 warp_reduce_max(half2 x) { @@ -350,94 +454,6 @@ static __device__ __forceinline__ uint32_t __hgt2_mask(const half2 a, const half } #endif // CUDART_VERSION < 12000 -#if defined(GGML_USE_HIPBLAS) -#define __CUDA_ARCH__ 1300 - -#if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \ - defined(__gfx1150__) || defined(__gfx1151__) -#define RDNA3 -#endif - -#if defined(__gfx1030__) || defined(__gfx1031__) || defined(__gfx1032__) || defined(__gfx1033__) || \ - defined(__gfx1034__) || defined(__gfx1035__) || defined(__gfx1036__) || defined(__gfx1037__) -#define RDNA2 -#endif - -#ifndef __has_builtin - #define __has_builtin(x) 0 -#endif - -typedef int8_t int8x4_t __attribute__((ext_vector_type(4))); -typedef uint8_t uint8x4_t __attribute__((ext_vector_type(4))); -static __device__ __forceinline__ int __vsubss4(const int a, const int b) { - const int8x4_t va = reinterpret_cast<const int8x4_t&>(a); - const int8x4_t vb = reinterpret_cast<const int8x4_t&>(b); -#if __has_builtin(__builtin_elementwise_sub_sat) - const int8x4_t c = __builtin_elementwise_sub_sat(va, vb); - return reinterpret_cast<const int &>(c); -#else - int8x4_t c; - int16_t tmp; -#pragma unroll - for (int i = 0; i < 4; i++) { - tmp = va[i] - vb[i]; - if(tmp > std::numeric_limits<int8_t>::max()) tmp = std::numeric_limits<int8_t>::max(); - if(tmp < std::numeric_limits<int8_t>::min()) tmp = std::numeric_limits<int8_t>::min(); - c[i] = tmp; - } - return reinterpret_cast<int &>(c); -#endif // __has_builtin(__builtin_elementwise_sub_sat) -} - -static __device__ __forceinline__ int __vsub4(const int a, const int b) { - return __vsubss4(a, b); -} - -static __device__ __forceinline__ unsigned int __vcmpeq4(unsigned int a, unsigned int b) { - const uint8x4_t& va = reinterpret_cast<const uint8x4_t&>(a); - const uint8x4_t& vb = reinterpret_cast<const uint8x4_t&>(b); - unsigned int c; - uint8x4_t& vc = reinterpret_cast<uint8x4_t&>(c); -#pragma unroll - for (int i = 0; i < 4; ++i) { - vc[i] = va[i] == vb[i] ? 0xff : 0x00; - } - return c; -} - -static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) { -#if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(__gfx1030__) - c = __builtin_amdgcn_sdot4(a, b, c, false); -#elif defined(RDNA3) - c = __builtin_amdgcn_sudot4( true, a, true, b, c, false); -#elif defined(__gfx1010__) || defined(__gfx900__) - int tmp1; - int tmp2; - asm("\n \ - v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_0 src1_sel:BYTE_0 \n \ - v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_1 src1_sel:BYTE_1 \n \ - v_add3_u32 %0, %1, %2, %0 \n \ - v_mul_i32_i24 %1, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_2 src1_sel:BYTE_2 \n \ - v_mul_i32_i24 %2, sext(%3), sext(%4) dst_sel:DWORD dst_unused:UNUSED_PAD src0_sel:BYTE_3 src1_sel:BYTE_3 \n \ - v_add3_u32 %0, %1, %2, %0 \n \ - " - : "+v"(c), "=&v"(tmp1), "=&v"(tmp2) - : "v"(a), "v"(b) - ); -#else - const int8x4_t va = reinterpret_cast<const int8x4_t&>(a); - const int8x4_t vb = reinterpret_cast<const int8x4_t&>(b); - c += va[0] * vb[0] + va[1] * vb[1] + va[2] * vb[2] + va[3] * vb[3]; -#endif - return c; -} -#endif // defined(GGML_USE_HIPBLAS) - -#define FP16_AVAILABLE defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) ? \ - defined(RDNA1) || defined(RDNA2) || defined(RDNA3) : __CUDA_ARCH__ >= CC_PASCAL - -#define FP16_MMA_AVAILABLE !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_VOLTA - // TODO: move to ggml-common.h static const __device__ int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113}; diff --git a/ggml-cuda/fattn.cu b/ggml-cuda/fattn.cu index c8a11d1733464..7c486f4829bdd 100644 --- a/ggml-cuda/fattn.cu +++ b/ggml-cuda/fattn.cu @@ -11,8 +11,10 @@ #define HALF_MAX_HALF __float2half(65504.0f/2) // Use neg. of this instead of -INFINITY to initialize KQ max vals to avoid NaN upon subtraction. #define SOFTMAX_FTZ_THRESHOLD -20.0f // Softmax exp. of values smaller than this are flushed to zero to avoid NaNs. -template<int D, int parallel_blocks> // D == head size -__launch_bounds__(((D + WARP_SIZE - 1) / WARP_SIZE)*WARP_SIZE, 1) +template<int D, int ncols, int parallel_blocks> // D == head size +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +__launch_bounds__(D, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) static __global__ void flash_attn_vec_ext_f16( const char * __restrict__ Q, const char * __restrict__ K, @@ -44,55 +46,77 @@ static __global__ void flash_attn_vec_ext_f16( #if FP16_AVAILABLE //In this kernel Q, K, V are matrices while i, j, k are matrix indices. - const int ic = blockIdx.x / parallel_blocks; // Index of the Q/QKV column to work on. - const int ip = blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel. + const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on. + const int ip = blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel. const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. - const float2 * Q_f2 = (const float2 *) (Q + nb02* blockIdx.y + nb01*ic); + const float2 * Q_f2 = (const float2 *) (Q + nb02* blockIdx.y + nb01*ic0); const half2 * K_h2 = (const half2 *) (K + nb12*(blockIdx.y / gqa_ratio)); const half * V_h = (const half *) (V + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape - const half * maskh = (const half *) mask + ne11*ic; + const half * maskh = (const half *) mask + ne11*ic0; const int stride_KV = nb11 / sizeof(half); const int stride_KV2 = nb11 / sizeof(half2); - constexpr int nwarps = (D + WARP_SIZE - 1) / WARP_SIZE; + static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64."); + constexpr int nwarps = D / WARP_SIZE; const int tid = WARP_SIZE*threadIdx.y + threadIdx.x; - __builtin_assume(tid < nwarps*WARP_SIZE); + __builtin_assume(tid < D); - __shared__ half KQ[nwarps*WARP_SIZE]; - KQ[tid] = -INFINITY; + __shared__ half KQ[ncols*D]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + KQ[j*D + tid] = -HALF_MAX_HALF; + } half2 * KQ2 = (half2 *) KQ; - half kqmax = -HALF_MAX_HALF; - half kqsum = 0.0f; + half kqmax[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax[j] = -HALF_MAX_HALF; + } + half kqsum[ncols] = {0.0f}; - __shared__ half kqmax_shared[WARP_SIZE]; - __shared__ half kqsum_shared[WARP_SIZE]; - if (threadIdx.y == 0) { - kqmax_shared[threadIdx.x] = -HALF_MAX_HALF; - kqsum_shared[threadIdx.x] = 0.0f; + __shared__ half kqmax_shared[ncols][WARP_SIZE]; + __shared__ half kqsum_shared[ncols][WARP_SIZE]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + if (threadIdx.y == 0) { + kqmax_shared[j][threadIdx.x] = -HALF_MAX_HALF; + kqsum_shared[j][threadIdx.x] = 0.0f; + } } __syncthreads(); // Convert Q to half2 and store in registers: - half2 Q_h2[(D/2 + WARP_SIZE - 1) / WARP_SIZE]; + half2 Q_h2[ncols][D/(2*WARP_SIZE)]; #pragma unroll - for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) { - const int i = i0 + threadIdx.x; - if (i0 + WARP_SIZE > D/2 && i >= D/2) { - break; - } + for (int j = 0; j < ncols; ++j) { +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) { + const int i = i0 + threadIdx.x; - Q_h2[i0/WARP_SIZE] = make_half2(scale, scale) * make_half2(Q_f2[i].x, Q_f2[i].y); + const float2 tmp = Q_f2[j*(nb01/sizeof(float2)) + i]; + Q_h2[j][i0/WARP_SIZE] = make_half2(scale, scale) * make_half2(tmp.x, tmp.y); + } } - half2 VKQ = make_half2(0.0f, 0.0f); // Each thread calculates a single VKQ value. + half2 VKQ[ncols] = {{0.0f, 0.0f}}; - const int k_start = parallel_blocks == 1 ? 0 : ip*D; + const int k_start = parallel_blocks == 1 ? 0 : ip*D; for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*D) { // Calculate KQ tile and keep track of new maximum KQ values: - half kqmax_new = kqmax; + + // For unknown reasons using a half array of size 1 for kqmax_new causes a performance regression, + // see https://github.com/ggerganov/llama.cpp/pull/7061 . + // Therefore this variable is defined twice but only used once (so that the compiler can optimize out the unused variable). + half kqmax_new = kqmax[0]; + half kqmax_new_arr[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax_new_arr[j] = kqmax[j]; + } + #pragma unroll for (int i_KQ_0 = 0; i_KQ_0 < D; i_KQ_0 += nwarps) { const int i_KQ = i_KQ_0 + threadIdx.y; @@ -101,89 +125,112 @@ static __global__ void flash_attn_vec_ext_f16( break; } - half2 sum2 = make_half2(0.0f, 0.0f); + half2 sum2[ncols] = {{0.0f, 0.0f}}; #pragma unroll for (int k_KQ_0 = 0; k_KQ_0 < D/2; k_KQ_0 += WARP_SIZE) { const int k_KQ = k_KQ_0 + threadIdx.x; - if (k_KQ_0 + WARP_SIZE > D/2 && k_KQ >= D/2) { - break; - } const half2 K_ik = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ]; - sum2 += K_ik * Q_h2[k_KQ_0/WARP_SIZE]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum2[j] += K_ik * Q_h2[j][k_KQ_0/WARP_SIZE]; + } } - sum2 = warp_reduce_sum(sum2); - half sum = __low2half(sum2) + __high2half(sum2); - sum += mask ? maskh[k_VKQ_0 + i_KQ] : __float2half(0.0f); - kqmax_new = ggml_cuda_hmax(kqmax_new, sum); - if (threadIdx.x == 0) { - KQ[i_KQ] = sum; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum2[j] = warp_reduce_sum(sum2[j]); + half sum = __low2half(sum2[j]) + __high2half(sum2[j]); + sum += mask ? maskh[j*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f); + + if (ncols == 1) { + kqmax_new = ggml_cuda_hmax(kqmax_new, sum); + } else { + kqmax_new_arr[j] = ggml_cuda_hmax(kqmax_new_arr[j], sum); + } + + if (threadIdx.x == 0) { + KQ[j*D + i_KQ] = sum; + } } } - kqmax_new = warp_reduce_max(kqmax_new); - if (threadIdx.x == 0) { - kqmax_shared[threadIdx.y] = kqmax_new; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + half kqmax_new_j = ncols == 1 ? kqmax_new : kqmax_new_arr[j]; + + kqmax_new_j = warp_reduce_max(kqmax_new_j); + if (threadIdx.x == 0) { + kqmax_shared[j][threadIdx.y] = kqmax_new_j; + } } + __syncthreads(); - kqmax_new = kqmax_shared[threadIdx.x]; - kqmax_new = warp_reduce_max(kqmax_new); - const half KQ_max_scale = hexp(kqmax - kqmax_new); - kqmax = kqmax_new; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + half kqmax_new_j = kqmax_shared[j][threadIdx.x]; + kqmax_new_j = warp_reduce_max(kqmax_new_j); + + const half KQ_max_scale = hexp(kqmax[j] - kqmax_new_j); + kqmax[j] = kqmax_new_j; - const half val = hexp(KQ[tid] - kqmax); - kqsum = kqsum*KQ_max_scale + val; - KQ[tid] = val; + const half val = hexp(KQ[j*D + tid] - kqmax[j]); + kqsum[j] = kqsum[j]*KQ_max_scale + val; + KQ[j*D + tid] = val; - VKQ *= __half2half2(KQ_max_scale); + VKQ[j] *= __half2half2(KQ_max_scale); + } __syncthreads(); - if (tid < D) { #pragma unroll - for (int k0 = 0; k0 < D; k0 += 2) { - if (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + k0 >= ne11) { - break; - } + for (int k0 = 0; k0 < D; k0 += 2) { + if (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + k0 >= ne11) { + break; + } - half2 V_k; - reinterpret_cast<half&>(V_k.x) = V_h[(k_VKQ_0 + k0 + 0)*stride_KV + tid]; - reinterpret_cast<half&>(V_k.y) = V_h[(k_VKQ_0 + k0 + 1)*stride_KV + tid]; - VKQ += V_k*KQ2[k0/2]; + half2 V_k; + reinterpret_cast<half&>(V_k.x) = V_h[(k_VKQ_0 + k0 + 0)*stride_KV + tid]; + reinterpret_cast<half&>(V_k.y) = V_h[(k_VKQ_0 + k0 + 1)*stride_KV + tid]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + VKQ[j] += V_k*KQ2[j*(D/2) + k0/2]; } } __syncthreads(); } - if (tid >= D) { - kqsum = 0.0f; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqsum[j] = warp_reduce_sum(kqsum[j]); + if (threadIdx.x == 0) { + kqsum_shared[j][threadIdx.y] = kqsum[j]; + } } - kqsum = warp_reduce_sum(kqsum); - if (threadIdx.x == 0) { - kqsum_shared[threadIdx.y] = kqsum; - } __syncthreads(); - kqsum = kqsum_shared[threadIdx.x]; - kqsum = warp_reduce_sum(kqsum); - if (tid >= D) { - return; - } +#pragma unroll + for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) { + kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x]; + kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]); - half dst_val = (__low2half(VKQ) + __high2half(VKQ)); - if (parallel_blocks == 1) { - dst_val /= kqsum; + half dst_val = (__low2half(VKQ[j_VKQ]) + __high2half(VKQ[j_VKQ])); + if (parallel_blocks == 1) { + dst_val /= kqsum[j_VKQ]; + } + const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip; + dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val; } - dst[D*gridDim.y*blockIdx.x + D*blockIdx.y + tid] = dst_val; - if (parallel_blocks == 1 || tid != 0) { - return; + if (parallel_blocks != 1 && tid != 0) { +#pragma unroll + for (int j = 0; j < ncols; ++j) { + dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]); + } } - dst_meta[ic*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax, kqsum); #else NO_DEVICE_CODE; #endif // FP16_AVAILABLE @@ -191,7 +238,9 @@ static __global__ void flash_attn_vec_ext_f16( // D == head size, VKQ_stride == num VKQ rows calculated in parallel: template<int D, int ncols, int nwarps, int VKQ_stride, int parallel_blocks, typename KQ_acc_t> +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) __launch_bounds__(nwarps*WARP_SIZE, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) static __global__ void flash_attn_ext_f16( const char * __restrict__ Q, const char * __restrict__ K, @@ -573,7 +622,9 @@ static __global__ void flash_attn_ext_f16( } template<int D, int parallel_blocks> // D == head size +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) __launch_bounds__(D, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) static __global__ void flash_attn_combine_results( const float * __restrict__ VKQ_parts, const float2 * __restrict__ VKQ_meta, @@ -642,7 +693,7 @@ static_assert(get_VKQ_stride( 80, 1, 16) == 16, "Test failed."); static_assert(get_VKQ_stride( 80, 2, 16) == 16, "Test failed."); static_assert(get_VKQ_stride( 80, 4, 16) == 16, "Test failed."); -template <int D, int parallel_blocks> void launch_fattn_vec_f16( +template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f16( const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask, ggml_cuda_pool & pool, cudaStream_t main_stream ) { @@ -656,13 +707,13 @@ template <int D, int parallel_blocks> void launch_fattn_vec_f16( constexpr int nwarps = (D + WARP_SIZE - 1) / WARP_SIZE; const dim3 block_dim(WARP_SIZE, nwarps, 1); - const dim3 blocks_num(parallel_blocks*Q->ne[1], Q->ne[2], Q->ne[3]); + const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]); const int shmem = 0; float scale; memcpy(&scale, KQV->op_params, sizeof(float)); - flash_attn_vec_ext_f16<D, parallel_blocks> + flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks> <<<blocks_num, block_dim, shmem, main_stream>>> ( (const char *) Q->data, (const char *) K->data, @@ -783,10 +834,99 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst ggml_cuda_set_device(ctx.device); + const int cc = ggml_cuda_info().devices[ggml_cuda_get_device()].cc; const int nsm = ggml_cuda_info().devices[ggml_cuda_get_device()].nsm; const int32_t precision = KQV->op_params[1]; + if (!fp16_mma_available(cc)) { + GGML_ASSERT(precision == GGML_PREC_DEFAULT); + GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128."); + + if (Q->ne[1] == 1) { + constexpr int cols_per_block = 1; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] == 2) { + constexpr int cols_per_block = 2; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 4) { + constexpr int cols_per_block = 4; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 8) { + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 1; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + if (precision != GGML_PREC_DEFAULT) { if (Q->ne[1] <= 32 || Q->ne[0] > 128) { constexpr int cols_per_block = 16; @@ -845,16 +985,17 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst } if (Q->ne[1] == 1 && Q->ne[0] % (2*WARP_SIZE) == 0) { + constexpr int cols_per_block = 1; constexpr int parallel_blocks = 4; switch (Q->ne[0]) { case 64: - launch_fattn_vec_f16< 64, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); break; case 128: - launch_fattn_vec_f16<128, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); break; case 256: - launch_fattn_vec_f16<256, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + launch_fattn_vec_f16<256, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); break; default: GGML_ASSERT(false); diff --git a/llama.cpp b/llama.cpp index 806c2093262b1..7572f8d56be29 100644 --- a/llama.cpp +++ b/llama.cpp @@ -15519,13 +15519,6 @@ struct llama_context * llama_new_context_with_model( cparams.flash_attn = false; } -#ifdef GGML_USE_HIPBLAS - if (cparams.flash_attn) { - LLAMA_LOG_WARN("%s: flash_attn is not yet compatible with HIPBLAS builds - forcing off\n", __func__); - cparams.flash_attn = false; - } -#endif - if (params.seed == LLAMA_DEFAULT_SEED) { params.seed = time(NULL); } diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 41718e00172bf..0d66de5d9d389 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -2175,7 +2175,11 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op test_cases.emplace_back(new test_timestep_embedding()); test_cases.emplace_back(new test_leaky_relu()); +#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) + for (int hs : { 64, 128, }) { // other head sizes not implemented +#else for (int hs : { 64, 80, 128, 256, }) { +#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) for (int nh : { 32, }) { for (int kv : { 512, 1024, }) { for (int nb : { 1, 2, 4, 8, }) { From 43248e559472556f368988575d9fba906b3eb139 Mon Sep 17 00:00:00 2001 From: jaime-m-p <167997752+jaime-m-p@users.noreply.github.com> Date: Thu, 9 May 2024 15:30:44 +0200 Subject: [PATCH 25/64] llama3 custom regex split (#6965) * merged the changes from deepseeker models to main branch * Moved regex patterns to unicode.cpp and updated unicode.h * Moved header files * Resolved issues * added and refactored unicode_regex_split and related functions * Updated/merged the deepseek coder pr * Refactored code * Adding unicode regex mappings * Adding unicode regex function * Added needed functionality, testing remains * Fixed issues * Fixed issue with gpt2 regex custom preprocessor * unicode : fix? unicode_wstring_to_utf8 * lint : fix whitespaces * tests : add tokenizer tests for numbers * unicode : remove redundant headers * tests : remove and rename tokenizer test scripts * tests : add sample usage * gguf-py : reader prints warnings on duplicate keys * llama : towards llama3 tokenization support (wip) * unicode : shot in the dark to fix tests on Windows * unicode : first try custom implementations * convert : add "tokenizer.ggml.pre" GGUF KV (wip) * llama : use new pre-tokenizer type * convert : fix pre-tokenizer type writing * lint : fix * make : add test-tokenizer-0-llama-v3 * wip * models : add llama v3 vocab file * llama : adapt punctuation regex + add llama 3 regex * minor * unicode : set bomb * unicode : set bomb * unicode : always use std::wregex * unicode : support \p{N}, \p{L} and \p{P} natively * unicode : try fix windows * unicode : category support via std::regex * unicode : clean-up * unicode : simplify * llama3 custom regex split * convert : add convert-hf-to-gguf-update.py ggml-ci * lint : update * convert : add falcon ggml-ci * unicode : normalize signatures * lint : fix * lint : fix * convert : remove unused functions * convert : add comments * convert : exercise contractions ggml-ci * Using char32_t for codepoints * lint : fix * already exists unicode_tolower() * Typing * Restore BOM * cmake : refactor test targets * tests : refactor vocab tests ggml-ci * tests : add more vocabs and tests ggml-ci * unicode : cleanup * scripts : ignore new update script in check-requirements.sh * Fix merge * models : add phi-3, mpt, gpt-2, starcoder * tests : disable obsolete ggml-ci * tests : use faster bpe test ggml-ci * llama : more prominent warning for old BPE models * tests : disable test-tokenizer-1-bpe due to slowness ggml-ci * Move unused variable value * GPT2 custom regex split * Add alternative regex for custom aplit llama3 Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Style * Add bruteforce random tests for token encoding * wip: fixing unicode codepoint ranges * Fix merge * Unicode tables: separator, lowercase, uppercase and whitespace * llama3 custom regex split: fix \s * Restore BOM * Style * wip: generate NDF table * Ignore special tokens for testing * Clean gen-unicode-data.py * Refactor random tokenizer test * lint : fix * tests : add fail test for llama-bpe --------- Co-authored-by: Jaggzh <jaggz.h@gmail.com> Co-authored-by: Kazim Abrar Mahi <kazimabrarmahi135@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: jaime-m-p <> --- convert-hf-to-gguf-update.py | 1 + llama.cpp | 2 +- scripts/gen-unicode-data.py | 78 +- tests/test-tokenizer-random.py | 295 ++++++++ unicode-data.cpp | 1260 ++++++++++++++++++++++---------- unicode-data.h | 1 + unicode.cpp | 366 +++++++--- unicode.h | 4 +- 8 files changed, 1463 insertions(+), 544 deletions(-) create mode 100644 tests/test-tokenizer-random.py diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index 6fdb502f90c6e..e6468772210f8 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -261,6 +261,7 @@ def get_vocab_base_pre(self, tokenizer) -> str: "3333333", "33333333", "333333333", + # "Cửa Việt", # llama-bpe fails on this chktxt, ] diff --git a/llama.cpp b/llama.cpp index 7572f8d56be29..e7b3fd8b433b4 100644 --- a/llama.cpp +++ b/llama.cpp @@ -12488,7 +12488,7 @@ struct llm_tokenizer_wpm { continue; } code = unicode_tolower(code); - if (type == CODEPOINT_TYPE_WHITESPACE) { + if (type == CODEPOINT_TYPE_SEPARATOR) { code = ' '; } std::string s = unicode_cpt_to_utf8(code); diff --git a/scripts/gen-unicode-data.py b/scripts/gen-unicode-data.py index 977e65613e8ee..37d1e396c437f 100644 --- a/scripts/gen-unicode-data.py +++ b/scripts/gen-unicode-data.py @@ -1,31 +1,14 @@ import regex -def cpt_to_utf8_str(cpt): - if cpt <= 0xFF: - return bytes([cpt, 0, 0, 0]) - elif cpt <= 0xFFFF: - return bytes([cpt & 0xFF, cpt >> 8, 0, 0]) - elif cpt <= 0xFFFFFF: - return bytes([cpt & 0xFF, (cpt >> 8) & 0xFF, (cpt >> 16) & 0xFF, 0]) - else: - return bytes([cpt & 0xFF, (cpt >> 8) & 0xFF, (cpt >> 16) & 0xFF, cpt >> 24]) - - -def is_match(codepoint, regex_expr): - try: - res = regex.match(regex_expr, cpt_to_utf8_str(codepoint).decode('utf-32')) - return res is not None - except Exception: - return False - - def get_matches(regex_expr): + regex_expr_compiled = regex.compile(regex_expr) unicode_ranges = [] current_range = None for codepoint in range(0x110000): - if is_match(codepoint, regex_expr): + char = chr(codepoint) + if regex_expr_compiled.match(char): if current_range is None: current_range = [codepoint, codepoint] else: @@ -40,27 +23,42 @@ def get_matches(regex_expr): return unicode_ranges -def print_cat(cat, ranges): - print("const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_{} = {{".format(cat)) # noqa: NP100 - cnt = 0 - for start, end in ranges: - if cnt % 4 != 0: - print(" ", end="") # noqa: NP100 - print("{{0x{:08X}, 0x{:08X}}},".format(start, end), end="") # noqa: NP100 - if cnt % 4 == 3: - print("") # noqa: NP100 - cnt += 1 - - if cnt % 4 != 0: - print("") # noqa: NP100 +def print_cat(mode, cat, ranges): + if mode == "range": + print("const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_{} = {{".format(cat)) # noqa: NP100 + if mode == "map": + print("const std::map<uint32_t, uint32_t> unicode_map_{} = {{".format(cat)) # noqa: NP100 + for i, values in enumerate(ranges): + end = ",\n" if (i % 4 == 3 or i + 1 == len(ranges)) else ", " + values = ["0x%08X" % value for value in values] + print("{" + ", ".join(values) + "}", end=end) # noqa: NP100 print("};") # noqa: NP100 print("") # noqa: NP100 -print_cat("number", get_matches(r'\p{N}')) -print_cat("letter", get_matches(r'\p{L}')) -print_cat("whitespace", get_matches(r'\p{Z}')) -print_cat("accent_mark", get_matches(r'\p{M}')) -print_cat("punctuation", get_matches(r'\p{P}')) -print_cat("symbol", get_matches(r'\p{S}')) -print_cat("control", get_matches(r'\p{C}')) +print_cat("range", "number", get_matches(r'\p{N}')) +print_cat("range", "letter", get_matches(r'\p{L}')) +print_cat("range", "separator", get_matches(r'\p{Z}')) +print_cat("range", "accent_mark", get_matches(r'\p{M}')) +print_cat("range", "punctuation", get_matches(r'\p{P}')) +print_cat("range", "symbol", get_matches(r'\p{S}')) +print_cat("range", "control", get_matches(r'\p{C}')) + +print_cat("range", "whitespace", get_matches(r'\s')) + + +map_lowercase = [] +map_uppercase = [] +for codepoint in range(0x110000): + char = chr(codepoint) + lower = ord(char.lower()[0]) + upper = ord(char.upper()[0]) + if codepoint != lower: + map_lowercase.append((codepoint, lower)) + if codepoint != upper: + map_uppercase.append((codepoint, upper)) +print_cat("map", "lowercase", map_lowercase) +print_cat("map", "uppercase", map_uppercase) + + +# TODO: generate unicode_map_nfd diff --git a/tests/test-tokenizer-random.py b/tests/test-tokenizer-random.py new file mode 100644 index 0000000000000..5b2ab8ef71163 --- /dev/null +++ b/tests/test-tokenizer-random.py @@ -0,0 +1,295 @@ +# Test libllama tokenizer == AutoTokenizer. +# Brute force random tokens/text generation. +# +# Sample usage: +# +# python3 tests/test-tokenizer-random.py ./models/ggml-vocab-llama-bpe.gguf ./models/tokenizers/llama-bpe +# + +import time +import logging +import argparse +import subprocess +import random + +from typing import Iterator + +import cffi +from transformers import AutoTokenizer, PreTrainedTokenizerBase + +logger = logging.getLogger("test-tokenizer-random-bpe") + + +class LibLlama: + + DEFAULT_PATH_LLAMA_H = "./llama.h" + DEFAULT_PATH_LIBLLAMA = "./build/libllama.so" # CMakeLists.txt: BUILD_SHARED_LIBS ON + + def __init__(self, path_llama_h: str = None, path_libllama: str = None): + path_llama_h = path_llama_h or self.DEFAULT_PATH_LLAMA_H + path_libllama = path_libllama or self.DEFAULT_PATH_LIBLLAMA + (self.ffi, self.lib) = self._load_libllama_cffi(path_llama_h, path_libllama) + self.lib.llama_backend_init() + + def _load_libllama_cffi(self, path_llama_h: str, path_libllama: str): + cmd = ["gcc", "-E", "-P", "-D__restrict=", "-D__attribute__(x)=", "-D__asm__(x)=", path_llama_h] + res = subprocess.run(cmd, stdout=subprocess.PIPE) + assert (res.returncode == 0) + source = res.stdout.decode() + ffi = cffi.FFI() + if True: # workarounds for pycparser + source = "typedef struct { } __builtin_va_list;" + "\n" + source + source = source.replace("sizeof (int)", str(ffi.sizeof("int"))) + source = source.replace("sizeof (void *)", str(ffi.sizeof("void*"))) + source = source.replace("sizeof (size_t)", str(ffi.sizeof("size_t"))) + source = source.replace("sizeof(int32_t)", str(ffi.sizeof("int32_t"))) + ffi.cdef(source, override=True) + lib = ffi.dlopen(path_libllama) + return (ffi, lib) + + def model_default_params(self, **kwargs): + mparams = self.lib.llama_model_default_params() + for k, v in kwargs.items(): + setattr(mparams, k, v) + return mparams + + def context_default_params(self, **kwargs): + cparams = self.lib.llama_context_default_params() + for k, v in kwargs.items(): + setattr(cparams, k, v) + return cparams + + +class LibLlamaModel: + + def __init__(self, libllama: LibLlama, path_model: str, mparams={}, cparams={}): + self.lib = libllama.lib + self.ffi = libllama.ffi + if isinstance(mparams, dict): + mparams = libllama.model_default_params(**mparams) + self.model = self.lib.llama_load_model_from_file(path_model.encode(), mparams) + if not self.model: + raise RuntimeError("error: failed to load model '%s'" % path_model) + if isinstance(cparams, dict): + cparams = libllama.context_default_params(**cparams) + self.ctx = self.lib.llama_new_context_with_model(self.model, cparams) + if not self.ctx: + raise RuntimeError("error: failed to create context for model '%s'" % path_model) + n_tokens_max = self.lib.llama_n_ctx(self.ctx) + self.token_ids = self.ffi.new("llama_token[]", n_tokens_max) + + def free(self): + if self.ctx: + self.lib.llama_free(self.ctx) + if self.model: + self.lib.llama_free_model(self.model) + self.ctx = None + self.model = None + self.lib = None + + def tokenize(self, text: str, n_tokens_max: int = 0, add_special: bool = False, parse_special: bool = False) -> list[int]: + n_tokens_max = n_tokens_max if n_tokens_max > 0 else len(self.token_ids) + text = text.encode("utf-8") + num = self.lib.llama_tokenize(self.model, text, len(text), self.token_ids, n_tokens_max, add_special, parse_special) + if num < 0: + return [] + return list(self.token_ids[0:num]) + + +def generator_custom_text() -> Iterator[str]: + """General tests""" + yield from [ + "", + " ", + " ", + " ", + "\t", + "\n", + "\n\n", + "\n\n\n", + "\t\n", + "Hello world", + " Hello world", + "Hello World", + " Hello World", + " Hello World!", + "Hello, world!", + " Hello, world!", + " this is 🦙.cpp", + "w048 7tuijk dsdfhu", + "нещо на Български", + "កាន់តែពិសេសអាចខលចេញ", + "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", + "Hello", + " Hello", + " Hello", + " Hello", + " Hello", + " Hello\n Hello", + " (", + "\n =", + "' era", + "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", + "3", + "33", + "333", + "3333", + "33333", + "333333", + "3333333", + "33333333", + "333333333", + ] + + +def generator_custom_text_edge_cases() -> Iterator[str]: + """Edge cases found while debugging""" + yield from [ + '\x1f-a', # unicode_ranges_control, {0x00001C, 0x00001F} + '¼-a', # unicode_ranges_digit, 0x00BC + '½-a', # unicode_ranges_digit, 0x00BD + '¾-a', # unicode_ranges_digit, 0x00BE + 'a 〇b', # unicode_ranges_digit, 0x3007 + 'Ⅵ-a', # unicode_ranges_digit, {0x00002150, 0x0000218F} // Number Forms + '\uFEFF//', # unicode_ranges_control, 0xFEFF (BOM) + '<s>a' # TODO: Phi-3 fail + ] + + +def generator_random_chars(iterations = 100) -> Iterator[str]: + """Brute force random text with simple characters""" + + WHITESPACES = list(" " * 20 + "\n" * 5 + "\r\n" * 5 + "\t" * 5) + CHARS = list(set(""" + ABCDEFGHIJKLMNOPQRSTUVWXYZ + abcdefghijklmnopqrstuvwxyz + ÁÉÍÓÚÀÈÌÒÙÂÊÎÔÛÄËÏÖÜ + áéíóúàèìòùâêîôûäëïöü + .-,*/-+ª!"·$%&/()=?¿[]{}<>\\|@#~½¬~;:_ + """)) + + rand = random.Random() + for m in range(iterations): + rand.seed(m) + text = [] + num_words = rand.randint(300, 400) + for i in range(num_words): + k = rand.randint(1, 7) + word = rand.choices(CHARS, k=k) + space = rand.choice(WHITESPACES) + text.append("".join(word) + space) + yield "".join(text) + + +def generator_random_vocab_chars(tokenizer: PreTrainedTokenizerBase, iterations = 100) -> Iterator[str]: + """Brute force random text with vocab characters""" + + vocab_ids = list(tokenizer.vocab.values()) + vocab_text = tokenizer.decode(vocab_ids, skip_special_tokens=True) + vocab_chars = list(set(vocab_text)) + del vocab_ids, vocab_text + + rand = random.Random() + for m in range(iterations): + rand.seed(m) + text = rand.choices(vocab_chars, k=1024) + yield "".join(text) + + +def generator_random_vocab_tokens(tokenizer: PreTrainedTokenizerBase, iterations = 100) -> Iterator[str]: + """Brute force random text from vocab tokens""" + + space_id = tokenizer.encode(" ", add_special_tokens=False)[0] + vocab_ids = list(tokenizer.vocab.values()) + vocab_ids = list(sorted(vocab_ids + vocab_ids)) + for i in range(1, len(vocab_ids), 2): + vocab_ids[i] = space_id + vocab_tokens = tokenizer.decode(vocab_ids, skip_special_tokens=True) + vocab_tokens = vocab_tokens.split(" ") + del vocab_ids + + yield from vocab_tokens + + rand = random.Random() + for m in range(iterations): + rand.seed(m) + text = [] + num_words = rand.randint(300, 400) + for i in range(num_words): + k = rand.randint(1, 3) + tokens = rand.choices(vocab_tokens, k=k) + tokens = [t.strip(" \n\r\t") for t in tokens] + sep = rand.choice(" \n\r\t") + text.append("".join(tokens) + sep) + yield "".join(text) + + +def generator_random_bytes(iterations = 100) -> Iterator[str]: + """Brute force random bytes""" + + WHITESPACES = list(" " * 20 + "\n" * 5 + "\r\n" * 5 + "\t" * 5) + + rand = random.Random() + for m in range(iterations): + rand.seed(m) + text = [] + num_words = rand.randint(300, 400) + for i in range(num_words): + k = rand.randint(1, 8) + word = [chr(r) for r in rand.randbytes(k) if r] + word.append(rand.choice(WHITESPACES)) + text.append("".join(word)) + yield "".join(text) + + +def test_compare_tokenizer(model: LibLlamaModel, tokenizer: PreTrainedTokenizerBase, generator: Iterator[str]): + + def find_first_mismatch(ids1: list[int], ids2: list[int]): + for i, (a,b) in enumerate(zip(ids1, ids2)): + if a != b: + return i + if len(ids1) == len(ids2): + return -1 + return min(len(ids1), len(ids2)) + + t0 = time.perf_counter() + logger.info("%s: %s" % (generator.__name__, "ini")) + for text in generator: + ids1 = model.tokenize(text, add_special=False, parse_special=False) + ids2 = tokenizer.encode(text, add_special_tokens=False) + if ids1 != ids2: + i = find_first_mismatch(ids1, ids2) + ids1 = list(ids1)[max(0, i - 2) : i + 2 + 1] + ids2 = list(ids2)[max(0, i - 2) : i + 2 + 1] + text2 = tokenizer.decode(ids2, skip_special_tokens=True) + assert (text2 in text) + logger.info(" Text: " + repr(text2)) + logger.info(" TokenIDs: " + str(ids1)) + logger.info(" Expected: " + str(ids2)) + raise Exception() + t1 = time.perf_counter() + logger.info("%s: end, time: %.3f secs" % (generator.__name__, t1 - t0)) + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("vocab_file", help="path to vocab 'gguf' file") + parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file") + parser.add_argument("--verbose", action="store_true", help="increase output verbosity") + args = parser.parse_args() + + logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO) + + model = LibLlamaModel(LibLlama(), args.vocab_file, mparams=dict(vocab_only=True), cparams=dict(n_ctx=2048)) + + tokenizer = AutoTokenizer.from_pretrained(args.dir_tokenizer) + + test_compare_tokenizer(model, tokenizer, generator_custom_text()) + test_compare_tokenizer(model, tokenizer, generator_custom_text_edge_cases()) + test_compare_tokenizer(model, tokenizer, generator_random_chars(10_000)) + test_compare_tokenizer(model, tokenizer, generator_random_vocab_chars(tokenizer, 10_000)) + test_compare_tokenizer(model, tokenizer, generator_random_vocab_tokens(tokenizer, 10_000)) + # test_compare_tokenizer(model, tokenizer, generator_random_bytes(10_000)) # FAIL + + model.free() diff --git a/unicode-data.cpp b/unicode-data.cpp index 07bf02c4509fb..c54175fc3b485 100644 --- a/unicode-data.cpp +++ b/unicode-data.cpp @@ -7,7 +7,6 @@ // generated with scripts/gen-unicode-data.py // -// TODO: generate unicode_map_lowercase // TODO: generate unicode_map_nfd const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_number = { @@ -213,14 +212,20 @@ const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_letter = { {0x0001EE79, 0x0001EE7C}, {0x0001EE7E, 0x0001EE7E}, {0x0001EE80, 0x0001EE89}, {0x0001EE8B, 0x0001EE9B}, {0x0001EEA1, 0x0001EEA3}, {0x0001EEA5, 0x0001EEA9}, {0x0001EEAB, 0x0001EEBB}, {0x00020000, 0x0002A6DF}, {0x0002A700, 0x0002B739}, {0x0002B740, 0x0002B81D}, {0x0002B820, 0x0002CEA1}, {0x0002CEB0, 0x0002EBE0}, -{0x0002F800, 0x0002FA1D}, {0x00030000, 0x0003134A}, {0x00031350, 0x000323AF}, +{0x0002EBF0, 0x0002EE5D}, {0x0002F800, 0x0002FA1D}, {0x00030000, 0x0003134A}, {0x00031350, 0x000323AF}, }; -const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_whitespace = { +const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_separator = { {0x00000020, 0x00000020}, {0x000000A0, 0x000000A0}, {0x00001680, 0x00001680}, {0x00002000, 0x0000200A}, {0x00002028, 0x00002029}, {0x0000202F, 0x0000202F}, {0x0000205F, 0x0000205F}, {0x00003000, 0x00003000}, }; +const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_whitespace = { +{0x00000009, 0x0000000D}, {0x00000020, 0x00000020}, {0x00000085, 0x00000085}, {0x000000A0, 0x000000A0}, +{0x00001680, 0x00001680}, {0x00002000, 0x0000200A}, {0x00002028, 0x00002029}, {0x0000202F, 0x0000202F}, +{0x0000205F, 0x0000205F}, {0x00003000, 0x00003000}, +}; + const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_accent_mark = { {0x00000300, 0x0000036F}, {0x00000483, 0x00000489}, {0x00000591, 0x000005BD}, {0x000005BF, 0x000005BF}, {0x000005C1, 0x000005C2}, {0x000005C4, 0x000005C5}, {0x000005C7, 0x000005C7}, {0x00000610, 0x0000061A}, @@ -380,38 +385,39 @@ const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_symbol = { {0x0000249C, 0x000024E9}, {0x00002500, 0x00002767}, {0x00002794, 0x000027C4}, {0x000027C7, 0x000027E5}, {0x000027F0, 0x00002982}, {0x00002999, 0x000029D7}, {0x000029DC, 0x000029FB}, {0x000029FE, 0x00002B73}, {0x00002B76, 0x00002B95}, {0x00002B97, 0x00002BFF}, {0x00002CE5, 0x00002CEA}, {0x00002E50, 0x00002E51}, -{0x00002E80, 0x00002E99}, {0x00002E9B, 0x00002EF3}, {0x00002F00, 0x00002FD5}, {0x00002FF0, 0x00002FFB}, +{0x00002E80, 0x00002E99}, {0x00002E9B, 0x00002EF3}, {0x00002F00, 0x00002FD5}, {0x00002FF0, 0x00002FFF}, {0x00003004, 0x00003004}, {0x00003012, 0x00003013}, {0x00003020, 0x00003020}, {0x00003036, 0x00003037}, {0x0000303E, 0x0000303F}, {0x0000309B, 0x0000309C}, {0x00003190, 0x00003191}, {0x00003196, 0x0000319F}, -{0x000031C0, 0x000031E3}, {0x00003200, 0x0000321E}, {0x0000322A, 0x00003247}, {0x00003250, 0x00003250}, -{0x00003260, 0x0000327F}, {0x0000328A, 0x000032B0}, {0x000032C0, 0x000033FF}, {0x00004DC0, 0x00004DFF}, -{0x0000A490, 0x0000A4C6}, {0x0000A700, 0x0000A716}, {0x0000A720, 0x0000A721}, {0x0000A789, 0x0000A78A}, -{0x0000A828, 0x0000A82B}, {0x0000A836, 0x0000A839}, {0x0000AA77, 0x0000AA79}, {0x0000AB5B, 0x0000AB5B}, -{0x0000AB6A, 0x0000AB6B}, {0x0000FB29, 0x0000FB29}, {0x0000FBB2, 0x0000FBC2}, {0x0000FD40, 0x0000FD4F}, -{0x0000FDCF, 0x0000FDCF}, {0x0000FDFC, 0x0000FDFF}, {0x0000FE62, 0x0000FE62}, {0x0000FE64, 0x0000FE66}, -{0x0000FE69, 0x0000FE69}, {0x0000FF04, 0x0000FF04}, {0x0000FF0B, 0x0000FF0B}, {0x0000FF1C, 0x0000FF1E}, -{0x0000FF3E, 0x0000FF3E}, {0x0000FF40, 0x0000FF40}, {0x0000FF5C, 0x0000FF5C}, {0x0000FF5E, 0x0000FF5E}, -{0x0000FFE0, 0x0000FFE6}, {0x0000FFE8, 0x0000FFEE}, {0x0000FFFC, 0x0000FFFD}, {0x00010137, 0x0001013F}, -{0x00010179, 0x00010189}, {0x0001018C, 0x0001018E}, {0x00010190, 0x0001019C}, {0x000101A0, 0x000101A0}, -{0x000101D0, 0x000101FC}, {0x00010877, 0x00010878}, {0x00010AC8, 0x00010AC8}, {0x0001173F, 0x0001173F}, -{0x00011FD5, 0x00011FF1}, {0x00016B3C, 0x00016B3F}, {0x00016B45, 0x00016B45}, {0x0001BC9C, 0x0001BC9C}, -{0x0001CF50, 0x0001CFC3}, {0x0001D000, 0x0001D0F5}, {0x0001D100, 0x0001D126}, {0x0001D129, 0x0001D164}, -{0x0001D16A, 0x0001D16C}, {0x0001D183, 0x0001D184}, {0x0001D18C, 0x0001D1A9}, {0x0001D1AE, 0x0001D1EA}, -{0x0001D200, 0x0001D241}, {0x0001D245, 0x0001D245}, {0x0001D300, 0x0001D356}, {0x0001D6C1, 0x0001D6C1}, -{0x0001D6DB, 0x0001D6DB}, {0x0001D6FB, 0x0001D6FB}, {0x0001D715, 0x0001D715}, {0x0001D735, 0x0001D735}, -{0x0001D74F, 0x0001D74F}, {0x0001D76F, 0x0001D76F}, {0x0001D789, 0x0001D789}, {0x0001D7A9, 0x0001D7A9}, -{0x0001D7C3, 0x0001D7C3}, {0x0001D800, 0x0001D9FF}, {0x0001DA37, 0x0001DA3A}, {0x0001DA6D, 0x0001DA74}, -{0x0001DA76, 0x0001DA83}, {0x0001DA85, 0x0001DA86}, {0x0001E14F, 0x0001E14F}, {0x0001E2FF, 0x0001E2FF}, -{0x0001ECAC, 0x0001ECAC}, {0x0001ECB0, 0x0001ECB0}, {0x0001ED2E, 0x0001ED2E}, {0x0001EEF0, 0x0001EEF1}, -{0x0001F000, 0x0001F02B}, {0x0001F030, 0x0001F093}, {0x0001F0A0, 0x0001F0AE}, {0x0001F0B1, 0x0001F0BF}, -{0x0001F0C1, 0x0001F0CF}, {0x0001F0D1, 0x0001F0F5}, {0x0001F10D, 0x0001F1AD}, {0x0001F1E6, 0x0001F202}, -{0x0001F210, 0x0001F23B}, {0x0001F240, 0x0001F248}, {0x0001F250, 0x0001F251}, {0x0001F260, 0x0001F265}, -{0x0001F300, 0x0001F6D7}, {0x0001F6DC, 0x0001F6EC}, {0x0001F6F0, 0x0001F6FC}, {0x0001F700, 0x0001F776}, -{0x0001F77B, 0x0001F7D9}, {0x0001F7E0, 0x0001F7EB}, {0x0001F7F0, 0x0001F7F0}, {0x0001F800, 0x0001F80B}, -{0x0001F810, 0x0001F847}, {0x0001F850, 0x0001F859}, {0x0001F860, 0x0001F887}, {0x0001F890, 0x0001F8AD}, -{0x0001F8B0, 0x0001F8B1}, {0x0001F900, 0x0001FA53}, {0x0001FA60, 0x0001FA6D}, {0x0001FA70, 0x0001FA7C}, -{0x0001FA80, 0x0001FA88}, {0x0001FA90, 0x0001FABD}, {0x0001FABF, 0x0001FAC5}, {0x0001FACE, 0x0001FADB}, -{0x0001FAE0, 0x0001FAE8}, {0x0001FAF0, 0x0001FAF8}, {0x0001FB00, 0x0001FB92}, {0x0001FB94, 0x0001FBCA}, +{0x000031C0, 0x000031E3}, {0x000031EF, 0x000031EF}, {0x00003200, 0x0000321E}, {0x0000322A, 0x00003247}, +{0x00003250, 0x00003250}, {0x00003260, 0x0000327F}, {0x0000328A, 0x000032B0}, {0x000032C0, 0x000033FF}, +{0x00004DC0, 0x00004DFF}, {0x0000A490, 0x0000A4C6}, {0x0000A700, 0x0000A716}, {0x0000A720, 0x0000A721}, +{0x0000A789, 0x0000A78A}, {0x0000A828, 0x0000A82B}, {0x0000A836, 0x0000A839}, {0x0000AA77, 0x0000AA79}, +{0x0000AB5B, 0x0000AB5B}, {0x0000AB6A, 0x0000AB6B}, {0x0000FB29, 0x0000FB29}, {0x0000FBB2, 0x0000FBC2}, +{0x0000FD40, 0x0000FD4F}, {0x0000FDCF, 0x0000FDCF}, {0x0000FDFC, 0x0000FDFF}, {0x0000FE62, 0x0000FE62}, +{0x0000FE64, 0x0000FE66}, {0x0000FE69, 0x0000FE69}, {0x0000FF04, 0x0000FF04}, {0x0000FF0B, 0x0000FF0B}, +{0x0000FF1C, 0x0000FF1E}, {0x0000FF3E, 0x0000FF3E}, {0x0000FF40, 0x0000FF40}, {0x0000FF5C, 0x0000FF5C}, +{0x0000FF5E, 0x0000FF5E}, {0x0000FFE0, 0x0000FFE6}, {0x0000FFE8, 0x0000FFEE}, {0x0000FFFC, 0x0000FFFD}, +{0x00010137, 0x0001013F}, {0x00010179, 0x00010189}, {0x0001018C, 0x0001018E}, {0x00010190, 0x0001019C}, +{0x000101A0, 0x000101A0}, {0x000101D0, 0x000101FC}, {0x00010877, 0x00010878}, {0x00010AC8, 0x00010AC8}, +{0x0001173F, 0x0001173F}, {0x00011FD5, 0x00011FF1}, {0x00016B3C, 0x00016B3F}, {0x00016B45, 0x00016B45}, +{0x0001BC9C, 0x0001BC9C}, {0x0001CF50, 0x0001CFC3}, {0x0001D000, 0x0001D0F5}, {0x0001D100, 0x0001D126}, +{0x0001D129, 0x0001D164}, {0x0001D16A, 0x0001D16C}, {0x0001D183, 0x0001D184}, {0x0001D18C, 0x0001D1A9}, +{0x0001D1AE, 0x0001D1EA}, {0x0001D200, 0x0001D241}, {0x0001D245, 0x0001D245}, {0x0001D300, 0x0001D356}, +{0x0001D6C1, 0x0001D6C1}, {0x0001D6DB, 0x0001D6DB}, {0x0001D6FB, 0x0001D6FB}, {0x0001D715, 0x0001D715}, +{0x0001D735, 0x0001D735}, {0x0001D74F, 0x0001D74F}, {0x0001D76F, 0x0001D76F}, {0x0001D789, 0x0001D789}, +{0x0001D7A9, 0x0001D7A9}, {0x0001D7C3, 0x0001D7C3}, {0x0001D800, 0x0001D9FF}, {0x0001DA37, 0x0001DA3A}, +{0x0001DA6D, 0x0001DA74}, {0x0001DA76, 0x0001DA83}, {0x0001DA85, 0x0001DA86}, {0x0001E14F, 0x0001E14F}, +{0x0001E2FF, 0x0001E2FF}, {0x0001ECAC, 0x0001ECAC}, {0x0001ECB0, 0x0001ECB0}, {0x0001ED2E, 0x0001ED2E}, +{0x0001EEF0, 0x0001EEF1}, {0x0001F000, 0x0001F02B}, {0x0001F030, 0x0001F093}, {0x0001F0A0, 0x0001F0AE}, +{0x0001F0B1, 0x0001F0BF}, {0x0001F0C1, 0x0001F0CF}, {0x0001F0D1, 0x0001F0F5}, {0x0001F10D, 0x0001F1AD}, +{0x0001F1E6, 0x0001F202}, {0x0001F210, 0x0001F23B}, {0x0001F240, 0x0001F248}, {0x0001F250, 0x0001F251}, +{0x0001F260, 0x0001F265}, {0x0001F300, 0x0001F6D7}, {0x0001F6DC, 0x0001F6EC}, {0x0001F6F0, 0x0001F6FC}, +{0x0001F700, 0x0001F776}, {0x0001F77B, 0x0001F7D9}, {0x0001F7E0, 0x0001F7EB}, {0x0001F7F0, 0x0001F7F0}, +{0x0001F800, 0x0001F80B}, {0x0001F810, 0x0001F847}, {0x0001F850, 0x0001F859}, {0x0001F860, 0x0001F887}, +{0x0001F890, 0x0001F8AD}, {0x0001F8B0, 0x0001F8B1}, {0x0001F900, 0x0001FA53}, {0x0001FA60, 0x0001FA6D}, +{0x0001FA70, 0x0001FA7C}, {0x0001FA80, 0x0001FA88}, {0x0001FA90, 0x0001FABD}, {0x0001FABF, 0x0001FAC5}, +{0x0001FACE, 0x0001FADB}, {0x0001FAE0, 0x0001FAE8}, {0x0001FAF0, 0x0001FAF8}, {0x0001FB00, 0x0001FB92}, +{0x0001FB94, 0x0001FBCA}, }; const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_control = { @@ -484,116 +490,842 @@ const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_control = { {0x00002D97, 0x00002D9F}, {0x00002DA7, 0x00002DA7}, {0x00002DAF, 0x00002DAF}, {0x00002DB7, 0x00002DB7}, {0x00002DBF, 0x00002DBF}, {0x00002DC7, 0x00002DC7}, {0x00002DCF, 0x00002DCF}, {0x00002DD7, 0x00002DD7}, {0x00002DDF, 0x00002DDF}, {0x00002E5E, 0x00002E7F}, {0x00002E9A, 0x00002E9A}, {0x00002EF4, 0x00002EFF}, -{0x00002FD6, 0x00002FEF}, {0x00002FFC, 0x00002FFF}, {0x00003040, 0x00003040}, {0x00003097, 0x00003098}, -{0x00003100, 0x00003104}, {0x00003130, 0x00003130}, {0x0000318F, 0x0000318F}, {0x000031E4, 0x000031EF}, -{0x0000321F, 0x0000321F}, {0x0000A48D, 0x0000A48F}, {0x0000A4C7, 0x0000A4CF}, {0x0000A62C, 0x0000A63F}, -{0x0000A6F8, 0x0000A6FF}, {0x0000A7CB, 0x0000A7CF}, {0x0000A7D2, 0x0000A7D2}, {0x0000A7D4, 0x0000A7D4}, -{0x0000A7DA, 0x0000A7F1}, {0x0000A82D, 0x0000A82F}, {0x0000A83A, 0x0000A83F}, {0x0000A878, 0x0000A87F}, -{0x0000A8C6, 0x0000A8CD}, {0x0000A8DA, 0x0000A8DF}, {0x0000A954, 0x0000A95E}, {0x0000A97D, 0x0000A97F}, -{0x0000A9CE, 0x0000A9CE}, {0x0000A9DA, 0x0000A9DD}, {0x0000A9FF, 0x0000A9FF}, {0x0000AA37, 0x0000AA3F}, -{0x0000AA4E, 0x0000AA4F}, {0x0000AA5A, 0x0000AA5B}, {0x0000AAC3, 0x0000AADA}, {0x0000AAF7, 0x0000AB00}, -{0x0000AB07, 0x0000AB08}, {0x0000AB0F, 0x0000AB10}, {0x0000AB17, 0x0000AB1F}, {0x0000AB27, 0x0000AB27}, -{0x0000AB2F, 0x0000AB2F}, {0x0000AB6C, 0x0000AB6F}, {0x0000ABEE, 0x0000ABEF}, {0x0000ABFA, 0x0000ABFF}, -{0x0000D7A4, 0x0000D7AF}, {0x0000D7C7, 0x0000D7CA}, {0x0000D7FC, 0x0000D7FF}, {0x0000E000, 0x0000F8FF}, -{0x0000FA6E, 0x0000FA6F}, {0x0000FADA, 0x0000FAFF}, {0x0000FB07, 0x0000FB12}, {0x0000FB18, 0x0000FB1C}, -{0x0000FB37, 0x0000FB37}, {0x0000FB3D, 0x0000FB3D}, {0x0000FB3F, 0x0000FB3F}, {0x0000FB42, 0x0000FB42}, -{0x0000FB45, 0x0000FB45}, {0x0000FBC3, 0x0000FBD2}, {0x0000FD90, 0x0000FD91}, {0x0000FDC8, 0x0000FDCE}, -{0x0000FDD0, 0x0000FDEF}, {0x0000FE1A, 0x0000FE1F}, {0x0000FE53, 0x0000FE53}, {0x0000FE67, 0x0000FE67}, -{0x0000FE6C, 0x0000FE6F}, {0x0000FE75, 0x0000FE75}, {0x0000FEFD, 0x0000FEFE}, {0x0000FF00, 0x0000FF00}, -{0x0000FFBF, 0x0000FFC1}, {0x0000FFC8, 0x0000FFC9}, {0x0000FFD0, 0x0000FFD1}, {0x0000FFD8, 0x0000FFD9}, -{0x0000FFDD, 0x0000FFDF}, {0x0000FFE7, 0x0000FFE7}, {0x0000FFEF, 0x0000FFFB}, {0x0000FFFE, 0x0000FFFF}, -{0x0001000C, 0x0001000C}, {0x00010027, 0x00010027}, {0x0001003B, 0x0001003B}, {0x0001003E, 0x0001003E}, -{0x0001004E, 0x0001004F}, {0x0001005E, 0x0001007F}, {0x000100FB, 0x000100FF}, {0x00010103, 0x00010106}, -{0x00010134, 0x00010136}, {0x0001018F, 0x0001018F}, {0x0001019D, 0x0001019F}, {0x000101A1, 0x000101CF}, -{0x000101FE, 0x0001027F}, {0x0001029D, 0x0001029F}, {0x000102D1, 0x000102DF}, {0x000102FC, 0x000102FF}, -{0x00010324, 0x0001032C}, {0x0001034B, 0x0001034F}, {0x0001037B, 0x0001037F}, {0x0001039E, 0x0001039E}, -{0x000103C4, 0x000103C7}, {0x000103D6, 0x000103FF}, {0x0001049E, 0x0001049F}, {0x000104AA, 0x000104AF}, -{0x000104D4, 0x000104D7}, {0x000104FC, 0x000104FF}, {0x00010528, 0x0001052F}, {0x00010564, 0x0001056E}, -{0x0001057B, 0x0001057B}, {0x0001058B, 0x0001058B}, {0x00010593, 0x00010593}, {0x00010596, 0x00010596}, -{0x000105A2, 0x000105A2}, {0x000105B2, 0x000105B2}, {0x000105BA, 0x000105BA}, {0x000105BD, 0x000105FF}, -{0x00010737, 0x0001073F}, {0x00010756, 0x0001075F}, {0x00010768, 0x0001077F}, {0x00010786, 0x00010786}, -{0x000107B1, 0x000107B1}, {0x000107BB, 0x000107FF}, {0x00010806, 0x00010807}, {0x00010809, 0x00010809}, -{0x00010836, 0x00010836}, {0x00010839, 0x0001083B}, {0x0001083D, 0x0001083E}, {0x00010856, 0x00010856}, -{0x0001089F, 0x000108A6}, {0x000108B0, 0x000108DF}, {0x000108F3, 0x000108F3}, {0x000108F6, 0x000108FA}, -{0x0001091C, 0x0001091E}, {0x0001093A, 0x0001093E}, {0x00010940, 0x0001097F}, {0x000109B8, 0x000109BB}, -{0x000109D0, 0x000109D1}, {0x00010A04, 0x00010A04}, {0x00010A07, 0x00010A0B}, {0x00010A14, 0x00010A14}, -{0x00010A18, 0x00010A18}, {0x00010A36, 0x00010A37}, {0x00010A3B, 0x00010A3E}, {0x00010A49, 0x00010A4F}, -{0x00010A59, 0x00010A5F}, {0x00010AA0, 0x00010ABF}, {0x00010AE7, 0x00010AEA}, {0x00010AF7, 0x00010AFF}, -{0x00010B36, 0x00010B38}, {0x00010B56, 0x00010B57}, {0x00010B73, 0x00010B77}, {0x00010B92, 0x00010B98}, -{0x00010B9D, 0x00010BA8}, {0x00010BB0, 0x00010BFF}, {0x00010C49, 0x00010C7F}, {0x00010CB3, 0x00010CBF}, -{0x00010CF3, 0x00010CF9}, {0x00010D28, 0x00010D2F}, {0x00010D3A, 0x00010E5F}, {0x00010E7F, 0x00010E7F}, -{0x00010EAA, 0x00010EAA}, {0x00010EAE, 0x00010EAF}, {0x00010EB2, 0x00010EFC}, {0x00010F28, 0x00010F2F}, -{0x00010F5A, 0x00010F6F}, {0x00010F8A, 0x00010FAF}, {0x00010FCC, 0x00010FDF}, {0x00010FF7, 0x00010FFF}, -{0x0001104E, 0x00011051}, {0x00011076, 0x0001107E}, {0x000110BD, 0x000110BD}, {0x000110C3, 0x000110CF}, -{0x000110E9, 0x000110EF}, {0x000110FA, 0x000110FF}, {0x00011135, 0x00011135}, {0x00011148, 0x0001114F}, -{0x00011177, 0x0001117F}, {0x000111E0, 0x000111E0}, {0x000111F5, 0x000111FF}, {0x00011212, 0x00011212}, -{0x00011242, 0x0001127F}, {0x00011287, 0x00011287}, {0x00011289, 0x00011289}, {0x0001128E, 0x0001128E}, -{0x0001129E, 0x0001129E}, {0x000112AA, 0x000112AF}, {0x000112EB, 0x000112EF}, {0x000112FA, 0x000112FF}, -{0x00011304, 0x00011304}, {0x0001130D, 0x0001130E}, {0x00011311, 0x00011312}, {0x00011329, 0x00011329}, -{0x00011331, 0x00011331}, {0x00011334, 0x00011334}, {0x0001133A, 0x0001133A}, {0x00011345, 0x00011346}, -{0x00011349, 0x0001134A}, {0x0001134E, 0x0001134F}, {0x00011351, 0x00011356}, {0x00011358, 0x0001135C}, -{0x00011364, 0x00011365}, {0x0001136D, 0x0001136F}, {0x00011375, 0x000113FF}, {0x0001145C, 0x0001145C}, -{0x00011462, 0x0001147F}, {0x000114C8, 0x000114CF}, {0x000114DA, 0x0001157F}, {0x000115B6, 0x000115B7}, -{0x000115DE, 0x000115FF}, {0x00011645, 0x0001164F}, {0x0001165A, 0x0001165F}, {0x0001166D, 0x0001167F}, -{0x000116BA, 0x000116BF}, {0x000116CA, 0x000116FF}, {0x0001171B, 0x0001171C}, {0x0001172C, 0x0001172F}, -{0x00011747, 0x000117FF}, {0x0001183C, 0x0001189F}, {0x000118F3, 0x000118FE}, {0x00011907, 0x00011908}, -{0x0001190A, 0x0001190B}, {0x00011914, 0x00011914}, {0x00011917, 0x00011917}, {0x00011936, 0x00011936}, -{0x00011939, 0x0001193A}, {0x00011947, 0x0001194F}, {0x0001195A, 0x0001199F}, {0x000119A8, 0x000119A9}, -{0x000119D8, 0x000119D9}, {0x000119E5, 0x000119FF}, {0x00011A48, 0x00011A4F}, {0x00011AA3, 0x00011AAF}, -{0x00011AF9, 0x00011AFF}, {0x00011B0A, 0x00011BFF}, {0x00011C09, 0x00011C09}, {0x00011C37, 0x00011C37}, -{0x00011C46, 0x00011C4F}, {0x00011C6D, 0x00011C6F}, {0x00011C90, 0x00011C91}, {0x00011CA8, 0x00011CA8}, -{0x00011CB7, 0x00011CFF}, {0x00011D07, 0x00011D07}, {0x00011D0A, 0x00011D0A}, {0x00011D37, 0x00011D39}, -{0x00011D3B, 0x00011D3B}, {0x00011D3E, 0x00011D3E}, {0x00011D48, 0x00011D4F}, {0x00011D5A, 0x00011D5F}, -{0x00011D66, 0x00011D66}, {0x00011D69, 0x00011D69}, {0x00011D8F, 0x00011D8F}, {0x00011D92, 0x00011D92}, -{0x00011D99, 0x00011D9F}, {0x00011DAA, 0x00011EDF}, {0x00011EF9, 0x00011EFF}, {0x00011F11, 0x00011F11}, -{0x00011F3B, 0x00011F3D}, {0x00011F5A, 0x00011FAF}, {0x00011FB1, 0x00011FBF}, {0x00011FF2, 0x00011FFE}, -{0x0001239A, 0x000123FF}, {0x0001246F, 0x0001246F}, {0x00012475, 0x0001247F}, {0x00012544, 0x00012F8F}, -{0x00012FF3, 0x00012FFF}, {0x00013430, 0x0001343F}, {0x00013456, 0x000143FF}, {0x00014647, 0x000167FF}, -{0x00016A39, 0x00016A3F}, {0x00016A5F, 0x00016A5F}, {0x00016A6A, 0x00016A6D}, {0x00016ABF, 0x00016ABF}, -{0x00016ACA, 0x00016ACF}, {0x00016AEE, 0x00016AEF}, {0x00016AF6, 0x00016AFF}, {0x00016B46, 0x00016B4F}, -{0x00016B5A, 0x00016B5A}, {0x00016B62, 0x00016B62}, {0x00016B78, 0x00016B7C}, {0x00016B90, 0x00016E3F}, -{0x00016E9B, 0x00016EFF}, {0x00016F4B, 0x00016F4E}, {0x00016F88, 0x00016F8E}, {0x00016FA0, 0x00016FDF}, -{0x00016FE5, 0x00016FEF}, {0x00016FF2, 0x00016FFF}, {0x000187F8, 0x000187FF}, {0x00018CD6, 0x00018CFF}, -{0x00018D09, 0x0001AFEF}, {0x0001AFF4, 0x0001AFF4}, {0x0001AFFC, 0x0001AFFC}, {0x0001AFFF, 0x0001AFFF}, -{0x0001B123, 0x0001B131}, {0x0001B133, 0x0001B14F}, {0x0001B153, 0x0001B154}, {0x0001B156, 0x0001B163}, -{0x0001B168, 0x0001B16F}, {0x0001B2FC, 0x0001BBFF}, {0x0001BC6B, 0x0001BC6F}, {0x0001BC7D, 0x0001BC7F}, -{0x0001BC89, 0x0001BC8F}, {0x0001BC9A, 0x0001BC9B}, {0x0001BCA0, 0x0001CEFF}, {0x0001CF2E, 0x0001CF2F}, -{0x0001CF47, 0x0001CF4F}, {0x0001CFC4, 0x0001CFFF}, {0x0001D0F6, 0x0001D0FF}, {0x0001D127, 0x0001D128}, -{0x0001D173, 0x0001D17A}, {0x0001D1EB, 0x0001D1FF}, {0x0001D246, 0x0001D2BF}, {0x0001D2D4, 0x0001D2DF}, -{0x0001D2F4, 0x0001D2FF}, {0x0001D357, 0x0001D35F}, {0x0001D379, 0x0001D3FF}, {0x0001D455, 0x0001D455}, -{0x0001D49D, 0x0001D49D}, {0x0001D4A0, 0x0001D4A1}, {0x0001D4A3, 0x0001D4A4}, {0x0001D4A7, 0x0001D4A8}, -{0x0001D4AD, 0x0001D4AD}, {0x0001D4BA, 0x0001D4BA}, {0x0001D4BC, 0x0001D4BC}, {0x0001D4C4, 0x0001D4C4}, -{0x0001D506, 0x0001D506}, {0x0001D50B, 0x0001D50C}, {0x0001D515, 0x0001D515}, {0x0001D51D, 0x0001D51D}, -{0x0001D53A, 0x0001D53A}, {0x0001D53F, 0x0001D53F}, {0x0001D545, 0x0001D545}, {0x0001D547, 0x0001D549}, -{0x0001D551, 0x0001D551}, {0x0001D6A6, 0x0001D6A7}, {0x0001D7CC, 0x0001D7CD}, {0x0001DA8C, 0x0001DA9A}, -{0x0001DAA0, 0x0001DAA0}, {0x0001DAB0, 0x0001DEFF}, {0x0001DF1F, 0x0001DF24}, {0x0001DF2B, 0x0001DFFF}, -{0x0001E007, 0x0001E007}, {0x0001E019, 0x0001E01A}, {0x0001E022, 0x0001E022}, {0x0001E025, 0x0001E025}, -{0x0001E02B, 0x0001E02F}, {0x0001E06E, 0x0001E08E}, {0x0001E090, 0x0001E0FF}, {0x0001E12D, 0x0001E12F}, -{0x0001E13E, 0x0001E13F}, {0x0001E14A, 0x0001E14D}, {0x0001E150, 0x0001E28F}, {0x0001E2AF, 0x0001E2BF}, -{0x0001E2FA, 0x0001E2FE}, {0x0001E300, 0x0001E4CF}, {0x0001E4FA, 0x0001E7DF}, {0x0001E7E7, 0x0001E7E7}, -{0x0001E7EC, 0x0001E7EC}, {0x0001E7EF, 0x0001E7EF}, {0x0001E7FF, 0x0001E7FF}, {0x0001E8C5, 0x0001E8C6}, -{0x0001E8D7, 0x0001E8FF}, {0x0001E94C, 0x0001E94F}, {0x0001E95A, 0x0001E95D}, {0x0001E960, 0x0001EC70}, -{0x0001ECB5, 0x0001ED00}, {0x0001ED3E, 0x0001EDFF}, {0x0001EE04, 0x0001EE04}, {0x0001EE20, 0x0001EE20}, -{0x0001EE23, 0x0001EE23}, {0x0001EE25, 0x0001EE26}, {0x0001EE28, 0x0001EE28}, {0x0001EE33, 0x0001EE33}, -{0x0001EE38, 0x0001EE38}, {0x0001EE3A, 0x0001EE3A}, {0x0001EE3C, 0x0001EE41}, {0x0001EE43, 0x0001EE46}, -{0x0001EE48, 0x0001EE48}, {0x0001EE4A, 0x0001EE4A}, {0x0001EE4C, 0x0001EE4C}, {0x0001EE50, 0x0001EE50}, -{0x0001EE53, 0x0001EE53}, {0x0001EE55, 0x0001EE56}, {0x0001EE58, 0x0001EE58}, {0x0001EE5A, 0x0001EE5A}, -{0x0001EE5C, 0x0001EE5C}, {0x0001EE5E, 0x0001EE5E}, {0x0001EE60, 0x0001EE60}, {0x0001EE63, 0x0001EE63}, -{0x0001EE65, 0x0001EE66}, {0x0001EE6B, 0x0001EE6B}, {0x0001EE73, 0x0001EE73}, {0x0001EE78, 0x0001EE78}, -{0x0001EE7D, 0x0001EE7D}, {0x0001EE7F, 0x0001EE7F}, {0x0001EE8A, 0x0001EE8A}, {0x0001EE9C, 0x0001EEA0}, -{0x0001EEA4, 0x0001EEA4}, {0x0001EEAA, 0x0001EEAA}, {0x0001EEBC, 0x0001EEEF}, {0x0001EEF2, 0x0001EFFF}, -{0x0001F02C, 0x0001F02F}, {0x0001F094, 0x0001F09F}, {0x0001F0AF, 0x0001F0B0}, {0x0001F0C0, 0x0001F0C0}, -{0x0001F0D0, 0x0001F0D0}, {0x0001F0F6, 0x0001F0FF}, {0x0001F1AE, 0x0001F1E5}, {0x0001F203, 0x0001F20F}, -{0x0001F23C, 0x0001F23F}, {0x0001F249, 0x0001F24F}, {0x0001F252, 0x0001F25F}, {0x0001F266, 0x0001F2FF}, -{0x0001F6D8, 0x0001F6DB}, {0x0001F6ED, 0x0001F6EF}, {0x0001F6FD, 0x0001F6FF}, {0x0001F777, 0x0001F77A}, -{0x0001F7DA, 0x0001F7DF}, {0x0001F7EC, 0x0001F7EF}, {0x0001F7F1, 0x0001F7FF}, {0x0001F80C, 0x0001F80F}, -{0x0001F848, 0x0001F84F}, {0x0001F85A, 0x0001F85F}, {0x0001F888, 0x0001F88F}, {0x0001F8AE, 0x0001F8AF}, -{0x0001F8B2, 0x0001F8FF}, {0x0001FA54, 0x0001FA5F}, {0x0001FA6E, 0x0001FA6F}, {0x0001FA7D, 0x0001FA7F}, -{0x0001FA89, 0x0001FA8F}, {0x0001FABE, 0x0001FABE}, {0x0001FAC6, 0x0001FACD}, {0x0001FADC, 0x0001FADF}, -{0x0001FAE9, 0x0001FAEF}, {0x0001FAF9, 0x0001FAFF}, {0x0001FB93, 0x0001FB93}, {0x0001FBCB, 0x0001FBEF}, -{0x0001FBFA, 0x0001FFFF}, {0x0002A6E0, 0x0002A6FF}, {0x0002B73A, 0x0002B73F}, {0x0002B81E, 0x0002B81F}, -{0x0002CEA2, 0x0002CEAF}, {0x0002EBE1, 0x0002F7FF}, {0x0002FA1E, 0x0002FFFF}, {0x0003134B, 0x0003134F}, -{0x000323B0, 0x000E00FF}, {0x000E01F0, 0x0010FFFF}, +{0x00002FD6, 0x00002FEF}, {0x00003040, 0x00003040}, {0x00003097, 0x00003098}, {0x00003100, 0x00003104}, +{0x00003130, 0x00003130}, {0x0000318F, 0x0000318F}, {0x000031E4, 0x000031EE}, {0x0000321F, 0x0000321F}, +{0x0000A48D, 0x0000A48F}, {0x0000A4C7, 0x0000A4CF}, {0x0000A62C, 0x0000A63F}, {0x0000A6F8, 0x0000A6FF}, +{0x0000A7CB, 0x0000A7CF}, {0x0000A7D2, 0x0000A7D2}, {0x0000A7D4, 0x0000A7D4}, {0x0000A7DA, 0x0000A7F1}, +{0x0000A82D, 0x0000A82F}, {0x0000A83A, 0x0000A83F}, {0x0000A878, 0x0000A87F}, {0x0000A8C6, 0x0000A8CD}, +{0x0000A8DA, 0x0000A8DF}, {0x0000A954, 0x0000A95E}, {0x0000A97D, 0x0000A97F}, {0x0000A9CE, 0x0000A9CE}, +{0x0000A9DA, 0x0000A9DD}, {0x0000A9FF, 0x0000A9FF}, {0x0000AA37, 0x0000AA3F}, {0x0000AA4E, 0x0000AA4F}, +{0x0000AA5A, 0x0000AA5B}, {0x0000AAC3, 0x0000AADA}, {0x0000AAF7, 0x0000AB00}, {0x0000AB07, 0x0000AB08}, +{0x0000AB0F, 0x0000AB10}, {0x0000AB17, 0x0000AB1F}, {0x0000AB27, 0x0000AB27}, {0x0000AB2F, 0x0000AB2F}, +{0x0000AB6C, 0x0000AB6F}, {0x0000ABEE, 0x0000ABEF}, {0x0000ABFA, 0x0000ABFF}, {0x0000D7A4, 0x0000D7AF}, +{0x0000D7C7, 0x0000D7CA}, {0x0000D7FC, 0x0000F8FF}, {0x0000FA6E, 0x0000FA6F}, {0x0000FADA, 0x0000FAFF}, +{0x0000FB07, 0x0000FB12}, {0x0000FB18, 0x0000FB1C}, {0x0000FB37, 0x0000FB37}, {0x0000FB3D, 0x0000FB3D}, +{0x0000FB3F, 0x0000FB3F}, {0x0000FB42, 0x0000FB42}, {0x0000FB45, 0x0000FB45}, {0x0000FBC3, 0x0000FBD2}, +{0x0000FD90, 0x0000FD91}, {0x0000FDC8, 0x0000FDCE}, {0x0000FDD0, 0x0000FDEF}, {0x0000FE1A, 0x0000FE1F}, +{0x0000FE53, 0x0000FE53}, {0x0000FE67, 0x0000FE67}, {0x0000FE6C, 0x0000FE6F}, {0x0000FE75, 0x0000FE75}, +{0x0000FEFD, 0x0000FF00}, {0x0000FFBF, 0x0000FFC1}, {0x0000FFC8, 0x0000FFC9}, {0x0000FFD0, 0x0000FFD1}, +{0x0000FFD8, 0x0000FFD9}, {0x0000FFDD, 0x0000FFDF}, {0x0000FFE7, 0x0000FFE7}, {0x0000FFEF, 0x0000FFFB}, +{0x0000FFFE, 0x0000FFFF}, {0x0001000C, 0x0001000C}, {0x00010027, 0x00010027}, {0x0001003B, 0x0001003B}, +{0x0001003E, 0x0001003E}, {0x0001004E, 0x0001004F}, {0x0001005E, 0x0001007F}, {0x000100FB, 0x000100FF}, +{0x00010103, 0x00010106}, {0x00010134, 0x00010136}, {0x0001018F, 0x0001018F}, {0x0001019D, 0x0001019F}, +{0x000101A1, 0x000101CF}, {0x000101FE, 0x0001027F}, {0x0001029D, 0x0001029F}, {0x000102D1, 0x000102DF}, +{0x000102FC, 0x000102FF}, {0x00010324, 0x0001032C}, {0x0001034B, 0x0001034F}, {0x0001037B, 0x0001037F}, +{0x0001039E, 0x0001039E}, {0x000103C4, 0x000103C7}, {0x000103D6, 0x000103FF}, {0x0001049E, 0x0001049F}, +{0x000104AA, 0x000104AF}, {0x000104D4, 0x000104D7}, {0x000104FC, 0x000104FF}, {0x00010528, 0x0001052F}, +{0x00010564, 0x0001056E}, {0x0001057B, 0x0001057B}, {0x0001058B, 0x0001058B}, {0x00010593, 0x00010593}, +{0x00010596, 0x00010596}, {0x000105A2, 0x000105A2}, {0x000105B2, 0x000105B2}, {0x000105BA, 0x000105BA}, +{0x000105BD, 0x000105FF}, {0x00010737, 0x0001073F}, {0x00010756, 0x0001075F}, {0x00010768, 0x0001077F}, +{0x00010786, 0x00010786}, {0x000107B1, 0x000107B1}, {0x000107BB, 0x000107FF}, {0x00010806, 0x00010807}, +{0x00010809, 0x00010809}, {0x00010836, 0x00010836}, {0x00010839, 0x0001083B}, {0x0001083D, 0x0001083E}, +{0x00010856, 0x00010856}, {0x0001089F, 0x000108A6}, {0x000108B0, 0x000108DF}, {0x000108F3, 0x000108F3}, +{0x000108F6, 0x000108FA}, {0x0001091C, 0x0001091E}, {0x0001093A, 0x0001093E}, {0x00010940, 0x0001097F}, +{0x000109B8, 0x000109BB}, {0x000109D0, 0x000109D1}, {0x00010A04, 0x00010A04}, {0x00010A07, 0x00010A0B}, +{0x00010A14, 0x00010A14}, {0x00010A18, 0x00010A18}, {0x00010A36, 0x00010A37}, {0x00010A3B, 0x00010A3E}, +{0x00010A49, 0x00010A4F}, {0x00010A59, 0x00010A5F}, {0x00010AA0, 0x00010ABF}, {0x00010AE7, 0x00010AEA}, +{0x00010AF7, 0x00010AFF}, {0x00010B36, 0x00010B38}, {0x00010B56, 0x00010B57}, {0x00010B73, 0x00010B77}, +{0x00010B92, 0x00010B98}, {0x00010B9D, 0x00010BA8}, {0x00010BB0, 0x00010BFF}, {0x00010C49, 0x00010C7F}, +{0x00010CB3, 0x00010CBF}, {0x00010CF3, 0x00010CF9}, {0x00010D28, 0x00010D2F}, {0x00010D3A, 0x00010E5F}, +{0x00010E7F, 0x00010E7F}, {0x00010EAA, 0x00010EAA}, {0x00010EAE, 0x00010EAF}, {0x00010EB2, 0x00010EFC}, +{0x00010F28, 0x00010F2F}, {0x00010F5A, 0x00010F6F}, {0x00010F8A, 0x00010FAF}, {0x00010FCC, 0x00010FDF}, +{0x00010FF7, 0x00010FFF}, {0x0001104E, 0x00011051}, {0x00011076, 0x0001107E}, {0x000110BD, 0x000110BD}, +{0x000110C3, 0x000110CF}, {0x000110E9, 0x000110EF}, {0x000110FA, 0x000110FF}, {0x00011135, 0x00011135}, +{0x00011148, 0x0001114F}, {0x00011177, 0x0001117F}, {0x000111E0, 0x000111E0}, {0x000111F5, 0x000111FF}, +{0x00011212, 0x00011212}, {0x00011242, 0x0001127F}, {0x00011287, 0x00011287}, {0x00011289, 0x00011289}, +{0x0001128E, 0x0001128E}, {0x0001129E, 0x0001129E}, {0x000112AA, 0x000112AF}, {0x000112EB, 0x000112EF}, +{0x000112FA, 0x000112FF}, {0x00011304, 0x00011304}, {0x0001130D, 0x0001130E}, {0x00011311, 0x00011312}, +{0x00011329, 0x00011329}, {0x00011331, 0x00011331}, {0x00011334, 0x00011334}, {0x0001133A, 0x0001133A}, +{0x00011345, 0x00011346}, {0x00011349, 0x0001134A}, {0x0001134E, 0x0001134F}, {0x00011351, 0x00011356}, +{0x00011358, 0x0001135C}, {0x00011364, 0x00011365}, {0x0001136D, 0x0001136F}, {0x00011375, 0x000113FF}, +{0x0001145C, 0x0001145C}, {0x00011462, 0x0001147F}, {0x000114C8, 0x000114CF}, {0x000114DA, 0x0001157F}, +{0x000115B6, 0x000115B7}, {0x000115DE, 0x000115FF}, {0x00011645, 0x0001164F}, {0x0001165A, 0x0001165F}, +{0x0001166D, 0x0001167F}, {0x000116BA, 0x000116BF}, {0x000116CA, 0x000116FF}, {0x0001171B, 0x0001171C}, +{0x0001172C, 0x0001172F}, {0x00011747, 0x000117FF}, {0x0001183C, 0x0001189F}, {0x000118F3, 0x000118FE}, +{0x00011907, 0x00011908}, {0x0001190A, 0x0001190B}, {0x00011914, 0x00011914}, {0x00011917, 0x00011917}, +{0x00011936, 0x00011936}, {0x00011939, 0x0001193A}, {0x00011947, 0x0001194F}, {0x0001195A, 0x0001199F}, +{0x000119A8, 0x000119A9}, {0x000119D8, 0x000119D9}, {0x000119E5, 0x000119FF}, {0x00011A48, 0x00011A4F}, +{0x00011AA3, 0x00011AAF}, {0x00011AF9, 0x00011AFF}, {0x00011B0A, 0x00011BFF}, {0x00011C09, 0x00011C09}, +{0x00011C37, 0x00011C37}, {0x00011C46, 0x00011C4F}, {0x00011C6D, 0x00011C6F}, {0x00011C90, 0x00011C91}, +{0x00011CA8, 0x00011CA8}, {0x00011CB7, 0x00011CFF}, {0x00011D07, 0x00011D07}, {0x00011D0A, 0x00011D0A}, +{0x00011D37, 0x00011D39}, {0x00011D3B, 0x00011D3B}, {0x00011D3E, 0x00011D3E}, {0x00011D48, 0x00011D4F}, +{0x00011D5A, 0x00011D5F}, {0x00011D66, 0x00011D66}, {0x00011D69, 0x00011D69}, {0x00011D8F, 0x00011D8F}, +{0x00011D92, 0x00011D92}, {0x00011D99, 0x00011D9F}, {0x00011DAA, 0x00011EDF}, {0x00011EF9, 0x00011EFF}, +{0x00011F11, 0x00011F11}, {0x00011F3B, 0x00011F3D}, {0x00011F5A, 0x00011FAF}, {0x00011FB1, 0x00011FBF}, +{0x00011FF2, 0x00011FFE}, {0x0001239A, 0x000123FF}, {0x0001246F, 0x0001246F}, {0x00012475, 0x0001247F}, +{0x00012544, 0x00012F8F}, {0x00012FF3, 0x00012FFF}, {0x00013430, 0x0001343F}, {0x00013456, 0x000143FF}, +{0x00014647, 0x000167FF}, {0x00016A39, 0x00016A3F}, {0x00016A5F, 0x00016A5F}, {0x00016A6A, 0x00016A6D}, +{0x00016ABF, 0x00016ABF}, {0x00016ACA, 0x00016ACF}, {0x00016AEE, 0x00016AEF}, {0x00016AF6, 0x00016AFF}, +{0x00016B46, 0x00016B4F}, {0x00016B5A, 0x00016B5A}, {0x00016B62, 0x00016B62}, {0x00016B78, 0x00016B7C}, +{0x00016B90, 0x00016E3F}, {0x00016E9B, 0x00016EFF}, {0x00016F4B, 0x00016F4E}, {0x00016F88, 0x00016F8E}, +{0x00016FA0, 0x00016FDF}, {0x00016FE5, 0x00016FEF}, {0x00016FF2, 0x00016FFF}, {0x000187F8, 0x000187FF}, +{0x00018CD6, 0x00018CFF}, {0x00018D09, 0x0001AFEF}, {0x0001AFF4, 0x0001AFF4}, {0x0001AFFC, 0x0001AFFC}, +{0x0001AFFF, 0x0001AFFF}, {0x0001B123, 0x0001B131}, {0x0001B133, 0x0001B14F}, {0x0001B153, 0x0001B154}, +{0x0001B156, 0x0001B163}, {0x0001B168, 0x0001B16F}, {0x0001B2FC, 0x0001BBFF}, {0x0001BC6B, 0x0001BC6F}, +{0x0001BC7D, 0x0001BC7F}, {0x0001BC89, 0x0001BC8F}, {0x0001BC9A, 0x0001BC9B}, {0x0001BCA0, 0x0001CEFF}, +{0x0001CF2E, 0x0001CF2F}, {0x0001CF47, 0x0001CF4F}, {0x0001CFC4, 0x0001CFFF}, {0x0001D0F6, 0x0001D0FF}, +{0x0001D127, 0x0001D128}, {0x0001D173, 0x0001D17A}, {0x0001D1EB, 0x0001D1FF}, {0x0001D246, 0x0001D2BF}, +{0x0001D2D4, 0x0001D2DF}, {0x0001D2F4, 0x0001D2FF}, {0x0001D357, 0x0001D35F}, {0x0001D379, 0x0001D3FF}, +{0x0001D455, 0x0001D455}, {0x0001D49D, 0x0001D49D}, {0x0001D4A0, 0x0001D4A1}, {0x0001D4A3, 0x0001D4A4}, +{0x0001D4A7, 0x0001D4A8}, {0x0001D4AD, 0x0001D4AD}, {0x0001D4BA, 0x0001D4BA}, {0x0001D4BC, 0x0001D4BC}, +{0x0001D4C4, 0x0001D4C4}, {0x0001D506, 0x0001D506}, {0x0001D50B, 0x0001D50C}, {0x0001D515, 0x0001D515}, +{0x0001D51D, 0x0001D51D}, {0x0001D53A, 0x0001D53A}, {0x0001D53F, 0x0001D53F}, {0x0001D545, 0x0001D545}, +{0x0001D547, 0x0001D549}, {0x0001D551, 0x0001D551}, {0x0001D6A6, 0x0001D6A7}, {0x0001D7CC, 0x0001D7CD}, +{0x0001DA8C, 0x0001DA9A}, {0x0001DAA0, 0x0001DAA0}, {0x0001DAB0, 0x0001DEFF}, {0x0001DF1F, 0x0001DF24}, +{0x0001DF2B, 0x0001DFFF}, {0x0001E007, 0x0001E007}, {0x0001E019, 0x0001E01A}, {0x0001E022, 0x0001E022}, +{0x0001E025, 0x0001E025}, {0x0001E02B, 0x0001E02F}, {0x0001E06E, 0x0001E08E}, {0x0001E090, 0x0001E0FF}, +{0x0001E12D, 0x0001E12F}, {0x0001E13E, 0x0001E13F}, {0x0001E14A, 0x0001E14D}, {0x0001E150, 0x0001E28F}, +{0x0001E2AF, 0x0001E2BF}, {0x0001E2FA, 0x0001E2FE}, {0x0001E300, 0x0001E4CF}, {0x0001E4FA, 0x0001E7DF}, +{0x0001E7E7, 0x0001E7E7}, {0x0001E7EC, 0x0001E7EC}, {0x0001E7EF, 0x0001E7EF}, {0x0001E7FF, 0x0001E7FF}, +{0x0001E8C5, 0x0001E8C6}, {0x0001E8D7, 0x0001E8FF}, {0x0001E94C, 0x0001E94F}, {0x0001E95A, 0x0001E95D}, +{0x0001E960, 0x0001EC70}, {0x0001ECB5, 0x0001ED00}, {0x0001ED3E, 0x0001EDFF}, {0x0001EE04, 0x0001EE04}, +{0x0001EE20, 0x0001EE20}, {0x0001EE23, 0x0001EE23}, {0x0001EE25, 0x0001EE26}, {0x0001EE28, 0x0001EE28}, +{0x0001EE33, 0x0001EE33}, {0x0001EE38, 0x0001EE38}, {0x0001EE3A, 0x0001EE3A}, {0x0001EE3C, 0x0001EE41}, +{0x0001EE43, 0x0001EE46}, {0x0001EE48, 0x0001EE48}, {0x0001EE4A, 0x0001EE4A}, {0x0001EE4C, 0x0001EE4C}, +{0x0001EE50, 0x0001EE50}, {0x0001EE53, 0x0001EE53}, {0x0001EE55, 0x0001EE56}, {0x0001EE58, 0x0001EE58}, +{0x0001EE5A, 0x0001EE5A}, {0x0001EE5C, 0x0001EE5C}, {0x0001EE5E, 0x0001EE5E}, {0x0001EE60, 0x0001EE60}, +{0x0001EE63, 0x0001EE63}, {0x0001EE65, 0x0001EE66}, {0x0001EE6B, 0x0001EE6B}, {0x0001EE73, 0x0001EE73}, +{0x0001EE78, 0x0001EE78}, {0x0001EE7D, 0x0001EE7D}, {0x0001EE7F, 0x0001EE7F}, {0x0001EE8A, 0x0001EE8A}, +{0x0001EE9C, 0x0001EEA0}, {0x0001EEA4, 0x0001EEA4}, {0x0001EEAA, 0x0001EEAA}, {0x0001EEBC, 0x0001EEEF}, +{0x0001EEF2, 0x0001EFFF}, {0x0001F02C, 0x0001F02F}, {0x0001F094, 0x0001F09F}, {0x0001F0AF, 0x0001F0B0}, +{0x0001F0C0, 0x0001F0C0}, {0x0001F0D0, 0x0001F0D0}, {0x0001F0F6, 0x0001F0FF}, {0x0001F1AE, 0x0001F1E5}, +{0x0001F203, 0x0001F20F}, {0x0001F23C, 0x0001F23F}, {0x0001F249, 0x0001F24F}, {0x0001F252, 0x0001F25F}, +{0x0001F266, 0x0001F2FF}, {0x0001F6D8, 0x0001F6DB}, {0x0001F6ED, 0x0001F6EF}, {0x0001F6FD, 0x0001F6FF}, +{0x0001F777, 0x0001F77A}, {0x0001F7DA, 0x0001F7DF}, {0x0001F7EC, 0x0001F7EF}, {0x0001F7F1, 0x0001F7FF}, +{0x0001F80C, 0x0001F80F}, {0x0001F848, 0x0001F84F}, {0x0001F85A, 0x0001F85F}, {0x0001F888, 0x0001F88F}, +{0x0001F8AE, 0x0001F8AF}, {0x0001F8B2, 0x0001F8FF}, {0x0001FA54, 0x0001FA5F}, {0x0001FA6E, 0x0001FA6F}, +{0x0001FA7D, 0x0001FA7F}, {0x0001FA89, 0x0001FA8F}, {0x0001FABE, 0x0001FABE}, {0x0001FAC6, 0x0001FACD}, +{0x0001FADC, 0x0001FADF}, {0x0001FAE9, 0x0001FAEF}, {0x0001FAF9, 0x0001FAFF}, {0x0001FB93, 0x0001FB93}, +{0x0001FBCB, 0x0001FBEF}, {0x0001FBFA, 0x0001FFFF}, {0x0002A6E0, 0x0002A6FF}, {0x0002B73A, 0x0002B73F}, +{0x0002B81E, 0x0002B81F}, {0x0002CEA2, 0x0002CEAF}, {0x0002EBE1, 0x0002EBEF}, {0x0002EE5E, 0x0002F7FF}, +{0x0002FA1E, 0x0002FFFF}, {0x0003134B, 0x0003134F}, {0x000323B0, 0x000E00FF}, {0x000E01F0, 0x0010FFFF}, +}; + +const std::map<char32_t, char32_t> unicode_map_lowercase = { +{0x00000041, 0x00000061}, {0x00000042, 0x00000062}, {0x00000043, 0x00000063}, {0x00000044, 0x00000064}, +{0x00000045, 0x00000065}, {0x00000046, 0x00000066}, {0x00000047, 0x00000067}, {0x00000048, 0x00000068}, +{0x00000049, 0x00000069}, {0x0000004A, 0x0000006A}, {0x0000004B, 0x0000006B}, {0x0000004C, 0x0000006C}, +{0x0000004D, 0x0000006D}, {0x0000004E, 0x0000006E}, {0x0000004F, 0x0000006F}, {0x00000050, 0x00000070}, +{0x00000051, 0x00000071}, {0x00000052, 0x00000072}, {0x00000053, 0x00000073}, {0x00000054, 0x00000074}, +{0x00000055, 0x00000075}, {0x00000056, 0x00000076}, {0x00000057, 0x00000077}, {0x00000058, 0x00000078}, +{0x00000059, 0x00000079}, {0x0000005A, 0x0000007A}, {0x000000C0, 0x000000E0}, {0x000000C1, 0x000000E1}, +{0x000000C2, 0x000000E2}, {0x000000C3, 0x000000E3}, {0x000000C4, 0x000000E4}, {0x000000C5, 0x000000E5}, +{0x000000C6, 0x000000E6}, {0x000000C7, 0x000000E7}, {0x000000C8, 0x000000E8}, {0x000000C9, 0x000000E9}, +{0x000000CA, 0x000000EA}, {0x000000CB, 0x000000EB}, {0x000000CC, 0x000000EC}, {0x000000CD, 0x000000ED}, +{0x000000CE, 0x000000EE}, {0x000000CF, 0x000000EF}, {0x000000D0, 0x000000F0}, 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{0x00000132, 0x00000133}, {0x00000134, 0x00000135}, {0x00000136, 0x00000137}, +{0x00000139, 0x0000013A}, {0x0000013B, 0x0000013C}, {0x0000013D, 0x0000013E}, {0x0000013F, 0x00000140}, +{0x00000141, 0x00000142}, {0x00000143, 0x00000144}, {0x00000145, 0x00000146}, {0x00000147, 0x00000148}, +{0x0000014A, 0x0000014B}, {0x0000014C, 0x0000014D}, {0x0000014E, 0x0000014F}, {0x00000150, 0x00000151}, +{0x00000152, 0x00000153}, {0x00000154, 0x00000155}, {0x00000156, 0x00000157}, {0x00000158, 0x00000159}, +{0x0000015A, 0x0000015B}, {0x0000015C, 0x0000015D}, {0x0000015E, 0x0000015F}, {0x00000160, 0x00000161}, +{0x00000162, 0x00000163}, {0x00000164, 0x00000165}, {0x00000166, 0x00000167}, {0x00000168, 0x00000169}, +{0x0000016A, 0x0000016B}, {0x0000016C, 0x0000016D}, {0x0000016E, 0x0000016F}, {0x00000170, 0x00000171}, +{0x00000172, 0x00000173}, {0x00000174, 0x00000175}, {0x00000176, 0x00000177}, {0x00000178, 0x000000FF}, +{0x00000179, 0x0000017A}, {0x0000017B, 0x0000017C}, {0x0000017D, 0x0000017E}, 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{0x0000A78D, 0x00000265}, +{0x0000A790, 0x0000A791}, {0x0000A792, 0x0000A793}, {0x0000A796, 0x0000A797}, {0x0000A798, 0x0000A799}, +{0x0000A79A, 0x0000A79B}, {0x0000A79C, 0x0000A79D}, {0x0000A79E, 0x0000A79F}, {0x0000A7A0, 0x0000A7A1}, +{0x0000A7A2, 0x0000A7A3}, {0x0000A7A4, 0x0000A7A5}, {0x0000A7A6, 0x0000A7A7}, {0x0000A7A8, 0x0000A7A9}, +{0x0000A7AA, 0x00000266}, {0x0000A7AB, 0x0000025C}, {0x0000A7AC, 0x00000261}, {0x0000A7AD, 0x0000026C}, +{0x0000A7AE, 0x0000026A}, {0x0000A7B0, 0x0000029E}, {0x0000A7B1, 0x00000287}, {0x0000A7B2, 0x0000029D}, +{0x0000A7B3, 0x0000AB53}, {0x0000A7B4, 0x0000A7B5}, {0x0000A7B6, 0x0000A7B7}, {0x0000A7B8, 0x0000A7B9}, +{0x0000A7BA, 0x0000A7BB}, {0x0000A7BC, 0x0000A7BD}, {0x0000A7BE, 0x0000A7BF}, {0x0000A7C2, 0x0000A7C3}, +{0x0000A7C4, 0x0000A794}, {0x0000A7C5, 0x00000282}, {0x0000A7C6, 0x00001D8E}, {0x0000A7C7, 0x0000A7C8}, +{0x0000A7C9, 0x0000A7CA}, {0x0000A7F5, 0x0000A7F6}, {0x0000FF21, 0x0000FF41}, {0x0000FF22, 0x0000FF42}, +{0x0000FF23, 0x0000FF43}, {0x0000FF24, 0x0000FF44}, {0x0000FF25, 0x0000FF45}, {0x0000FF26, 0x0000FF46}, +{0x0000FF27, 0x0000FF47}, {0x0000FF28, 0x0000FF48}, {0x0000FF29, 0x0000FF49}, {0x0000FF2A, 0x0000FF4A}, +{0x0000FF2B, 0x0000FF4B}, {0x0000FF2C, 0x0000FF4C}, {0x0000FF2D, 0x0000FF4D}, {0x0000FF2E, 0x0000FF4E}, +{0x0000FF2F, 0x0000FF4F}, {0x0000FF30, 0x0000FF50}, {0x0000FF31, 0x0000FF51}, {0x0000FF32, 0x0000FF52}, +{0x0000FF33, 0x0000FF53}, {0x0000FF34, 0x0000FF54}, {0x0000FF35, 0x0000FF55}, {0x0000FF36, 0x0000FF56}, +{0x0000FF37, 0x0000FF57}, {0x0000FF38, 0x0000FF58}, {0x0000FF39, 0x0000FF59}, {0x0000FF3A, 0x0000FF5A}, +{0x00010400, 0x00010428}, {0x00010401, 0x00010429}, {0x00010402, 0x0001042A}, {0x00010403, 0x0001042B}, +{0x00010404, 0x0001042C}, {0x00010405, 0x0001042D}, {0x00010406, 0x0001042E}, {0x00010407, 0x0001042F}, +{0x00010408, 0x00010430}, {0x00010409, 0x00010431}, {0x0001040A, 0x00010432}, {0x0001040B, 0x00010433}, +{0x0001040C, 0x00010434}, {0x0001040D, 0x00010435}, {0x0001040E, 0x00010436}, {0x0001040F, 0x00010437}, +{0x00010410, 0x00010438}, {0x00010411, 0x00010439}, {0x00010412, 0x0001043A}, {0x00010413, 0x0001043B}, +{0x00010414, 0x0001043C}, {0x00010415, 0x0001043D}, {0x00010416, 0x0001043E}, {0x00010417, 0x0001043F}, +{0x00010418, 0x00010440}, {0x00010419, 0x00010441}, {0x0001041A, 0x00010442}, {0x0001041B, 0x00010443}, +{0x0001041C, 0x00010444}, {0x0001041D, 0x00010445}, {0x0001041E, 0x00010446}, {0x0001041F, 0x00010447}, +{0x00010420, 0x00010448}, {0x00010421, 0x00010449}, {0x00010422, 0x0001044A}, {0x00010423, 0x0001044B}, +{0x00010424, 0x0001044C}, {0x00010425, 0x0001044D}, {0x00010426, 0x0001044E}, {0x00010427, 0x0001044F}, +{0x000104B0, 0x000104D8}, {0x000104B1, 0x000104D9}, {0x000104B2, 0x000104DA}, {0x000104B3, 0x000104DB}, +{0x000104B4, 0x000104DC}, {0x000104B5, 0x000104DD}, {0x000104B6, 0x000104DE}, {0x000104B7, 0x000104DF}, +{0x000104B8, 0x000104E0}, {0x000104B9, 0x000104E1}, {0x000104BA, 0x000104E2}, {0x000104BB, 0x000104E3}, +{0x000104BC, 0x000104E4}, {0x000104BD, 0x000104E5}, {0x000104BE, 0x000104E6}, {0x000104BF, 0x000104E7}, +{0x000104C0, 0x000104E8}, {0x000104C1, 0x000104E9}, {0x000104C2, 0x000104EA}, {0x000104C3, 0x000104EB}, +{0x000104C4, 0x000104EC}, {0x000104C5, 0x000104ED}, {0x000104C6, 0x000104EE}, {0x000104C7, 0x000104EF}, +{0x000104C8, 0x000104F0}, {0x000104C9, 0x000104F1}, {0x000104CA, 0x000104F2}, {0x000104CB, 0x000104F3}, +{0x000104CC, 0x000104F4}, {0x000104CD, 0x000104F5}, {0x000104CE, 0x000104F6}, {0x000104CF, 0x000104F7}, +{0x000104D0, 0x000104F8}, {0x000104D1, 0x000104F9}, {0x000104D2, 0x000104FA}, {0x000104D3, 0x000104FB}, +{0x00010C80, 0x00010CC0}, {0x00010C81, 0x00010CC1}, {0x00010C82, 0x00010CC2}, {0x00010C83, 0x00010CC3}, +{0x00010C84, 0x00010CC4}, {0x00010C85, 0x00010CC5}, {0x00010C86, 0x00010CC6}, {0x00010C87, 0x00010CC7}, +{0x00010C88, 0x00010CC8}, {0x00010C89, 0x00010CC9}, {0x00010C8A, 0x00010CCA}, {0x00010C8B, 0x00010CCB}, +{0x00010C8C, 0x00010CCC}, {0x00010C8D, 0x00010CCD}, {0x00010C8E, 0x00010CCE}, {0x00010C8F, 0x00010CCF}, +{0x00010C90, 0x00010CD0}, {0x00010C91, 0x00010CD1}, {0x00010C92, 0x00010CD2}, {0x00010C93, 0x00010CD3}, +{0x00010C94, 0x00010CD4}, {0x00010C95, 0x00010CD5}, {0x00010C96, 0x00010CD6}, {0x00010C97, 0x00010CD7}, +{0x00010C98, 0x00010CD8}, {0x00010C99, 0x00010CD9}, {0x00010C9A, 0x00010CDA}, {0x00010C9B, 0x00010CDB}, +{0x00010C9C, 0x00010CDC}, {0x00010C9D, 0x00010CDD}, {0x00010C9E, 0x00010CDE}, {0x00010C9F, 0x00010CDF}, +{0x00010CA0, 0x00010CE0}, {0x00010CA1, 0x00010CE1}, {0x00010CA2, 0x00010CE2}, {0x00010CA3, 0x00010CE3}, +{0x00010CA4, 0x00010CE4}, {0x00010CA5, 0x00010CE5}, {0x00010CA6, 0x00010CE6}, {0x00010CA7, 0x00010CE7}, +{0x00010CA8, 0x00010CE8}, {0x00010CA9, 0x00010CE9}, {0x00010CAA, 0x00010CEA}, {0x00010CAB, 0x00010CEB}, +{0x00010CAC, 0x00010CEC}, {0x00010CAD, 0x00010CED}, {0x00010CAE, 0x00010CEE}, {0x00010CAF, 0x00010CEF}, +{0x00010CB0, 0x00010CF0}, {0x00010CB1, 0x00010CF1}, {0x00010CB2, 0x00010CF2}, {0x000118A0, 0x000118C0}, +{0x000118A1, 0x000118C1}, {0x000118A2, 0x000118C2}, {0x000118A3, 0x000118C3}, {0x000118A4, 0x000118C4}, +{0x000118A5, 0x000118C5}, {0x000118A6, 0x000118C6}, {0x000118A7, 0x000118C7}, {0x000118A8, 0x000118C8}, +{0x000118A9, 0x000118C9}, {0x000118AA, 0x000118CA}, {0x000118AB, 0x000118CB}, {0x000118AC, 0x000118CC}, +{0x000118AD, 0x000118CD}, {0x000118AE, 0x000118CE}, {0x000118AF, 0x000118CF}, {0x000118B0, 0x000118D0}, +{0x000118B1, 0x000118D1}, {0x000118B2, 0x000118D2}, {0x000118B3, 0x000118D3}, {0x000118B4, 0x000118D4}, +{0x000118B5, 0x000118D5}, {0x000118B6, 0x000118D6}, {0x000118B7, 0x000118D7}, {0x000118B8, 0x000118D8}, +{0x000118B9, 0x000118D9}, {0x000118BA, 0x000118DA}, {0x000118BB, 0x000118DB}, {0x000118BC, 0x000118DC}, +{0x000118BD, 0x000118DD}, {0x000118BE, 0x000118DE}, {0x000118BF, 0x000118DF}, {0x00016E40, 0x00016E60}, +{0x00016E41, 0x00016E61}, {0x00016E42, 0x00016E62}, {0x00016E43, 0x00016E63}, {0x00016E44, 0x00016E64}, +{0x00016E45, 0x00016E65}, {0x00016E46, 0x00016E66}, {0x00016E47, 0x00016E67}, {0x00016E48, 0x00016E68}, +{0x00016E49, 0x00016E69}, {0x00016E4A, 0x00016E6A}, {0x00016E4B, 0x00016E6B}, {0x00016E4C, 0x00016E6C}, +{0x00016E4D, 0x00016E6D}, {0x00016E4E, 0x00016E6E}, {0x00016E4F, 0x00016E6F}, {0x00016E50, 0x00016E70}, +{0x00016E51, 0x00016E71}, {0x00016E52, 0x00016E72}, {0x00016E53, 0x00016E73}, {0x00016E54, 0x00016E74}, +{0x00016E55, 0x00016E75}, {0x00016E56, 0x00016E76}, {0x00016E57, 0x00016E77}, {0x00016E58, 0x00016E78}, +{0x00016E59, 0x00016E79}, {0x00016E5A, 0x00016E7A}, {0x00016E5B, 0x00016E7B}, {0x00016E5C, 0x00016E7C}, +{0x00016E5D, 0x00016E7D}, {0x00016E5E, 0x00016E7E}, {0x00016E5F, 0x00016E7F}, {0x0001E900, 0x0001E922}, +{0x0001E901, 0x0001E923}, {0x0001E902, 0x0001E924}, {0x0001E903, 0x0001E925}, {0x0001E904, 0x0001E926}, +{0x0001E905, 0x0001E927}, {0x0001E906, 0x0001E928}, {0x0001E907, 0x0001E929}, {0x0001E908, 0x0001E92A}, +{0x0001E909, 0x0001E92B}, {0x0001E90A, 0x0001E92C}, {0x0001E90B, 0x0001E92D}, {0x0001E90C, 0x0001E92E}, +{0x0001E90D, 0x0001E92F}, {0x0001E90E, 0x0001E930}, {0x0001E90F, 0x0001E931}, {0x0001E910, 0x0001E932}, +{0x0001E911, 0x0001E933}, {0x0001E912, 0x0001E934}, {0x0001E913, 0x0001E935}, {0x0001E914, 0x0001E936}, +{0x0001E915, 0x0001E937}, {0x0001E916, 0x0001E938}, {0x0001E917, 0x0001E939}, {0x0001E918, 0x0001E93A}, +{0x0001E919, 0x0001E93B}, {0x0001E91A, 0x0001E93C}, {0x0001E91B, 0x0001E93D}, {0x0001E91C, 0x0001E93E}, +{0x0001E91D, 0x0001E93F}, {0x0001E91E, 0x0001E940}, {0x0001E91F, 0x0001E941}, {0x0001E920, 0x0001E942}, +{0x0001E921, 0x0001E943}, +}; + +const std::map<char32_t, char32_t> unicode_map_uppercase = { +{0x00000061, 0x00000041}, {0x00000062, 0x00000042}, {0x00000063, 0x00000043}, {0x00000064, 0x00000044}, +{0x00000065, 0x00000045}, {0x00000066, 0x00000046}, {0x00000067, 0x00000047}, {0x00000068, 0x00000048}, +{0x00000069, 0x00000049}, {0x0000006A, 0x0000004A}, {0x0000006B, 0x0000004B}, {0x0000006C, 0x0000004C}, +{0x0000006D, 0x0000004D}, {0x0000006E, 0x0000004E}, {0x0000006F, 0x0000004F}, {0x00000070, 0x00000050}, +{0x00000071, 0x00000051}, {0x00000072, 0x00000052}, {0x00000073, 0x00000053}, {0x00000074, 0x00000054}, +{0x00000075, 0x00000055}, {0x00000076, 0x00000056}, {0x00000077, 0x00000057}, {0x00000078, 0x00000058}, +{0x00000079, 0x00000059}, {0x0000007A, 0x0000005A}, {0x000000B5, 0x0000039C}, {0x000000DF, 0x00000053}, +{0x000000E0, 0x000000C0}, {0x000000E1, 0x000000C1}, {0x000000E2, 0x000000C2}, {0x000000E3, 0x000000C3}, +{0x000000E4, 0x000000C4}, {0x000000E5, 0x000000C5}, {0x000000E6, 0x000000C6}, {0x000000E7, 0x000000C7}, +{0x000000E8, 0x000000C8}, {0x000000E9, 0x000000C9}, {0x000000EA, 0x000000CA}, {0x000000EB, 0x000000CB}, +{0x000000EC, 0x000000CC}, {0x000000ED, 0x000000CD}, {0x000000EE, 0x000000CE}, {0x000000EF, 0x000000CF}, +{0x000000F0, 0x000000D0}, {0x000000F1, 0x000000D1}, {0x000000F2, 0x000000D2}, {0x000000F3, 0x000000D3}, +{0x000000F4, 0x000000D4}, {0x000000F5, 0x000000D5}, {0x000000F6, 0x000000D6}, {0x000000F8, 0x000000D8}, +{0x000000F9, 0x000000D9}, {0x000000FA, 0x000000DA}, {0x000000FB, 0x000000DB}, {0x000000FC, 0x000000DC}, +{0x000000FD, 0x000000DD}, {0x000000FE, 0x000000DE}, {0x000000FF, 0x00000178}, {0x00000101, 0x00000100}, +{0x00000103, 0x00000102}, {0x00000105, 0x00000104}, {0x00000107, 0x00000106}, {0x00000109, 0x00000108}, +{0x0000010B, 0x0000010A}, {0x0000010D, 0x0000010C}, {0x0000010F, 0x0000010E}, {0x00000111, 0x00000110}, +{0x00000113, 0x00000112}, {0x00000115, 0x00000114}, {0x00000117, 0x00000116}, {0x00000119, 0x00000118}, +{0x0000011B, 0x0000011A}, {0x0000011D, 0x0000011C}, {0x0000011F, 0x0000011E}, {0x00000121, 0x00000120}, +{0x00000123, 0x00000122}, {0x00000125, 0x00000124}, {0x00000127, 0x00000126}, {0x00000129, 0x00000128}, +{0x0000012B, 0x0000012A}, {0x0000012D, 0x0000012C}, {0x0000012F, 0x0000012E}, {0x00000131, 0x00000049}, +{0x00000133, 0x00000132}, {0x00000135, 0x00000134}, {0x00000137, 0x00000136}, {0x0000013A, 0x00000139}, +{0x0000013C, 0x0000013B}, {0x0000013E, 0x0000013D}, {0x00000140, 0x0000013F}, {0x00000142, 0x00000141}, +{0x00000144, 0x00000143}, {0x00000146, 0x00000145}, {0x00000148, 0x00000147}, {0x00000149, 0x000002BC}, +{0x0000014B, 0x0000014A}, {0x0000014D, 0x0000014C}, {0x0000014F, 0x0000014E}, {0x00000151, 0x00000150}, +{0x00000153, 0x00000152}, {0x00000155, 0x00000154}, {0x00000157, 0x00000156}, {0x00000159, 0x00000158}, +{0x0000015B, 0x0000015A}, {0x0000015D, 0x0000015C}, {0x0000015F, 0x0000015E}, {0x00000161, 0x00000160}, +{0x00000163, 0x00000162}, {0x00000165, 0x00000164}, {0x00000167, 0x00000166}, {0x00000169, 0x00000168}, +{0x0000016B, 0x0000016A}, {0x0000016D, 0x0000016C}, {0x0000016F, 0x0000016E}, {0x00000171, 0x00000170}, +{0x00000173, 0x00000172}, {0x00000175, 0x00000174}, {0x00000177, 0x00000176}, {0x0000017A, 0x00000179}, +{0x0000017C, 0x0000017B}, {0x0000017E, 0x0000017D}, {0x0000017F, 0x00000053}, {0x00000180, 0x00000243}, +{0x00000183, 0x00000182}, {0x00000185, 0x00000184}, {0x00000188, 0x00000187}, {0x0000018C, 0x0000018B}, +{0x00000192, 0x00000191}, {0x00000195, 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0x000013D3}, {0x0000ABA4, 0x000013D4}, {0x0000ABA5, 0x000013D5}, +{0x0000ABA6, 0x000013D6}, {0x0000ABA7, 0x000013D7}, {0x0000ABA8, 0x000013D8}, {0x0000ABA9, 0x000013D9}, +{0x0000ABAA, 0x000013DA}, {0x0000ABAB, 0x000013DB}, {0x0000ABAC, 0x000013DC}, {0x0000ABAD, 0x000013DD}, +{0x0000ABAE, 0x000013DE}, {0x0000ABAF, 0x000013DF}, {0x0000ABB0, 0x000013E0}, {0x0000ABB1, 0x000013E1}, +{0x0000ABB2, 0x000013E2}, {0x0000ABB3, 0x000013E3}, {0x0000ABB4, 0x000013E4}, {0x0000ABB5, 0x000013E5}, +{0x0000ABB6, 0x000013E6}, {0x0000ABB7, 0x000013E7}, {0x0000ABB8, 0x000013E8}, {0x0000ABB9, 0x000013E9}, +{0x0000ABBA, 0x000013EA}, {0x0000ABBB, 0x000013EB}, {0x0000ABBC, 0x000013EC}, {0x0000ABBD, 0x000013ED}, +{0x0000ABBE, 0x000013EE}, {0x0000ABBF, 0x000013EF}, {0x0000FB00, 0x00000046}, {0x0000FB01, 0x00000046}, +{0x0000FB02, 0x00000046}, {0x0000FB03, 0x00000046}, {0x0000FB04, 0x00000046}, {0x0000FB05, 0x00000053}, +{0x0000FB06, 0x00000053}, {0x0000FB13, 0x00000544}, {0x0000FB14, 0x00000544}, {0x0000FB15, 0x00000544}, +{0x0000FB16, 0x0000054E}, {0x0000FB17, 0x00000544}, {0x0000FF41, 0x0000FF21}, {0x0000FF42, 0x0000FF22}, +{0x0000FF43, 0x0000FF23}, {0x0000FF44, 0x0000FF24}, {0x0000FF45, 0x0000FF25}, {0x0000FF46, 0x0000FF26}, +{0x0000FF47, 0x0000FF27}, {0x0000FF48, 0x0000FF28}, {0x0000FF49, 0x0000FF29}, {0x0000FF4A, 0x0000FF2A}, +{0x0000FF4B, 0x0000FF2B}, {0x0000FF4C, 0x0000FF2C}, {0x0000FF4D, 0x0000FF2D}, {0x0000FF4E, 0x0000FF2E}, +{0x0000FF4F, 0x0000FF2F}, {0x0000FF50, 0x0000FF30}, {0x0000FF51, 0x0000FF31}, {0x0000FF52, 0x0000FF32}, +{0x0000FF53, 0x0000FF33}, {0x0000FF54, 0x0000FF34}, {0x0000FF55, 0x0000FF35}, {0x0000FF56, 0x0000FF36}, +{0x0000FF57, 0x0000FF37}, {0x0000FF58, 0x0000FF38}, {0x0000FF59, 0x0000FF39}, {0x0000FF5A, 0x0000FF3A}, +{0x00010428, 0x00010400}, {0x00010429, 0x00010401}, {0x0001042A, 0x00010402}, {0x0001042B, 0x00010403}, +{0x0001042C, 0x00010404}, {0x0001042D, 0x00010405}, {0x0001042E, 0x00010406}, {0x0001042F, 0x00010407}, +{0x00010430, 0x00010408}, {0x00010431, 0x00010409}, {0x00010432, 0x0001040A}, {0x00010433, 0x0001040B}, +{0x00010434, 0x0001040C}, {0x00010435, 0x0001040D}, {0x00010436, 0x0001040E}, {0x00010437, 0x0001040F}, +{0x00010438, 0x00010410}, {0x00010439, 0x00010411}, {0x0001043A, 0x00010412}, {0x0001043B, 0x00010413}, +{0x0001043C, 0x00010414}, {0x0001043D, 0x00010415}, {0x0001043E, 0x00010416}, {0x0001043F, 0x00010417}, +{0x00010440, 0x00010418}, {0x00010441, 0x00010419}, {0x00010442, 0x0001041A}, {0x00010443, 0x0001041B}, +{0x00010444, 0x0001041C}, {0x00010445, 0x0001041D}, {0x00010446, 0x0001041E}, {0x00010447, 0x0001041F}, +{0x00010448, 0x00010420}, {0x00010449, 0x00010421}, {0x0001044A, 0x00010422}, {0x0001044B, 0x00010423}, +{0x0001044C, 0x00010424}, {0x0001044D, 0x00010425}, {0x0001044E, 0x00010426}, {0x0001044F, 0x00010427}, +{0x000104D8, 0x000104B0}, {0x000104D9, 0x000104B1}, {0x000104DA, 0x000104B2}, {0x000104DB, 0x000104B3}, +{0x000104DC, 0x000104B4}, {0x000104DD, 0x000104B5}, {0x000104DE, 0x000104B6}, {0x000104DF, 0x000104B7}, +{0x000104E0, 0x000104B8}, {0x000104E1, 0x000104B9}, {0x000104E2, 0x000104BA}, {0x000104E3, 0x000104BB}, +{0x000104E4, 0x000104BC}, {0x000104E5, 0x000104BD}, {0x000104E6, 0x000104BE}, {0x000104E7, 0x000104BF}, +{0x000104E8, 0x000104C0}, {0x000104E9, 0x000104C1}, {0x000104EA, 0x000104C2}, {0x000104EB, 0x000104C3}, +{0x000104EC, 0x000104C4}, {0x000104ED, 0x000104C5}, {0x000104EE, 0x000104C6}, {0x000104EF, 0x000104C7}, +{0x000104F0, 0x000104C8}, {0x000104F1, 0x000104C9}, {0x000104F2, 0x000104CA}, {0x000104F3, 0x000104CB}, +{0x000104F4, 0x000104CC}, {0x000104F5, 0x000104CD}, {0x000104F6, 0x000104CE}, {0x000104F7, 0x000104CF}, +{0x000104F8, 0x000104D0}, {0x000104F9, 0x000104D1}, {0x000104FA, 0x000104D2}, {0x000104FB, 0x000104D3}, +{0x00010CC0, 0x00010C80}, {0x00010CC1, 0x00010C81}, {0x00010CC2, 0x00010C82}, {0x00010CC3, 0x00010C83}, +{0x00010CC4, 0x00010C84}, {0x00010CC5, 0x00010C85}, {0x00010CC6, 0x00010C86}, {0x00010CC7, 0x00010C87}, +{0x00010CC8, 0x00010C88}, {0x00010CC9, 0x00010C89}, {0x00010CCA, 0x00010C8A}, {0x00010CCB, 0x00010C8B}, +{0x00010CCC, 0x00010C8C}, {0x00010CCD, 0x00010C8D}, {0x00010CCE, 0x00010C8E}, {0x00010CCF, 0x00010C8F}, +{0x00010CD0, 0x00010C90}, {0x00010CD1, 0x00010C91}, {0x00010CD2, 0x00010C92}, {0x00010CD3, 0x00010C93}, +{0x00010CD4, 0x00010C94}, {0x00010CD5, 0x00010C95}, {0x00010CD6, 0x00010C96}, {0x00010CD7, 0x00010C97}, +{0x00010CD8, 0x00010C98}, {0x00010CD9, 0x00010C99}, {0x00010CDA, 0x00010C9A}, {0x00010CDB, 0x00010C9B}, +{0x00010CDC, 0x00010C9C}, {0x00010CDD, 0x00010C9D}, {0x00010CDE, 0x00010C9E}, {0x00010CDF, 0x00010C9F}, +{0x00010CE0, 0x00010CA0}, {0x00010CE1, 0x00010CA1}, {0x00010CE2, 0x00010CA2}, {0x00010CE3, 0x00010CA3}, +{0x00010CE4, 0x00010CA4}, {0x00010CE5, 0x00010CA5}, {0x00010CE6, 0x00010CA6}, {0x00010CE7, 0x00010CA7}, +{0x00010CE8, 0x00010CA8}, {0x00010CE9, 0x00010CA9}, {0x00010CEA, 0x00010CAA}, {0x00010CEB, 0x00010CAB}, +{0x00010CEC, 0x00010CAC}, {0x00010CED, 0x00010CAD}, {0x00010CEE, 0x00010CAE}, {0x00010CEF, 0x00010CAF}, +{0x00010CF0, 0x00010CB0}, {0x00010CF1, 0x00010CB1}, {0x00010CF2, 0x00010CB2}, {0x000118C0, 0x000118A0}, +{0x000118C1, 0x000118A1}, {0x000118C2, 0x000118A2}, {0x000118C3, 0x000118A3}, {0x000118C4, 0x000118A4}, +{0x000118C5, 0x000118A5}, {0x000118C6, 0x000118A6}, {0x000118C7, 0x000118A7}, {0x000118C8, 0x000118A8}, +{0x000118C9, 0x000118A9}, {0x000118CA, 0x000118AA}, {0x000118CB, 0x000118AB}, {0x000118CC, 0x000118AC}, +{0x000118CD, 0x000118AD}, {0x000118CE, 0x000118AE}, {0x000118CF, 0x000118AF}, {0x000118D0, 0x000118B0}, +{0x000118D1, 0x000118B1}, {0x000118D2, 0x000118B2}, {0x000118D3, 0x000118B3}, {0x000118D4, 0x000118B4}, +{0x000118D5, 0x000118B5}, {0x000118D6, 0x000118B6}, {0x000118D7, 0x000118B7}, {0x000118D8, 0x000118B8}, +{0x000118D9, 0x000118B9}, {0x000118DA, 0x000118BA}, {0x000118DB, 0x000118BB}, {0x000118DC, 0x000118BC}, +{0x000118DD, 0x000118BD}, {0x000118DE, 0x000118BE}, {0x000118DF, 0x000118BF}, {0x00016E60, 0x00016E40}, +{0x00016E61, 0x00016E41}, {0x00016E62, 0x00016E42}, {0x00016E63, 0x00016E43}, {0x00016E64, 0x00016E44}, +{0x00016E65, 0x00016E45}, {0x00016E66, 0x00016E46}, {0x00016E67, 0x00016E47}, {0x00016E68, 0x00016E48}, +{0x00016E69, 0x00016E49}, {0x00016E6A, 0x00016E4A}, {0x00016E6B, 0x00016E4B}, {0x00016E6C, 0x00016E4C}, +{0x00016E6D, 0x00016E4D}, {0x00016E6E, 0x00016E4E}, {0x00016E6F, 0x00016E4F}, {0x00016E70, 0x00016E50}, +{0x00016E71, 0x00016E51}, {0x00016E72, 0x00016E52}, {0x00016E73, 0x00016E53}, {0x00016E74, 0x00016E54}, +{0x00016E75, 0x00016E55}, {0x00016E76, 0x00016E56}, {0x00016E77, 0x00016E57}, {0x00016E78, 0x00016E58}, +{0x00016E79, 0x00016E59}, {0x00016E7A, 0x00016E5A}, {0x00016E7B, 0x00016E5B}, {0x00016E7C, 0x00016E5C}, +{0x00016E7D, 0x00016E5D}, {0x00016E7E, 0x00016E5E}, {0x00016E7F, 0x00016E5F}, {0x0001E922, 0x0001E900}, +{0x0001E923, 0x0001E901}, {0x0001E924, 0x0001E902}, {0x0001E925, 0x0001E903}, {0x0001E926, 0x0001E904}, +{0x0001E927, 0x0001E905}, {0x0001E928, 0x0001E906}, {0x0001E929, 0x0001E907}, {0x0001E92A, 0x0001E908}, +{0x0001E92B, 0x0001E909}, {0x0001E92C, 0x0001E90A}, {0x0001E92D, 0x0001E90B}, {0x0001E92E, 0x0001E90C}, +{0x0001E92F, 0x0001E90D}, {0x0001E930, 0x0001E90E}, {0x0001E931, 0x0001E90F}, {0x0001E932, 0x0001E910}, +{0x0001E933, 0x0001E911}, {0x0001E934, 0x0001E912}, {0x0001E935, 0x0001E913}, {0x0001E936, 0x0001E914}, +{0x0001E937, 0x0001E915}, {0x0001E938, 0x0001E916}, {0x0001E939, 0x0001E917}, {0x0001E93A, 0x0001E918}, +{0x0001E93B, 0x0001E919}, {0x0001E93C, 0x0001E91A}, {0x0001E93D, 0x0001E91B}, {0x0001E93E, 0x0001E91C}, +{0x0001E93F, 0x0001E91D}, {0x0001E940, 0x0001E91E}, {0x0001E941, 0x0001E91F}, {0x0001E942, 0x0001E920}, +{0x0001E943, 0x0001E921}, }; const std::multimap<uint32_t, uint32_t> unicode_map_nfd = { @@ -1449,245 +2181,3 @@ const std::multimap<uint32_t, uint32_t> unicode_map_nfd = { {0x0002FA16, 0x00004D56}, {0x0002FA17, 0x00009EF9}, {0x0002FA18, 0x00009EFE}, {0x0002FA19, 0x00009F05}, {0x0002FA1A, 0x00009F0F}, {0x0002FA1B, 0x00009F16}, {0x0002FA1D, 0x0002A600}, }; - -const std::map<char32_t, char32_t> unicode_map_lowercase = { -{0x00041, 0x00061}, {0x00042, 0x00062}, {0x00043, 0x00063}, {0x00044, 0x00064}, {0x00045, 0x00065}, {0x00046, 0x00066}, -{0x00047, 0x00067}, {0x00048, 0x00068}, {0x00049, 0x00069}, {0x0004A, 0x0006A}, {0x0004B, 0x0006B}, {0x0004C, 0x0006C}, -{0x0004D, 0x0006D}, {0x0004E, 0x0006E}, {0x0004F, 0x0006F}, {0x00050, 0x00070}, {0x00051, 0x00071}, {0x00052, 0x00072}, -{0x00053, 0x00073}, {0x00054, 0x00074}, {0x00055, 0x00075}, {0x00056, 0x00076}, {0x00057, 0x00077}, {0x00058, 0x00078}, -{0x00059, 0x00079}, {0x0005A, 0x0007A}, {0x000C0, 0x000E0}, {0x000C1, 0x000E1}, {0x000C2, 0x000E2}, {0x000C3, 0x000E3}, -{0x000C4, 0x000E4}, {0x000C5, 0x000E5}, {0x000C6, 0x000E6}, {0x000C7, 0x000E7}, {0x000C8, 0x000E8}, {0x000C9, 0x000E9}, -{0x000CA, 0x000EA}, {0x000CB, 0x000EB}, {0x000CC, 0x000EC}, {0x000CD, 0x000ED}, {0x000CE, 0x000EE}, {0x000CF, 0x000EF}, -{0x000D0, 0x000F0}, {0x000D1, 0x000F1}, {0x000D2, 0x000F2}, {0x000D3, 0x000F3}, {0x000D4, 0x000F4}, {0x000D5, 0x000F5}, -{0x000D6, 0x000F6}, {0x000D8, 0x000F8}, {0x000D9, 0x000F9}, {0x000DA, 0x000FA}, {0x000DB, 0x000FB}, {0x000DC, 0x000FC}, -{0x000DD, 0x000FD}, {0x000DE, 0x000FE}, {0x00100, 0x00101}, {0x00102, 0x00103}, {0x00104, 0x00105}, {0x00106, 0x00107}, -{0x00108, 0x00109}, {0x0010A, 0x0010B}, {0x0010C, 0x0010D}, {0x0010E, 0x0010F}, {0x00110, 0x00111}, {0x00112, 0x00113}, -{0x00114, 0x00115}, {0x00116, 0x00117}, {0x00118, 0x00119}, {0x0011A, 0x0011B}, {0x0011C, 0x0011D}, {0x0011E, 0x0011F}, -{0x00120, 0x00121}, {0x00122, 0x00123}, {0x00124, 0x00125}, {0x00126, 0x00127}, {0x00128, 0x00129}, {0x0012A, 0x0012B}, -{0x0012C, 0x0012D}, {0x0012E, 0x0012F}, {0x00130, 0x00069}, {0x00132, 0x00133}, {0x00134, 0x00135}, {0x00136, 0x00137}, -{0x00139, 0x0013A}, {0x0013B, 0x0013C}, {0x0013D, 0x0013E}, {0x0013F, 0x00140}, {0x00141, 0x00142}, {0x00143, 0x00144}, -{0x00145, 0x00146}, {0x00147, 0x00148}, {0x0014A, 0x0014B}, {0x0014C, 0x0014D}, {0x0014E, 0x0014F}, {0x00150, 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{0x104C5, 0x104ED}, {0x104C6, 0x104EE}, -{0x104C7, 0x104EF}, {0x104C8, 0x104F0}, {0x104C9, 0x104F1}, {0x104CA, 0x104F2}, {0x104CB, 0x104F3}, {0x104CC, 0x104F4}, -{0x104CD, 0x104F5}, {0x104CE, 0x104F6}, {0x104CF, 0x104F7}, {0x104D0, 0x104F8}, {0x104D1, 0x104F9}, {0x104D2, 0x104FA}, -{0x104D3, 0x104FB}, {0x10570, 0x10597}, {0x10571, 0x10598}, {0x10572, 0x10599}, {0x10573, 0x1059A}, {0x10574, 0x1059B}, -{0x10575, 0x1059C}, {0x10576, 0x1059D}, {0x10577, 0x1059E}, {0x10578, 0x1059F}, {0x10579, 0x105A0}, {0x1057A, 0x105A1}, -{0x1057C, 0x105A3}, {0x1057D, 0x105A4}, {0x1057E, 0x105A5}, {0x1057F, 0x105A6}, {0x10580, 0x105A7}, {0x10581, 0x105A8}, -{0x10582, 0x105A9}, {0x10583, 0x105AA}, {0x10584, 0x105AB}, {0x10585, 0x105AC}, {0x10586, 0x105AD}, {0x10587, 0x105AE}, -{0x10588, 0x105AF}, {0x10589, 0x105B0}, {0x1058A, 0x105B1}, {0x1058C, 0x105B3}, {0x1058D, 0x105B4}, {0x1058E, 0x105B5}, -{0x1058F, 0x105B6}, {0x10590, 0x105B7}, {0x10591, 0x105B8}, {0x10592, 0x105B9}, {0x10594, 0x105BB}, {0x10595, 0x105BC}, -{0x10C80, 0x10CC0}, {0x10C81, 0x10CC1}, {0x10C82, 0x10CC2}, {0x10C83, 0x10CC3}, {0x10C84, 0x10CC4}, {0x10C85, 0x10CC5}, -{0x10C86, 0x10CC6}, {0x10C87, 0x10CC7}, {0x10C88, 0x10CC8}, {0x10C89, 0x10CC9}, {0x10C8A, 0x10CCA}, {0x10C8B, 0x10CCB}, -{0x10C8C, 0x10CCC}, {0x10C8D, 0x10CCD}, {0x10C8E, 0x10CCE}, {0x10C8F, 0x10CCF}, {0x10C90, 0x10CD0}, {0x10C91, 0x10CD1}, -{0x10C92, 0x10CD2}, {0x10C93, 0x10CD3}, {0x10C94, 0x10CD4}, {0x10C95, 0x10CD5}, {0x10C96, 0x10CD6}, {0x10C97, 0x10CD7}, -{0x10C98, 0x10CD8}, {0x10C99, 0x10CD9}, {0x10C9A, 0x10CDA}, {0x10C9B, 0x10CDB}, {0x10C9C, 0x10CDC}, {0x10C9D, 0x10CDD}, -{0x10C9E, 0x10CDE}, {0x10C9F, 0x10CDF}, {0x10CA0, 0x10CE0}, {0x10CA1, 0x10CE1}, {0x10CA2, 0x10CE2}, {0x10CA3, 0x10CE3}, -{0x10CA4, 0x10CE4}, {0x10CA5, 0x10CE5}, {0x10CA6, 0x10CE6}, {0x10CA7, 0x10CE7}, {0x10CA8, 0x10CE8}, {0x10CA9, 0x10CE9}, -{0x10CAA, 0x10CEA}, {0x10CAB, 0x10CEB}, {0x10CAC, 0x10CEC}, {0x10CAD, 0x10CED}, {0x10CAE, 0x10CEE}, {0x10CAF, 0x10CEF}, -{0x10CB0, 0x10CF0}, {0x10CB1, 0x10CF1}, {0x10CB2, 0x10CF2}, {0x118A0, 0x118C0}, {0x118A1, 0x118C1}, {0x118A2, 0x118C2}, -{0x118A3, 0x118C3}, {0x118A4, 0x118C4}, {0x118A5, 0x118C5}, {0x118A6, 0x118C6}, {0x118A7, 0x118C7}, {0x118A8, 0x118C8}, -{0x118A9, 0x118C9}, {0x118AA, 0x118CA}, {0x118AB, 0x118CB}, {0x118AC, 0x118CC}, {0x118AD, 0x118CD}, {0x118AE, 0x118CE}, -{0x118AF, 0x118CF}, {0x118B0, 0x118D0}, {0x118B1, 0x118D1}, {0x118B2, 0x118D2}, {0x118B3, 0x118D3}, {0x118B4, 0x118D4}, -{0x118B5, 0x118D5}, {0x118B6, 0x118D6}, {0x118B7, 0x118D7}, {0x118B8, 0x118D8}, {0x118B9, 0x118D9}, {0x118BA, 0x118DA}, -{0x118BB, 0x118DB}, {0x118BC, 0x118DC}, {0x118BD, 0x118DD}, {0x118BE, 0x118DE}, {0x118BF, 0x118DF}, {0x16E40, 0x16E60}, -{0x16E41, 0x16E61}, {0x16E42, 0x16E62}, {0x16E43, 0x16E63}, {0x16E44, 0x16E64}, {0x16E45, 0x16E65}, {0x16E46, 0x16E66}, -{0x16E47, 0x16E67}, {0x16E48, 0x16E68}, {0x16E49, 0x16E69}, {0x16E4A, 0x16E6A}, {0x16E4B, 0x16E6B}, {0x16E4C, 0x16E6C}, -{0x16E4D, 0x16E6D}, {0x16E4E, 0x16E6E}, {0x16E4F, 0x16E6F}, {0x16E50, 0x16E70}, {0x16E51, 0x16E71}, {0x16E52, 0x16E72}, -{0x16E53, 0x16E73}, {0x16E54, 0x16E74}, {0x16E55, 0x16E75}, {0x16E56, 0x16E76}, {0x16E57, 0x16E77}, {0x16E58, 0x16E78}, -{0x16E59, 0x16E79}, {0x16E5A, 0x16E7A}, {0x16E5B, 0x16E7B}, {0x16E5C, 0x16E7C}, {0x16E5D, 0x16E7D}, {0x16E5E, 0x16E7E}, -{0x16E5F, 0x16E7F}, {0x1E900, 0x1E922}, {0x1E901, 0x1E923}, {0x1E902, 0x1E924}, {0x1E903, 0x1E925}, {0x1E904, 0x1E926}, -{0x1E905, 0x1E927}, {0x1E906, 0x1E928}, {0x1E907, 0x1E929}, {0x1E908, 0x1E92A}, {0x1E909, 0x1E92B}, {0x1E90A, 0x1E92C}, -{0x1E90B, 0x1E92D}, {0x1E90C, 0x1E92E}, {0x1E90D, 0x1E92F}, {0x1E90E, 0x1E930}, {0x1E90F, 0x1E931}, {0x1E910, 0x1E932}, -{0x1E911, 0x1E933}, {0x1E912, 0x1E934}, {0x1E913, 0x1E935}, {0x1E914, 0x1E936}, {0x1E915, 0x1E937}, {0x1E916, 0x1E938}, -{0x1E917, 0x1E939}, {0x1E918, 0x1E93A}, {0x1E919, 0x1E93B}, {0x1E91A, 0x1E93C}, {0x1E91B, 0x1E93D}, {0x1E91C, 0x1E93E}, -{0x1E91D, 0x1E93F}, {0x1E91E, 0x1E940}, {0x1E91F, 0x1E941}, {0x1E920, 0x1E942}, {0x1E921, 0x1E943}, -}; diff --git a/unicode-data.h b/unicode-data.h index 3cf84117cf164..3cccf20685429 100644 --- a/unicode-data.h +++ b/unicode-data.h @@ -7,6 +7,7 @@ extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_number; extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_letter; +extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_separator; extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_whitespace; extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_accent_mark; extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_punctuation; diff --git a/unicode.cpp b/unicode.cpp index 955c569650329..ca03c49d39c7c 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -9,6 +9,7 @@ #include <stdexcept> #include <string> #include <unordered_map> +#include <unordered_set> #include <utility> #include <vector> #include <locale> @@ -111,27 +112,27 @@ static uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset) static std::unordered_map<uint32_t, int> unicode_cpt_type_map() { std::unordered_map<uint32_t, int> cpt_types; for (auto p : unicode_ranges_number) { - for (auto i = p.first; i <= p.second; ++ i) { + for (auto i = p.first; i <= p.second; ++i) { cpt_types[i] = CODEPOINT_TYPE_NUMBER; } } for (auto p : unicode_ranges_letter) { - for (auto i = p.first; i <= p.second; ++ i) { + for (auto i = p.first; i <= p.second; ++i) { cpt_types[i] = CODEPOINT_TYPE_LETTER; } } - for (auto p : unicode_ranges_whitespace) { - for (auto i = p.first; i <= p.second; ++ i) { - cpt_types[i] = CODEPOINT_TYPE_WHITESPACE; + for (auto p : unicode_ranges_separator) { + for (auto i = p.first; i <= p.second; ++i) { + cpt_types[i] = CODEPOINT_TYPE_SEPARATOR; } } for (auto p : unicode_ranges_accent_mark) { - for (auto i = p.first; i <= p.second; ++ i) { + for (auto i = p.first; i <= p.second; ++i) { cpt_types[i] = CODEPOINT_TYPE_ACCENT_MARK; } } for (auto p : unicode_ranges_punctuation) { - for (auto i = p.first; i <= p.second; ++ i) { + for (auto i = p.first; i <= p.second; ++i) { cpt_types[i] = CODEPOINT_TYPE_PUNCTUATION; } } @@ -141,7 +142,7 @@ static std::unordered_map<uint32_t, int> unicode_cpt_type_map() { } } for (auto p : unicode_ranges_control) { - for (auto i = p.first; i <= p.second; ++ i) { + for (auto i = p.first; i <= p.second; ++i) { cpt_types[i] = CODEPOINT_TYPE_CONTROL; } } @@ -224,138 +225,256 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & t std::vector<size_t> bpe_offsets; // store the offset of each word bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size - size_t start = 0; - const auto cpts = unicode_cpts_from_utf8(text); + size_t start = 0; for (auto offset : offsets) { - std::string token; + const size_t offset_ini = start; + const size_t offset_end = start + offset; + assert(offset_end <= cpts.size()); + start = offset_end; + + auto _get_cpt = [&] (const size_t pos) -> char32_t { + return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : 0; + }; + + auto _get_cpt_type = [&] (const size_t pos) -> int { + return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_type(cpts[pos]) : CODEPOINT_TYPE_UNIDENTIFIED; + }; + + size_t _prev_end = offset_ini; + auto _add_token = [&] (const size_t end) -> size_t { + assert(_prev_end <= end && end <= offset_end); + size_t len = end - _prev_end; + if (len > 0) { + bpe_offsets.push_back(len); + } + _prev_end = end; + //if (len > 0) { + // std::string s = ""; + // for(size_t p = end-len; p < end; p++) + // s += unicode_cpt_to_utf8(cpts[p]); + // printf(">>> '%s'\n", s.c_str()); + //} + return len; + }; + + for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) { + const char32_t cpt = _get_cpt(pos); + const int cpt_type = _get_cpt_type(pos); + + // regex: 's|'t|'re|'ve|'m|'ll|'d + if (cpt == '\'' && pos+1 < offset_end) { + char32_t cpt_next = _get_cpt(pos+1); + if (cpt_next == 's' || cpt_next == 't' || cpt_next == 'm' || cpt_next == 'd') { + pos += _add_token(pos+2); + continue; + } + if (pos+2 < offset_end) { + char32_t cpt_next_next = _get_cpt(pos+2); + if ((cpt_next == 'r' && cpt_next_next == 'e') || + (cpt_next == 'v' && cpt_next_next == 'e') || + (cpt_next == 'l' && cpt_next_next == 'l')) { + pos += _add_token(pos+3); + continue; + } + } + } - bool collecting_numeric = false; - bool collecting_letter = false; - bool collecting_special = false; - bool collecting_whitespace_lookahead = false; - bool collecting = false; + char32_t cpt2 = (cpt == ' ' ? _get_cpt(pos+1) : cpt); + int cpt2_type = (cpt == ' ' ? _get_cpt_type(pos+1) : cpt_type); + // regex: <space>?\p{L}+ + if (cpt2_type == CODEPOINT_TYPE_LETTER) { + pos += (cpt == ' '); + while (cpt2_type == CODEPOINT_TYPE_LETTER) { + cpt2_type = _get_cpt_type(++pos); + } + _add_token(pos); + continue; + } + // regex: <space>?\p{N}+ + if (cpt2_type == CODEPOINT_TYPE_NUMBER) { + pos += (cpt == ' '); + while (cpt2_type == CODEPOINT_TYPE_NUMBER) { + cpt2_type = _get_cpt_type(++pos); + } + _add_token(pos); + continue; + } + // regex: <space>?[^\s\p{L}\p{N}]+ + if (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) { + pos += (cpt == ' '); + while (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) { + cpt2_type = _get_cpt_type(++pos); + cpt2 = _get_cpt(pos); + } + _add_token(pos); + continue; + } - std::vector<std::string> text_utf; - text_utf.reserve(offset); + size_t num_whitespaces = 0; + while (unicode_cpt_is_whitespace(_get_cpt(pos+num_whitespaces))) { + num_whitespaces++; + } - for (size_t i = start; i < start + offset; ++i) { - text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i])); + // regex: \s+(?!\S) + if (num_whitespaces > 1 && _get_cpt(pos+num_whitespaces) != 0) { + pos += num_whitespaces - 1; + _add_token(pos); + continue; + } + + // regex: \s+ + if (num_whitespaces > 0) { + pos += num_whitespaces; + _add_token(pos); + continue; + } + + // no matches + _add_token(++pos); } + } + + return bpe_offsets; +} - for (int i = 0; i < (int)text_utf.size(); i++) { - const std::string & utf_char = text_utf[i]; - bool split_condition = false; - int bytes_remain = text_utf.size() - i; +// LLAMA3 system regex: "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+" +static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string & text, const std::vector<size_t> & offsets) { + std::vector<size_t> bpe_offsets; // store the offset of each word + bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size - // forward backward lookups - const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : ""; - const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : ""; + const auto cpts = unicode_cpts_from_utf8(text); - // handling contractions - if (!split_condition && bytes_remain >= 2) { - // 's|'t|'m|'d - if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) { - split_condition = true; + size_t start = 0; + for (auto offset : offsets) { + const size_t offset_ini = start; + const size_t offset_end = start + offset; + assert(offset_end <= cpts.size()); + start = offset_end; + + auto _get_cpt = [&] (const size_t pos) -> char32_t { + return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : 0; + }; + + auto _get_cpt_type = [&] (const size_t pos) -> int { + return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_type(cpts[pos]) : CODEPOINT_TYPE_UNIDENTIFIED; + }; + + size_t _prev_end = offset_ini; + auto _add_token = [&] (const size_t end) -> size_t { + assert(_prev_end <= end && end <= offset_end); + size_t len = end - _prev_end; + if (len > 0) { + bpe_offsets.push_back(len); + } + _prev_end = end; + //if (len > 0) { + // std::string s = ""; + // for(size_t p = end-len; p < end; p++) + // s += unicode_cpt_to_utf8(cpts[p]); + // printf(">>> '%s'\n", s.c_str()); + //} + return len; + }; + + for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) { + const char32_t cpt = _get_cpt(pos); + const int cpt_type = _get_cpt_type(pos); + + // regex: (?i:'s|'t|'re|'ve|'m|'ll|'d) // case insensitive + if (cpt == '\'' && pos+1 < offset_end) { + char32_t cpt_next = unicode_tolower(_get_cpt(pos+1)); + if (cpt_next == 's' || cpt_next == 't' || cpt_next == 'm' || cpt_next == 'd') { + pos += _add_token(pos+2); + continue; } - if (split_condition) { - if (token.size()) { - bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size()); + if (pos+2 < offset_end) { + char32_t cpt_next_next = unicode_tolower(_get_cpt(pos+2)); + if ((cpt_next == 'r' && cpt_next_next == 'e') || + (cpt_next == 'v' && cpt_next_next == 'e') || + (cpt_next == 'l' && cpt_next_next == 'l')) { + pos += _add_token(pos+3); + continue; } - token = utf_char + utf_char_next; - bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size()); - token = ""; - i++; - continue; } } - if (!split_condition && bytes_remain >= 3) { - // 're|'ve|'ll - if (utf_char == "\'" && ( - (utf_char_next == "r" && utf_char_next_next == "e") || - (utf_char_next == "v" && utf_char_next_next == "e") || - (utf_char_next == "l" && utf_char_next_next == "l")) - ) { - split_condition = true; - } - if (split_condition) { - // current token + next token can be defined - if (token.size()) { - bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size()); - } - token = utf_char; - token += utf_char_next; - token += utf_char_next_next; - bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size()); - token = ""; - i += 2; + // regex: [^\r\n\p{L}\p{N}]?\p{L}+ //####FIXME: the first \p{L} is correct? + if (cpt != '\r' && cpt != '\n' && /*cpt_type != CODEPOINT_TYPE_LETTER &&*/ cpt_type != CODEPOINT_TYPE_NUMBER) { + if (cpt_type == CODEPOINT_TYPE_LETTER || _get_cpt_type(pos+1) == CODEPOINT_TYPE_LETTER) { // one or more letters + pos++; + while (_get_cpt_type(pos) == CODEPOINT_TYPE_LETTER) { + pos++; + } + _add_token(pos); continue; } } - if (!split_condition && !collecting) { - if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) { - collecting_letter = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_NUMBER || (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_NUMBER)) { - collecting_numeric = true; - collecting = true; - } - else if ( - ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_NUMBER) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) || - (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_NUMBER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE) - ) { - collecting_special = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) { - collecting_whitespace_lookahead = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) { - split_condition = true; + // regex: \p{N}{1,3} + if (cpt_type == CODEPOINT_TYPE_NUMBER) { + size_t ini = pos; + while (_get_cpt_type(pos) == CODEPOINT_TYPE_NUMBER) { + if (++pos - ini >= 3 ) { + _add_token(pos); + ini = pos; + } } + _add_token(pos); + continue; } - else if (!split_condition && collecting) { - if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) { - split_condition = true; - } - else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_NUMBER) { - split_condition = true; + + // regex: <space>?[^\s\p{L}\p{N}]+[\r\n]* + char32_t cpt2 = (cpt == ' ' ? _get_cpt(pos+1) : cpt); + int cpt2_type = (cpt == ' ' ? _get_cpt_type(pos+1) : cpt_type); + if (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) { + pos += (cpt == ' '); + while (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) { + cpt2_type = _get_cpt_type(++pos); + cpt2 = _get_cpt(pos); } - else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_NUMBER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) { - split_condition = true; + while (cpt2 == '\r' || cpt2 == '\n') { + cpt2 = _get_cpt(++pos); } - else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_NUMBER)) { - split_condition = true; + _add_token(pos); + continue; + } + + size_t num_whitespaces = 0; + size_t last_end_r_or_n = 0; + while (unicode_cpt_is_whitespace(_get_cpt(pos+num_whitespaces))) { + char32_t cpt2 = _get_cpt(pos+num_whitespaces); + if (cpt2 == '\r' || cpt2 == '\n') { + last_end_r_or_n = pos + num_whitespaces + 1; } + num_whitespaces++; } - if (utf_char_next == "") { - split_condition = true; // final - token += utf_char; + // regex: \s*[\r\n]+ + if (last_end_r_or_n > 0) { + pos = last_end_r_or_n; + _add_token(pos); + continue; } - if (split_condition) { - if (token.size()) { - bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size()); - } - token = utf_char; - collecting = false; - collecting_letter = false; - collecting_numeric = false; - collecting_special = false; - collecting_whitespace_lookahead = false; + // regex: \s+(?!\S) + if (num_whitespaces > 1 && _get_cpt(pos+num_whitespaces) != 0) { + pos += num_whitespaces - 1; + _add_token(pos); + continue; } - else { - token += utf_char; + + // regex: \s+ + if (num_whitespaces > 0) { + pos += num_whitespaces; + _add_token(pos); + continue; } - } - start += offset; + // no matches + _add_token(++pos); + } } return bpe_offsets; @@ -424,14 +543,14 @@ static std::vector<size_t> unicode_regex_split_stl(const std::string & text, con static std::vector<size_t> unicode_regex_split_custom(const std::string & text, const std::string & regex_expr, const std::vector<size_t> & offsets) { std::vector<size_t> bpe_offsets; - (void)(text); - (void)(regex_expr); - (void)(offsets); - // TODO: this implementation is actually wrong, uncomment and run: - // make -j && ./bin/test-tokenizer-0 ../models/ggml-vocab-gpt-2.gguf - //if (regex_expr == "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)") { - // bpe_offsets = unicode_regex_split_custom_gpt2(text, offsets); - //} + if (regex_expr == "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)") { + bpe_offsets = unicode_regex_split_custom_gpt2(text, offsets); + } else if ( + regex_expr == "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+" || + regex_expr == "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+") { + + bpe_offsets = unicode_regex_split_custom_llama3(text, offsets); + } return bpe_offsets; } @@ -506,6 +625,19 @@ int unicode_cpt_type(const std::string & utf8) { return unicode_cpt_type(unicode_cpt_from_utf8(utf8, offset)); } +bool unicode_cpt_is_whitespace(uint32_t cp) { + static const std::unordered_set<uint32_t> is_whitespace = [] { + std::unordered_set<uint32_t> is_whitespace; + for (auto p : unicode_ranges_whitespace) { + for (auto i = p.first; i <= p.second; ++i) { + is_whitespace.insert(i); + } + } + return is_whitespace; + }(); + return (bool)is_whitespace.count(cp); +} + std::string unicode_byte_to_utf8(uint8_t byte) { static std::unordered_map<uint8_t, std::string> map = unicode_byte_to_utf8_map(); return map.at(byte); diff --git a/unicode.h b/unicode.h index e9026dc81493f..d6a14d470bfc3 100644 --- a/unicode.h +++ b/unicode.h @@ -7,7 +7,7 @@ #define CODEPOINT_TYPE_UNIDENTIFIED 0 #define CODEPOINT_TYPE_NUMBER 1 #define CODEPOINT_TYPE_LETTER 2 -#define CODEPOINT_TYPE_WHITESPACE 3 +#define CODEPOINT_TYPE_SEPARATOR 3 #define CODEPOINT_TYPE_ACCENT_MARK 4 #define CODEPOINT_TYPE_PUNCTUATION 5 #define CODEPOINT_TYPE_SYMBOL 6 @@ -21,6 +21,8 @@ std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & c int unicode_cpt_type(uint32_t cp); int unicode_cpt_type(const std::string & utf8); +bool unicode_cpt_is_whitespace(uint32_t cp); + std::string unicode_byte_to_utf8(uint8_t byte); uint8_t unicode_utf8_to_byte(const std::string & utf8); From 0961d866044143eefec5b525e991611f73fd4f6e Mon Sep 17 00:00:00 2001 From: l3utterfly <gc.pthzfoldr@gmail.com> Date: Thu, 9 May 2024 22:32:40 +0900 Subject: [PATCH 26/64] readme : add app (#6371) * added Layla to supported UIs * Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 15686047031c1..3c4b6d6921a61 100644 --- a/README.md +++ b/README.md @@ -175,6 +175,7 @@ Unless otherwise noted these projects are open-source with permissive licensing: - [nat/openplayground](https://github.com/nat/openplayground) - [Faraday](https://faraday.dev/) (proprietary) - [LMStudio](https://lmstudio.ai/) (proprietary) +- [Layla](https://play.google.com/store/apps/details?id=com.laylalite) (proprietary) - [LocalAI](https://github.com/mudler/LocalAI) (MIT) - [LostRuins/koboldcpp](https://github.com/LostRuins/koboldcpp) (AGPL) - [Mozilla-Ocho/llamafile](https://github.com/Mozilla-Ocho/llamafile) From d46dbc76f8770caec0175f1e57777173c70556a0 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Thu, 9 May 2024 16:40:42 +0300 Subject: [PATCH 27/64] readme : add scheduled server workflow status badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3c4b6d6921a61..ff00f9966f2ef 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ ![llama](https://user-images.githubusercontent.com/1991296/230134379-7181e485-c521-4d23-a0d6-f7b3b61ba524.png) -[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT) +[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![Server](https://github.com/ggerganov/llama.cpp/actions/workflows/server.yml/badge.svg?branch=master&event=schedule)](https://github.com/ggerganov/llama.cpp/actions/workflows/server.yml) [Roadmap](https://github.com/users/ggerganov/projects/7) / [Project status](https://github.com/ggerganov/llama.cpp/discussions/3471) / [Manifesto](https://github.com/ggerganov/llama.cpp/discussions/205) / [ggml](https://github.com/ggerganov/ggml) From befddd0f15de6efb15d7e7f5b527dfb671f4196f Mon Sep 17 00:00:00 2001 From: 0cc4m <picard12@live.de> Date: Thu, 9 May 2024 20:39:54 +0200 Subject: [PATCH 28/64] Vulkan Bugfixes and Improvements (#7084) * Modify mat mat mul shader for mul_mat_id, modify mat vec mul shaders for single call batch operation * Further work towards MoE, disabled for now * Disable MoE code (not ready yet), fix a number of bugs in shaders and Vulkan code * Add softmax with f16 mask and pos buffer support * Disable mul_mat_id shaders for now * Fix flake8 * Fix validation errors caused by empty buffers on larger batch sizes --- ggml-vulkan-shaders.hpp | 86048 ++++++++++++++++++---------------- ggml-vulkan.cpp | 1217 +- ggml_vk_generate_shaders.py | 716 +- 3 files changed, 48334 insertions(+), 39647 deletions(-) diff --git a/ggml-vulkan-shaders.hpp b/ggml-vulkan-shaders.hpp index fcb6f384bc2e2..d3a2fcf388b6a 100644 --- a/ggml-vulkan-shaders.hpp +++ b/ggml-vulkan-shaders.hpp @@ -6563,14 +6563,14 @@ const uint64_t dequant_q8_0_len = 4780; unsigned char diag_mask_inf_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x4c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x53,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30, 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x09,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x2d,0x00,0x00,0x00, -0x32,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, +0x45,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00, @@ -6580,23 +6580,23 @@ unsigned char diag_mask_inf_f32_data[] = { 0x48,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00, 0x15,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x2a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2b,0x00,0x00,0x00, +0x37,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x48,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x38,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x03,0x00,0x2b,0x00,0x00,0x00,0x02,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x22,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2d,0x00,0x00,0x00, +0x47,0x00,0x03,0x00,0x38,0x00,0x00,0x00,0x02,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x3a,0x00,0x00,0x00,0x22,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3a,0x00,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x2f,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0x30,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x30,0x00,0x00,0x00, +0x42,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x48,0x00,0x04,0x00,0x43,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x43,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x03,0x00,0x30,0x00,0x00,0x00,0x02,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x32,0x00,0x00,0x00,0x22,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x32,0x00,0x00,0x00, +0x47,0x00,0x03,0x00,0x43,0x00,0x00,0x00,0x02,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x45,0x00,0x00,0x00,0x22,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x45,0x00,0x00,0x00, 0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x49,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x4b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00, 0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00, 0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00, @@ -6617,30 +6617,30 @@ unsigned char diag_mask_inf_f32_data[] = { 0x18,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x09,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x1d,0x00,0x00,0x00, -0x16,0x00,0x03,0x00,0x29,0x00,0x00,0x00,0x20,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x2a,0x00,0x00,0x00,0x29,0x00,0x00,0x00, -0x1e,0x00,0x03,0x00,0x2b,0x00,0x00,0x00,0x2a,0x00,0x00,0x00, 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+0x28,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x3f,0x00,0x00,0x00, +0x52,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x35,0x00,0x00,0x00, +0xf8,0x00,0x02,0x00,0x40,0x00,0x00,0x00,0x41,0x00,0x06,0x00, +0x3e,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x45,0x00,0x00,0x00, +0x19,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x36,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x47,0x00,0x00,0x00, +0x41,0x00,0x06,0x00,0x3e,0x00,0x00,0x00,0x49,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x28,0x00,0x00,0x00, +0x3e,0x00,0x03,0x00,0x49,0x00,0x00,0x00,0x48,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0x35,0x00,0x00,0x00,0xf8,0x00,0x02,0x00, +0x35,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4c,0x00,0x00,0x00, +0xf8,0x00,0x02,0x00,0x4c,0x00,0x00,0x00,0xfd,0x00,0x01,0x00, 0x38,0x00,0x01,0x00, }; -const uint64_t diag_mask_inf_f32_len = 1480; +const uint64_t diag_mask_inf_f32_len = 1504; unsigned char gelu_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, @@ -7840,110 +7842,133 @@ const uint64_t get_rows_f32_f32_len = 2976; unsigned char get_rows_q4_0_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xf8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00, 0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00, 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64, 0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00, 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00, 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e, -0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00, -0x36,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,0xac,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x41,0x00,0x00,0x00, +0x51,0x00,0x00,0x00,0x69,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00, 0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 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+0xc1,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x41,0x00,0x06,0x00,0xc2,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, +0xba,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, +0x3e,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0xc1,0x00,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc9,0x00,0x00,0x00, +0xbf,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x51,0x00,0x05,0x00, +0x08,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0xf1,0x00,0x00,0x00, +0x01,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0xc2,0x00,0x00,0x00, +0xcc,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x1c,0x00,0x00,0x00, +0xc9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0xcc,0x00,0x00,0x00, +0xcb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xcf,0x00,0x00,0x00, +0xf8,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,0xfd,0x00,0x01,0x00, 0x38,0x00,0x01,0x00, }; const uint64_t get_rows_q8_0_f32_len = 3628; unsigned char matmul_f16_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 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+0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x53,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x60,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x62,0x00,0x00,0x00, +0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb8,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00, @@ -11200,15 +11202,15 @@ unsigned char matmul_f16_data[] = { 0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 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-0x82,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00, +0x81,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00, 0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00, @@ -11219,77 +11221,77 @@ unsigned char matmul_f16_data[] = { 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00, -0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x20,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x09,0x00,0x00,0x00, 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0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -11298,7 +11300,7 @@ unsigned char matmul_f16_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -11308,19 +11310,19 @@ unsigned char matmul_f16_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xf6,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xf9,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0xf8,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0xf9,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xfa,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x03,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x05,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x04,0x01,0x00,0x00, @@ -11329,20 +11331,20 @@ unsigned char matmul_f16_data[] = { 0x0c,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x14,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xf6,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0xf6,0x00,0x00,0x00,0x1e,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x20,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 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0x44,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,0x43,0x01,0x00,0x00, @@ -11350,32 +11352,32 @@ unsigned char matmul_f16_data[] = { 0x44,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x45,0x01,0x00,0x00, 0x46,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x4e,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x4f,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x50,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, 0x3b,0x00,0x04,0x00,0x50,0x01,0x00,0x00,0x51,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x63,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x63,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_f16_len = 10316; unsigned char matmul_f16_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x09,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xf5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00, 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64, 0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00, 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00, 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e, -0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0xfe,0x00,0x00,0x00, -0x05,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x69,0x01,0x00,0x00, -0x69,0x02,0x00,0x00,0xb2,0x02,0x00,0x00,0x10,0x00,0x06,0x00, +0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00, 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0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -12180,753 +12179,724 @@ unsigned char matmul_f16_aligned_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, -0x16,0x00,0x03,0x00,0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00, -0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, -0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, -0x1c,0x00,0x04,0x00,0xfc,0x00,0x00,0x00,0xf9,0x00,0x00,0x00, -0xfb,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xfd,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, 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+13071,7 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -13111,210 +13081,212 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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0x33,0x02,0x00,0x00,0x32,0x02,0x00,0x00,0x84,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x34,0x02,0x00,0x00,0x0f,0x00,0x00,0x00, 0x33,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x38,0x02,0x00,0x00,0x47,0x00,0x00,0x00,0x33,0x02,0x00,0x00, +0x38,0x02,0x00,0x00,0x48,0x00,0x00,0x00,0x33,0x02,0x00,0x00, 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x3a,0x02,0x00,0x00, 0x39,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x3b,0x02,0x00,0x00,0x3a,0x02,0x00,0x00, @@ -13674,7 +13644,7 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,0x34,0x02,0x00,0x00, 0x3c,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf5,0x00,0x07,0x00, -0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0x3e,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,0x3f,0x00,0x00,0x00, 0xd6,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0x42,0x02,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x45,0x02,0x00,0x00, 0xa9,0x02,0x00,0x00,0xbf,0x00,0x00,0x00,0xf6,0x00,0x04,0x00, @@ -13683,29 +13653,29 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0x41,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x47,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xaa,0x02,0x00,0x00,0x3e,0x00,0x00,0x00,0x40,0x02,0x00,0x00, +0xaa,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x40,0x02,0x00,0x00, 0xa4,0x02,0x00,0x00,0x4a,0x02,0x00,0x00,0xb0,0x00,0x05,0x00, 0xc2,0x00,0x00,0x00,0x4d,0x02,0x00,0x00,0xaa,0x02,0x00,0x00, -0x60,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x49,0x02,0x00,0x00, +0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x49,0x02,0x00,0x00, 0x4a,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00, 0x4d,0x02,0x00,0x00,0x48,0x02,0x00,0x00,0x49,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x48,0x02,0x00,0x00,0x84,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,0xaa,0x02,0x00,0x00, -0x61,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x52,0x02,0x00,0x00,0x27,0x02,0x00,0x00,0x51,0x02,0x00,0x00, +0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x52,0x02,0x00,0x00,0x28,0x02,0x00,0x00,0x51,0x02,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x54,0x02,0x00,0x00, -0x64,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00, +0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x55,0x02,0x00,0x00,0x52,0x02,0x00,0x00, 0x54,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x59,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xc7,0x01,0x00,0x00, +0x59,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xc8,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5a,0x02,0x00,0x00, -0x2d,0x02,0x00,0x00,0x59,0x02,0x00,0x00,0x84,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0x68,0x00,0x00,0x00, +0x2e,0x02,0x00,0x00,0x59,0x02,0x00,0x00,0x84,0x00,0x05,0x00, +0x06,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0x69,0x00,0x00,0x00, 0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x5d,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0x5c,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x5f,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xac,0x02,0x00,0x00,0x3e,0x00,0x00,0x00,0x48,0x02,0x00,0x00, +0xac,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x48,0x02,0x00,0x00, 0xa2,0x02,0x00,0x00,0x62,0x02,0x00,0x00,0xb0,0x00,0x05,0x00, 0xc2,0x00,0x00,0x00,0x65,0x02,0x00,0x00,0xac,0x02,0x00,0x00, 0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x61,0x02,0x00,0x00, @@ -13714,22 +13684,22 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0xf8,0x00,0x02,0x00,0x60,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0x67,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00, 0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00, -0x3e,0x00,0x00,0x00,0x60,0x02,0x00,0x00,0xa0,0x02,0x00,0x00, +0x3f,0x00,0x00,0x00,0x60,0x02,0x00,0x00,0xa0,0x02,0x00,0x00, 0x6a,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00, -0x6d,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x62,0x00,0x00,0x00, +0x6d,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x63,0x00,0x00,0x00, 0xf6,0x00,0x04,0x00,0x69,0x02,0x00,0x00,0x6a,0x02,0x00,0x00, 0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6d,0x02,0x00,0x00, 0x68,0x02,0x00,0x00,0x69,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x68,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x70,0x02,0x00,0x00,0x55,0x02,0x00,0x00,0xae,0x02,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x73,0x02,0x00,0x00, -0x70,0x02,0x00,0x00,0x36,0x00,0x00,0x00,0xf7,0x00,0x03,0x00, +0x70,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00, 0x75,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00, 0x73,0x02,0x00,0x00,0x74,0x02,0x00,0x00,0x75,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x78,0x02,0x00,0x00,0x5d,0x02,0x00,0x00, -0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x79,0x02,0x00,0x00,0x12,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00, +0x79,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x7a,0x02,0x00,0x00, 0x79,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00, 0x7b,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0x7a,0x02,0x00,0x00, @@ -13741,8 +13711,8 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0x7c,0x02,0x00,0x00,0x7d,0x02,0x00,0x00,0x7e,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,0x5d,0x02,0x00,0x00, -0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x88,0x02,0x00,0x00,0x12,0x00,0x00,0x00,0x87,0x02,0x00,0x00, +0xac,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00, +0x88,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x87,0x02,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00, 0x88,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x8a,0x02,0x00,0x00,0x86,0x02,0x00,0x00,0x89,0x02,0x00,0x00, @@ -13757,7 +13727,7 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0xac,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x95,0x02,0x00,0x00,0x93,0x02,0x00,0x00,0x94,0x02,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00, -0xaa,0x02,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00, +0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x98,0x02,0x00,0x00,0x95,0x02,0x00,0x00, 0x97,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x9a,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0xae,0x02,0x00,0x00, @@ -13765,7 +13735,7 @@ unsigned char matmul_f16_aligned_fp32_data[] = { 0xca,0x00,0x00,0x00,0x9a,0x02,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0x9b,0x02,0x00,0x00, 0x41,0x00,0x06,0x00,0x9d,0x02,0x00,0x00,0x9e,0x02,0x00,0x00, -0x82,0x02,0x00,0x00,0x34,0x00,0x00,0x00,0x8f,0x02,0x00,0x00, +0x82,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8f,0x02,0x00,0x00, 0x3e,0x00,0x03,0x00,0x9e,0x02,0x00,0x00,0x9c,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x7e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x6a,0x02,0x00,0x00, @@ -13792,55 +13762,55 @@ const uint64_t matmul_f16_aligned_fp32_len = 10288; unsigned char matmul_f16_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xda,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00, 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64, 0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00, 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00, 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e, -0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00, +0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 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+0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -13972,19 +13942,19 @@ unsigned char matmul_f16_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xf6,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xf9,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0xf8,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0xf9,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xfa,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x03,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x04,0x01,0x00,0x00,0x03,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x05,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x04,0x01,0x00,0x00, @@ -13993,20 +13963,20 @@ unsigned char matmul_f16_f32_data[] = { 0x0c,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x14,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xf6,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00, 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0x06,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x44,0x01,0x00,0x00,0xf6,0x00,0x00,0x00,0x43,0x01,0x00,0x00, @@ -14014,7 +13984,7 @@ unsigned char matmul_f16_f32_data[] = { 0x44,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x45,0x01,0x00,0x00, 0x46,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x4e,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x4f,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x50,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, @@ -14022,25 +13992,25 @@ unsigned char matmul_f16_f32_data[] = { 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+14020,20 @@ unsigned char matmul_f16_f32_data[] = { 0x06,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,0x86,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xcf,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xfe,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x33,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, -0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x3b,0x02,0x00,0x00, -0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x81,0x02,0x00,0x00, -0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x82,0x02,0x00,0x00, -0x81,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0x83,0x02,0x00,0x00, -0x0c,0x00,0x00,0x00,0x82,0x02,0x00,0x00,0x3b,0x00,0x04,0x00, -0x83,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x89,0x02,0x00,0x00, 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+0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -17507,17 +16581,17 @@ unsigned char matmul_f16_fp32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf6,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf7,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0xf6,0x00,0x00,0x00, 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-0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x44,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x43,0x01,0x00,0x00, @@ -17547,54 +16621,54 @@ unsigned char matmul_f16_fp32_data[] = { 0x44,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x45,0x01,0x00,0x00, 0x46,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0x4e,0x01,0x00,0x00,0x02,0x01,0x00,0x00,0x1e,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x4e,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x4f,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x50,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, 0x3b,0x00,0x04,0x00,0x50,0x01,0x00,0x00,0x51,0x01,0x00,0x00, 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0x14,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -17782,42 +16856,42 @@ unsigned char matmul_f16_fp32_data[] = { 0x01,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x16,0x01,0x00,0x00, 0x14,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00, 0xf8,0x00,0x02,0x00,0x17,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x73,0x00,0x00,0x00, -0xb6,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00,0x74,0x00,0x00,0x00, +0xb4,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x1c,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x1b,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x01,0x00,0x00, -0x1c,0x01,0x00,0x00,0x6e,0x00,0x00,0x00,0x41,0x00,0x05,0x00, +0x1c,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,0x41,0x00,0x05,0x00, 0x15,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0xfa,0x00,0x00,0x00, 0x1e,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x1f,0x01,0x00,0x00, 0xcb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf5,0x00,0x00,0x00, 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matmul_f16_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xda,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, -0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, +0xd6,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00, 0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c, 0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00, 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, -0xfb,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x47,0x01,0x00,0x00, -0x52,0x01,0x00,0x00,0x3b,0x02,0x00,0x00,0x84,0x02,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, +0xfa,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0x46,0x01,0x00,0x00, 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0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -18278,77 +17351,77 @@ unsigned char matmul_f32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x11,0x00,0x00,0x00, -0x09,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x11,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00, -0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x20,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, 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0x38,0x00,0x01,0x00, }; -const uint64_t matmul_f32_len = 10324; +const uint64_t matmul_f16_fp32_len = 10276; -unsigned char matmul_f32_aligned_data[] = { +unsigned char matmul_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x18,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c, 0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00, 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, -0xfe,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x6b,0x01,0x00,0x00, -0x71,0x01,0x00,0x00,0x79,0x02,0x00,0x00,0xc2,0x02,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 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10208; -unsigned char matmul_q2_k_f32_aligned_data[] = { +unsigned char matmul_q2_k_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x68,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x4e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -22662,51 +21618,51 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0x58,0x01,0x00,0x00, -0x8d,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0xa2,0x02,0x00,0x00, -0xeb,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 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0xc4,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x9f,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0xa1,0x01,0x00,0x00, 0xa0,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x5d,0x01,0x00,0x00, @@ -23250,7 +23147,7 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, 0x88,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x97,0x01,0x00,0x00,0xa6,0x01,0x00,0x00,0x95,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xa7,0x01,0x00,0x00,0xa6,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x19,0x01,0x00,0x00,0xa8,0x01,0x00,0x00,0xa7,0x01,0x00,0x00, @@ -23259,8 +23156,8 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0xa9,0x01,0x00,0x00,0xa8,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xab,0x01,0x00,0x00,0x88,0x01,0x00,0x00, 0x47,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x97,0x01,0x00,0x00, -0xad,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x7f,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x01,0x00,0x00, +0xad,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x7f,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x47,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xae,0x01,0x00,0x00, 0xad,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x19,0x01,0x00,0x00, 0xaf,0x01,0x00,0x00,0xae,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -23269,8 +23166,8 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0xaf,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xb3,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0xb2,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x97,0x01,0x00,0x00,0xb5,0x01,0x00,0x00, -0x95,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, -0xd0,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x95,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, +0xd0,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xb6,0x01,0x00,0x00,0xb5,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0xb7,0x01,0x00,0x00, 0xb6,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x5d,0x01,0x00,0x00, @@ -23279,8 +23176,8 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, 0x88,0x01,0x00,0x00,0xba,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x97,0x01,0x00,0x00,0xbd,0x01,0x00,0x00,0x95,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x01,0x00,0x00,0xbd,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x19,0x01,0x00,0x00,0xbf,0x01,0x00,0x00,0xbe,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x5d,0x01,0x00,0x00,0xc0,0x01,0x00,0x00, @@ -23288,7 +23185,7 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0xc0,0x01,0x00,0x00,0xbf,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00,0x88,0x01,0x00,0x00, 0xc2,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x97,0x01,0x00,0x00, -0xc5,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0xc5,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x7f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xc6,0x01,0x00,0x00, 0xc5,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x19,0x01,0x00,0x00, @@ -23298,7 +23195,7 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0xc7,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xcb,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0xca,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x97,0x01,0x00,0x00,0xcd,0x01,0x00,0x00, -0x95,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, +0x95,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xce,0x01,0x00,0x00,0xcd,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0xcf,0x01,0x00,0x00, @@ -23306,162 +23203,162 @@ unsigned char matmul_q2_k_f32_aligned_data[] = { 0xd0,0x01,0x00,0x00,0x8d,0x01,0x00,0x00,0xcb,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0xd0,0x01,0x00,0x00,0xcf,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd5,0x01,0x00,0x00, -0x25,0x03,0x00,0x00,0xd3,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0x24,0x03,0x00,0x00,0xd3,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0x6d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x6f,0x01,0x00,0x00, 0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0xd6,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xd9,0x01,0x00,0x00,0x28,0x03,0x00,0x00,0xd7,0x01,0x00,0x00, +0xd9,0x01,0x00,0x00,0x27,0x03,0x00,0x00,0xd7,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdc,0x01,0x00,0x00, -0x2c,0x03,0x00,0x00,0xda,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0x2b,0x03,0x00,0x00,0xda,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xde,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x01,0x00,0x00, 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+23618,15 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x91,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x93,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x93,0x01,0x00,0x00,0x21,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x79,0x02,0x00,0x00, +0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x78,0x02,0x00,0x00, 0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xbf,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0xc0,0x02,0x00,0x00,0x00,0x00,0x00,0x00, -0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xc0,0x02,0x00,0x00, +0xbe,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x48,0x00,0x04,0x00,0xbf,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xbf,0x02,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x03,0x00,0xc0,0x02,0x00,0x00,0x02,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xc2,0x02,0x00,0x00,0x22,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc2,0x02,0x00,0x00, +0x47,0x00,0x03,0x00,0xbf,0x02,0x00,0x00,0x02,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0xc1,0x02,0x00,0x00,0x22,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xc1,0x02,0x00,0x00, 0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00, 0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -23740,79 +23637,79 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 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+0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00, @@ -23831,10 +23728,10 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x07,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x80,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00, 0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -23863,9 +23760,9 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x40,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x03,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x56,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x55,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x55,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x57,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0x56,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x58,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -23874,17 +23771,17 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x64,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x65,0x01,0x00,0x00,0x64,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x66,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x65,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x67,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x66,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x68,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x67,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x67,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x83,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x88,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x89,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0x88,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x8a,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x89,0x01,0x00,0x00, @@ -23901,21 +23798,21 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xab,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x65,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xac,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xab,0x01,0x00,0x00,0x77,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xab,0x01,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xad,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xac,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xac,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb0,0x01,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xb1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0xb1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xb4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xcf,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xd0,0x01,0x00,0x00, +0xb4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xcf,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xd0,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0xcf,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0xd1,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0xd0,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe1,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfc,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0xfd,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, @@ -23924,21 +23821,21 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00,0x86,0x00,0x00,0x00, 0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0f,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x3e,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x71,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, -0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x79,0x02,0x00,0x00, -0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xbf,0x02,0x00,0x00, -0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xc0,0x02,0x00,0x00, -0xbf,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0xc1,0x02,0x00,0x00, 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0xf5,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf7,0x00,0x00,0x00, -0x6e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00, +0x6f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0xf5,0x00,0x00,0x00, 0xf7,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xfc,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, @@ -24122,27 +24019,27 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x13,0x01,0x00,0x00, 0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x23,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x20,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x0a,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x17,0x01,0x00,0x00, 0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00, 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0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, 0x41,0x00,0x07,0x00,0x38,0x01,0x00,0x00,0x39,0x01,0x00,0x00, -0x20,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, -0x86,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x1b,0x01,0x00,0x00, +0x20,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, +0x87,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x1b,0x01,0x00,0x00, 0x3a,0x01,0x00,0x00,0x39,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x34,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,0x3a,0x01,0x00,0x00, 0x51,0x00,0x05,0x00,0xc4,0x00,0x00,0x00,0x3e,0x01,0x00,0x00, @@ -24156,7 +24053,7 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0xc2,0x00,0x05,0x00,0x14,0x01,0x00,0x00,0x47,0x01,0x00,0x00, 0x2d,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0xc7,0x00,0x05,0x00, 0x14,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x47,0x01,0x00,0x00, -0x3e,0x03,0x00,0x00,0x70,0x00,0x04,0x00,0x34,0x01,0x00,0x00, +0x3d,0x03,0x00,0x00,0x70,0x00,0x04,0x00,0x34,0x01,0x00,0x00, 0x4b,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x8e,0x00,0x05,0x00, 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+0x42,0x02,0x00,0x00,0x12,0x03,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x48,0x02,0x00,0x00,0x41,0x02,0x00,0x00, -0x13,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00, +0x12,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00, 0x49,0x02,0x00,0x00,0xd2,0x01,0x00,0x00,0x48,0x02,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x4a,0x02,0x00,0x00, 0x49,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00, @@ -24405,219 +24302,219 @@ unsigned char matmul_q2_k_f32_aligned_fp32_data[] = { 0x4a,0x02,0x00,0x00,0x50,0x02,0x00,0x00,0x53,0x02,0x00,0x00, 0x3e,0x00,0x03,0x00,0x52,0x02,0x00,0x00,0x54,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00, -0x13,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x12,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x33,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x35,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x2e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 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0x38,0x00,0x01,0x00, }; const uint64_t matmul_q2_k_f32_aligned_fp32_len = 11068; unsigned char matmul_q2_k_f32_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x48,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x47,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00, 0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00, 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64, 0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00, 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00, 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e, -0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x1f,0x01,0x00,0x00, +0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00, +0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x1f,0x01,0x00,0x00, 0x58,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x94,0x01,0x00,0x00, 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+0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -24757,10 +24654,10 @@ unsigned char matmul_q2_k_f32_fp32_data[] = { 0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfa,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 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0xc3,0x00,0x00,0x00,0xfd,0x01,0x00,0x00,0x20,0x00,0x04,0x00, @@ -24850,21 +24747,21 @@ unsigned char matmul_q2_k_f32_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x08,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x10,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3f,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x72,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x71,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0x7a,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0xc0,0x02,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, -0xc1,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 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-0x38,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xfb,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x38,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xfb,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x1a,0x01,0x00,0x00,0x39,0x01,0x00,0x00,0x38,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x33,0x01,0x00,0x00,0x3a,0x01,0x00,0x00, 0x39,0x01,0x00,0x00,0x51,0x00,0x05,0x00,0xc3,0x00,0x00,0x00, @@ -25082,7 +24979,7 @@ unsigned char matmul_q2_k_f32_fp32_data[] = { 0x12,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x13,0x01,0x00,0x00, 0x46,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,0x45,0x01,0x00,0x00, 0xc7,0x00,0x05,0x00,0x13,0x01,0x00,0x00,0x49,0x01,0x00,0x00, -0x46,0x01,0x00,0x00,0x47,0x03,0x00,0x00,0x70,0x00,0x04,0x00, +0x46,0x01,0x00,0x00,0x46,0x03,0x00,0x00,0x70,0x00,0x04,0x00, 0x33,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x49,0x01,0x00,0x00, 0x8e,0x00,0x05,0x00,0x33,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, 0x4a,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0x51,0x00,0x05,0x00, @@ -25101,27 +24998,27 @@ unsigned char matmul_q2_k_f32_fp32_data[] = { 0x58,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,0x3e,0x00,0x03,0x00, 0x5d,0x01,0x00,0x00,0x5b,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0xf7,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0xc3,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x51,0x00,0x05,0x00,0xc3,0x00,0x00,0x00, 0x61,0x01,0x00,0x00,0x53,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x41,0x00,0x05,0x00,0x5c,0x01,0x00,0x00,0x62,0x01,0x00,0x00, 0x58,0x01,0x00,0x00,0x5f,0x01,0x00,0x00,0x3e,0x00,0x03,0x00, 0x62,0x01,0x00,0x00,0x61,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0xfc,0x02,0x00,0x00, +0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0xfb,0x02,0x00,0x00, 0x67,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xdc,0x00,0x00,0x00, 0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x6b,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x6b,0x01,0x00,0x00, -0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xfd,0x02,0x00,0x00, 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-25139,190 +25036,190 @@ unsigned char matmul_q2_k_f32_fp32_data[] = { 0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x82,0x01,0x00,0x00, 0x83,0x01,0x00,0x00,0xa3,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x83,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x8c,0x01,0x00,0x00,0x7d,0x00,0x00,0x00,0xfd,0x02,0x00,0x00, +0x8c,0x01,0x00,0x00,0x7e,0x00,0x00,0x00,0xfc,0x02,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x01,0x00,0x00, 0x8c,0x01,0x00,0x00,0x8d,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x8e,0x01,0x00,0x00, -0x78,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x79,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x9b,0x01,0x00,0x00,0x8c,0x01,0x00,0x00,0xaa,0x00,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9c,0x01,0x00,0x00, -0x04,0x03,0x00,0x00,0x9b,0x01,0x00,0x00,0x80,0x00,0x05,0x00, +0x03,0x03,0x00,0x00,0x9b,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,0x9c,0x01,0x00,0x00, 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0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q2_k_f32_fp32_len = 11120; unsigned char matmul_q3_k_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xa8,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xa7,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -25509,47 +25406,47 @@ unsigned char matmul_q3_k_f32_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00,0x0b,0x02,0x00,0x00, -0x16,0x02,0x00,0x00,0x01,0x03,0x00,0x00,0x4a,0x03,0x00,0x00, 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0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -25584,15 +25481,15 @@ unsigned char matmul_q3_k_f32_data[] = { 0x47,0x00,0x04,0x00,0x16,0x02,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x16,0x02,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x01,0x03,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x47,0x03,0x00,0x00,0x06,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x48,0x03,0x00,0x00, +0x00,0x03,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x46,0x03,0x00,0x00,0x06,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x47,0x03,0x00,0x00, 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00, -0x48,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x48,0x03,0x00,0x00, -0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4a,0x03,0x00,0x00, +0x47,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, 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0xbb,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -25682,7 +25579,7 @@ unsigned char matmul_q3_k_f32_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -25692,10 +25589,10 @@ unsigned char matmul_q3_k_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x80,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -25721,14 +25618,14 @@ unsigned char matmul_q3_k_f32_data[] = { 0x3b,0x00,0x04,0x00,0x39,0x01,0x00,0x00,0x3a,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x3e,0x01,0x00,0x00, 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+25633,51 @@ unsigned char matmul_q3_k_f32_data[] = { 0xc5,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x35,0x01,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00, 0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00, -0xe6,0x01,0x00,0x00,0xe5,0x01,0x00,0x00,0x39,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xe6,0x01,0x00,0x00,0xe5,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe7,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0xe6,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe8,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xe7,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe9,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xe8,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x07,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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0xc0,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc4,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -26797,9 +26694,9 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x02,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -26824,14 +26721,14 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x3b,0x00,0x04,0x00,0x39,0x01,0x00,0x00,0x3a,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x3e,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x30,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x9c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x35,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x35,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xa2,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa7,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0xa8,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0xa7,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0xa9,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0xa8,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0xa9,0x01,0x00,0x00, @@ -26839,18 +26736,18 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0xc5,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x35,0x01,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00, 0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00, -0xe6,0x01,0x00,0x00,0xe5,0x01,0x00,0x00,0x39,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xe6,0x01,0x00,0x00,0xe5,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe7,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0xe6,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe8,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xe7,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe9,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xe8,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x04,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x09,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x04,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x09,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x0a,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00, 0x09,0x02,0x00,0x00,0x1c,0x00,0x04,0x00,0x0b,0x02,0x00,0x00, 0x35,0x01,0x00,0x00,0x0a,0x02,0x00,0x00,0x20,0x00,0x04,0x00, @@ -26874,21 +26771,21 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x51,0x02,0x00,0x00,0x51,0x00,0x00,0x00,0xe6,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x52,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x51,0x02,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x53,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x52,0x02,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x56,0x02,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 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+26794,20 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0xa4,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xae,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xb6,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xe5,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0x1a,0x03,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0x22,0x03,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x68,0x03,0x00,0x00,0xc4,0x00,0x00,0x00, -0x1e,0x00,0x03,0x00,0x69,0x03,0x00,0x00,0x68,0x03,0x00,0x00, -0x20,0x00,0x04,0x00,0x6a,0x03,0x00,0x00,0x0c,0x00,0x00,0x00, -0x69,0x03,0x00,0x00,0x3b,0x00,0x04,0x00,0x6a,0x03,0x00,0x00, -0x6b,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x70,0x03,0x00,0x00,0x05,0x00,0x00,0x00, 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+27207,43 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0xe4,0x01,0x00,0x00,0xe3,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xeb,0x01,0x00,0x00, -0xa0,0x03,0x00,0x00,0xe9,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0x9f,0x03,0x00,0x00,0xe9,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xed,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xed,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xa1,0x03,0x00,0x00,0x3e,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, +0xa0,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, 0x55,0x02,0x00,0x00,0xee,0x01,0x00,0x00,0xb0,0x00,0x05,0x00, -0xc2,0x00,0x00,0x00,0xf3,0x01,0x00,0x00,0xa1,0x03,0x00,0x00, +0xc2,0x00,0x00,0x00,0xf3,0x01,0x00,0x00,0xa0,0x03,0x00,0x00, 0xa7,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xef,0x01,0x00,0x00, 0xee,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00, 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0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1d,0x02,0x00,0x00, -0x08,0x02,0x00,0x00,0x39,0x00,0x00,0x00,0x41,0x00,0x08,0x00, +0x08,0x02,0x00,0x00,0x3a,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x17,0x02,0x00,0x00,0x1f,0x02,0x00,0x00,0x15,0x02,0x00,0x00, -0x34,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x20,0x02,0x00,0x00,0x1f,0x02,0x00,0x00,0x73,0x00,0x04,0x00, 0x35,0x01,0x00,0x00,0x21,0x02,0x00,0x00,0x20,0x02,0x00,0x00, 0x41,0x00,0x05,0x00,0xc5,0x01,0x00,0x00,0x22,0x02,0x00,0x00, @@ -27354,8 +27251,8 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x22,0x02,0x00,0x00,0x21,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x24,0x02,0x00,0x00,0x08,0x02,0x00,0x00, 0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x17,0x02,0x00,0x00, -0x26,0x02,0x00,0x00,0x15,0x02,0x00,0x00,0x34,0x00,0x00,0x00, -0xff,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x26,0x02,0x00,0x00,0x15,0x02,0x00,0x00,0x35,0x00,0x00,0x00, +0xff,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x27,0x02,0x00,0x00, 0x26,0x02,0x00,0x00,0x73,0x00,0x04,0x00,0x35,0x01,0x00,0x00, 0x28,0x02,0x00,0x00,0x27,0x02,0x00,0x00,0x41,0x00,0x05,0x00, @@ -27364,8 +27261,8 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x28,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x2c,0x02,0x00,0x00,0x08,0x02,0x00,0x00,0x2b,0x02,0x00,0x00, 0x41,0x00,0x08,0x00,0x17,0x02,0x00,0x00,0x2e,0x02,0x00,0x00, -0x15,0x02,0x00,0x00,0x34,0x00,0x00,0x00,0xff,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00, +0x15,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xff,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x2f,0x02,0x00,0x00,0x2e,0x02,0x00,0x00, 0x73,0x00,0x04,0x00,0x35,0x01,0x00,0x00,0x30,0x02,0x00,0x00, 0x2f,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xc5,0x01,0x00,0x00, @@ -27374,8 +27271,8 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x33,0x02,0x00,0x00, 0x08,0x02,0x00,0x00,0x14,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x17,0x02,0x00,0x00,0x35,0x02,0x00,0x00,0x15,0x02,0x00,0x00, -0x34,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x36,0x02,0x00,0x00,0x35,0x02,0x00,0x00,0x73,0x00,0x04,0x00, 0x35,0x01,0x00,0x00,0x37,0x02,0x00,0x00,0x36,0x02,0x00,0x00, 0x41,0x00,0x05,0x00,0xc5,0x01,0x00,0x00,0x38,0x02,0x00,0x00, @@ -27383,8 +27280,8 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x38,0x02,0x00,0x00,0x37,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x3b,0x02,0x00,0x00,0x08,0x02,0x00,0x00, 0x3a,0x02,0x00,0x00,0x41,0x00,0x08,0x00,0x17,0x02,0x00,0x00, -0x3d,0x02,0x00,0x00,0x15,0x02,0x00,0x00,0x34,0x00,0x00,0x00, -0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x3d,0x02,0x00,0x00,0x15,0x02,0x00,0x00,0x35,0x00,0x00,0x00, +0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x3e,0x02,0x00,0x00, 0x3d,0x02,0x00,0x00,0x73,0x00,0x04,0x00,0x35,0x01,0x00,0x00, 0x3f,0x02,0x00,0x00,0x3e,0x02,0x00,0x00,0x41,0x00,0x05,0x00, @@ -27393,7 +27290,7 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x43,0x02,0x00,0x00,0x08,0x02,0x00,0x00,0x42,0x02,0x00,0x00, 0x41,0x00,0x08,0x00,0x17,0x02,0x00,0x00,0x45,0x02,0x00,0x00, -0x15,0x02,0x00,0x00,0x34,0x00,0x00,0x00,0xff,0x01,0x00,0x00, +0x15,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xff,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x46,0x02,0x00,0x00,0x45,0x02,0x00,0x00, 0x73,0x00,0x04,0x00,0x35,0x01,0x00,0x00,0x47,0x02,0x00,0x00, @@ -27403,170 +27300,170 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00, 0x08,0x02,0x00,0x00,0x4a,0x02,0x00,0x00,0x41,0x00,0x08,0x00, 0x17,0x02,0x00,0x00,0x4d,0x02,0x00,0x00,0x15,0x02,0x00,0x00, -0x34,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xff,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, 0x2b,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x4e,0x02,0x00,0x00,0x4d,0x02,0x00,0x00,0x73,0x00,0x04,0x00, 0x35,0x01,0x00,0x00,0x4f,0x02,0x00,0x00,0x4e,0x02,0x00,0x00, 0x41,0x00,0x05,0x00,0xc5,0x01,0x00,0x00,0x50,0x02,0x00,0x00, 0x0d,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,0x3e,0x00,0x03,0x00, 0x50,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x55,0x02,0x00,0x00,0xa1,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0x55,0x02,0x00,0x00,0xa0,0x03,0x00,0x00, 0x53,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xed,0x01,0x00,0x00, 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0xf0,0x02,0x00,0x00,0x73,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, @@ -27582,172 +27479,172 @@ unsigned char matmul_q3_k_f32_aligned_data[] = { 0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xf2,0x02,0x00,0x00, 0xf9,0x02,0x00,0x00,0xfc,0x02,0x00,0x00,0x3e,0x00,0x03,0x00, 0xfb,0x02,0x00,0x00,0xfd,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0xb8,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0xb7,0x03,0x00,0x00, 0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xda,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0xd5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd5,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x02,0x03,0x00,0x00, -0xb6,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xb5,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0xd2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xd4,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0xcd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0xcd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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+0x9c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -27755,47 +27652,47 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00, -0x0b,0x02,0x00,0x00,0x12,0x02,0x00,0x00,0xf9,0x02,0x00,0x00, -0x42,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00, +0x0b,0x02,0x00,0x00,0x12,0x02,0x00,0x00,0xf8,0x02,0x00,0x00, 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+27727,15 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x12,0x02,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x12,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xf9,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3f,0x03,0x00,0x00, +0x47,0x00,0x04,0x00,0xf8,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x03,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0x40,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0x40,0x03,0x00,0x00,0x00,0x00,0x00,0x00, +0x3f,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0x3f,0x03,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0x40,0x03,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x42,0x03,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x42,0x03,0x00,0x00,0x21,0x00,0x00,0x00, +0x3f,0x03,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, +0x41,0x03,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x41,0x03,0x00,0x00,0x21,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00, 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -27849,78 +27746,78 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 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-0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -27940,10 +27837,10 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x40,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x06,0x01,0x00,0x00, @@ -27967,14 +27864,14 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x38,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x39,0x01,0x00,0x00, 0x3a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x3e,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x30,0x01,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x43,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x43,0x01,0x00,0x00, 0x0f,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x9c,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x20,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa7,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xa8,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0xa7,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xa9,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0xa8,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -27983,17 +27880,17 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xe3,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0xe4,0x01,0x00,0x00,0xe3,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0xe4,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe6,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xe5,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xe6,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xe6,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x02,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x08,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0x07,0x02,0x00,0x00,0x1c,0x00,0x04,0x00, 0x09,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x08,0x02,0x00,0x00, @@ -28012,21 +27909,21 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x2b,0x02,0x00,0x00,0x51,0x00,0x00,0x00,0xe4,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x2c,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x2b,0x02,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x2d,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x2c,0x02,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x30,0x02,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x31,0x02,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x34,0x02,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4f,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0x50,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x4f,0x02,0x00,0x00, 0x20,0x00,0x04,0x00,0x51,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x50,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x61,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x61,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x7c,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x7d,0x02,0x00,0x00, 0xc4,0x00,0x00,0x00,0x7c,0x02,0x00,0x00,0x20,0x00,0x04,0x00, @@ -28034,20 +27931,20 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x8f,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbe,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xf1,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xf0,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0xf9,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0x3f,0x03,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, -0x40,0x03,0x00,0x00,0x3f,0x03,0x00,0x00,0x20,0x00,0x04,0x00, -0x41,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x40,0x03,0x00,0x00, -0x3b,0x00,0x04,0x00,0x41,0x03,0x00,0x00,0x42,0x03,0x00,0x00, -0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0x47,0x03,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00, -0x06,0x00,0x00,0x00,0x54,0x03,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x36,0x00,0x05,0x00, +0xf8,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x3e,0x03,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, +0x3f,0x03,0x00,0x00,0x3e,0x03,0x00,0x00,0x20,0x00,0x04,0x00, +0x40,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x3f,0x03,0x00,0x00, +0x3b,0x00,0x04,0x00,0x40,0x03,0x00,0x00,0x41,0x03,0x00,0x00, +0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, +0x46,0x03,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x06,0x00,0x00,0x00,0x53,0x03,0x00,0x00,0x84,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x36,0x00,0x05,0x00, 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00, 0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0xca,0x00,0x00,0x00, @@ -28057,158 +27954,158 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 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0xdf,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0xc4,0x00,0x00,0x00, @@ -28444,48 +28341,48 @@ unsigned char matmul_q3_k_f32_aligned_fp32_data[] = { 0xe2,0x01,0x00,0x00,0xe1,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe9,0x01,0x00,0x00, -0x77,0x03,0x00,0x00,0xe7,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0x76,0x03,0x00,0x00,0xe7,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xeb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xeb,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0x78,0x03,0x00,0x00,0x3e,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, +0x77,0x03,0x00,0x00,0x3f,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, 0x2f,0x02,0x00,0x00,0xec,0x01,0x00,0x00,0xb0,0x00,0x05,0x00, -0xc2,0x00,0x00,0x00,0xf1,0x01,0x00,0x00,0x78,0x03,0x00,0x00, +0xc2,0x00,0x00,0x00,0xf1,0x01,0x00,0x00,0x77,0x03,0x00,0x00, 0xa7,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0xed,0x01,0x00,0x00, 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0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -28841,47 +28738,47 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00, -0x09,0x02,0x00,0x00,0x14,0x02,0x00,0x00,0xfa,0x02,0x00,0x00, -0x43,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0xaa,0x01,0x00,0x00, +0x09,0x02,0x00,0x00,0x14,0x02,0x00,0x00,0xf9,0x02,0x00,0x00, +0x42,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00, 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0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0xbc,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xbc,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 0xb9,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -29014,8 +28911,8 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0xbf,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -29025,9 +28922,9 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -29053,14 +28950,14 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x38,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x39,0x01,0x00,0x00, 0x3a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x3e,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x30,0x01,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x43,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x43,0x01,0x00,0x00, 0x0f,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x9c,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x20,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa7,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xa8,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0xa7,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xa9,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0xa8,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -29069,15 +28966,15 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xe3,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0xe4,0x01,0x00,0x00,0xe3,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0xe4,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe6,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xe5,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xe6,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xe6,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x05,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x06,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x05,0x02,0x00,0x00,0x1c,0x00,0x04,0x00, 0x07,0x02,0x00,0x00,0xc3,0x00,0x00,0x00,0x06,0x02,0x00,0x00, @@ -29085,7 +28982,7 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x07,0x02,0x00,0x00,0x3b,0x00,0x04,0x00,0x08,0x02,0x00,0x00, 0x09,0x02,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x11,0x02,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x12,0x02,0x00,0x00,0x11,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 0x13,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x12,0x02,0x00,0x00, @@ -29093,25 +28990,25 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1f,0x02,0x00,0x00, 0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x27,0x02,0x00,0x00,0x80,0x00,0x00,0x00, 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+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x50,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0x51,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, 0x50,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0x52,0x02,0x00,0x00, 0x07,0x00,0x00,0x00,0x51,0x02,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x62,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7d,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0x7e,0x02,0x00,0x00,0xc3,0x00,0x00,0x00,0x7d,0x02,0x00,0x00, @@ -29119,20 +29016,20 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x7e,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x88,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, 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-29142,159 +29039,159 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x07,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00, 0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00, -0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00, -0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00, -0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x41,0x00,0x05,0x00, -0x15,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x21,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00, -0x23,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x86,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x23,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, 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+29215,7 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x06,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x13,0x01,0x00,0x00, 0x02,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x24,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x1c,0x01,0x00,0x00, -0xc4,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x25,0x01,0x00,0x00, +0xc4,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x25,0x01,0x00,0x00, 0xcf,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x7c,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x2b,0x01,0x00,0x00, @@ -29327,29 +29224,29 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0x2b,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x50,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x2e,0x01,0x00,0x00,0x82,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x18,0x01,0x00,0x00, -0x3e,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x3e,0x01,0x00,0x00, -0x3f,0x01,0x00,0x00,0x3a,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xfb,0x00,0x00,0x00,0x85,0x00,0x00,0x00,0x3d,0x01,0x00,0x00, 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0xca,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00, @@ -29759,171 +29656,171 @@ unsigned char matmul_q3_k_f32_fp32_data[] = { 0xcb,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0xd4,0x02,0x00,0x00, 0x3e,0x00,0x03,0x00,0xd3,0x02,0x00,0x00,0xd5,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd8,0x02,0x00,0x00, -0x90,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x8f,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0xb4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xb6,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0xaf,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xda,0x02,0x00,0x00,0x8e,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, +0xda,0x02,0x00,0x00,0x8d,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0xae,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xa7,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0xa7,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0x8c,0x03,0x00,0x00, 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0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -29931,47 +29828,47 @@ unsigned char matmul_q4_0_f32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x27,0x01,0x00,0x00, -0x5a,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x50,0x02,0x00,0x00, -0x99,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x27,0x01,0x00,0x00, +0x5a,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x4f,0x02,0x00,0x00, +0x98,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00, 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0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -30109,9 +30006,9 @@ unsigned char matmul_q4_0_f32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00, 0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00, @@ -30131,9 +30028,9 @@ unsigned char matmul_q4_0_f32_data[] = { 0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0x1e,0x01,0x00,0x00,0x00,0x00,0x00,0x41,0x34,0x00,0x06,0x00, 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0x49,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00, 0x4b,0x01,0x00,0x00,0x48,0x01,0x00,0x00,0x4a,0x01,0x00,0x00, @@ -30433,9 +30330,9 @@ unsigned char matmul_q4_0_f32_data[] = { 0xfa,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,0x4c,0x01,0x00,0x00, 0x4d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x4c,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x50,0x01,0x00,0x00, -0xc0,0x02,0x00,0x00,0x78,0x00,0x00,0x00,0xb0,0x00,0x05,0x00, +0xbf,0x02,0x00,0x00,0x79,0x00,0x00,0x00,0xb0,0x00,0x05,0x00, 0xc1,0x00,0x00,0x00,0x52,0x01,0x00,0x00,0x50,0x01,0x00,0x00, -0x8d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4d,0x01,0x00,0x00, +0x8e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4d,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x4d,0x01,0x00,0x00,0xf5,0x00,0x07,0x00, 0xc1,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, 0x3d,0x01,0x00,0x00,0x52,0x01,0x00,0x00,0x4c,0x01,0x00,0x00, @@ -30443,17 +30340,17 @@ unsigned char matmul_q4_0_f32_data[] = { 0xfa,0x00,0x04,0x00,0x53,0x01,0x00,0x00,0x54,0x01,0x00,0x00, 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0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_0_f32_len = 10564; unsigned char matmul_q4_0_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x37,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x36,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -30816,47 +30713,47 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x28,0x01,0x00,0x00, -0x5d,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x73,0x02,0x00,0x00, -0xbc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 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0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -30998,10 +30895,10 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -31020,9 +30917,9 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,0x00,0x00,0x00,0x41, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x24,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x24,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x26,0x01,0x00,0x00,0x01,0x01,0x00,0x00, 0x25,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x27,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -31031,17 +30928,17 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x01,0x01,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x35,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x35,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x37,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x36,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x38,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x37,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x38,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x38,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x5b,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x5a,0x01,0x00,0x00, @@ -31066,21 +30963,21 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa2,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x77,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, 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0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xd8,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xde,0x01,0x00,0x00,0x07,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xf4,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -31090,21 +30987,21 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xff,0x01,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x36,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x6b,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 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0x0c,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x11,0x01,0x00,0x00, -0x12,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x12,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0xff,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x13,0x01,0x00,0x00, 0x12,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -31289,7 +31186,7 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x1d,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,0x50,0x00,0x05,0x00, 0x15,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x1a,0x01,0x00,0x00, 0x1d,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x15,0x01,0x00,0x00, -0x21,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x36,0x03,0x00,0x00, +0x21,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x35,0x03,0x00,0x00, 0x8e,0x00,0x05,0x00,0x15,0x01,0x00,0x00,0x23,0x01,0x00,0x00, 0x21,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,0x51,0x00,0x05,0x00, 0xc4,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x23,0x01,0x00,0x00, @@ -31305,43 +31202,43 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x41,0x00,0x05,0x00,0x2d,0x01,0x00,0x00,0x34,0x01,0x00,0x00, 0x28,0x01,0x00,0x00,0x30,0x01,0x00,0x00,0x3e,0x00,0x03,0x00, 0x34,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0xf3,0x02,0x00,0x00, +0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0xf2,0x02,0x00,0x00, 0x39,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xdd,0x00,0x00,0x00, 0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x3d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x3d,0x01,0x00,0x00, -0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xf4,0x02,0x00,0x00, -0x3e,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, +0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xf3,0x02,0x00,0x00, +0x3f,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0xa6,0x01,0x00,0x00, 0x3e,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00, -0x43,0x01,0x00,0x00,0xf4,0x02,0x00,0x00,0xa7,0x00,0x00,0x00, +0x43,0x01,0x00,0x00,0xf3,0x02,0x00,0x00,0xa7,0x00,0x00,0x00, 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0x06,0x00,0x00,0x00,0x6d,0x01,0x00,0x00,0x58,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00, -0x6f,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x4f,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00, +0x6f,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x4f,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x70,0x01,0x00,0x00, 0x6f,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, 0x71,0x01,0x00,0x00,0x70,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -31350,8 +31247,8 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x71,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x74,0x01,0x00,0x00,0x58,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00,0x76,0x01,0x00,0x00, -0x65,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x65,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x77,0x01,0x00,0x00,0x76,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x78,0x01,0x00,0x00, 0x77,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2d,0x01,0x00,0x00, @@ -31360,7 +31257,7 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7c,0x01,0x00,0x00, 0x58,0x01,0x00,0x00,0x7b,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x67,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,0x65,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x7b,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x7f,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0x80,0x01,0x00,0x00,0x7f,0x01,0x00,0x00, @@ -31369,8 +31266,8 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x81,0x01,0x00,0x00,0x80,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x84,0x01,0x00,0x00,0x58,0x01,0x00,0x00, 0x83,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00, -0x86,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x4f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x86,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x4f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3f,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x87,0x01,0x00,0x00, 0x86,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, 0x88,0x01,0x00,0x00,0x87,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -31379,8 +31276,8 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x88,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x8c,0x01,0x00,0x00,0x58,0x01,0x00,0x00,0x8b,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00,0x8e,0x01,0x00,0x00, -0x65,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, -0xd0,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x65,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, +0xd0,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x8e,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x90,0x01,0x00,0x00, 0x8f,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x2d,0x01,0x00,0x00, @@ -31389,7 +31286,7 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x01,0x00,0x00, 0x58,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x67,0x01,0x00,0x00,0x96,0x01,0x00,0x00,0x65,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x97,0x01,0x00,0x00,0x96,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0x98,0x01,0x00,0x00,0x97,0x01,0x00,0x00, @@ -31398,7 +31295,7 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x99,0x01,0x00,0x00,0x98,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x9c,0x01,0x00,0x00,0x58,0x01,0x00,0x00, 0x9b,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x67,0x01,0x00,0x00, -0x9e,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x9e,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x4f,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x7b,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, 0x9e,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, @@ -31406,162 +31303,162 @@ unsigned char matmul_q4_0_f32_aligned_data[] = { 0x2d,0x01,0x00,0x00,0xa1,0x01,0x00,0x00,0x5d,0x01,0x00,0x00, 0x9c,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xa1,0x01,0x00,0x00, 0xa0,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xa6,0x01,0x00,0x00,0xf4,0x02,0x00,0x00,0xa4,0x01,0x00,0x00, +0xa6,0x01,0x00,0x00,0xf3,0x02,0x00,0x00,0xa4,0x01,0x00,0x00, 0xf9,0x00,0x02,0x00,0x3d,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x3f,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00, 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0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00, @@ -31818,15 +31715,15 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x60,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x62,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x62,0x01,0x00,0x00,0x21,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x49,0x02,0x00,0x00, +0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x48,0x02,0x00,0x00, 0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x8f,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0x90,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 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0xbf,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xba,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc0,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, @@ -31918,7 +31815,7 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0xbc,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00, @@ -31928,10 +31825,10 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x07,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00, @@ -31950,9 +31847,9 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x15,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x1f,0x01,0x00,0x00, 0x00,0x00,0x00,0x41,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x24,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x25,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x24,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x25,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x24,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x26,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x27,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x26,0x01,0x00,0x00, @@ -31961,17 +31858,17 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x34,0x01,0x00,0x00, -0x33,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x33,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x35,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x34,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x37,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x52,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x58,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x57,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x59,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, @@ -31990,21 +31887,21 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0x7b,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x34,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7c,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x7b,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x7b,0x01,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x7c,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x7c,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00,0x08,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x84,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0xa0,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0x9f,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xa1,0x01,0x00,0x00, 0x07,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xb1,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xcc,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xcd,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0xcc,0x01,0x00,0x00, @@ -32012,21 +31909,21 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0xcd,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xd7,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xdf,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x0e,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, 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0x19,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00, @@ -32450,219 +32347,219 @@ unsigned char matmul_q4_0_f32_aligned_fp32_data[] = { 0x1a,0x02,0x00,0x00,0x20,0x02,0x00,0x00,0x23,0x02,0x00,0x00, 0x3e,0x00,0x03,0x00,0x22,0x02,0x00,0x00,0x24,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x27,0x02,0x00,0x00, -0xe1,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xe0,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x03,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0xfe,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xfe,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x29,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xd0,0x00,0x00,0x00, +0x29,0x02,0x00,0x00,0xde,0x02,0x00,0x00,0xd0,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xfb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xfd,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0xf6,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 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-0x53,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x60,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x62,0x00,0x00,0x00, +0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb8,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00, @@ -32690,15 +32587,15 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x61,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x63,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x63,0x01,0x00,0x00,0x21,0x00,0x00,0x00, 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0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xb7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xb7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x53,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x54,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x4f,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x32,0x00,0x04,0x00, +0x50,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x60,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x61,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -32789,7 +32686,7 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -32799,10 +32696,10 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x00,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -32821,9 +32718,9 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0xc3,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0x1e,0x01,0x00,0x00,0x00,0x00,0x00,0x41, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x23,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x23,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x25,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x24,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x26,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -32832,15 +32729,15 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x32,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x34,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x33,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x34,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x36,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x35,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x35,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x56,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x55,0x01,0x00,0x00, @@ -32848,7 +32745,7 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x56,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x57,0x01,0x00,0x00, 0x58,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x60,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x61,0x01,0x00,0x00,0x60,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x62,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x61,0x01,0x00,0x00, @@ -32856,25 +32753,25 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x6e,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x76,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7b,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x33,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7c,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x7b,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x7b,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x7c,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x7c,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00,0x08,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x84,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0xa0,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x9f,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xa1,0x01,0x00,0x00, 0x07,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xb1,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xcc,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xcd,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0xcc,0x01,0x00,0x00, @@ -32882,21 +32779,21 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0xcd,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xd7,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xdf,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x0e,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0x41,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0x49,0x02,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x8f,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, 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+0x20,0x00,0x04,0x00,0x90,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, +0x8f,0x02,0x00,0x00,0x3b,0x00,0x04,0x00,0x90,0x02,0x00,0x00, +0x91,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x15,0x00,0x00,0x00,0x96,0x02,0x00,0x00,0x05,0x00,0x00,0x00, +0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa3,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2c,0x00,0x05,0x00,0x14,0x01,0x00,0x00,0x13,0x03,0x00,0x00, 0x1e,0x01,0x00,0x00,0x1e,0x01,0x00,0x00,0x36,0x00,0x05,0x00, 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00, @@ -32907,169 +32804,169 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, -0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 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0x19,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcc,0x00,0x00,0x00, @@ -33325,171 +33222,171 @@ unsigned char matmul_q4_0_f32_fp32_data[] = { 0x1a,0x02,0x00,0x00,0x20,0x02,0x00,0x00,0x23,0x02,0x00,0x00, 0x3e,0x00,0x03,0x00,0x22,0x02,0x00,0x00,0x24,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x27,0x02,0x00,0x00, -0xe1,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xe0,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x03,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0xfe,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xfe,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x29,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xcf,0x00,0x00,0x00, +0x29,0x02,0x00,0x00,0xde,0x02,0x00,0x00,0xcf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xfb,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0xfd,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0xf6,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x2b,0x02,0x00,0x00,0xdd,0x02,0x00,0x00, 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+0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x59,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0xb2,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xcf,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x58,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x51,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0x51,0x02,0x00,0x00,0x80,0x00,0x05,0x00, +0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0xb9,0x02,0x00,0x00, +0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x4e,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0x50,0x02,0x00,0x00,0xfd,0x00,0x01,0x00, 0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_0_f32_fp32_len = 10444; unsigned char matmul_q4_1_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xf6,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xf5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -33497,47 +33394,47 @@ unsigned char matmul_q4_1_f32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x2c,0x01,0x00,0x00, -0x5f,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x55,0x02,0x00,0x00, -0x9e,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x2c,0x01,0x00,0x00, +0x5f,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x54,0x02,0x00,0x00, +0x9d,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00, 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0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -33666,7 +33563,7 @@ unsigned char matmul_q4_1_f32_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -33676,10 +33573,10 @@ unsigned char matmul_q4_1_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x00,0x01,0x00,0x00, @@ -33697,9 +33594,9 @@ unsigned char matmul_q4_1_f32_data[] = { 0x15,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x17,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x28,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x29,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x28,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x29,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x28,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x2a,0x01,0x00,0x00, 0x00,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x2b,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x2a,0x01,0x00,0x00, @@ -33708,15 +33605,15 @@ unsigned char matmul_q4_1_f32_data[] = { 0x04,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x3a,0x01,0x00,0x00, -0x39,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x39,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5b,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0x5b,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x5d,0x01,0x00,0x00,0x00,0x01,0x00,0x00, @@ -33724,7 +33621,7 @@ unsigned char matmul_q4_1_f32_data[] = { 0x04,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0x5e,0x01,0x00,0x00,0x5f,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x63,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x1d,0x00,0x03,0x00,0x67,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x1e,0x00,0x03,0x00,0x68,0x01,0x00,0x00,0x67,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x69,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -33732,27 +33629,27 @@ unsigned char matmul_q4_1_f32_data[] = { 0x6a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x75,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7e,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x00,0x01,0x00,0x00,0x82,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x84,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x3a,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x85,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x84,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x86,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x85,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 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+0xba,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xc0,0x01,0x00,0x00, 0x07,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xd6,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, @@ -33761,20 +33658,20 @@ unsigned char matmul_q4_1_f32_data[] = { 0xd7,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xe1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xe9,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x18,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0x4d,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0x55,0x02,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x9b,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, 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+0x9b,0x02,0x00,0x00,0x3b,0x00,0x04,0x00,0x9c,0x02,0x00,0x00, +0x9d,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x15,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0x05,0x00,0x00,0x00, +0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00, 0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc8,0x00,0x00,0x00, @@ -33784,175 +33681,175 @@ unsigned char matmul_q4_1_f32_data[] = { 0x07,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00, 0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00, -0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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+33930,173 @@ unsigned char matmul_q4_1_f32_data[] = { 0x3e,0x00,0x03,0x00,0x79,0x01,0x00,0x00,0x78,0x01,0x00,0x00, 0xf9,0x00,0x02,0x00,0x5a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x7a,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x7d,0x01,0x00,0x00,0x7d,0x00,0x00,0x00,0xd6,0x02,0x00,0x00, +0x7d,0x01,0x00,0x00,0x7e,0x00,0x00,0x00,0xd5,0x02,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, 0x7d,0x01,0x00,0x00,0x7e,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00,0x7f,0x01,0x00,0x00, -0x78,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x31,0x01,0x00,0x00, +0x79,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x31,0x01,0x00,0x00, 0x83,0x01,0x00,0x00,0x5f,0x01,0x00,0x00,0x81,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0x83,0x01,0x00,0x00,0x82,0x01,0x00,0x00, 0xf9,0x00,0x02,0x00,0x5a,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x5a,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x44,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x44,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 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matmul_q4_1_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x19,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x18,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -34388,47 +34285,47 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x08,0x01,0x00,0x00,0x2d,0x01,0x00,0x00, -0x62,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x78,0x02,0x00,0x00, -0xc1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, 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-0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -34572,9 +34469,9 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, 0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfe,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00, @@ -34593,9 +34490,9 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x02,0x01,0x00,0x00,0x17,0x00,0x04,0x00,0x1a,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x2b,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x2a,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x2c,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x2b,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x2c,0x01,0x00,0x00, @@ -34603,18 +34500,18 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 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-0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x59,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x5e,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x5f,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00, 0x5e,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x60,0x01,0x00,0x00, 0x01,0x01,0x00,0x00,0x5f,0x01,0x00,0x00,0x20,0x00,0x04,0x00, @@ -34639,21 +34536,21 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x06,0x00,0x00,0x00,0xa7,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x3b,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa8,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0xa7,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xa7,0x01,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa9,0x01,0x00,0x00,0x86,0x00,0x00,0x00, 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+0x35,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x75,0x01,0x00,0x00,0x74,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x76,0x01,0x00,0x00, 0x75,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x32,0x01,0x00,0x00, @@ -34928,7 +34825,7 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x79,0x01,0x00,0x00, 0x5d,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x6c,0x01,0x00,0x00,0x7b,0x01,0x00,0x00,0x6a,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x7c,0x01,0x00,0x00,0x7b,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0x7d,0x01,0x00,0x00,0x7c,0x01,0x00,0x00, @@ -34937,8 +34834,8 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x7e,0x01,0x00,0x00,0x7d,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00,0x5d,0x01,0x00,0x00, 0x80,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x6c,0x01,0x00,0x00, -0x83,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x54,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x80,0x01,0x00,0x00, +0x83,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x54,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x80,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x84,0x01,0x00,0x00, 0x83,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, 0x85,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -34947,8 +34844,8 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x85,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x89,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x88,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x6c,0x01,0x00,0x00,0x8b,0x01,0x00,0x00, -0x6a,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x54,0x01,0x00,0x00, -0xd0,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x6a,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x54,0x01,0x00,0x00, +0xd0,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x8c,0x01,0x00,0x00,0x8b,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x8d,0x01,0x00,0x00, 0x8c,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x32,0x01,0x00,0x00, @@ -34957,8 +34854,8 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x91,0x01,0x00,0x00, 0x5d,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x6c,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x6a,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x94,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x94,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x32,0x01,0x00,0x00,0x96,0x01,0x00,0x00, @@ -34966,7 +34863,7 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x96,0x01,0x00,0x00,0x95,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x99,0x01,0x00,0x00,0x5d,0x01,0x00,0x00, 0x98,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x6c,0x01,0x00,0x00, -0x9b,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x9b,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x54,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x9c,0x01,0x00,0x00, 0x9b,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, @@ -34976,7 +34873,7 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0x9d,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xa1,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0xa0,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x6c,0x01,0x00,0x00,0xa3,0x01,0x00,0x00, -0x6a,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x54,0x01,0x00,0x00, +0x6a,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x54,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0x80,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0xa3,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0xa5,0x01,0x00,0x00, @@ -34984,162 +34881,162 @@ unsigned char matmul_q4_1_f32_aligned_data[] = { 0xa6,0x01,0x00,0x00,0x62,0x01,0x00,0x00,0xa1,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0xa6,0x01,0x00,0x00,0xa5,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xab,0x01,0x00,0x00, -0xf9,0x02,0x00,0x00,0xa9,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xf8,0x02,0x00,0x00,0xa9,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0x42,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x44,0x01,0x00,0x00, 0xe0,0x00,0x04,0x00,0x0c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0xac,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xaf,0x01,0x00,0x00,0xfc,0x02,0x00,0x00,0xad,0x01,0x00,0x00, +0xaf,0x01,0x00,0x00,0xfb,0x02,0x00,0x00,0xad,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x01,0x00,0x00, -0x00,0x03,0x00,0x00,0xb0,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xff,0x02,0x00,0x00,0xb0,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xb4,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xb4,0x01,0x00,0x00, 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+35295,15 @@ unsigned char matmul_q4_1_f32_aligned_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x67,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x67,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x4e,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x94,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0x4d,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x93,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0x95,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0x95,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0x94,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0x94,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0x95,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x97,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 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-0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -35508,10 +35405,10 @@ unsigned char matmul_q4_1_f32_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -35529,9 +35426,9 @@ unsigned char matmul_q4_1_f32_aligned_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x17,0x00,0x04,0x00, 0x1a,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x29,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x29,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x2b,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0x2a,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x2c,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x2b,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -35540,17 +35437,17 @@ unsigned char matmul_q4_1_f32_aligned_fp32_data[] = { 0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x38,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x39,0x01,0x00,0x00,0x38,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x39,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x3a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x3b,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3b,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x5e,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x5d,0x01,0x00,0x00, @@ -35569,21 +35466,21 @@ unsigned char matmul_q4_1_f32_aligned_fp32_data[] = { 0x80,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x39,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x81,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x80,0x01,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x82,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x81,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x85,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 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+36173,15 @@ unsigned char matmul_q4_1_f32_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x68,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x68,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x4e,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x94,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0x4d,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x93,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0x95,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0x95,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0x94,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0x94,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0x95,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x97,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 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0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00, @@ -36406,9 +36303,9 @@ unsigned char matmul_q4_1_f32_fp32_data[] = { 0x01,0x01,0x00,0x00,0x17,0x00,0x04,0x00,0x19,0x01,0x00,0x00, 0xc3,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x2a,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x29,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x2b,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x2a,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x2b,0x01,0x00,0x00, @@ -36416,50 +36313,50 @@ unsigned char matmul_q4_1_f32_fp32_data[] = { 0x30,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x37,0x01,0x00,0x00, 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+36364,20 @@ unsigned char matmul_q4_1_f32_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xdc,0x01,0x00,0x00, 0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe4,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x13,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x46,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x45,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0x4e,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0x94,0x02,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, -0x95,0x02,0x00,0x00,0x94,0x02,0x00,0x00,0x20,0x00,0x04,0x00, -0x96,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x95,0x02,0x00,0x00, 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matmul_q4_k_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x8e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x8d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -37088,47 +36985,47 @@ unsigned char matmul_q4_k_f32_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 0x21,0x01,0x00,0x00,0x78,0x01,0x00,0x00,0xc6,0x01,0x00,0x00, -0xd1,0x01,0x00,0x00,0xbc,0x02,0x00,0x00,0x05,0x03,0x00,0x00, +0xd1,0x01,0x00,0x00,0xbb,0x02,0x00,0x00,0x04,0x03,0x00,0x00, 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+0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x4f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x53,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x60,0x00,0x00,0x00, +0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x62,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -37160,15 +37057,15 @@ unsigned char matmul_q4_k_f32_data[] = { 0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xbc,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x02,0x03,0x00,0x00,0x06,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x03,0x03,0x00,0x00, +0xbb,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x01,0x03,0x00,0x00,0x06,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x02,0x03,0x00,0x00, 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00, -0x03,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x03,0x03,0x00,0x00, -0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x05,0x03,0x00,0x00, +0x02,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x02,0x03,0x00,0x00, +0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x04,0x03,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x05,0x03,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00, +0x04,0x03,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00, 0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00, @@ -37179,77 +37076,77 @@ unsigned char matmul_q4_k_f32_data[] = { 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00, -0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 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0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -37258,7 +37155,7 @@ unsigned char matmul_q4_k_f32_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -37268,10 +37165,10 @@ unsigned char matmul_q4_k_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x80,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -37295,14 +37192,14 @@ unsigned char matmul_q4_k_f32_data[] = { 0x18,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x28,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x30,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x19,0x01,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x35,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x35,0x01,0x00,0x00, 0x3f,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x37,0x01,0x00,0x00, 0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x74,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x75,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x74,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x74,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x76,0x01,0x00,0x00,0x17,0x01,0x00,0x00, 0x75,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x77,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x76,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -37311,15 +37208,15 @@ unsigned char matmul_q4_k_f32_data[] = { 0x17,0x01,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xa0,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0xa0,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0xa1,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa2,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xa3,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xa3,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0xc4,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0xc3,0x01,0x00,0x00, @@ -37327,7 +37224,7 @@ unsigned char matmul_q4_k_f32_data[] = { 0xc4,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0xc5,0x01,0x00,0x00, 0xc6,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xca,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0xce,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0xcf,0x01,0x00,0x00,0xce,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0xd0,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xcf,0x01,0x00,0x00, @@ -37335,26 +37232,26 @@ unsigned char matmul_q4_k_f32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xdc,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x17,0x01,0x00,0x00,0xe9,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xeb,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xec,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xeb,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xeb,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xed,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xec,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xec,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf0,0x01,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0xf1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x0f,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x10,0x02,0x00,0x00, +0xf4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x0f,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x10,0x02,0x00,0x00, 0x17,0x01,0x00,0x00,0x0f,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 0x11,0x02,0x00,0x00,0x07,0x00,0x00,0x00,0x10,0x02,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x21,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x27,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x17,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x3d,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, @@ -37364,20 +37261,20 @@ unsigned char matmul_q4_k_f32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x48,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x50,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7f,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xb4,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xb3,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0xbc,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0x02,0x03,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, -0x03,0x03,0x00,0x00,0x02,0x03,0x00,0x00,0x20,0x00,0x04,0x00, -0x04,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x03,0x03,0x00,0x00, -0x3b,0x00,0x04,0x00,0x04,0x03,0x00,0x00,0x05,0x03,0x00,0x00, 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-37387,158 +37284,158 @@ unsigned char matmul_q4_k_f32_data[] = { 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, -0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, -0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00, -0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x89,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x17,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x22,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x21,0x00,0x00,0x00, -0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00, -0x22,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x24,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x23,0x00,0x00,0x00, -0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x28,0x00,0x00,0x00, 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0x06,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x0f,0x01,0x00,0x00, 0x12,0x01,0x00,0x00,0x41,0x00,0x07,0x00,0x23,0x01,0x00,0x00, -0x24,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xfb,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x24,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xfb,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x18,0x01,0x00,0x00,0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x14,0x01,0x00,0x00,0x26,0x01,0x00,0x00, 0x25,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00, @@ -37570,25 +37467,25 @@ unsigned char matmul_q4_k_f32_data[] = { 0xfa,0x00,0x04,0x00,0x29,0x01,0x00,0x00,0x2a,0x01,0x00,0x00, 0x45,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x2a,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x30,0x01,0x00,0x00,0x31,0x01,0x00,0x00, -0x21,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, +0x21,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 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+0x27,0x03,0x00,0x00,0x2c,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0xc1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xc3,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_k_f32_len = 12072; unsigned char matmul_q4_k_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xa8,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xa7,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -38099,47 +37996,47 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, 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+0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -38174,15 +38071,15 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xd1,0x01,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xde,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x24,0x03,0x00,0x00,0x06,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x25,0x03,0x00,0x00, +0xdd,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x23,0x03,0x00,0x00,0x06,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x24,0x03,0x00,0x00, 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00, -0x25,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, 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0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -38284,9 +38181,9 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x02,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -38310,14 +38207,14 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x0c,0x00,0x00,0x00,0x19,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x31,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x1a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x1a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x36,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x38,0x01,0x00,0x00,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x4e,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x4e,0x01,0x00,0x00, 0x0f,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x75,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x76,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x75,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x76,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x75,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x77,0x01,0x00,0x00, 0x18,0x01,0x00,0x00,0x76,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x78,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x77,0x01,0x00,0x00, @@ -38326,17 +38223,17 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x04,0x00,0x00,0x00,0x18,0x01,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0xa2,0x01,0x00,0x00, -0xa1,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0xa1,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xc5,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xc7,0x01,0x00,0x00,0x18,0x01,0x00,0x00, @@ -38360,21 +38257,21 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00, 0x51,0x00,0x00,0x00,0xa2,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0e,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x77,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0f,0x02,0x00,0x00, -0x86,0x00,0x00,0x00,0x0e,0x02,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x0e,0x02,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x12,0x02,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x13,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0x13,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x16,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x31,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x32,0x02,0x00,0x00, +0x16,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x31,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x32,0x02,0x00,0x00, 0x18,0x01,0x00,0x00,0x31,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 0x33,0x02,0x00,0x00,0x07,0x00,0x00,0x00,0x32,0x02,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x43,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x49,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x18,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x5f,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -38384,20 +38281,20 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x6a,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x72,0x02,0x00,0x00, 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-0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x36,0x00,0x05,0x00, +0xdd,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x23,0x03,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, +0x24,0x03,0x00,0x00,0x23,0x03,0x00,0x00,0x20,0x00,0x04,0x00, +0x25,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x24,0x03,0x00,0x00, +0x3b,0x00,0x04,0x00,0x25,0x03,0x00,0x00,0x26,0x03,0x00,0x00, +0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, +0x2b,0x03,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x06,0x00,0x00,0x00,0x38,0x03,0x00,0x00,0x84,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x36,0x00,0x05,0x00, 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00, 0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0xca,0x00,0x00,0x00, @@ -38407,158 +38304,158 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 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-0x25,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xfc,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x25,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xfc,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x19,0x01,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x15,0x01,0x00,0x00,0x27,0x01,0x00,0x00, 0x26,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00, @@ -38590,25 +38487,25 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0xfa,0x00,0x04,0x00,0x2a,0x01,0x00,0x00,0x2b,0x01,0x00,0x00, 0x46,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x2b,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x31,0x01,0x00,0x00,0x32,0x01,0x00,0x00, -0x22,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, +0x22,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0x1a,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, 0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x34,0x01,0x00,0x00, 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-0x7c,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x42,0x01,0x00,0x00, -0x41,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x13,0x00,0x00,0x00, +0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x42,0x01,0x00,0x00, +0x41,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x15,0x00,0x00,0x00, 0x43,0x01,0x00,0x00,0x42,0x01,0x00,0x00,0x36,0x01,0x00,0x00, 0x72,0x00,0x04,0x00,0x38,0x01,0x00,0x00,0x44,0x01,0x00,0x00, 0x43,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x1a,0x01,0x00,0x00, @@ -38617,26 +38514,26 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00, 0x0d,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x31,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x22,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x49,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x1a,0x01,0x00,0x00, 0x4b,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, 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-0xc4,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x41,0x00,0x08,0x00, +0xc4,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0xd3,0x01,0x00,0x00,0xdb,0x01,0x00,0x00,0xd1,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xbb,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xbb,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xdc,0x01,0x00,0x00,0xdb,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x18,0x01,0x00,0x00,0xdd,0x01,0x00,0x00,0xdc,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x8b,0x01,0x00,0x00,0xde,0x01,0x00,0x00, @@ -38756,8 +38653,8 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0xde,0x01,0x00,0x00,0xdd,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,0xc4,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0xd3,0x01,0x00,0x00, -0xe2,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xbb,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0xe2,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xbb,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xe3,0x01,0x00,0x00, 0xe2,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0xe4,0x01,0x00,0x00,0xe3,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -38766,8 +38663,8 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0xe4,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xe8,0x01,0x00,0x00,0xc4,0x01,0x00,0x00,0xe7,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0xd3,0x01,0x00,0x00,0xea,0x01,0x00,0x00, -0xd1,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, +0xd1,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xeb,0x01,0x00,0x00,0xea,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0xec,0x01,0x00,0x00, 0xeb,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x8b,0x01,0x00,0x00, @@ -38776,8 +38673,8 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xef,0x01,0x00,0x00, 0xc4,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0xd3,0x01,0x00,0x00,0xf1,0x01,0x00,0x00,0xd1,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xbb,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xbb,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xf2,0x01,0x00,0x00,0xf1,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x18,0x01,0x00,0x00,0xf3,0x01,0x00,0x00,0xf2,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x8b,0x01,0x00,0x00,0xf4,0x01,0x00,0x00, @@ -38785,8 +38682,8 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0xf4,0x01,0x00,0x00,0xf3,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xf7,0x01,0x00,0x00,0xc4,0x01,0x00,0x00, 0xf6,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0xd3,0x01,0x00,0x00, -0xf9,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xbb,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0xf9,0x01,0x00,0x00,0xd1,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xbb,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xfa,0x01,0x00,0x00, 0xf9,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0xfb,0x01,0x00,0x00,0xfa,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -38795,7 +38692,7 @@ unsigned char matmul_q4_k_f32_aligned_data[] = { 0xfb,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xff,0x01,0x00,0x00,0xc4,0x01,0x00,0x00,0xfe,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0xd3,0x01,0x00,0x00,0x01,0x02,0x00,0x00, -0xd1,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, +0xd1,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x02,0x02,0x00,0x00,0x01,0x02,0x00,0x00, 0x73,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x03,0x02,0x00,0x00, @@ 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+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x03,0x03,0x00,0x00, +0xf8,0x00,0x02,0x00,0x05,0x03,0x00,0x00,0xf9,0x00,0x02,0x00, +0xee,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xee,0x02,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x47,0x03,0x00,0x00, +0x4f,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xeb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xed,0x02,0x00,0x00, +0xf9,0x00,0x02,0x00,0xe6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xe6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x49,0x03,0x00,0x00,0x4e,0x03,0x00,0x00,0xd0,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0xe3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xe5,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_k_f32_aligned_len = 12648; unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x7e,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x7d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -39157,47 +39054,47 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x78,0x01,0x00,0x00, -0xc6,0x01,0x00,0x00,0xcd,0x01,0x00,0x00,0xb4,0x02,0x00,0x00, -0xfd,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x78,0x01,0x00,0x00, +0xc6,0x01,0x00,0x00,0xcd,0x01,0x00,0x00,0xb3,0x02,0x00,0x00, +0xfc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 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-0x47,0x00,0x04,0x00,0x4f,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x53,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x60,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x62,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00, @@ -39229,15 +39126,15 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xcd,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xcd,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xb4,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xfa,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0xb3,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xf9,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0xfb,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0xfb,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0xfa,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0xfa,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0xfb,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xfd,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xfd,0x02,0x00,0x00,0x21,0x00,0x00,0x00, +0xfa,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, +0xfc,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0xfc,0x02,0x00,0x00,0x21,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00, 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -39248,78 +39145,78 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 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-0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -39339,10 +39236,10 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x20,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x07,0x01,0x00,0x00, @@ -39364,14 +39261,14 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x22,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x24,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x19,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x30,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x1a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x1a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x35,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x37,0x01,0x00,0x00,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, 0x0f,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x74,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x75,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x74,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x75,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x74,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x76,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x75,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x77,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x76,0x01,0x00,0x00, @@ -39380,17 +39277,17 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, -0x9e,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x9e,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa0,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa1,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa2,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbd,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc2,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xc2,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xc4,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, @@ -39409,21 +39306,21 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0xe6,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x9f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0xe6,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xe6,0x01,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe8,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xe7,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0xe7,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xeb,0x01,0x00,0x00,0x08,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xec,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xef,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0a,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0x0b,0x02,0x00,0x00,0xc4,0x00,0x00,0x00, 0x0a,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0x0c,0x02,0x00,0x00, 0x07,0x00,0x00,0x00,0x0b,0x02,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x1c,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x37,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0x38,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x37,0x02,0x00,0x00, @@ -39431,20 +39328,20 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x38,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x42,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x4a,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, 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+0x63,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, +0xab,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, +0x0a,0x00,0x00,0x00,0xb3,0x02,0x00,0x00,0x01,0x00,0x00,0x00, +0x1d,0x00,0x03,0x00,0xf9,0x02,0x00,0x00,0xc4,0x00,0x00,0x00, +0x1e,0x00,0x03,0x00,0xfa,0x02,0x00,0x00,0xf9,0x02,0x00,0x00, +0x20,0x00,0x04,0x00,0xfb,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, +0xfa,0x02,0x00,0x00,0x3b,0x00,0x04,0x00,0xfb,0x02,0x00,0x00, +0xfc,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x15,0x00,0x00,0x00,0x01,0x03,0x00,0x00,0x05,0x00,0x00,0x00, +0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0e,0x03,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00, 0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00, @@ -39454,159 +39351,159 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 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{ 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00, 0x10,0x01,0x00,0x00,0x13,0x01,0x00,0x00,0x41,0x00,0x07,0x00, 0x24,0x01,0x00,0x00,0x25,0x01,0x00,0x00,0x22,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x35,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0x26,0x01,0x00,0x00, 0x25,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x15,0x01,0x00,0x00, 0x27,0x01,0x00,0x00,0x26,0x01,0x00,0x00,0xb0,0x00,0x05,0x00, 0xc2,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x0d,0x01,0x00,0x00, -0x77,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2b,0x01,0x00,0x00, +0x78,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2b,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x29,0x01,0x00,0x00, 0x2a,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x2a,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x30,0x01,0x00,0x00, -0x31,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x31,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 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+39588,106 @@ unsigned char matmul_q4_k_f32_aligned_fp32_data[] = { 0x5f,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0xc2,0x00,0x05,0x00, 0x1a,0x01,0x00,0x00,0x60,0x01,0x00,0x00,0x5f,0x01,0x00,0x00, 0xa9,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0x30,0x01,0x00,0x00, -0x63,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x63,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0xfc,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x0d,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0x1a,0x01,0x00,0x00,0x64,0x01,0x00,0x00, 0x63,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x1a,0x01,0x00,0x00, -0x65,0x01,0x00,0x00,0x64,0x01,0x00,0x00,0x81,0x00,0x00,0x00, +0x65,0x01,0x00,0x00,0x64,0x01,0x00,0x00,0x82,0x00,0x00,0x00, 0xc4,0x00,0x05,0x00,0x1a,0x01,0x00,0x00,0x66,0x01,0x00,0x00, 0x65,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,0xc5,0x00,0x05,0x00, 0x1a,0x01,0x00,0x00,0x67,0x01,0x00,0x00,0x60,0x01,0x00,0x00, 0x66,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x2b,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x2b,0x01,0x00,0x00,0xf5,0x00,0x07,0x00, 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+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc1,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0xc3,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, +0xbc,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbc,0x02,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x03,0x00,0x00, +0x24,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xb9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xbb,0x02,0x00,0x00, 0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_k_f32_aligned_fp32_len = 11900; unsigned char matmul_q4_k_f32_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x87,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x86,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -40153,47 +40050,47 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 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0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -40244,77 +40141,77 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x11,0x00,0x00,0x00, -0x09,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x11,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00, -0x15,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x20,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, 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+0xbc,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 0xb9,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -40323,8 +40220,8 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0xbf,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -40334,9 +40231,9 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -40360,14 +40257,14 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x18,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x30,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x19,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x19,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x35,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x15,0x00,0x04,0x00, 0x37,0x01,0x00,0x00,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, 0x0f,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x74,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x75,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x74,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x75,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x74,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x76,0x01,0x00,0x00, 0xc3,0x00,0x00,0x00,0x75,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x77,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x76,0x01,0x00,0x00, @@ -40376,15 +40273,15 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x9e,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, -0x9e,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x9e,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa0,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa1,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa2,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xa1,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc1,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0xc0,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xc2,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -40392,7 +40289,7 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0xc3,0x01,0x00,0x00,0xc4,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc8,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x1d,0x00,0x03,0x00,0xcc,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x1e,0x00,0x03,0x00,0xcd,0x01,0x00,0x00,0xcc,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0xce,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -40400,25 +40297,25 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0xcf,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xda,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe2,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe8,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe9,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xe8,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xe8,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xec,0x01,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xed,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0xed,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf0,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x0b,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x0c,0x02,0x00,0x00, +0xf0,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x0b,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x0c,0x02,0x00,0x00, 0xc3,0x00,0x00,0x00,0x0b,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x02,0x00,0x00,0x07,0x00,0x00,0x00,0x0c,0x02,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x1d,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x38,0x02,0x00,0x00, 0x84,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0x39,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -40427,20 +40324,20 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x06,0x00,0x00,0x00,0x43,0x02,0x00,0x00,0x86,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7a,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xad,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, -0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0xb5,0x02,0x00,0x00, -0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xfb,0x02,0x00,0x00, -0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xfc,0x02,0x00,0x00, -0xfb,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0xfd,0x02,0x00,0x00, -0x0c,0x00,0x00,0x00,0xfc,0x02,0x00,0x00,0x3b,0x00,0x04,0x00, -0xfd,0x02,0x00,0x00,0xfe,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x03,0x03,0x00,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x15,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, +0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0xb4,0x02,0x00,0x00, +0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xfa,0x02,0x00,0x00, +0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xfb,0x02,0x00,0x00, +0xfa,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0xfc,0x02,0x00,0x00, +0x0c,0x00,0x00,0x00,0xfb,0x02,0x00,0x00,0x3b,0x00,0x04,0x00, +0xfc,0x02,0x00,0x00,0xfd,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x02,0x03,0x00,0x00, 0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x10,0x03,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00, +0x0f,0x03,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00, 0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, 0xc8,0x00,0x00,0x00,0xc9,0x00,0x00,0x00,0x07,0x00,0x00,0x00, @@ -40450,158 +40347,158 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 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0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x13,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x12,0x01,0x00,0x00, 0x41,0x00,0x07,0x00,0x23,0x01,0x00,0x00,0x24,0x01,0x00,0x00, -0x21,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, -0x34,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00, +0x21,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x14,0x01,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x29,0x01,0x00,0x00, @@ -40633,25 +40530,25 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0x29,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x45,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x2a,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x30,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x21,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 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0x3d,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0x3f,0x01,0x00,0x00, 0x3e,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x40,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x7c,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x40,0x01,0x00,0x00, -0xc7,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x42,0x01,0x00,0x00, +0x15,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x40,0x01,0x00,0x00, +0xc7,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x42,0x01,0x00,0x00, 0x41,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0x72,0x00,0x04,0x00, 0x37,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x42,0x01,0x00,0x00, 0x7c,0x00,0x04,0x00,0x19,0x01,0x00,0x00,0x44,0x01,0x00,0x00, @@ -40659,26 +40556,26 @@ unsigned char matmul_q4_k_f32_fp32_data[] = { 0xf8,0x00,0x02,0x00,0x45,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x0c,0x01,0x00,0x00, 0x28,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x30,0x01,0x00,0x00, -0x49,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x49,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 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+0xf8,0x00,0x02,0x00,0xdd,0x02,0x00,0x00,0x80,0x00,0x05,0x00, +0x06,0x00,0x00,0x00,0x1c,0x03,0x00,0x00,0x28,0x03,0x00,0x00, +0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xda,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0xdc,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, +0xc5,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc5,0x02,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x03,0x00,0x00, +0x26,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0xc2,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xc4,0x02,0x00,0x00, +0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xbd,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x20,0x03,0x00,0x00,0x25,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0xba,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xbc,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q4_k_f32_fp32_len = 11952; unsigned char matmul_q5_0_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x47,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x46,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -41154,47 +41051,47 @@ unsigned char matmul_q5_0_f32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x50,0x01,0x00,0x00, -0x83,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x79,0x02,0x00,0x00, -0xc2,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x50,0x01,0x00,0x00, +0x83,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x78,0x02,0x00,0x00, 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+41123,15 @@ unsigned char matmul_q5_0_f32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8e,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x8e,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x79,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbf,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0x78,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbe,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0xc0,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0xc0,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0xbf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0xbf,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0xc0,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xc2,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xc2,0x02,0x00,0x00,0x21,0x00,0x00,0x00, +0xbf,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, +0xc1,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0xc1,0x02,0x00,0x00,0x21,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00, 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -41245,77 +41142,77 @@ unsigned char matmul_q5_0_f32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 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+0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -41335,9 +41232,9 @@ unsigned char matmul_q5_0_f32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00, 0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00, @@ -41356,7 +41253,7 @@ unsigned char matmul_q5_0_f32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0b,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x11,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x01,0x01,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x15,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x15,0x01,0x00,0x00, 0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x27,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x30,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x03,0x01,0x00,0x00, @@ -41364,9 +41261,9 @@ unsigned char matmul_q5_0_f32_data[] = { 0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0x47,0x01,0x00,0x00,0x00,0x00,0x80,0x41,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x4e,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x4d,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x4e,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x4f,0x01,0x00,0x00, @@ -41374,51 +41271,51 @@ unsigned char matmul_q5_0_f32_data[] = { 0x55,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x01,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00, 0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00, -0x5e,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x39,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x5e,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x5f,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x5e,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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0x1c,0x00,0x04,0x00,0xcd,0x01,0x00,0x00,0x00,0x01,0x00,0x00, 0xcc,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xce,0x01,0x00,0x00, 0x07,0x00,0x00,0x00,0xcd,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xde,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x20,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xe4,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0x00,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfa,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, @@ -41428,21 +41325,21 @@ unsigned char matmul_q5_0_f32_data[] = { 0x06,0x00,0x00,0x00,0x05,0x02,0x00,0x00,0x86,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x3c,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 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0x01,0x01,0x00,0x00,0x19,0x01,0x00,0x00,0x18,0x01,0x00,0x00, 0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1a,0x01,0x00,0x00, 0x19,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00, @@ -41632,16 +41529,16 @@ unsigned char matmul_q5_0_f32_data[] = { 0x06,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x21,0x01,0x00,0x00, 0xa8,0x00,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0xf9,0x00,0x00,0x00, -0x7c,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x24,0x01,0x00,0x00, +0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x24,0x01,0x00,0x00, 0x23,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x28,0x01,0x00,0x00,0xfe,0x00,0x00,0x00,0x27,0x01,0x00,0x00, 0xc2,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00, 0x1b,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0xc7,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,0x29,0x01,0x00,0x00, -0xf9,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xf9,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x2b,0x01,0x00,0x00,0x2a,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x30,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x09,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x85,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 0xfe,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x03,0x01,0x00,0x00, 0x32,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, @@ -41660,7 +41557,7 @@ unsigned char matmul_q5_0_f32_data[] = { 0x50,0x00,0x05,0x00,0x34,0x01,0x00,0x00,0x46,0x01,0x00,0x00, 0x3e,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x83,0x00,0x05,0x00, 0x34,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x46,0x01,0x00,0x00, -0x46,0x03,0x00,0x00,0x8e,0x00,0x05,0x00,0x34,0x01,0x00,0x00, +0x45,0x03,0x00,0x00,0x8e,0x00,0x05,0x00,0x34,0x01,0x00,0x00, 0x4b,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x0e,0x01,0x00,0x00, 0x51,0x00,0x05,0x00,0xc3,0x00,0x00,0x00,0x53,0x01,0x00,0x00, 0x4b,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x73,0x00,0x04,0x00, @@ -41676,31 +41573,31 @@ unsigned char matmul_q5_0_f32_data[] = { 0x5c,0x01,0x00,0x00,0x50,0x01,0x00,0x00,0x58,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x63,0x01,0x00,0x00, -0xfb,0x02,0x00,0x00,0x61,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xfa,0x02,0x00,0x00,0x61,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x65,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x65,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xfc,0x02,0x00,0x00,0x3e,0x00,0x00,0x00,0xde,0x00,0x00,0x00, +0xfb,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0xde,0x00,0x00,0x00, 0xac,0x01,0x00,0x00,0x68,0x01,0x00,0x00,0xb0,0x00,0x05,0x00, -0xc1,0x00,0x00,0x00,0x6b,0x01,0x00,0x00,0xfc,0x02,0x00,0x00, +0xc1,0x00,0x00,0x00,0x6b,0x01,0x00,0x00,0xfb,0x02,0x00,0x00, 0xa6,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x67,0x01,0x00,0x00, 0x68,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00, 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0xf8,0x00,0x02,0x00,0x75,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x79,0x01,0x00,0x00,0xeb,0x02,0x00,0x00, -0x78,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00, -0x7b,0x01,0x00,0x00,0x79,0x01,0x00,0x00,0x8d,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x79,0x01,0x00,0x00,0xea,0x02,0x00,0x00, +0x79,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00, +0x7b,0x01,0x00,0x00,0x79,0x01,0x00,0x00,0x8e,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x76,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x76,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00, 0x7c,0x01,0x00,0x00,0x74,0x01,0x00,0x00,0x66,0x01,0x00,0x00, @@ -41708,18 +41605,18 @@ unsigned char matmul_q5_0_f32_data[] = { 0x7e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00, 0x7c,0x01,0x00,0x00,0x7d,0x01,0x00,0x00,0x9e,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x7d,0x01,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x86,0x01,0x00,0x00,0x7d,0x00,0x00,0x00, -0xfc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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+0xf9,0x00,0x02,0x00,0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x80,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q5_0_f32_len = 11076; unsigned char matmul_q5_0_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x62,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x61,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -42082,47 +41979,47 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x51,0x01,0x00,0x00, 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+0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00, @@ -42157,15 +42054,15 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8e,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x8e,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x9c,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe2,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0x9b,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe1,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0xe3,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0xe3,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 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0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00, @@ -42257,7 +42154,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -42267,10 +42164,10 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -42288,7 +42185,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x0a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x02,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x02,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x16,0x01,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x31,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -42296,9 +42193,9 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x00,0x00,0x80,0x41, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x4e,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x01,0x01,0x00,0x00, 0x4e,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x50,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x4f,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -42307,17 +42204,17 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x01,0x01,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x5e,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x5e,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x60,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x5f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x61,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x60,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x62,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x61,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x82,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x83,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0x82,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x84,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x83,0x01,0x00,0x00, @@ -42342,21 +42239,21 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xcb,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xcc,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xcb,0x01,0x00,0x00,0x77,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xcb,0x01,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xcd,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xcc,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xcc,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xd0,0x01,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xd1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0xd1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xd4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xef,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xf0,0x01,0x00,0x00, +0xd4,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xef,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xf0,0x01,0x00,0x00, 0x01,0x01,0x00,0x00,0xef,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0xf1,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0xf0,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x01,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x07,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x1d,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -42366,21 +42263,21 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x28,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x30,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5f,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x94,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x93,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0x9c,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 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+0x06,0x00,0x00,0x00,0xf6,0x02,0x00,0x00,0x84,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x2c,0x00,0x05,0x00, +0x35,0x01,0x00,0x00,0x60,0x03,0x00,0x00,0x48,0x01,0x00,0x00, 0x48,0x01,0x00,0x00,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00, 0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -42391,176 +42288,176 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00, -0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x14,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00, -0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x86,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x17,0x00,0x00,0x00,0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00, 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0x04,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, 0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x34,0x01,0x00,0x00, 0x33,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00, @@ -42598,7 +42495,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x45,0x01,0x00,0x00,0x50,0x00,0x05,0x00,0x35,0x01,0x00,0x00, 0x47,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x46,0x01,0x00,0x00, 0x83,0x00,0x05,0x00,0x35,0x01,0x00,0x00,0x4a,0x01,0x00,0x00, -0x47,0x01,0x00,0x00,0x61,0x03,0x00,0x00,0x8e,0x00,0x05,0x00, +0x47,0x01,0x00,0x00,0x60,0x03,0x00,0x00,0x8e,0x00,0x05,0x00, 0x35,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,0x4a,0x01,0x00,0x00, 0x0f,0x01,0x00,0x00,0x51,0x00,0x05,0x00,0xc4,0x00,0x00,0x00, 0x54,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,0x00,0x00,0x00,0x00, @@ -42614,43 +42511,43 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x56,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x51,0x01,0x00,0x00, 0x59,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x5d,0x01,0x00,0x00, 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-0x34,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x8e,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x78,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x99,0x01,0x00,0x00,0x98,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x9a,0x01,0x00,0x00, 0x99,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x56,0x01,0x00,0x00, @@ -42659,7 +42556,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9d,0x01,0x00,0x00, 0x81,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x90,0x01,0x00,0x00,0x9f,0x01,0x00,0x00,0x8e,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x78,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x78,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xa0,0x01,0x00,0x00,0x9f,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0xa1,0x01,0x00,0x00,0xa0,0x01,0x00,0x00, @@ -42668,8 +42565,8 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xa2,0x01,0x00,0x00,0xa1,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00,0x81,0x01,0x00,0x00, 0xa4,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x90,0x01,0x00,0x00, -0xa7,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x78,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, +0xa7,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x78,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xa8,0x01,0x00,0x00, 0xa7,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, 0xa9,0x01,0x00,0x00,0xa8,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -42678,8 +42575,8 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xa9,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xad,0x01,0x00,0x00,0x81,0x01,0x00,0x00,0xac,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x90,0x01,0x00,0x00,0xaf,0x01,0x00,0x00, -0x8e,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x78,0x01,0x00,0x00, -0xd0,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x8e,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x78,0x01,0x00,0x00, +0xd0,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xb0,0x01,0x00,0x00,0xaf,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0xb1,0x01,0x00,0x00, 0xb0,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x56,0x01,0x00,0x00, @@ -42688,8 +42585,8 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb5,0x01,0x00,0x00, 0x81,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x90,0x01,0x00,0x00,0xb7,0x01,0x00,0x00,0x8e,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x78,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x78,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xb8,0x01,0x00,0x00,0xb7,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0xb8,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x56,0x01,0x00,0x00,0xba,0x01,0x00,0x00, @@ -42697,7 +42594,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xba,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xbd,0x01,0x00,0x00,0x81,0x01,0x00,0x00, 0xbc,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x90,0x01,0x00,0x00, -0xbf,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0xbf,0x01,0x00,0x00,0x8e,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x78,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xc0,0x01,0x00,0x00, 0xbf,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, @@ -42707,7 +42604,7 @@ unsigned char matmul_q5_0_f32_aligned_data[] = { 0xc1,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xc5,0x01,0x00,0x00,0x81,0x01,0x00,0x00,0xc4,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x90,0x01,0x00,0x00,0xc7,0x01,0x00,0x00, -0x8e,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x78,0x01,0x00,0x00, +0x8e,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x78,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 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11668; unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x38,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x37,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00, 0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00, 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64, 0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00, 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00, 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e, -0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00, -0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,0x0a,0x01,0x00,0x00, +0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00, +0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x0a,0x01,0x00,0x00, 0x51,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0x8b,0x01,0x00,0x00, -0x72,0x02,0x00,0x00,0xbb,0x02,0x00,0x00,0x10,0x00,0x06,0x00, 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0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00, @@ -43130,15 +43027,15 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x89,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x8b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x8b,0x01,0x00,0x00,0x21,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x72,0x02,0x00,0x00, +0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x71,0x02,0x00,0x00, 0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xb8,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0xb9,0x02,0x00,0x00,0x00,0x00,0x00,0x00, -0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xb9,0x02,0x00,0x00, +0xb7,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x48,0x00,0x04,0x00,0xb8,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xb8,0x02,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 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+0x84,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0xbc,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xba,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc0,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, @@ -43230,7 +43127,7 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0xbc,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00, @@ -43240,10 +43137,10 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x07,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00, @@ -43262,16 +43159,16 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x20,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x12,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x10,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x31,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x17,0x00,0x04,0x00, 0x35,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x48,0x01,0x00,0x00, 0x00,0x00,0x80,0x41,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x4d,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x4e,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x4d,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x4e,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x4d,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x4f,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x50,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x4f,0x01,0x00,0x00, @@ -43280,17 +43177,17 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x5d,0x01,0x00,0x00, -0x5c,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x5c,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5e,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5f,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0x5e,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x60,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7b,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x81,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x80,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x82,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, @@ -43309,21 +43206,21 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x5d,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0xa4,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xa4,0x01,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xa5,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0xa5,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xa9,0x01,0x00,0x00,0x08,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xaa,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xad,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc8,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0xc9,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0xc8,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0xca,0x01,0x00,0x00, 0x07,0x00,0x00,0x00,0xc9,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xda,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf5,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xf6,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0xf5,0x01,0x00,0x00, @@ -43331,21 +43228,21 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0xf6,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x00,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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-0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, -0x34,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x02,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x02,0x01,0x00,0x00, 0x1a,0x01,0x00,0x00,0x19,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,0x1a,0x01,0x00,0x00, 0xc5,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1c,0x01,0x00,0x00, @@ -43536,16 +43433,16 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0xa9,0x00,0x00,0x00, 0xc7,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00, 0x23,0x01,0x00,0x00,0xfa,0x00,0x00,0x00,0x7c,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00, +0x15,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x24,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x29,0x01,0x00,0x00, 0xff,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0xc2,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,0x1c,0x01,0x00,0x00, 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-0x4a,0x01,0x00,0x00,0x47,0x01,0x00,0x00,0x37,0x03,0x00,0x00, +0x4a,0x01,0x00,0x00,0x47,0x01,0x00,0x00,0x36,0x03,0x00,0x00, 0x8e,0x00,0x05,0x00,0x35,0x01,0x00,0x00,0x4c,0x01,0x00,0x00, 0x4a,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x51,0x00,0x05,0x00, 0xc4,0x00,0x00,0x00,0x54,0x01,0x00,0x00,0x4c,0x01,0x00,0x00, @@ -43577,48 +43474,48 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x5b,0x01,0x00,0x00,0x51,0x01,0x00,0x00,0x58,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0x5b,0x01,0x00,0x00,0x5a,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x62,0x01,0x00,0x00, -0xf4,0x02,0x00,0x00,0x60,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xf3,0x02,0x00,0x00,0x60,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x64,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x64,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xf5,0x02,0x00,0x00,0x3e,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, +0xf4,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, 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0xc4,0x00,0x00,0x00,0x43,0x02,0x00,0x00,0x42,0x02,0x00,0x00, @@ -43801,220 +43698,220 @@ unsigned char matmul_q5_0_f32_aligned_fp32_data[] = { 0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x43,0x02,0x00,0x00, 0x49,0x02,0x00,0x00,0x4c,0x02,0x00,0x00,0x3e,0x00,0x03,0x00, 0x4b,0x02,0x00,0x00,0x4d,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x50,0x02,0x00,0x00,0x0c,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0x50,0x02,0x00,0x00,0x0b,0x03,0x00,0x00, 0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x2c,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x2e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0x27,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x27,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00, -0x0a,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x09,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x24,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x26,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x1f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x1f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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0x84,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x60,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x61,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -44144,7 +44041,7 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -44154,10 +44051,10 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x00,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -44175,7 +44072,7 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0x09,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x11,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x01,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x01,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x15,0x01,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x30,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -44183,9 +44080,9 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0xc3,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x00,0x00,0x80,0x41, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x4c,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x4c,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x4d,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x4f,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -44194,15 +44091,15 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x5b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x5b,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x5c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5e,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x5d,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x5e,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x5e,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7e,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x7d,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x7f,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x7e,0x01,0x00,0x00, @@ -44210,7 +44107,7 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0x7f,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x80,0x01,0x00,0x00, 0x81,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x85,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x89,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x8b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x8a,0x01,0x00,0x00, @@ -44218,25 +44115,25 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 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+44141,21 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0xf6,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x00,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb8,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x08,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x37,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0x6a,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0x72,0x02,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0xb8,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, -0x1e,0x00,0x03,0x00,0xb9,0x02,0x00,0x00,0xb8,0x02,0x00,0x00, -0x20,0x00,0x04,0x00,0xba,0x02,0x00,0x00,0x0c,0x00,0x00,0x00, -0xb9,0x02,0x00,0x00,0x3b,0x00,0x04,0x00,0xba,0x02,0x00,0x00, -0xbb,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,0x05,0x00,0x00,0x00, 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0x45,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0x50,0x00,0x05,0x00, 0x34,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0x3e,0x01,0x00,0x00, 0x45,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x34,0x01,0x00,0x00, -0x49,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0x3f,0x03,0x00,0x00, +0x49,0x01,0x00,0x00,0x46,0x01,0x00,0x00,0x3e,0x03,0x00,0x00, 0x8e,0x00,0x05,0x00,0x34,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, 0x49,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,0x51,0x00,0x05,0x00, 0xc3,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, @@ -44490,31 +44387,31 @@ unsigned char matmul_q5_0_f32_fp32_data[] = { 0x5a,0x01,0x00,0x00,0x50,0x01,0x00,0x00,0x57,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0x5a,0x01,0x00,0x00,0x59,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x61,0x01,0x00,0x00, -0xf4,0x02,0x00,0x00,0x5f,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xf3,0x02,0x00,0x00,0x5f,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x63,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 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0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -45063,7 +44960,7 @@ unsigned char matmul_q5_1_f32_data[] = { 0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -45073,10 +44970,10 @@ unsigned char matmul_q5_1_f32_data[] = { 0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0x00,0x01,0x00,0x00,0x10,0x00,0x00,0x00, @@ -45097,9 +44994,9 @@ unsigned char matmul_q5_1_f32_data[] = { 0x0c,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0x17,0x00,0x04,0x00, 0x2f,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x47,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x47,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x47,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x49,0x01,0x00,0x00,0x00,0x01,0x00,0x00, 0x48,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x4a,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x49,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, @@ -45108,15 +45005,15 @@ unsigned char matmul_q5_1_f32_data[] = { 0x00,0x01,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x58,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x58,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x59,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x5a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x5b,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x5b,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x7b,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x7c,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x7b,0x01,0x00,0x00, @@ -45124,7 +45021,7 @@ unsigned char matmul_q5_1_f32_data[] = { 0x7c,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x7d,0x01,0x00,0x00, 0x7e,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x82,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0x86,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0x87,0x01,0x00,0x00,0x86,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x88,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x87,0x01,0x00,0x00, @@ -45132,26 +45029,26 @@ unsigned char matmul_q5_1_f32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x94,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x9d,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x00,0x01,0x00,0x00,0xa1,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa4,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xa4,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xa8,0x01,0x00,0x00, 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+45782,15 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x87,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x89,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x89,0x01,0x00,0x00,0x21,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x02,0x00,0x00, +0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x96,0x02,0x00,0x00, 0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xdd,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, -0x48,0x00,0x04,0x00,0xde,0x02,0x00,0x00,0x00,0x00,0x00,0x00, -0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xde,0x02,0x00,0x00, +0xdc,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, +0x48,0x00,0x04,0x00,0xdd,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xdd,0x02,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x03,0x00,0xde,0x02,0x00,0x00,0x02,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xe0,0x02,0x00,0x00,0x22,0x00,0x00,0x00, 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+0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00, @@ -45995,10 +45892,10 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x07,0x00,0x00,0x00,0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x01,0x01,0x00,0x00, @@ -46019,9 +45916,9 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x2c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x02,0x01,0x00,0x00, 0x17,0x00,0x04,0x00,0x30,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x48,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x49,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x48,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x49,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x48,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x4a,0x01,0x00,0x00, 0x01,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x4b,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x4a,0x01,0x00,0x00, @@ -46030,17 +45927,17 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x04,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x5a,0x01,0x00,0x00, -0x59,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x59,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5b,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5c,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0x5b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x5c,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x78,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7d,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7e,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x7d,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x7f,0x01,0x00,0x00,0x01,0x01,0x00,0x00, @@ -46066,21 +45963,21 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0xc6,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x5a,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x01,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc8,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xc7,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xcb,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xcc,0x01,0x00,0x00,0x86,0x00,0x00,0x00, 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-0x89,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x73,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0x89,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x73,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x94,0x01,0x00,0x00,0x93,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x95,0x01,0x00,0x00, 0x94,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x51,0x01,0x00,0x00, @@ -46377,7 +46274,7 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x98,0x01,0x00,0x00, 0x7c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x8b,0x01,0x00,0x00,0x9a,0x01,0x00,0x00,0x89,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x73,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x73,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x9b,0x01,0x00,0x00,0x9a,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x01,0x01,0x00,0x00,0x9c,0x01,0x00,0x00,0x9b,0x01,0x00,0x00, @@ -46386,8 +46283,8 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0x9d,0x01,0x00,0x00,0x9c,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x7c,0x01,0x00,0x00, 0x9f,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x8b,0x01,0x00,0x00, -0xa2,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0x73,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, +0xa2,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0x73,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, 0xa2,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, 0xa4,0x01,0x00,0x00,0xa3,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -46396,8 +46293,8 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0xa4,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xa8,0x01,0x00,0x00,0x7c,0x01,0x00,0x00,0xa7,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x8b,0x01,0x00,0x00,0xaa,0x01,0x00,0x00, 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0x01,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0xb3,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x51,0x01,0x00,0x00,0xb5,0x01,0x00,0x00, @@ -46415,7 +46312,7 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0xb5,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xb8,0x01,0x00,0x00,0x7c,0x01,0x00,0x00, 0xb7,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x8b,0x01,0x00,0x00, -0xba,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0xba,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x73,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xbb,0x01,0x00,0x00, 0xba,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x01,0x01,0x00,0x00, @@ -46425,7 +46322,7 @@ unsigned char matmul_q5_1_f32_aligned_data[] = { 0xbc,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xc0,0x01,0x00,0x00,0x7c,0x01,0x00,0x00,0xbf,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x8b,0x01,0x00,0x00,0xc2,0x01,0x00,0x00, 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0xc0,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc4,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -46959,9 +46856,9 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, 0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfe,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00, @@ -46983,9 +46880,9 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x02,0x01,0x00,0x00,0x17,0x00,0x04,0x00,0x30,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x37,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, +0x38,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0x4a,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x49,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x4a,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x4b,0x01,0x00,0x00, @@ -46993,18 +46890,18 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x50,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00, 0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00, -0x58,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x39,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x58,0x01,0x00,0x00,0x57,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x59,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x58,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x5a,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x59,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x5b,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x5a,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x76,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x7b,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x76,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x7b,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x7c,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00, 0x7b,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x7d,0x01,0x00,0x00, 0xc4,0x00,0x00,0x00,0x7c,0x01,0x00,0x00,0x20,0x00,0x04,0x00, @@ -47022,21 +46919,21 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 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-0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x97,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x98,0x00,0x00,0x00, 0xff,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x02,0x01,0x00,0x00, 0x2e,0x01,0x00,0x00,0x2d,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x2e,0x01,0x00,0x00, @@ -47285,48 +47182,48 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x56,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,0x53,0x01,0x00,0x00, 0x3e,0x00,0x03,0x00,0x56,0x01,0x00,0x00,0x55,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00, -0xef,0x02,0x00,0x00,0x5b,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, +0xee,0x02,0x00,0x00,0x5b,0x01,0x00,0x00,0xf9,0x00,0x02,0x00, 0xdd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x5f,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x5f,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00, -0xf0,0x02,0x00,0x00,0x3e,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, +0xef,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0xdf,0x00,0x00,0x00, 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0xc4,0x00,0x00,0x00,0x3e,0x02,0x00,0x00,0x3d,0x02,0x00,0x00, @@ -47509,220 +47406,220 @@ unsigned char matmul_q5_1_f32_aligned_fp32_data[] = { 0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x3e,0x02,0x00,0x00, 0x44,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0x3e,0x00,0x03,0x00, 0x46,0x02,0x00,0x00,0x48,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,0x07,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,0x06,0x03,0x00,0x00, 0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x27,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x29,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0x22,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x22,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4d,0x02,0x00,0x00, -0x05,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x04,0x03,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x1f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x21,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x1a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x1a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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+0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -47852,7 +47749,7 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -47862,10 +47759,10 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfd,0x00,0x00,0x00, 0x0f,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x00,0x01,0x00,0x00, @@ -47886,9 +47783,9 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x2b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x17,0x00,0x04,0x00,0x2f,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x47,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x48,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x47,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x48,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x47,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x49,0x01,0x00,0x00, 0xc3,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x4a,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x49,0x01,0x00,0x00, @@ -47897,15 +47794,15 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x04,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x56,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x57,0x01,0x00,0x00, -0x56,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x56,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x58,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x59,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5a,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x59,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x78,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x79,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0x78,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x7a,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -47913,7 +47810,7 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x04,0x00,0x00,0x00,0x7a,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0x7b,0x01,0x00,0x00,0x7c,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x1d,0x00,0x03,0x00,0x84,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x1e,0x00,0x03,0x00,0x85,0x01,0x00,0x00,0x84,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x86,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -47921,25 +47818,25 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x87,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x92,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x9a,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa0,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x9f,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xa1,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xa0,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, 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0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xd5,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf0,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0xf1,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -47948,20 +47845,20 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x06,0x00,0x00,0x00,0xfb,0x01,0x00,0x00,0x86,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x03,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x32,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x65,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, -0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x6d,0x02,0x00,0x00, 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0xc3,0x00,0x00,0x00,0x3e,0x02,0x00,0x00,0x3d,0x02,0x00,0x00, @@ -48417,172 +48314,172 @@ unsigned char matmul_q5_1_f32_fp32_data[] = { 0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x3e,0x02,0x00,0x00, 0x44,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0x3e,0x00,0x03,0x00, 0x46,0x02,0x00,0x00,0x48,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,0x07,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,0x06,0x03,0x00,0x00, 0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x27,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x29,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0x22,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x22,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4d,0x02,0x00,0x00, -0x05,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x04,0x03,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, 0x1f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x21,0x02,0x00,0x00, 0xf9,0x00,0x02,0x00,0x1a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x1a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 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+0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xe2,0x02,0x00,0x00, +0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x92,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, +0x7d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7d,0x02,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd6,0x02,0x00,0x00, +0xe0,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x7a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00, +0xf9,0x00,0x02,0x00,0x75,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x75,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0xd8,0x02,0x00,0x00,0xdf,0x02,0x00,0x00,0xcf,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x74,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q5_1_f32_fp32_len = 10836; unsigned char matmul_q5_k_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xb3,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xb2,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -48591,47 +48488,47 @@ unsigned char matmul_q5_k_f32_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 0x2e,0x01,0x00,0x00,0x83,0x01,0x00,0x00,0xeb,0x01,0x00,0x00, -0xf6,0x01,0x00,0x00,0xe1,0x02,0x00,0x00,0x2a,0x03,0x00,0x00, +0xf6,0x01,0x00,0x00,0xe0,0x02,0x00,0x00,0x29,0x03,0x00,0x00, 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, 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-0x47,0x00,0x04,0x00,0x53,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x60,0x00,0x00,0x00, +0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x62,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -48666,15 +48563,15 @@ unsigned char matmul_q5_k_f32_data[] = { 0x47,0x00,0x04,0x00,0xf6,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xf6,0x01,0x00,0x00, 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0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xb7,0x00,0x00,0x00, @@ -48764,7 +48661,7 @@ unsigned char matmul_q5_k_f32_data[] = { 0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0xc1,0x00,0x00,0x00, 0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -48774,10 +48671,10 @@ unsigned char matmul_q5_k_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x80,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -48804,31 +48701,31 @@ unsigned char matmul_q5_k_f32_data[] = { 0x25,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x35,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x3c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x18,0x01,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x41,0x01,0x00,0x00, -0x3f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x41,0x01,0x00,0x00, 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0xc5,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,0xc5,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0xc6,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc8,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xc7,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc9,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0xc8,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xc8,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xe8,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa6,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0xe9,0x01,0x00,0x00,0x24,0x01,0x00,0x00,0xe8,0x01,0x00,0x00, @@ -48836,7 +48733,7 @@ unsigned char matmul_q5_k_f32_data[] = { 0xe9,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0xea,0x01,0x00,0x00, 0xeb,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xef,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 0xf3,0x01,0x00,0x00,0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, 0xf4,0x01,0x00,0x00,0xf3,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0xf5,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xf4,0x01,0x00,0x00, @@ -48844,26 +48741,26 @@ unsigned char matmul_q5_k_f32_data[] = { 0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x01,0x02,0x00,0x00, 0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0a,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 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+49036,121 @@ unsigned char matmul_q5_k_f32_data[] = { 0x54,0x01,0x00,0x00,0xc2,0x00,0x05,0x00,0x18,0x01,0x00,0x00, 0x6b,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,0xa8,0x00,0x00,0x00, 0x41,0x00,0x08,0x00,0x3c,0x01,0x00,0x00,0x6e,0x01,0x00,0x00, -0x2e,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, +0x2e,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0x18,0x01,0x00,0x00,0x6f,0x01,0x00,0x00,0x6e,0x01,0x00,0x00, 0xc2,0x00,0x05,0x00,0x18,0x01,0x00,0x00,0x70,0x01,0x00,0x00, -0x6f,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0xc4,0x00,0x05,0x00, +0x6f,0x01,0x00,0x00,0x81,0x00,0x00,0x00,0xc4,0x00,0x05,0x00, 0x18,0x01,0x00,0x00,0x71,0x01,0x00,0x00,0x70,0x01,0x00,0x00, 0xa8,0x00,0x00,0x00,0xc5,0x00,0x05,0x00,0x18,0x01,0x00,0x00, 0x72,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,0x71,0x01,0x00,0x00, 0xf9,0x00,0x02,0x00,0x38,0x01,0x00,0x00,0xf8,0x00,0x02,0x00, 0x38,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x18,0x01,0x00,0x00, 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0x24,0x01,0x00,0x00,0xb0,0x02,0x00,0x00,0xaf,0x02,0x00,0x00, @@ -49472,171 +49369,171 @@ unsigned char matmul_q5_k_f32_data[] = { 0x32,0x00,0x00,0x00,0xb1,0x02,0x00,0x00,0xb8,0x02,0x00,0x00, 0xbb,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xba,0x02,0x00,0x00, 0xbc,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xbf,0x02,0x00,0x00,0x79,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, +0xbf,0x02,0x00,0x00,0x78,0x03,0x00,0x00,0xcf,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x94,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,0x77,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0xc1,0x02,0x00,0x00,0x76,0x03,0x00,0x00, 0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0x93,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x8c,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc3,0x02,0x00,0x00, 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@@ -49645,47 +49542,47 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 0x2f,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0xee,0x01,0x00,0x00, -0xf6,0x01,0x00,0x00,0x03,0x03,0x00,0x00,0x4c,0x03,0x00,0x00, +0xf6,0x01,0x00,0x00,0x02,0x03,0x00,0x00,0x4b,0x03,0x00,0x00, 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x10,0x00,0x00,0x00, +0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 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-0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xeb,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xea,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xec,0x01,0x00,0x00,0x25,0x01,0x00,0x00, @@ -49912,21 +49809,21 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x32,0x02,0x00,0x00, 0x51,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x33,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x32,0x02,0x00,0x00,0x77,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x32,0x02,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x34,0x02,0x00,0x00, -0x86,0x00,0x00,0x00,0x33,0x02,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x33,0x02,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x37,0x02,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 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0x20,0x00,0x04,0x00,0x6e,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x25,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x84,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, @@ -49936,20 +49833,20 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x8f,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xfb,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xfa,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0x03,0x03,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, 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0x26,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x22,0x01,0x00,0x00,0x34,0x01,0x00,0x00, 0x33,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00, @@ -50148,25 +50045,25 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0xfa,0x00,0x04,0x00,0x37,0x01,0x00,0x00,0x38,0x01,0x00,0x00, 0x51,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0x3d,0x01,0x00,0x00,0x3e,0x01,0x00,0x00, -0x2f,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, +0x2f,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, 0xd0,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0x19,0x01,0x00,0x00,0x3f,0x01,0x00,0x00,0x3e,0x01,0x00,0x00, 0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00, -0x3f,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x3f,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x41,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0xc7,0x00,0x05,0x00, -0x13,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x41,0x01,0x00,0x00, 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0x02,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x05,0x02,0x00,0x00,0xe9,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x41,0x00,0x08,0x00,0xf8,0x01,0x00,0x00,0x07,0x02,0x00,0x00, -0xf6,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xe0,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0xf6,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xe0,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x08,0x02,0x00,0x00,0x07,0x02,0x00,0x00, 0x73,0x00,0x04,0x00,0x25,0x01,0x00,0x00,0x09,0x02,0x00,0x00, 0x08,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xa3,0x01,0x00,0x00, @@ -50356,7 +50253,7 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00, 0xe9,0x01,0x00,0x00,0x0c,0x02,0x00,0x00,0x41,0x00,0x08,0x00, 0xf8,0x01,0x00,0x00,0x0f,0x02,0x00,0x00,0xf6,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0x0c,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x10,0x02,0x00,0x00,0x0f,0x02,0x00,0x00,0x73,0x00,0x04,0x00, 0x25,0x01,0x00,0x00,0x11,0x02,0x00,0x00,0x10,0x02,0x00,0x00, @@ -50365,8 +50262,8 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x12,0x02,0x00,0x00,0x11,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x14,0x02,0x00,0x00,0xe9,0x01,0x00,0x00, 0x36,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0xf8,0x01,0x00,0x00, -0x16,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xe0,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x16,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xe0,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3f,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x17,0x02,0x00,0x00, 0x16,0x02,0x00,0x00,0x73,0x00,0x04,0x00,0x25,0x01,0x00,0x00, 0x18,0x02,0x00,0x00,0x17,0x02,0x00,0x00,0x41,0x00,0x05,0x00, @@ -50375,8 +50272,8 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x18,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0x1c,0x02,0x00,0x00,0xe9,0x01,0x00,0x00,0x1b,0x02,0x00,0x00, 0x41,0x00,0x08,0x00,0xf8,0x01,0x00,0x00,0x1e,0x02,0x00,0x00, -0xf6,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xe0,0x01,0x00,0x00, -0xd0,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, +0xf6,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xe0,0x01,0x00,0x00, +0xd0,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0x1f,0x02,0x00,0x00,0x1e,0x02,0x00,0x00, 0x73,0x00,0x04,0x00,0x25,0x01,0x00,0x00,0x20,0x02,0x00,0x00, 0x1f,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xa3,0x01,0x00,0x00, @@ -50385,7 +50282,7 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x24,0x02,0x00,0x00, 0xe9,0x01,0x00,0x00,0x23,0x02,0x00,0x00,0x41,0x00,0x08,0x00, 0xf8,0x01,0x00,0x00,0x26,0x02,0x00,0x00,0xf6,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xe0,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x27,0x02,0x00,0x00,0x26,0x02,0x00,0x00,0x73,0x00,0x04,0x00, 0x25,0x01,0x00,0x00,0x28,0x02,0x00,0x00,0x27,0x02,0x00,0x00, @@ -50394,7 +50291,7 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x29,0x02,0x00,0x00,0x28,0x02,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x2c,0x02,0x00,0x00,0xe9,0x01,0x00,0x00, 0x2b,0x02,0x00,0x00,0x41,0x00,0x08,0x00,0xf8,0x01,0x00,0x00, -0x2e,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x2e,0x02,0x00,0x00,0xf6,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0xe0,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x0c,0x02,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x2f,0x02,0x00,0x00, 0x2e,0x02,0x00,0x00,0x73,0x00,0x04,0x00,0x25,0x01,0x00,0x00, @@ -50402,162 +50299,162 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0xa3,0x01,0x00,0x00,0x31,0x02,0x00,0x00,0xee,0x01,0x00,0x00, 0x2c,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x31,0x02,0x00,0x00, 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0x25,0x01,0x00,0x00,0xd2,0x02,0x00,0x00,0xd1,0x02,0x00,0x00, @@ -50574,171 +50471,171 @@ unsigned char matmul_q5_k_f32_aligned_data[] = { 0x32,0x00,0x00,0x00,0xd3,0x02,0x00,0x00,0xda,0x02,0x00,0x00, 0xdd,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xdc,0x02,0x00,0x00, 0xde,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xe1,0x02,0x00,0x00,0x9b,0x03,0x00,0x00,0xd0,0x00,0x00,0x00, +0xe1,0x02,0x00,0x00,0x9a,0x03,0x00,0x00,0xd0,0x00,0x00,0x00, 0xf9,0x00,0x02,0x00,0xbb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, 0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb6,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0xb6,0x02,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0x99,0x03,0x00,0x00, +0x06,0x00,0x00,0x00,0xe3,0x02,0x00,0x00,0x98,0x03,0x00,0x00, 0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xb3,0x02,0x00,0x00, 0xf8,0x00,0x02,0x00,0xb5,0x02,0x00,0x00,0xf9,0x00,0x02,0x00, 0xae,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xae,0x02,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe5,0x02,0x00,0x00, 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0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -50746,47 +50643,47 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, -0x4c,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x83,0x01,0x00,0x00, -0xeb,0x01,0x00,0x00,0xf2,0x01,0x00,0x00,0xd9,0x02,0x00,0x00, -0x22,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, +0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00, +0x4d,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x83,0x01,0x00,0x00, +0xeb,0x01,0x00,0x00,0xf2,0x01,0x00,0x00,0xd8,0x02,0x00,0x00, +0x21,0x03,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00, 0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00, 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+0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x60,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x62,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00, @@ -50821,15 +50718,15 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xf2,0x01,0x00,0x00, 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+0x21,0x03,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x21,0x03,0x00,0x00,0x21,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00, 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -50840,78 +50737,78 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x1e,0x00,0x10,0x00,0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00, -0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x11,0x00,0x00,0x00, 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+0x50,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00, 0x84,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0xbc,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, -0x84,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x60,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x61,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x86,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00, @@ -50921,7 +50818,7 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -50931,10 +50828,10 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x20,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x07,0x01,0x00,0x00, @@ -50959,33 +50856,33 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x2f,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x31,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x26,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x3c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x19,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x19,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x41,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, 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0x84,0x00,0x00,0x00,0xc5,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe2,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe7,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe8,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xe7,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xe9,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, @@ -51004,21 +50901,21 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x06,0x00,0x00,0x00,0x0b,0x02,0x00,0x00,0x51,0x00,0x00,0x00, 0xc4,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0c,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x0b,0x02,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x0b,0x02,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x86,0x00,0x00,0x00, -0x0c,0x02,0x00,0x00,0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x0c,0x02,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x10,0x02,0x00,0x00,0x08,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x11,0x02,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x14,0x02,0x00,0x00, -0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x2f,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0x30,0x02,0x00,0x00,0xc4,0x00,0x00,0x00, 0x2f,0x02,0x00,0x00,0x20,0x00,0x04,0x00,0x31,0x02,0x00,0x00, 0x07,0x00,0x00,0x00,0x30,0x02,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x41,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x5c,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0x5d,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x5c,0x02,0x00,0x00, @@ -51026,20 +50923,20 @@ unsigned char matmul_q5_k_f32_aligned_fp32_data[] = { 0x5d,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x67,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x6f,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x9e,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0xd1,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x1f,0x03,0x00,0x00,0xc4,0x00,0x00,0x00, -0x1e,0x00,0x03,0x00,0x20,0x03,0x00,0x00,0x1f,0x03,0x00,0x00, -0x20,0x00,0x04,0x00,0x21,0x03,0x00,0x00,0x0c,0x00,0x00,0x00, -0x20,0x03,0x00,0x00,0x3b,0x00,0x04,0x00,0x21,0x03,0x00,0x00, -0x22,0x03,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x27,0x03,0x00,0x00,0x05,0x00,0x00,0x00, -0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x34,0x03,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, +0x6f,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x9e,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, +0xd0,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, 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0xba,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0xbc,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xbc,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 0xb9,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -51959,8 +51856,8 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0xbf,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc1,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc3,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc4,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, 0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, @@ -51970,9 +51867,9 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x2b,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x01,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -51999,31 +51896,31 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x35,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x3c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x18,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x18,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x41,0x01,0x00,0x00,0x3f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x58,0x01,0x00,0x00,0x0f,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x80,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x7f,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x81,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x80,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x82,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x81,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0x82,0x01,0x00,0x00,0x83,0x01,0x00,0x00,0x04,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x9a,0x01,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x9a,0x01,0x00,0x00, 0x10,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xa1,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,0x32,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xc3,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0xc4,0x01,0x00,0x00, -0xc3,0x01,0x00,0x00,0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0xc3,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc5,0x01,0x00,0x00, 0x51,0x00,0x00,0x00,0xc4,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc6,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xc5,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x01,0x00,0x00, -0x86,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0xc6,0x01,0x00,0x00,0x6d,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe5,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe6,0x01,0x00,0x00, 0x84,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0xe5,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0xe7,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -52031,7 +51928,7 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x04,0x00,0x00,0x00,0xe7,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0xe8,0x01,0x00,0x00,0xe9,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xed,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x1d,0x00,0x03,0x00,0xf1,0x01,0x00,0x00,0xc3,0x00,0x00,0x00, 0x1e,0x00,0x03,0x00,0xf2,0x01,0x00,0x00,0xf1,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0xf3,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, @@ -52039,25 +51936,25 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0xf4,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xff,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xc3,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x07,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0c,0x02,0x00,0x00, 0x51,0x00,0x00,0x00,0xc4,0x01,0x00,0x00,0x00,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0d,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x0c,0x02,0x00,0x00,0x39,0x00,0x00,0x00, +0x84,0x00,0x00,0x00,0x0c,0x02,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x0e,0x02,0x00,0x00, -0x86,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x6c,0x00,0x00,0x00, +0x86,0x00,0x00,0x00,0x0d,0x02,0x00,0x00,0x6d,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x11,0x02,0x00,0x00, 0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x12,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, +0x12,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x15,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x30,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x31,0x02,0x00,0x00, +0x15,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x30,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x31,0x02,0x00,0x00, 0xc3,0x00,0x00,0x00,0x30,0x02,0x00,0x00,0x20,0x00,0x04,0x00, 0x32,0x02,0x00,0x00,0x07,0x00,0x00,0x00,0x31,0x02,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x42,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x5d,0x02,0x00,0x00, 0x84,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0xbb,0x00,0x00,0x00, 0x1c,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,0xc3,0x00,0x00,0x00, @@ -52066,20 +51963,20 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x06,0x00,0x00,0x00,0x68,0x02,0x00,0x00,0x86,0x00,0x00,0x00, 0xb8,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x70,0x02,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,0x0d,0x00,0x00,0x00, -0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0xda,0x02,0x00,0x00, -0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x20,0x03,0x00,0x00, -0xc3,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x21,0x03,0x00,0x00, -0x20,0x03,0x00,0x00,0x20,0x00,0x04,0x00,0x22,0x03,0x00,0x00, -0x0c,0x00,0x00,0x00,0x21,0x03,0x00,0x00,0x3b,0x00,0x04,0x00, 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0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf7,0x00,0x00,0x00, 0xf4,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,0x86,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xee,0x00,0x00,0x00, @@ -52263,13 +52160,13 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x13,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x12,0x01,0x00,0x00, 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1c,0x01,0x00,0x00, 0xfe,0x00,0x00,0x00,0x06,0x01,0x00,0x00,0xc4,0x00,0x05,0x00, -0x13,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0xcf,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0xcf,0x00,0x00,0x00, 0x1c,0x01,0x00,0x00,0x72,0x00,0x04,0x00,0x1e,0x01,0x00,0x00, 0x1f,0x01,0x00,0x00,0x1d,0x01,0x00,0x00,0x7c,0x00,0x04,0x00, 0x18,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0x1f,0x01,0x00,0x00, 0x41,0x00,0x07,0x00,0x30,0x01,0x00,0x00,0x31,0x01,0x00,0x00, -0x2e,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, -0x34,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x25,0x01,0x00,0x00, +0x2e,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x25,0x01,0x00,0x00, 0x32,0x01,0x00,0x00,0x31,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x21,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x36,0x01,0x00,0x00, @@ -52278,25 +52175,25 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0x36,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x50,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x37,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x3c,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,0x2e,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x0c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0x3e,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,0x3e,0x01,0x00,0x00, -0x7c,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x40,0x01,0x00,0x00, -0x3f,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x13,0x00,0x00,0x00, +0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x40,0x01,0x00,0x00, +0x3f,0x01,0x00,0x00,0xc7,0x00,0x05,0x00,0x15,0x00,0x00,0x00, 0x42,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x41,0x01,0x00,0x00, 0x72,0x00,0x04,0x00,0x1e,0x01,0x00,0x00,0x43,0x01,0x00,0x00, 0x42,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0x44,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x0c,0x01,0x00,0x00, 0x35,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x3c,0x01,0x00,0x00, -0x49,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x49,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x48,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x4a,0x01,0x00,0x00, 0x49,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x4b,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,0x7c,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, -0xc7,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, +0x15,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x4b,0x01,0x00,0x00, +0xc7,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x4d,0x01,0x00,0x00, 0x4c,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x72,0x00,0x04,0x00, 0x1e,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x4d,0x01,0x00,0x00, 0x7c,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x4f,0x01,0x00,0x00, @@ -52304,26 +52201,26 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0xf8,0x00,0x02,0x00,0x50,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x53,0x01,0x00,0x00,0x0c,0x01,0x00,0x00, 0x35,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0x3c,0x01,0x00,0x00, -0x54,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x34,0x00,0x00,0x00, +0x54,0x01,0x00,0x00,0x2e,0x01,0x00,0x00,0x35,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x53,0x01,0x00,0x00, 0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00,0x55,0x01,0x00,0x00, 0x54,0x01,0x00,0x00,0x71,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x56,0x01,0x00,0x00,0x55,0x01,0x00,0x00,0x7c,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x57,0x01,0x00,0x00,0x56,0x01,0x00,0x00, -0xc7,0x00,0x05,0x00,0x13,0x00,0x00,0x00,0x59,0x01,0x00,0x00, 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-0x61,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x13,0x00,0x00,0x00, +0x7c,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x62,0x01,0x00,0x00, +0x61,0x01,0x00,0x00,0xc5,0x00,0x05,0x00,0x15,0x00,0x00,0x00, 0x63,0x01,0x00,0x00,0x59,0x01,0x00,0x00,0x62,0x01,0x00,0x00, 0x72,0x00,0x04,0x00,0x1e,0x01,0x00,0x00,0x64,0x01,0x00,0x00, 0x63,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x18,0x01,0x00,0x00, @@ -52332,118 +52229,118 @@ unsigned char matmul_q5_k_f32_fp32_data[] = { 0xc2,0x00,0x05,0x00,0x18,0x01,0x00,0x00,0x6b,0x01,0x00,0x00, 0x6a,0x01,0x00,0x00,0xa8,0x00,0x00,0x00,0x41,0x00,0x08,0x00, 0x3c,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,0x2e,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x0c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x18,0x01,0x00,0x00, 0x6f,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,0xc2,0x00,0x05,0x00, 0x18,0x01,0x00,0x00,0x70,0x01,0x00,0x00,0x6f,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0xc4,0x00,0x05,0x00,0x18,0x01,0x00,0x00, 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0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q5_k_f32_fp32_len = 12476; unsigned char matmul_q6_k_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x44,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x43,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -52831,47 +52728,47 @@ unsigned char matmul_q6_k_f32_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x4c,0x00,0x00,0x00, +0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00, 0x33,0x01,0x00,0x00,0x44,0x01,0x00,0x00,0xaf,0x01,0x00,0x00, -0xba,0x01,0x00,0x00,0xa5,0x02,0x00,0x00,0xee,0x02,0x00,0x00, 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0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -52906,15 +52803,15 @@ unsigned char matmul_q6_k_f32_data[] = { 0x47,0x00,0x04,0x00,0xba,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xba,0x01,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xa5,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xeb,0x02,0x00,0x00,0x06,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xec,0x02,0x00,0x00, +0xa4,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0xea,0x02,0x00,0x00,0x06,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xeb,0x02,0x00,0x00, 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00, -0xec,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xec,0x02,0x00,0x00, -0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xee,0x02,0x00,0x00, +0xeb,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00, 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+52911,10 @@ unsigned char matmul_q6_k_f32_data[] = { 0x07,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,0x07,0x00,0x00,0x00, -0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0xc3,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0xcf,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x80,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00, 0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -53042,9 +52939,9 @@ unsigned char matmul_q6_k_f32_data[] = { 0x35,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x2e,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x3b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 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+0x15,0x00,0x00,0x00,0x60,0x01,0x00,0x00,0x5f,0x01,0x00,0x00, +0x82,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x62,0x01,0x00,0x00, 0x60,0x01,0x00,0x00,0x61,0x01,0x00,0x00,0x6f,0x00,0x04,0x00, 0xc3,0x00,0x00,0x00,0x63,0x01,0x00,0x00,0x62,0x01,0x00,0x00, 0x85,0x00,0x05,0x00,0xc3,0x00,0x00,0x00,0x64,0x01,0x00,0x00, @@ -53370,37 +53267,37 @@ unsigned char matmul_q6_k_f32_data[] = { 0x44,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,0x3e,0x00,0x03,0x00, 0x67,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0xf7,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x6d,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x6d,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x41,0x00,0x08,0x00,0x49,0x01,0x00,0x00,0x6e,0x01,0x00,0x00, -0x33,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, -0x34,0x00,0x00,0x00,0x6d,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 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0x81,0x01,0x00,0x00,0x75,0x01,0x00,0x00,0x80,0x01,0x00,0x00, 0x72,0x00,0x04,0x00,0x2c,0x01,0x00,0x00,0x82,0x01,0x00,0x00, -0x81,0x01,0x00,0x00,0x72,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x81,0x01,0x00,0x00,0x72,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x83,0x01,0x00,0x00,0x82,0x01,0x00,0x00,0x82,0x00,0x05,0x00, -0x13,0x00,0x00,0x00,0x84,0x01,0x00,0x00,0x83,0x01,0x00,0x00, +0x15,0x00,0x00,0x00,0x84,0x01,0x00,0x00,0x83,0x01,0x00,0x00, 0x61,0x01,0x00,0x00,0x6f,0x00,0x04,0x00,0xc3,0x00,0x00,0x00, 0x85,0x01,0x00,0x00,0x84,0x01,0x00,0x00,0x85,0x00,0x05,0x00, 0xc3,0x00,0x00,0x00,0x86,0x01,0x00,0x00,0x3f,0x01,0x00,0x00, @@ -53409,22 +53306,22 @@ unsigned char matmul_q6_k_f32_data[] = { 0x66,0x01,0x00,0x00,0x88,0x01,0x00,0x00,0x44,0x01,0x00,0x00, 0x69,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x88,0x01,0x00,0x00, 0x87,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x8f,0x01,0x00,0x00,0x23,0x03,0x00,0x00,0x8d,0x01,0x00,0x00, +0x8f,0x01,0x00,0x00,0x22,0x03,0x00,0x00,0x8d,0x01,0x00,0x00, 0xf9,0x00,0x02,0x00,0xdc,0x00,0x00,0x00,0xf8,0x00,0x02,0x00, 0xde,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x91,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0x91,0x01,0x00,0x00,0xf5,0x00,0x07,0x00, -0x06,0x00,0x00,0x00,0x24,0x03,0x00,0x00,0x3e,0x00,0x00,0x00, +0x06,0x00,0x00,0x00,0x23,0x03,0x00,0x00,0x3f,0x00,0x00,0x00, 0xde,0x00,0x00,0x00,0xd8,0x01,0x00,0x00,0x94,0x01,0x00,0x00, 0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x97,0x01,0x00,0x00, -0x24,0x03,0x00,0x00,0xa6,0x00,0x00,0x00,0xf6,0x00,0x04,0x00, +0x23,0x03,0x00,0x00,0xa6,0x00,0x00,0x00,0xf6,0x00,0x04,0x00, 0x93,0x01,0x00,0x00,0x94,0x01,0x00,0x00,0x01,0x00,0x00,0x00, 0xfa,0x00,0x04,0x00,0x97,0x01,0x00,0x00,0x92,0x01,0x00,0x00, 0x93,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x92,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x01,0x00,0x00, -0xa7,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x80,0x00,0x05,0x00, +0xa7,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x9d,0x01,0x00,0x00,0x9b,0x01,0x00,0x00, -0x24,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x9e,0x01,0x00,0x00,0x12,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, +0x23,0x03,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00, +0x9e,0x01,0x00,0x00,0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x9f,0x01,0x00,0x00, 0x9e,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00, 0xa0,0x01,0x00,0x00,0x9d,0x01,0x00,0x00,0x9f,0x01,0x00,0x00, @@ -53432,9 +53329,9 @@ unsigned char matmul_q6_k_f32_data[] = { 0xfa,0x00,0x04,0x00,0xa0,0x01,0x00,0x00,0xa1,0x01,0x00,0x00, 0xa2,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xa1,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa5,0x01,0x00,0x00, -0x13,0x03,0x00,0x00,0x78,0x00,0x00,0x00,0xb0,0x00,0x05,0x00, +0x12,0x03,0x00,0x00,0x79,0x00,0x00,0x00,0xb0,0x00,0x05,0x00, 0xc1,0x00,0x00,0x00,0xa7,0x01,0x00,0x00,0xa5,0x01,0x00,0x00, -0x8d,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa2,0x01,0x00,0x00, +0x8e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xa2,0x01,0x00,0x00, 0xf8,0x00,0x02,0x00,0xa2,0x01,0x00,0x00,0xf5,0x00,0x07,0x00, 0xc1,0x00,0x00,0x00,0xa8,0x01,0x00,0x00,0xa0,0x01,0x00,0x00, 0x92,0x01,0x00,0x00,0xa7,0x01,0x00,0x00,0xa1,0x01,0x00,0x00, @@ -53442,17 +53339,17 @@ unsigned char matmul_q6_k_f32_data[] = { 0xfa,0x00,0x04,0x00,0xa8,0x01,0x00,0x00,0xa9,0x01,0x00,0x00, 0xca,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xa9,0x01,0x00,0x00, 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb2,0x01,0x00,0x00, -0x7d,0x00,0x00,0x00,0x24,0x03,0x00,0x00,0x84,0x00,0x05,0x00, +0x7e,0x00,0x00,0x00,0x23,0x03,0x00,0x00,0x84,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xb4,0x01,0x00,0x00,0xb2,0x01,0x00,0x00, 0xb3,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0xb6,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0x78,0x00,0x00,0x00, +0xb6,0x01,0x00,0x00,0xb4,0x01,0x00,0x00,0x79,0x00,0x00,0x00, 0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc1,0x01,0x00,0x00, 0xb2,0x01,0x00,0x00,0xaa,0x00,0x00,0x00,0x80,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0xc2,0x01,0x00,0x00,0x2b,0x03,0x00,0x00, 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+0xb4,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xad,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0xad,0x02,0x00,0x00,0x80,0x00,0x05,0x00, +0x06,0x00,0x00,0x00,0x10,0x03,0x00,0x00,0x13,0x03,0x00,0x00, +0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xaa,0x02,0x00,0x00, +0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0xfd,0x00,0x01,0x00, 0x38,0x00,0x01,0x00, }; const uint64_t matmul_q6_k_f32_len = 11764; unsigned char matmul_q6_k_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x65,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x64,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00,0x60,0x11,0x00,0x00, @@ -53816,47 +53713,47 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 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-0x47,0x00,0x04,0x00,0x6c,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00, @@ -53894,15 +53791,15 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x47,0x00,0x04,0x00,0xb9,0x01,0x00,0x00,0x22,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x01,0x00,0x00, 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xc6,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x0c,0x03,0x00,0x00,0x06,0x00,0x00,0x00, -0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x0d,0x03,0x00,0x00, +0xc5,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x0b,0x03,0x00,0x00,0x06,0x00,0x00,0x00, +0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x0c,0x03,0x00,0x00, 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+0xba,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x54,0x00,0x00,0x00, 0xb9,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xbb,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x4f,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xbb,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x50,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xbc,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xbb,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0xbd,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0xbd,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 0xba,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -53993,8 +53890,8 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xc0,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x14,0x00,0x02,0x00, 0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xc4,0x00,0x00,0x00, 0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00, +0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc5,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0xc6,0x00,0x00,0x00, @@ -54004,9 +53901,9 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcc,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00, 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, 0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x02,0x01,0x00,0x00,0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, @@ -54030,9 +53927,9 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x35,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x2e,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0x3b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, 0x2c,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x40,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x41,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00, +0x40,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x41,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00, 0x40,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x42,0x01,0x00,0x00, 0x2e,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x43,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x42,0x01,0x00,0x00, @@ -54040,24 +53937,24 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x49,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x04,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x52,0x01,0x00,0x00, -0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x52,0x01,0x00,0x00, +0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x61,0x01,0x00,0x00,0x20,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0x66,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x2e,0x01,0x00,0x00, 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x89,0x01,0x00,0x00, 0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00, -0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x39,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x8a,0x01,0x00,0x00,0x89,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x8b,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x8a,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x8c,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x8b,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x8d,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x8c,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xa8,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xad,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xa8,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0xad,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xae,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00, 0xad,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0xaf,0x01,0x00,0x00, 0x2e,0x01,0x00,0x00,0xae,0x01,0x00,0x00,0x20,0x00,0x04,0x00, @@ -54081,21 +53978,21 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xf5,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x8a,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xf6,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xf5,0x01,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xf7,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xf6,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfa,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xfb,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xfe,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x19,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0x1a,0x02,0x00,0x00,0x2e,0x01,0x00,0x00,0x19,0x02,0x00,0x00, 0x20,0x00,0x04,0x00,0x1b,0x02,0x00,0x00,0x07,0x00,0x00,0x00, 0x1a,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x2b,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x31,0x02,0x00,0x00, +0x2b,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x31,0x02,0x00,0x00, 0x07,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x47,0x02,0x00,0x00,0x84,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, @@ -54104,20 +54001,20 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x48,0x02,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x52,0x02,0x00,0x00,0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00, 0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x5a,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x89,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00, -0x62,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0xbe,0x02,0x00,0x00,0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00, -0x0a,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,0x01,0x00,0x00,0x00, -0x1d,0x00,0x03,0x00,0x0c,0x03,0x00,0x00,0xc4,0x00,0x00,0x00, -0x1e,0x00,0x03,0x00,0x0d,0x03,0x00,0x00,0x0c,0x03,0x00,0x00, -0x20,0x00,0x04,0x00,0x0e,0x03,0x00,0x00,0x0c,0x00,0x00,0x00, -0x0d,0x03,0x00,0x00,0x3b,0x00,0x04,0x00,0x0e,0x03,0x00,0x00, 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+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x20,0x03,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, 0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00, 0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00, 0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00, @@ -54127,159 +54024,159 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x07,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00, 0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x0e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00, -0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00, -0x16,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00, -0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00, -0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x41,0x00,0x05,0x00, 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-0x6e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00, +0x6f,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0xf5,0x00,0x00,0x00, 0xf7,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xfc,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xfb,0x00,0x00,0x00, @@ -54292,12 +54189,12 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x06,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x89,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0xff,0x00,0x00,0x00, 0x0b,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x0d,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,0x77,0x00,0x00,0x00, +0x0d,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,0x78,0x00,0x00,0x00, 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x11,0x01,0x00,0x00, 0x06,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,0x84,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x12,0x01,0x00,0x00,0x11,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x15,0x01,0x00,0x00,0x77,0x00,0x00,0x00,0x03,0x01,0x00,0x00, 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0x41,0x00,0x05,0x00,0x66,0x01,0x00,0x00,0xc6,0x01,0x00,0x00, @@ -54446,8 +54343,8 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xc6,0x01,0x00,0x00,0xc5,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xc8,0x01,0x00,0x00,0xac,0x01,0x00,0x00, 0x0c,0x00,0x00,0x00,0x41,0x00,0x08,0x00,0xbb,0x01,0x00,0x00, -0xca,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xa3,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, +0xca,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xa3,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x0c,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xcb,0x01,0x00,0x00, 0xca,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x2e,0x01,0x00,0x00, 0xcc,0x01,0x00,0x00,0xcb,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -54456,8 +54353,8 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xcc,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xd0,0x01,0x00,0x00,0xac,0x01,0x00,0x00,0xcf,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0xbb,0x01,0x00,0x00,0xd2,0x01,0x00,0x00, -0xb9,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xcf,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, +0xb9,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, +0x35,0x00,0x00,0x00,0xcf,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xd3,0x01,0x00,0x00,0xd2,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x2e,0x01,0x00,0x00,0xd4,0x01,0x00,0x00, 0xd3,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x66,0x01,0x00,0x00, @@ -54466,8 +54363,8 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x01,0x00,0x00, 0xac,0x01,0x00,0x00,0x4d,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0xbb,0x01,0x00,0x00,0xd9,0x01,0x00,0x00,0xb9,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, -0x3e,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x3f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xda,0x01,0x00,0x00,0xd9,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 0x2e,0x01,0x00,0x00,0xdb,0x01,0x00,0x00,0xda,0x01,0x00,0x00, 0x41,0x00,0x05,0x00,0x66,0x01,0x00,0x00,0xdc,0x01,0x00,0x00, @@ -54475,8 +54372,8 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xdc,0x01,0x00,0x00,0xdb,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0xdf,0x01,0x00,0x00,0xac,0x01,0x00,0x00, 0xde,0x01,0x00,0x00,0x41,0x00,0x08,0x00,0xbb,0x01,0x00,0x00, -0xe1,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0x34,0x00,0x00,0x00, -0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0xe1,0x01,0x00,0x00,0xb9,0x01,0x00,0x00,0x35,0x00,0x00,0x00, +0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xe2,0x01,0x00,0x00, 0xe1,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0x2e,0x01,0x00,0x00, 0xe3,0x01,0x00,0x00,0xe2,0x01,0x00,0x00,0x41,0x00,0x05,0x00, @@ -54485,7 +54382,7 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0xe3,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xe7,0x01,0x00,0x00,0xac,0x01,0x00,0x00,0xe6,0x01,0x00,0x00, 0x41,0x00,0x08,0x00,0xbb,0x01,0x00,0x00,0xe9,0x01,0x00,0x00, -0xb9,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, +0xb9,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xa3,0x01,0x00,0x00, 0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0xc4,0x00,0x00,0x00,0xea,0x01,0x00,0x00,0xe9,0x01,0x00,0x00, 0x73,0x00,0x04,0x00,0x2e,0x01,0x00,0x00,0xeb,0x01,0x00,0x00, @@ -54495,170 +54392,170 @@ unsigned char matmul_q6_k_f32_aligned_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xef,0x01,0x00,0x00, 0xac,0x01,0x00,0x00,0xee,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0xbb,0x01,0x00,0x00,0xf1,0x01,0x00,0x00,0xb9,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xa3,0x01,0x00,0x00,0xd0,0x00,0x00,0x00, 0xcf,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xf2,0x01,0x00,0x00,0xf1,0x01,0x00,0x00,0x73,0x00,0x04,0x00, 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+0x31,0x03,0x00,0x00,0x34,0x03,0x00,0x00,0xd0,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0xcb,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0xcd,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; const uint64_t matmul_q6_k_f32_aligned_len = 12324; unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x3c,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x3b,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, @@ -54847,47 +54744,47 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3d,0x00,0x00,0x00, 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+0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00, +0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00, @@ -54922,15 +54819,15 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb6,0x01,0x00,0x00, 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0xb6,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x9d,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, -0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe3,0x02,0x00,0x00, +0x47,0x00,0x04,0x00,0x9c,0x02,0x00,0x00,0x0b,0x00,0x00,0x00, +0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xe2,0x02,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0xe4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0xe4,0x02,0x00,0x00,0x00,0x00,0x00,0x00, +0xe3,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0xe3,0x02,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0xe4,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0xe6,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0xe6,0x02,0x00,0x00,0x21,0x00,0x00,0x00, +0xe3,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, +0xe5,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0xe5,0x02,0x00,0x00,0x21,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00, 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00, @@ -54941,78 +54838,78 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 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+0x84,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x61,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x86,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0xbe,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00, @@ -55022,7 +54919,7 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00, 0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00, 0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00, @@ -55032,10 +54929,10 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00, 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00, 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xfb,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x40,0x00,0x00,0x00, 0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x07,0x01,0x00,0x00, @@ -55060,32 +54957,32 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x0c,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,0x20,0x00,0x04,0x00, 0x3c,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x2d,0x01,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x42,0x01,0x00,0x00, -0x84,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x41,0x01,0x00,0x00, +0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x41,0x01,0x00,0x00, 0x1c,0x00,0x04,0x00,0x43,0x01,0x00,0x00,0xc4,0x00,0x00,0x00, 0x42,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x44,0x01,0x00,0x00, 0x04,0x00,0x00,0x00,0x43,0x01,0x00,0x00,0x3b,0x00,0x04,0x00, 0x44,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x4a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00, -0x2a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, +0x2a,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, 0x52,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x2b,0x00,0x04,0x00, -0x13,0x00,0x00,0x00,0x61,0x01,0x00,0x00,0x20,0x00,0x00,0x00, +0x15,0x00,0x00,0x00,0x61,0x01,0x00,0x00,0x20,0x00,0x00,0x00, 0x20,0x00,0x04,0x00,0x65,0x01,0x00,0x00,0x04,0x00,0x00,0x00, 0xc4,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0x87,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00, 0x09,0x00,0x00,0x00,0x88,0x01,0x00,0x00,0x87,0x01,0x00,0x00, -0x39,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x89,0x01,0x00,0x00,0x51,0x00,0x00,0x00, 0x88,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x8a,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0x89,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0x8b,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x8a,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x8a,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xa6,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xab,0x01,0x00,0x00,0x80,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xac,0x01,0x00,0x00,0x84,0x00,0x00,0x00, 0xa7,0x00,0x00,0x00,0xab,0x01,0x00,0x00,0x1c,0x00,0x04,0x00, 0xad,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0xac,0x01,0x00,0x00, @@ -55104,21 +55001,21 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0xcf,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x88,0x01,0x00,0x00, 0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xd0,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xcf,0x01,0x00,0x00, -0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0xd1,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0xd0,0x01,0x00,0x00, -0x6c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, +0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00, 0xd4,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xd5,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xd8,0x01,0x00,0x00,0x86,0x00,0x00,0x00, -0x6c,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00, 0x06,0x00,0x00,0x00,0xf3,0x01,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00, 0xf4,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0xf3,0x01,0x00,0x00, 0x20,0x00,0x04,0x00,0xf5,0x01,0x00,0x00,0x07,0x00,0x00,0x00, 0xf4,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, -0x05,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, +0x05,0x02,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00, 0x20,0x02,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0x21,0x02,0x00,0x00, 0xc4,0x00,0x00,0x00,0x20,0x02,0x00,0x00,0x20,0x00,0x04,0x00, @@ -55126,20 +55023,20 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x2b,0x02,0x00,0x00, 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x33,0x02,0x00,0x00, -0x80,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x39,0x00,0x00,0x00, +0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00, 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x62,0x02,0x00,0x00, -0x84,0x00,0x00,0x00,0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x95,0x02,0x00,0x00, +0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00, +0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x94,0x02,0x00,0x00, 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00, -0x9d,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, -0xe3,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, -0xe4,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x20,0x00,0x04,0x00, -0xe5,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0xe4,0x02,0x00,0x00, -0x3b,0x00,0x04,0x00,0xe5,0x02,0x00,0x00,0xe6,0x02,0x00,0x00, -0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x13,0x00,0x00,0x00, -0xeb,0x02,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00, -0x06,0x00,0x00,0x00,0xf8,0x02,0x00,0x00,0x84,0x00,0x00,0x00, -0x60,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x36,0x00,0x05,0x00, +0x9c,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00, +0xe2,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00, +0xe3,0x02,0x00,0x00,0xe2,0x02,0x00,0x00,0x20,0x00,0x04,0x00, +0xe4,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0xe3,0x02,0x00,0x00, +0x3b,0x00,0x04,0x00,0xe4,0x02,0x00,0x00,0xe5,0x02,0x00,0x00, +0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00, +0xea,0x02,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00, +0x06,0x00,0x00,0x00,0xf7,0x02,0x00,0x00,0x84,0x00,0x00,0x00, +0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x36,0x00,0x05,0x00, 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00, 0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0xca,0x00,0x00,0x00, @@ -55149,158 +55046,158 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,0x0e,0x00,0x00,0x00, -0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00, -0x12,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3d,0x00,0x04,0x00, -0x06,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x16,0x00,0x00,0x00, -0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x18,0x00,0x00,0x00, -0x0f,0x00,0x00,0x00,0x17,0x00,0x00,0x00,0x89,0x00,0x05,0x00, -0x06,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,0x0f,0x00,0x00,0x00, -0x17,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00, 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0x0c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, 0xf8,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,0xf7,0x00,0x00,0x00, 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, @@ -55336,45 +55233,45 @@ unsigned char matmul_q6_k_f32_aligned_fp32_data[] = { 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00, 0x24,0x01,0x00,0x00,0x27,0x01,0x00,0x00,0x41,0x00,0x07,0x00, 0x36,0x01,0x00,0x00,0x37,0x01,0x00,0x00,0x34,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x97,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x98,0x00,0x00,0x00, 0x3d,0x00,0x04,0x00,0x2f,0x01,0x00,0x00,0x38,0x01,0x00,0x00, 0x37,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0xc4,0x00,0x00,0x00, 0x39,0x01,0x00,0x00,0x38,0x01,0x00,0x00,0x41,0x00,0x08,0x00, 0x3c,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,0x34,0x01,0x00,0x00, -0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x86,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x87,0x00,0x00,0x00, 0x1a,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,0x2d,0x01,0x00,0x00, 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0x45,0x01,0x00,0x00,0xf8,0x00,0x00,0x00,0x3e,0x00,0x03,0x00, 0x66,0x01,0x00,0x00,0x64,0x01,0x00,0x00,0x80,0x00,0x05,0x00, 0x06,0x00,0x00,0x00,0x68,0x01,0x00,0x00,0xf8,0x00,0x00,0x00, -0x39,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, -0x6c,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x39,0x00,0x00,0x00, +0x3a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0x6c,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00, 0x41,0x00,0x08,0x00,0x4a,0x01,0x00,0x00,0x6d,0x01,0x00,0x00, -0x34,0x01,0x00,0x00,0x34,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, -0x34,0x00,0x00,0x00,0x6c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, +0x34,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0xfc,0x00,0x00,0x00, +0x35,0x00,0x00,0x00,0x6c,0x01,0x00,0x00,0x3d,0x00,0x04,0x00, 0x2a,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,0x6d,0x01,0x00,0x00, 0xc2,0x00,0x05,0x00,0x2a,0x01,0x00,0x00,0x71,0x01,0x00,0x00, 0x6e,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x71,0x00,0x04,0x00, 0x06,0x00,0x00,0x00,0x72,0x01,0x00,0x00,0x71,0x01,0x00,0x00, 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+0x59,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00, +0xbc,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0xcf,0x00,0x00,0x00, +0xf9,0x00,0x02,0x00,0x56,0x02,0x00,0x00,0xf8,0x00,0x02,0x00, +0x58,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; -const uint64_t matmul_q6_k_f32_aligned_fp32_len = 11592; +const uint64_t matmul_q8_0_f32_len = 10608; -unsigned char matmul_q6_k_f32_fp32_data[] = { +unsigned char matmul_q8_0_f32_aligned_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x3d,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, -0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, +0x14,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30, 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+0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, }; -const uint64_t mul_mat_vec_q5_1_f32_len = 3592; +const uint64_t mul_mat_vec_q5_K_f32_f32_len = 12776; -unsigned char mul_mat_vec_q5_K_f32_data[] = { +unsigned char mul_mat_vec_q6_K_f16_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0x8a,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xee,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30, 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00, +0x01,0x00,0x00,0x00,0x0f,0x00,0x0d,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x20,0x00,0x00,0x00, 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mul_mat_vec_q5_K_f32_len = 12016; +const uint64_t mul_mat_vec_q6_K_f16_f32_len = 11960; -unsigned char mul_mat_vec_q6_K_f32_data[] = { +unsigned char mul_mat_vec_q6_K_f32_f32_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, -0xc5,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, +0xde,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x27,0x00,0x00,0x00, 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x11,0x00,0x02,0x00, 0x60,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00, 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30, 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00, +0x01,0x00,0x00,0x00,0x0f,0x00,0x0d,0x00,0x05,0x00,0x00,0x00, 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00, -0x0b,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x20,0x00,0x00,0x00, -0x53,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x8f,0x00,0x00,0x00, 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+0x29,0x00,0x00,0x00,0x36,0x00,0x00,0x00,0x9a,0x00,0x00,0x00, 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00, 0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00, @@ -66970,15 +74183,15 @@ unsigned char norm_f32_data[] = { 0x34,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, 0x36,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x47,0x00,0x04,0x00,0x36,0x00,0x00,0x00,0x21,0x00,0x00,0x00, -0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x94,0x00,0x00,0x00, +0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00, 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00, -0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, -0x48,0x00,0x05,0x00,0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x98,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00, +0x48,0x00,0x05,0x00,0x98,0x00,0x00,0x00,0x00,0x00,0x00,0x00, 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00, -0x95,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, -0x97,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, -0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0x21,0x00,0x00,0x00, -0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xad,0x00,0x00,0x00, +0x98,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00, +0x9a,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00, +0x47,0x00,0x04,0x00,0x9a,0x00,0x00,0x00,0x21,0x00,0x00,0x00, +0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb0,0x00,0x00,0x00, 0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00, 0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00, 0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00, @@ -67026,138 +74239,142 @@ unsigned char norm_f32_data[] = { 0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x2a,0x00,0x00,0x00, 0x56,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x2b,0x00,0x04,0x00, 0x2a,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x01,0x00,0x00,0x00, -0x2b,0x00,0x04,0x00,0x14,0x00,0x00,0x00,0x86,0x00,0x00,0x00, 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+0x46,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x31,0x01,0x00,0x00, +0x3e,0x00,0x03,0x00,0x44,0x01,0x00,0x00,0x46,0x01,0x00,0x00, +0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00, +0x51,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0xf9,0x00,0x02,0x00, +0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x36,0x01,0x00,0x00, +0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00, +}; +const uint64_t soft_max_f32_f16_len = 5000; + unsigned char split_k_reduce_data[] = { 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00, 0x50,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00, diff --git a/ggml-vulkan.cpp b/ggml-vulkan.cpp index f712cdd5a900e..95f7189740539 100644 --- a/ggml-vulkan.cpp +++ b/ggml-vulkan.cpp @@ -120,8 +120,16 @@ struct vk_device { vk_matmul_pipeline pipeline_dequant_mul_mat_mat[VK_NUM_TYPES]; + vk_matmul_pipeline pipeline_matmul_id_f32; + vk_matmul_pipeline pipeline_matmul_id_f16; + vk_matmul_pipeline pipeline_matmul_id_f16_f32; + + vk_matmul_pipeline pipeline_dequant_mul_mat_mat_id[VK_NUM_TYPES]; + vk_pipeline pipeline_dequant[VK_NUM_TYPES]; - vk_pipeline pipeline_dequant_mul_mat_vec_f32[VK_NUM_TYPES]; + vk_pipeline pipeline_dequant_mul_mat_vec_f32_f32[VK_NUM_TYPES]; + vk_pipeline pipeline_dequant_mul_mat_vec_f16_f32[VK_NUM_TYPES]; + vk_pipeline pipeline_dequant_mul_mat_vec_id_f32[VK_NUM_TYPES]; vk_pipeline pipeline_mul_mat_vec_p021_f16_f32; vk_pipeline pipeline_mul_mat_vec_nc_f16_f32; @@ -139,7 +147,7 @@ struct vk_device { vk_pipeline pipeline_silu_f32; vk_pipeline pipeline_relu_f32; vk_pipeline pipeline_diag_mask_inf_f32; - vk_pipeline pipeline_soft_max_f32; + vk_pipeline pipeline_soft_max_f32, pipeline_soft_max_f32_f16; vk_pipeline pipeline_rope_f32, pipeline_rope_f16; vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16; vk_pipeline pipeline_argsort_f32; @@ -215,6 +223,21 @@ struct vk_submission { typedef std::vector<vk_submission> vk_sequence; +struct vk_mat_mat_push_constants { + uint32_t M; uint32_t N; uint32_t K; + uint32_t stride_a; uint32_t stride_b; uint32_t stride_d; uint32_t k_split; + uint32_t ne02; uint32_t ne12; uint32_t broadcast2; uint32_t broadcast3; + uint32_t batch_stride_a; uint32_t batch_stride_b; uint32_t batch_stride_d; + uint32_t expert_stride_b; uint32_t expert_stride_d; + uint32_t idx; uint32_t nbi1; uint32_t n_as; +}; + +struct vk_mat_vec_push_constants { + uint32_t ncols; uint32_t stride_a; uint32_t stride_b; uint32_t stride_d; + uint32_t ne02; uint32_t ne12; uint32_t broadcast2; uint32_t broadcast3; + uint32_t batch_stride_a; uint32_t batch_stride_b; uint32_t batch_stride_d; +}; + struct vk_op_push_constants { uint32_t KX; uint32_t KY; @@ -1003,201 +1026,422 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) { ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K] = std::make_shared<vk_matmul_pipeline_struct>(); ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K] = std::make_shared<vk_matmul_pipeline_struct>(); + /*ctx->device->pipeline_matmul_id_f32 = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_matmul_id_f16_f32 = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_matmul_id_f16 = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K] = std::make_shared<vk_matmul_pipeline_struct>(); + ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K] = std::make_shared<vk_matmul_pipeline_struct>();*/ + if (device->fp16) { - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_len, matmul_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_len, matmul_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_len, matmul_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_len, matmul_f16_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_len, matmul_f16_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_len, matmul_f16_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_0_f32_l", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_0_f32_m", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_0_f32_s", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_len, matmul_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_len, matmul_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_len, matmul_f16_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_len, matmul_f16_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_len, matmul_q4_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_len, matmul_q4_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_0_f32_l", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_0_f32_m", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_0_f32_s", matmul_q4_1_f32_len, matmul_q4_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_1_f32_aligned_len, matmul_q4_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_len, matmul_q5_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_len, matmul_q5_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_len, matmul_q5_1_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_len, matmul_q5_1_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_len, matmul_q8_0_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_len, matmul_q8_0_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_len, matmul_q2_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_len, matmul_q2_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_len, matmul_q3_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_len, matmul_q3_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_len, matmul_q4_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_len, matmul_q4_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_len, matmul_q5_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_len, matmul_q5_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_len, matmul_q6_k_f32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_len, matmul_q6_k_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->l, "matmul_id_f32_l", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->m, "matmul_id_f32_m", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->s, "matmul_id_f32_s", matmul_id_f32_len, matmul_id_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_l, "matmul_id_f32_aligned_l", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_m, "matmul_id_f32_aligned_m", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_s, "matmul_id_f32_aligned_s", matmul_id_f32_aligned_len, matmul_id_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->l, "matmul_id_f16_l", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->m, "matmul_id_f16_m", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->s, "matmul_id_f16_s", matmul_id_f16_len, matmul_id_f16_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_l, "matmul_id_f16_aligned_l", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_m, "matmul_id_f16_aligned_m", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_s, "matmul_id_f16_aligned_s", matmul_id_f16_aligned_len, matmul_id_f16_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->l, "matmul_id_f16_f32_l", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->m, "matmul_id_f16_f32_m", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->s, "matmul_id_f16_f32_s", matmul_id_f16_f32_len, matmul_id_f16_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_l, "matmul_id_f16_f32_aligned_l", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_m, "matmul_id_f16_f32_aligned_m", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_s, "matmul_id_f16_f32_aligned_s", matmul_id_f16_f32_aligned_len, matmul_id_f16_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_0_f32_len, matmul_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_0_f32_aligned_len, matmul_id_q4_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_1_f32_len, matmul_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_1_f32_aligned_len, matmul_id_q4_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->l, "matmul_id_q5_0_f32_l", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->m, "matmul_id_q5_0_f32_m", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->s, "matmul_id_q5_0_f32_s", matmul_id_q5_0_f32_len, matmul_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_l, "matmul_id_q5_0_f32_aligned_l", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_m, "matmul_id_q5_0_f32_aligned_m", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_s, "matmul_id_q5_0_f32_aligned_s", matmul_id_q5_0_f32_aligned_len, matmul_id_q5_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->l, "matmul_id_q5_1_f32_l", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->m, "matmul_id_q5_1_f32_m", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->s, "matmul_id_q5_1_f32_s", matmul_id_q5_1_f32_len, matmul_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_l, "matmul_id_q5_1_f32_aligned_l", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_m, "matmul_id_q5_1_f32_aligned_m", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_s, "matmul_id_q5_1_f32_aligned_s", matmul_id_q5_1_f32_aligned_len, matmul_id_q5_1_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->l, "matmul_id_q8_0_f32_l", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->m, "matmul_id_q8_0_f32_m", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->s, "matmul_id_q8_0_f32_s", matmul_id_q8_0_f32_len, matmul_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_l, "matmul_id_q8_0_f32_aligned_l", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_m, "matmul_id_q8_0_f32_aligned_m", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_s, "matmul_id_q8_0_f32_aligned_s", matmul_id_q8_0_f32_aligned_len, matmul_id_q8_0_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->l, "matmul_id_q2_k_f32_l", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->m, "matmul_id_q2_k_f32_m", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->s, "matmul_id_q2_k_f32_s", matmul_id_q2_k_f32_len, matmul_id_q2_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_l, "matmul_id_q2_k_f32_aligned_l", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_m, "matmul_id_q2_k_f32_aligned_m", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_s, "matmul_id_q2_k_f32_aligned_s", matmul_id_q2_k_f32_aligned_len, matmul_id_q2_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->l, "matmul_id_q3_k_f32_l", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->m, "matmul_id_q3_k_f32_m", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->s, "matmul_id_q3_k_f32_s", matmul_id_q3_k_f32_len, matmul_id_q3_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_l, "matmul_id_q3_k_f32_aligned_l", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_m, "matmul_id_q3_k_f32_aligned_m", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_s, "matmul_id_q3_k_f32_aligned_s", matmul_id_q3_k_f32_aligned_len, matmul_id_q3_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->l, "matmul_id_q4_k_f32_l", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->m, "matmul_id_q4_k_f32_m", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->s, "matmul_id_q4_k_f32_s", matmul_id_q4_k_f32_len, matmul_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_l, "matmul_id_q4_k_f32_aligned_l", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_m, "matmul_id_q4_k_f32_aligned_m", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_s, "matmul_id_q4_k_f32_aligned_s", matmul_id_q4_k_f32_aligned_len, matmul_id_q4_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->l, "matmul_id_q5_k_f32_l", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->m, "matmul_id_q5_k_f32_m", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->s, "matmul_id_q5_k_f32_s", matmul_id_q5_k_f32_len, matmul_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_l, "matmul_id_q5_k_f32_aligned_l", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_m, "matmul_id_q5_k_f32_aligned_m", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_s, "matmul_id_q5_k_f32_aligned_s", matmul_id_q5_k_f32_aligned_len, matmul_id_q5_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->l, "matmul_id_q6_k_f32_l", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->m, "matmul_id_q6_k_f32_m", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->s, "matmul_id_q6_k_f32_s", matmul_id_q6_k_f32_len, matmul_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_l, "matmul_id_q6_k_f32_aligned_l", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_m, "matmul_id_q6_k_f32_aligned_m", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_s, "matmul_id_q6_k_f32_aligned_s", matmul_id_q6_k_f32_aligned_len, matmul_id_q6_k_f32_aligned_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align);*/ } else { - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_1_f32_l", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_1_f32_m", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_1_f32_s", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_1_f32_aligned_l", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_1_f32_aligned_m", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_1_f32_aligned_s", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), l_wg_denoms, warptile_mmq_l, l_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), m_wg_denoms, warptile_mmq_m, m_align); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, 14 * sizeof(uint32_t), s_wg_denoms, warptile_mmq_s, s_align); - } - - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_F16 ], "mul_mat_vec_f16_f32", mul_mat_vec_f16_f32_len, mul_mat_vec_f16_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q4_0], "mul_mat_vec_q4_0_f32", mul_mat_vec_q4_0_f32_len, mul_mat_vec_q4_0_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q4_1], "mul_mat_vec_q4_1_f32", mul_mat_vec_q4_1_f32_len, mul_mat_vec_q4_1_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q5_0], "mul_mat_vec_q5_0_f32", mul_mat_vec_q5_0_f32_len, mul_mat_vec_q5_0_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q5_1], "mul_mat_vec_q5_1_f32", mul_mat_vec_q5_1_f32_len, mul_mat_vec_q5_1_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q8_0], "mul_mat_vec_q8_0_f32", mul_mat_vec_q8_0_f32_len, mul_mat_vec_q8_0_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q2_K], "mul_mat_vec_q2_K_f32", mul_mat_vec_q2_K_f32_len, mul_mat_vec_q2_K_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q3_K], "mul_mat_vec_q3_K_f32", mul_mat_vec_q3_K_f32_len, mul_mat_vec_q3_K_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q4_K], "mul_mat_vec_q4_K_f32", mul_mat_vec_q4_K_f32_len, mul_mat_vec_q4_K_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q5_K], "mul_mat_vec_q5_K_f32", mul_mat_vec_q5_K_f32_len, mul_mat_vec_q5_K_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); - ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32[GGML_TYPE_Q6_K], "mul_mat_vec_q6_K_f32", mul_mat_vec_q6_K_f32_len, mul_mat_vec_q6_K_f32_data, "main", 3, 3 * sizeof(uint32_t), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->l, "matmul_f32_l", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->m, "matmul_f32_m", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->s, "matmul_f32_s", matmul_f32_fp32_len, matmul_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_l, "matmul_f32_aligned_l", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_l, "matmul_f16_aligned_l", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_m, "matmul_f16_aligned_m", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->a_s, "matmul_f16_aligned_s", matmul_f16_aligned_fp32_len, matmul_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->l, "matmul_f16_f32_l", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->m, "matmul_f16_f32_m", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->s, "matmul_f16_f32_s", matmul_f16_f32_fp32_len, matmul_f16_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_l, "matmul_f16_f32_aligned_l", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_m, "matmul_f16_f32_aligned_m", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16_f32->a_s, "matmul_f16_f32_aligned_s", matmul_f16_f32_aligned_fp32_len, matmul_f16_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->l, "matmul_q4_0_f32_l", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->m, "matmul_q4_0_f32_m", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->s, "matmul_q4_0_f32_s", matmul_q4_0_f32_fp32_len, matmul_q4_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_l, "matmul_q4_0_f32_aligned_l", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_m, "matmul_q4_0_f32_aligned_m", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0]->a_s, "matmul_q4_0_f32_aligned_s", matmul_q4_0_f32_aligned_fp32_len, matmul_q4_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->l, "matmul_q4_1_f32_l", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->m, "matmul_q4_1_f32_m", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->s, "matmul_q4_1_f32_s", matmul_q4_1_f32_fp32_len, matmul_q4_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_l, "matmul_q4_1_f32_aligned_l", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_m, "matmul_q4_1_f32_aligned_m", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1]->a_s, "matmul_q4_1_f32_aligned_s", matmul_q4_1_f32_aligned_fp32_len, matmul_q4_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->l, "matmul_q5_0_f32_l", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->m, "matmul_q5_0_f32_m", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->s, "matmul_q5_0_f32_s", matmul_q5_0_f32_fp32_len, matmul_q5_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_l, "matmul_q5_0_f32_aligned_l", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_m, "matmul_q5_0_f32_aligned_m", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0]->a_s, "matmul_q5_0_f32_aligned_s", matmul_q5_0_f32_aligned_fp32_len, matmul_q5_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->l, "matmul_q5_1_f32_l", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->m, "matmul_q5_1_f32_m", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->s, "matmul_q5_1_f32_s", matmul_q5_1_f32_fp32_len, matmul_q5_1_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_l, "matmul_q5_1_f32_aligned_l", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_m, "matmul_q5_1_f32_aligned_m", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1]->a_s, "matmul_q5_1_f32_aligned_s", matmul_q5_1_f32_aligned_fp32_len, matmul_q5_1_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->l, "matmul_q8_0_f32_l", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->m, "matmul_q8_0_f32_m", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->s, "matmul_q8_0_f32_s", matmul_q8_0_f32_fp32_len, matmul_q8_0_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_l, "matmul_q8_0_f32_aligned_l", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_m, "matmul_q8_0_f32_aligned_m", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0]->a_s, "matmul_q8_0_f32_aligned_s", matmul_q8_0_f32_aligned_fp32_len, matmul_q8_0_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->l, "matmul_q2_k_f32_l", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->m, "matmul_q2_k_f32_m", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->s, "matmul_q2_k_f32_s", matmul_q2_k_f32_fp32_len, matmul_q2_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_l, "matmul_q2_k_f32_aligned_l", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_m, "matmul_q2_k_f32_aligned_m", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K]->a_s, "matmul_q2_k_f32_aligned_s", matmul_q2_k_f32_aligned_fp32_len, matmul_q2_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->l, "matmul_q3_k_f32_l", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->m, "matmul_q3_k_f32_m", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->s, "matmul_q3_k_f32_s", matmul_q3_k_f32_fp32_len, matmul_q3_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_l, "matmul_q3_k_f32_aligned_l", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_m, "matmul_q3_k_f32_aligned_m", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K]->a_s, "matmul_q3_k_f32_aligned_s", matmul_q3_k_f32_aligned_fp32_len, matmul_q3_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->l, "matmul_q4_k_f32_l", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->m, "matmul_q4_k_f32_m", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->s, "matmul_q4_k_f32_s", matmul_q4_k_f32_fp32_len, matmul_q4_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_l, "matmul_q4_k_f32_aligned_l", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_m, "matmul_q4_k_f32_aligned_m", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K]->a_s, "matmul_q4_k_f32_aligned_s", matmul_q4_k_f32_aligned_fp32_len, matmul_q4_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->l, "matmul_q5_k_f32_l", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->m, "matmul_q5_k_f32_m", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->s, "matmul_q5_k_f32_s", matmul_q5_k_f32_fp32_len, matmul_q5_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_l, "matmul_q5_k_f32_aligned_l", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_m, "matmul_q5_k_f32_aligned_m", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K]->a_s, "matmul_q5_k_f32_aligned_s", matmul_q5_k_f32_aligned_fp32_len, matmul_q5_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->l, "matmul_q6_k_f32_l", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->m, "matmul_q6_k_f32_m", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->s, "matmul_q6_k_f32_s", matmul_q6_k_f32_fp32_len, matmul_q6_k_f32_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_l, "matmul_q6_k_f32_aligned_l", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_m, "matmul_q6_k_f32_aligned_m", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K]->a_s, "matmul_q6_k_f32_aligned_s", matmul_q6_k_f32_aligned_fp32_len, matmul_q6_k_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->l, "matmul_id_f32_l", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->m, "matmul_id_f32_m", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->s, "matmul_id_f32_s", matmul_id_f32_fp32_len, matmul_id_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_l, "matmul_id_f32_aligned_l", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_m, "matmul_id_f32_aligned_m", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f32->a_s, "matmul_id_f32_aligned_s", matmul_id_f32_aligned_fp32_len, matmul_id_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->l, "matmul_id_f16_l", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->m, "matmul_id_f16_m", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->s, "matmul_id_f16_s", matmul_id_f16_fp32_len, matmul_id_f16_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_l, "matmul_id_f16_aligned_l", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_m, "matmul_id_f16_aligned_m", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16->a_s, "matmul_id_f16_aligned_s", matmul_id_f16_aligned_fp32_len, matmul_id_f16_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->l, "matmul_id_f16_f32_l", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->m, "matmul_id_f16_f32_m", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->s, "matmul_id_f16_f32_s", matmul_id_f16_f32_fp32_len, matmul_id_f16_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_l, "matmul_id_f16_f32_aligned_l", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_m, "matmul_id_f16_f32_aligned_m", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_id_f16_f32->a_s, "matmul_id_f16_f32_aligned_s", matmul_id_f16_f32_aligned_fp32_len, matmul_id_f16_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_0_f32_fp32_len, matmul_id_q4_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_0_f32_aligned_fp32_len, matmul_id_q4_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->l, "matmul_id_q4_0_f32_l", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->m, "matmul_id_q4_0_f32_m", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->s, "matmul_id_q4_0_f32_s", matmul_id_q4_1_f32_fp32_len, matmul_id_q4_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_l, "matmul_id_q4_0_f32_aligned_l", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_m, "matmul_id_q4_0_f32_aligned_m", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1]->a_s, "matmul_id_q4_0_f32_aligned_s", matmul_id_q4_1_f32_aligned_fp32_len, matmul_id_q4_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->l, "matmul_id_q5_0_f32_l", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->m, "matmul_id_q5_0_f32_m", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->s, "matmul_id_q5_0_f32_s", matmul_id_q5_0_f32_fp32_len, matmul_id_q5_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_l, "matmul_id_q5_0_f32_aligned_l", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_m, "matmul_id_q5_0_f32_aligned_m", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0]->a_s, "matmul_id_q5_0_f32_aligned_s", matmul_id_q5_0_f32_aligned_fp32_len, matmul_id_q5_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->l, "matmul_id_q5_1_f32_l", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->m, "matmul_id_q5_1_f32_m", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->s, "matmul_id_q5_1_f32_s", matmul_id_q5_1_f32_fp32_len, matmul_id_q5_1_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_l, "matmul_id_q5_1_f32_aligned_l", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_m, "matmul_id_q5_1_f32_aligned_m", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1]->a_s, "matmul_id_q5_1_f32_aligned_s", matmul_id_q5_1_f32_aligned_fp32_len, matmul_id_q5_1_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->l, "matmul_id_q8_0_f32_l", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->m, "matmul_id_q8_0_f32_m", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->s, "matmul_id_q8_0_f32_s", matmul_id_q8_0_f32_fp32_len, matmul_id_q8_0_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_l, "matmul_id_q8_0_f32_aligned_l", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_m, "matmul_id_q8_0_f32_aligned_m", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0]->a_s, "matmul_id_q8_0_f32_aligned_s", matmul_id_q8_0_f32_aligned_fp32_len, matmul_id_q8_0_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->l, "matmul_id_q2_k_f32_l", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->m, "matmul_id_q2_k_f32_m", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->s, "matmul_id_q2_k_f32_s", matmul_id_q2_k_f32_fp32_len, matmul_id_q2_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_l, "matmul_id_q2_k_f32_aligned_l", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_m, "matmul_id_q2_k_f32_aligned_m", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K]->a_s, "matmul_id_q2_k_f32_aligned_s", matmul_id_q2_k_f32_aligned_fp32_len, matmul_id_q2_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->l, "matmul_id_q3_k_f32_l", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->m, "matmul_id_q3_k_f32_m", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->s, "matmul_id_q3_k_f32_s", matmul_id_q3_k_f32_fp32_len, matmul_id_q3_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_l, "matmul_id_q3_k_f32_aligned_l", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_m, "matmul_id_q3_k_f32_aligned_m", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K]->a_s, "matmul_id_q3_k_f32_aligned_s", matmul_id_q3_k_f32_aligned_fp32_len, matmul_id_q3_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->l, "matmul_id_q4_k_f32_l", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->m, "matmul_id_q4_k_f32_m", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->s, "matmul_id_q4_k_f32_s", matmul_id_q4_k_f32_fp32_len, matmul_id_q4_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_l, "matmul_id_q4_k_f32_aligned_l", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_m, "matmul_id_q4_k_f32_aligned_m", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K]->a_s, "matmul_id_q4_k_f32_aligned_s", matmul_id_q4_k_f32_aligned_fp32_len, matmul_id_q4_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->l, "matmul_id_q5_k_f32_l", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->m, "matmul_id_q5_k_f32_m", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->s, "matmul_id_q5_k_f32_s", matmul_id_q5_k_f32_fp32_len, matmul_id_q5_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_l, "matmul_id_q5_k_f32_aligned_l", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_m, "matmul_id_q5_k_f32_aligned_m", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K]->a_s, "matmul_id_q5_k_f32_aligned_s", matmul_id_q5_k_f32_aligned_fp32_len, matmul_id_q5_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->l, "matmul_id_q6_k_f32_l", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->m, "matmul_id_q6_k_f32_m", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->s, "matmul_id_q6_k_f32_s", matmul_id_q6_k_f32_fp32_len, matmul_id_q6_k_f32_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_l, "matmul_id_q6_k_f32_aligned_l", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_mmq_l, l_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_m, "matmul_id_q6_k_f32_aligned_m", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_mmq_m, m_align); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K]->a_s, "matmul_id_q6_k_f32_aligned_s", matmul_id_q6_k_f32_aligned_fp32_len, matmul_id_q6_k_f32_aligned_fp32_data, "main", 4, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_mmq_s, s_align);*/ + } + + // mul mat vec + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_F16 ], "mul_mat_vec_f16_f32_f32", mul_mat_vec_f16_f32_f32_len, mul_mat_vec_f16_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_0], "mul_mat_vec_q4_0_f32_f32", mul_mat_vec_q4_0_f32_f32_len, mul_mat_vec_q4_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_1], "mul_mat_vec_q4_1_f32_f32", mul_mat_vec_q4_1_f32_f32_len, mul_mat_vec_q4_1_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_0], "mul_mat_vec_q5_0_f32_f32", mul_mat_vec_q5_0_f32_f32_len, mul_mat_vec_q5_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_1], "mul_mat_vec_q5_1_f32_f32", mul_mat_vec_q5_1_f32_f32_len, mul_mat_vec_q5_1_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q8_0], "mul_mat_vec_q8_0_f32_f32", mul_mat_vec_q8_0_f32_f32_len, mul_mat_vec_q8_0_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q2_K], "mul_mat_vec_q2_K_f32_f32", mul_mat_vec_q2_K_f32_f32_len, mul_mat_vec_q2_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q3_K], "mul_mat_vec_q3_K_f32_f32", mul_mat_vec_q3_K_f32_f32_len, mul_mat_vec_q3_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_K], "mul_mat_vec_q4_K_f32_f32", mul_mat_vec_q4_K_f32_f32_len, mul_mat_vec_q4_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_K], "mul_mat_vec_q5_K_f32_f32", mul_mat_vec_q5_K_f32_f32_len, mul_mat_vec_q5_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q6_K], "mul_mat_vec_q6_K_f32_f32", mul_mat_vec_q6_K_f32_f32_len, mul_mat_vec_q6_K_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F16 ], "mul_mat_vec_f16_f16_f32", mul_mat_vec_f16_f16_f32_len, mul_mat_vec_f16_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_0], "mul_mat_vec_q4_0_f16_f32", mul_mat_vec_q4_0_f16_f32_len, mul_mat_vec_q4_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_1], "mul_mat_vec_q4_1_f16_f32", mul_mat_vec_q4_1_f16_f32_len, mul_mat_vec_q4_1_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_0], "mul_mat_vec_q5_0_f16_f32", mul_mat_vec_q5_0_f16_f32_len, mul_mat_vec_q5_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_1], "mul_mat_vec_q5_1_f16_f32", mul_mat_vec_q5_1_f16_f32_len, mul_mat_vec_q5_1_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q8_0], "mul_mat_vec_q8_0_f16_f32", mul_mat_vec_q8_0_f16_f32_len, mul_mat_vec_q8_0_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q2_K], "mul_mat_vec_q2_K_f16_f32", mul_mat_vec_q2_K_f16_f32_len, mul_mat_vec_q2_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q3_K], "mul_mat_vec_q3_K_f16_f32", mul_mat_vec_q3_K_f16_f32_len, mul_mat_vec_q3_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_K], "mul_mat_vec_q4_K_f16_f32", mul_mat_vec_q4_K_f16_f32_len, mul_mat_vec_q4_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_K], "mul_mat_vec_q5_K_f16_f32", mul_mat_vec_q5_K_f16_f32_len, mul_mat_vec_q5_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q6_K], "mul_mat_vec_q6_K_f16_f32", mul_mat_vec_q6_K_f16_f32_len, mul_mat_vec_q6_K_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + + /*ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_F16 ], "mul_mat_vec_id_f16_f32", mul_mat_vec_id_f16_f32_len, mul_mat_vec_id_f16_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_0], "mul_mat_vec_id_q4_0_f32", mul_mat_vec_id_q4_0_f32_len, mul_mat_vec_id_q4_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_1], "mul_mat_vec_id_q4_1_f32", mul_mat_vec_id_q4_1_f32_len, mul_mat_vec_id_q4_1_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_0], "mul_mat_vec_id_q5_0_f32", mul_mat_vec_id_q5_0_f32_len, mul_mat_vec_id_q5_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_1], "mul_mat_vec_id_q5_1_f32", mul_mat_vec_id_q5_1_f32_len, mul_mat_vec_id_q5_1_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q8_0], "mul_mat_vec_id_q8_0_f32", mul_mat_vec_id_q8_0_f32_len, mul_mat_vec_id_q8_0_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q2_K], "mul_mat_vec_id_q2_K_f32", mul_mat_vec_id_q2_K_f32_len, mul_mat_vec_id_q2_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q3_K], "mul_mat_vec_id_q3_K_f32", mul_mat_vec_id_q3_K_f32_len, mul_mat_vec_id_q3_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_K], "mul_mat_vec_id_q4_K_f32", mul_mat_vec_id_q4_K_f32_len, mul_mat_vec_id_q4_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_K], "mul_mat_vec_id_q5_K_f32", mul_mat_vec_id_q5_K_f32_len, mul_mat_vec_id_q5_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q6_K], "mul_mat_vec_id_q6_K_f32", mul_mat_vec_id_q6_K_f32_len, mul_mat_vec_id_q6_K_f32_data, "main", 4, sizeof(vk_mat_vec_push_constants), {1, 1, 1}, { device->subgroup_size }, 1);*/ // dequant shaders ggml_vk_create_pipeline(ctx, ctx->device->pipeline_dequant[GGML_TYPE_F32 ], "f32_to_f16", dequant_f32_len, dequant_f32_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1); @@ -1258,6 +1502,7 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) { ggml_vk_create_pipeline(ctx, ctx->device->pipeline_diag_mask_inf_f32, "diag_mask_inf_f32", diag_mask_inf_f32_len, diag_mask_inf_f32_data, "main", 2, sizeof(vk_op_diag_mask_push_constants), {512, 1, 1}, {}, 1); ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32, "soft_max_f32", soft_max_f32_len, soft_max_f32_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1); + ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32_f16, "soft_max_f32_f16", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1); ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f32, "rope_f32", rope_f32_len, rope_f32_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1); ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f16, "rope_f16", rope_f16_len, rope_f16_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1); @@ -1686,11 +1931,48 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte return ctx->device->pipeline_dequant_mul_mat_mat[src0_type]; } -static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec(ggml_backend_vk_context * ctx, ggml_type type) { +static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_context * ctx, ggml_type src0_type, ggml_type src1_type) { +#ifdef GGML_VULKAN_DEBUG + std::cerr << "ggml_vk_get_mul_mat_mat_id_pipeline()" << std::endl; +#endif + if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) { + return ctx->device->pipeline_matmul_id_f32; + } + if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) { + return ctx->device->pipeline_matmul_id_f16_f32; + } + if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F16) { + return ctx->device->pipeline_matmul_id_f16; + } + + GGML_ASSERT(src1_type == GGML_TYPE_F32); + + switch (src0_type) { + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_Q8_0: + case GGML_TYPE_Q2_K: + case GGML_TYPE_Q3_K: + case GGML_TYPE_Q4_K: + case GGML_TYPE_Q5_K: + case GGML_TYPE_Q6_K: + break; + default: + return nullptr; + } + + return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type]; +} + +static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec(ggml_backend_vk_context * ctx, ggml_type a_type, ggml_type b_type) { #ifdef GGML_VULKAN_DEBUG std::cerr << "ggml_vk_get_dequantize_mul_mat_vec()" << std::endl; #endif - switch (type) { + GGML_ASSERT(b_type == GGML_TYPE_F32 || b_type == GGML_TYPE_F16); + + switch (a_type) { case GGML_TYPE_F16: case GGML_TYPE_Q4_0: case GGML_TYPE_Q4_1: @@ -1707,7 +1989,7 @@ static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec(ggml_backend_vk_context * return nullptr; } - return ctx->device->pipeline_dequant_mul_mat_vec_f32[type]; + return b_type == GGML_TYPE_F32 ? ctx->device->pipeline_dequant_mul_mat_vec_f32_f32[a_type] : ctx->device->pipeline_dequant_mul_mat_vec_f16_f32[a_type]; } static vk_buffer ggml_vk_pool_malloc(ggml_backend_vk_context * ctx, size_t size) { @@ -1913,6 +2195,9 @@ static void ggml_vk_ctx_begin(ggml_backend_vk_context * ctx, vk_context * subctx } static size_t ggml_vk_align_size(size_t width, size_t align) { +#ifdef GGML_VULKAN_DEBUG + std::cerr << "ggml_vk_align_size(" << width << ", " << align << ")" << std::endl; +#endif return CEIL_DIV(width, align) * align; } @@ -2368,11 +2653,13 @@ static uint32_t ggml_vk_guess_split_k(int m, int n, int k) { #ifdef GGML_VULKAN_DEBUG std::cerr << "ggml_vk_guess_split_k(" << m << ", " << n << ", " << k << ")" << std::endl; #endif - if (k > 128 && (m < 128 || n < 128) && m > 2 && n > 2) { - return 4; - } + // if (k > 128 && (m < 128 || n < 128) && m > 2 && n > 2) { + // return 4; + // } return 1; + + GGML_UNUSED(m); GGML_UNUSED(n); GGML_UNUSED(k); } static vk_pipeline ggml_vk_guess_matmul_pipeline_amd(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, bool aligned) { @@ -2424,25 +2711,58 @@ static uint32_t ggml_vk_guess_matmul_pipeline_align(ggml_backend_vk_context * ct #ifdef GGML_VULKAN_DEBUG std::cerr << "ggml_vk_guess_matmul_pipeline_align(" << m << ", " << n << ")" << std::endl; #endif - return ggml_vk_guess_matmul_pipeline(ctx, mmp, m, n, false)->align; + return ggml_vk_guess_matmul_pipeline(ctx, mmp, m, n, true)->align; +} + +static void ggml_vk_matmul( + ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, + vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& split_k_buffer, + uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, + uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, + uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d, + uint32_t expert_stride_b, uint32_t expert_stride_d, uint32_t idx, uint32_t nbi1, uint32_t n_as) { +#ifdef GGML_VULKAN_DEBUG + std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << split_k_buffer.buffer->buffer << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl; +#endif + ggml_vk_sync_buffers(subctx); + if (split_k == 1) { + const vk_mat_mat_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, k, ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; + ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, d }, sizeof(vk_mat_mat_push_constants), &pc, { m, n, batch }); + return; + } + + GGML_ASSERT(batch_stride_d == m * n); + + const vk_mat_mat_push_constants pc1 = { m, n, k, stride_a, stride_b, stride_d, CEIL_DIV(k, split_k), ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; + // Make sure enough workgroups get assigned for split k to work + ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, split_k_buffer }, sizeof(vk_mat_mat_push_constants), &pc1, { (CEIL_DIV(m, pipeline->wg_denoms[0]) * pipeline->wg_denoms[0]) * split_k, n, batch }); + ggml_vk_sync_buffers(subctx); + const std::array<uint32_t, 2> pc2 = { (uint32_t)(m * n * batch), split_k }; + ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_matmul_split_k_reduce, { split_k_buffer, d }, pc2.size() * sizeof(uint32_t), pc2.data(), { m * n * batch, 1, 1 }); } -static void ggml_vk_matmul(ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, vk_subbuffer&& a, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& split_k_buffer, uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d) { +static void ggml_vk_matmul_id( + ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline& pipeline, + vk_subbuffer&& ids, vk_subbuffer&& b, vk_subbuffer&& d, vk_subbuffer&& a, vk_subbuffer&& split_k_buffer, + uint32_t m, uint32_t n, uint32_t k, uint32_t stride_a, uint32_t stride_b, uint32_t stride_d, + uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3, + uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d, + uint32_t expert_stride_b, uint32_t expert_stride_d, uint32_t idx, uint32_t nbi1, uint32_t n_as) { #ifdef GGML_VULKAN_DEBUG std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << split_k_buffer.buffer->buffer << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl; #endif ggml_vk_sync_buffers(subctx); if (split_k == 1) { - const std::array<uint32_t, 14> pc = { m, n, k, stride_a, stride_b, stride_d, k, ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d }; - ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, d }, pc.size() * sizeof(uint32_t), pc.data(), { m, n, batch }); + const vk_mat_mat_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, k, ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; + ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { ids, b, d, a }, sizeof(vk_mat_mat_push_constants), &pc, { m, n, batch }); return; } GGML_ASSERT(batch_stride_d == m * n); - const std::array<uint32_t, 14> pc1 = { m, n, k, stride_a, stride_b, stride_d, CEIL_DIV(k, split_k), ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d }; + const vk_mat_mat_push_constants pc1 = { m, n, k, stride_a, stride_b, stride_d, CEIL_DIV(k, split_k), ne02, ne12, broadcast2, broadcast3, batch_stride_a, batch_stride_b, batch_stride_d, expert_stride_b, expert_stride_d, idx, nbi1, n_as }; // Make sure enough workgroups get assigned for split k to work - ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { a, b, split_k_buffer }, pc1.size() * sizeof(uint32_t), pc1.data(), { (CEIL_DIV(m, pipeline->wg_denoms[0]) * pipeline->wg_denoms[0]) * split_k, n, batch }); + ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { ids, b, split_k_buffer, a }, sizeof(vk_mat_mat_push_constants), &pc1, { (CEIL_DIV(m, pipeline->wg_denoms[0]) * pipeline->wg_denoms[0]) * split_k, n, batch }); ggml_vk_sync_buffers(subctx); const std::array<uint32_t, 2> pc2 = { (uint32_t)(m * n * batch), split_k }; ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_matmul_split_k_reduce, { split_k_buffer, d }, pc2.size() * sizeof(uint32_t), pc2.data(), { m * n * batch, 1, 1 }); @@ -2557,7 +2877,7 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context * su const int d_ne = ne11 * ne01; const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11)); - const bool aligned = ne10 == kpad; + const bool aligned = ne10 == kpad && ne01 > 8 && ne11 > 8; const uint32_t split_k = ggml_vk_guess_split_k(ne01, ne11, ne10); @@ -2655,7 +2975,13 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context * su } // compute - ggml_vk_matmul(ctx, subctx, pipeline, { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, { d_D, d_buf_offset, d_sz * ne12 * ne13 }, { ctx->prealloc_split_k, 0, d_sz * ne12 * ne13 * split_k }, ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21); // NOLINT + ggml_vk_matmul( + ctx, subctx, pipeline, + { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, + { d_D, d_buf_offset, d_sz * ne12 * ne13 }, { ctx->prealloc_split_k, 0, d_sz * ne12 * ne13 * split_k }, + ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21, + 0, 0, 0, 0, 1 + ); // NOLINT if (dst->backend == GGML_BACKEND_TYPE_CPU) { // copy dst to host @@ -2685,8 +3011,10 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context GGML_ASSERT(ne11 == 1); - const uint64_t nb2 = dst->nb[2]; - const uint64_t nb3 = dst->nb[3]; + const uint64_t ne20 = dst->ne[0]; + const uint64_t ne21 = dst->ne[1]; + const uint64_t ne22 = dst->ne[2]; + const uint64_t ne23 = dst->ne[3]; const uint64_t r2 = ne12 / ne02; const uint64_t r3 = ne13 / ne03; @@ -2718,6 +3046,9 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context const bool qx_needs_dequant = x_non_contig; const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !f16_f32_kernel) || y_non_contig; + // Not implemented + GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT + const uint64_t x_ne = ne01 * ne00; const uint64_t y_ne = ne11 * ne10; const uint64_t d_ne = ne11 * ne01; @@ -2770,7 +3101,7 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context } else { to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); } - vk_pipeline dmmv = ggml_vk_get_dequantize_mul_mat_vec(ctx, src0->type); + vk_pipeline dmmv = ggml_vk_get_dequantize_mul_mat_vec(ctx, src0->type, src1->type); GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT GGML_ASSERT(dmmv != nullptr); @@ -2793,43 +3124,25 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); } - for (uint64_t i13 = 0; i13 < ne13; i13++) { - const uint64_t i03 = i13 / r3; - for (uint64_t i12 = 0; i12 < ne12; i12++) { - const uint64_t i02 = i12 / r2; - - const uint64_t it_idx0 = (i03 * ne02 + i02); - const uint64_t it_idx1 = (i13 * ne12 + i12); - const uint64_t x_offset = x_buf_offset + x_sz * it_idx0; - const uint64_t qy_offset = qy_buf_offset + qy_sz * it_idx1; - const uint64_t y_offset = y_buf_offset + y_sz * it_idx1; - const uint64_t d_offset = d_buf_offset + d_sz * it_idx1; - - const uint64_t y_buffer_offset = (y_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; - const uint64_t y_shader_offset = y_offset - y_buffer_offset; - - const uint64_t d_buffer_offset = (d_offset / ctx->device->properties.limits.minStorageBufferOffsetAlignment) * ctx->device->properties.limits.minStorageBufferOffsetAlignment; - const uint64_t d_shader_offset = d_offset - d_buffer_offset; - - if (!y_non_contig && qy_needs_dequant) { - const std::vector<uint32_t> pc = { (uint32_t)ne11, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)(y_ne / 32) }; - ggml_vk_sync_buffers(subctx); - ggml_vk_dispatch_pipeline(ctx, subctx, to_fp16_vk_1, { { d_Qy, qy_offset, qy_sz }, { d_Y, y_offset, y_sz } }, pc.size() * sizeof(uint32_t), pc.data(), { (uint32_t)y_ne, 1, 1}); - } + uint32_t stride_batch_x = ne00*ne01; + uint32_t stride_batch_y = ne10*ne11; - // compute - const std::array<uint32_t, 3> pc = { (uint32_t)ne00, (uint32_t)(y_shader_offset / ggml_type_size(src1->type)), (uint32_t)(d_shader_offset / ggml_type_size(dst->type))}; - ggml_vk_sync_buffers(subctx); - ggml_vk_dispatch_pipeline(ctx, subctx, dmmv, { { d_X, x_offset, x_sz }, { d_Y, y_buffer_offset, y_sz + y_shader_offset }, { d_D, d_buffer_offset, d_sz + d_shader_offset } }, 3 * sizeof(int), &pc, { (uint32_t)ne01, 1, 1}); + if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { + stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); + } - if (dst->backend == GGML_BACKEND_TYPE_CPU) { - // copy dst to host - float * d = (float *) ((char *) dst->data + i12*nb2 + i13*nb3); - ggml_vk_sync_buffers(subctx); - ggml_vk_buffer_read_async(ctx, subctx, d_D, d_offset, d, sizeof(float) * d_ne); - } - } + if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { + stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); } + + // compute + const vk_mat_vec_push_constants pc = { + (uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01, + (uint32_t)ne02, (uint32_t)ne12, (uint32_t)r2, (uint32_t)r3, + stride_batch_x, stride_batch_y, (uint32_t)(ne20*ne21), + }; + ggml_vk_sync_buffers(subctx); + ggml_vk_dispatch_pipeline(ctx, subctx, dmmv, { { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, { d_D, d_buf_offset, d_sz * ne22 * ne23} }, sizeof(vk_mat_vec_push_constants), &pc, { (uint32_t)ne01, (uint32_t)(ne12 * ne13), 1}); } static void ggml_vk_mul_mat_vec_p021_f16_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { @@ -3011,7 +3324,7 @@ static bool ggml_vk_can_mul_mat(const ggml_tensor * src0, const ggml_tensor * sr ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32) || src0->backend == GGML_BACKEND_TYPE_GPU); } -static void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context * subctx, const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) { +static void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { #ifdef GGML_VULKAN_DEBUG std::cerr << "ggml_vk_mul_mat(" << src0 << ", " << src1 << ", " << dst << ")" << std::endl; #endif @@ -3026,9 +3339,347 @@ static void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context * subctx, } } -// static void ggml_vk_mul_mat_id(ggml_backend_vk_context * ctx, vk_context * subctx, const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) { -// -// } +/*static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * ids, ggml_tensor * dst) { +#ifdef GGML_VULKAN_DEBUG + std::cerr << "ggml_vk_mul_mat_id_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; + std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; + std::cerr << "), (" << ids << ", name=" << ids->name << ", type=" << ids->type << ", backend=" << ids->backend << ", ne0=" << ids->ne[0] << ", ne1=" << ids->ne[1] << ", ne2=" << ids->ne[2] << ", ne3=" << ids->ne[3] << ", nb0=" << ids->nb[0] << ", nb1=" << ids->nb[1] << ", nb2=" << ids->nb[2] << ", nb3=" << ids->nb[3]; + std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; +#endif + GGML_ASSERT(src0->type == GGML_TYPE_I32); + GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT + + const uint64_t ne00 = src0->ne[0]; + const uint64_t ne01 = src0->ne[1]; + const uint64_t ne02 = src0->ne[2]; + const uint64_t ne03 = src0->ne[3]; + + const uint64_t ne10 = src1->ne[0]; + const uint64_t ne11 = src1->ne[1]; + const uint64_t ne12 = src1->ne[2]; + const uint64_t ne13 = src1->ne[3]; + + const uint32_t nb11 = src1->nb[1]; + + const uint64_t ne20 = dst->ne[0]; + const uint64_t ne21 = dst->ne[1]; + + const uint64_t r2 = ne12 / ne02; + const uint64_t r3 = ne13 / ne03; + + const uint32_t nbi1 = src0->nb[1]; + const uint32_t idx = ((uint32_t *) dst->op_params)[0]; + const uint64_t n_as = ne02; + + GGML_ASSERT(n_as <= 8); + + ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; + ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; + ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; + ggml_tensor_extra_gpu * extra_ids = (ggml_tensor_extra_gpu *) ids->extra; + + vk_buffer d_Qx; + size_t qx_buf_offset = 0; + vk_buffer d_Qy; + size_t qy_buf_offset = 0; + + bool src0_uma = false; + bool src1_uma = false; + + if (ctx->device->uma) { + ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); + ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); + src0_uma = d_Qx != nullptr; + src1_uma = d_Qy != nullptr; + } + + const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); + const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); + + const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig; + + vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? GGML_TYPE_F16 : src1->type); + + const bool qx_needs_dequant = mmp == nullptr || x_non_contig; + const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig; + + if (mmp == nullptr) { + GGML_ASSERT(false); + } + + // Not implemented + GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT + + const int x_ne = ne01 * ne00; + const int y_ne = ne11 * ne10; + const int d_ne = ne11 * ne01; + + const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11)); + const bool aligned = ne10 == kpad && ne01 > 8 && ne11 > 8; + + const uint32_t split_k = ggml_vk_guess_split_k(ne01, ne11, ne10); + + vk_pipeline pipeline = ggml_vk_guess_matmul_pipeline(ctx, mmp, ne01, ne11, aligned); + + const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type); + const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); + const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne; + const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; + const uint64_t d_sz = sizeof(float) * d_ne; + + vk_buffer d_D = extra->buffer_gpu.lock(); + const uint64_t d_buf_offset = extra->offset; + GGML_ASSERT(d_D != nullptr); + GGML_ASSERT(d_D->size >= d_buf_offset + d_sz * ne02 * ne03); + vk_buffer d_X; + uint64_t x_buf_offset = 0; + vk_buffer d_Y; + uint64_t y_buf_offset = 0; + if (!src0_uma) { + d_Qx = extra_src0->buffer_gpu.lock(); + qx_buf_offset = extra_src0->offset; + GGML_ASSERT(d_Qx != nullptr); + } + if (!src1_uma) { + d_Qy = extra_src1->buffer_gpu.lock(); + qy_buf_offset = extra_src1->offset; + GGML_ASSERT(d_Qy != nullptr); + } + if (qx_needs_dequant) { + d_X = ctx->prealloc_x; + GGML_ASSERT(d_X->size >= x_sz * ne02 * ne03); + } else { + d_X = d_Qx; + x_buf_offset = qx_buf_offset; + GGML_ASSERT(qx_sz == x_sz); + } + if (qy_needs_dequant) { + d_Y = ctx->prealloc_y; + GGML_ASSERT(d_Y->size >= y_sz * ne02 * ne03); + } else { + d_Y = d_Qy; + y_buf_offset = qy_buf_offset; + GGML_ASSERT(qy_sz == y_sz); + } + + vk_pipeline to_fp16_vk_0 = nullptr; + vk_pipeline to_fp16_vk_1 = nullptr; + + if (x_non_contig) { + to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, GGML_TYPE_F16); + } else { + to_fp16_vk_0 = ggml_vk_get_to_fp16(ctx, src0->type); + } + if (y_non_contig) { + to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, GGML_TYPE_F16); + } else { + to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); + } + GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT + GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT + + // Allocate descriptor sets + ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, 1); + if (qx_needs_dequant) { + ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); + } + if (qy_needs_dequant) { + ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, 1); + } + if (split_k > 1) { + ggml_pipeline_allocate_descriptor_sets(ctx, ctx->device->pipeline_matmul_split_k_reduce, 1); + } + + if (x_non_contig) { + ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); + } else if (qx_needs_dequant) { + const std::vector<uint32_t> pc = { (uint32_t)ne01, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)(ggml_nelements(src0)) }; + ggml_vk_sync_buffers(subctx); + ggml_vk_dispatch_pipeline(ctx, subctx, to_fp16_vk_0, { { d_Qx, qx_buf_offset, qx_sz * ne02 * ne03 }, { d_X, 0, x_sz * ne02 * ne03 } }, pc.size() * sizeof(uint32_t), pc.data(), { (uint32_t)(x_ne * ne02 * ne03), 1, 1}); + } + if (y_non_contig) { + ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); + } + + uint32_t stride_batch_x = ne00*ne01; + uint32_t stride_batch_y = ne10*ne11; + + if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { + stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); + } + + if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { + stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); + } + + // compute + ggml_vk_matmul( + ctx, subctx, pipeline, + { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, + { d_D, d_buf_offset, d_sz * ne12 * ne13 }, { ctx->prealloc_split_k, 0, d_sz * ne12 * ne13 * split_k }, + ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21, + nb11 / ggml_type_size(src1->type), ne20, idx, nbi1, n_as + ); // NOLINT +} + +static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { +#ifdef GGML_VULKAN_DEBUG + std::cerr << "ggml_vk_mul_mat_vec_id_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3]; + std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3]; + std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl; +#endif + GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16); // NOLINT + GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); // NOLINT + + const uint64_t ne00 = src0->ne[0]; + const uint64_t ne01 = src0->ne[1]; + const uint64_t ne02 = src0->ne[2]; + const uint64_t ne03 = src0->ne[3]; + + const uint64_t ne10 = src1->ne[0]; + const uint64_t ne11 = src1->ne[1]; + const uint64_t ne12 = src1->ne[2]; + const uint64_t ne13 = src1->ne[3]; + + GGML_ASSERT(ne11 == 1); + + const uint64_t ne20 = dst->ne[0]; + const uint64_t ne21 = dst->ne[1]; + const uint64_t ne22 = dst->ne[2]; + const uint64_t ne23 = dst->ne[3]; + + const uint64_t nb22 = dst->nb[2]; + const uint64_t nb23 = dst->nb[3]; + + const uint64_t r2 = ne12 / ne02; + const uint64_t r3 = ne13 / ne03; + + ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; + ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; + ggml_tensor_extra_gpu * extra_src1 = (ggml_tensor_extra_gpu *) src1->extra; + + vk_buffer d_Qx; + size_t qx_buf_offset = 0; + vk_buffer d_Qy; + size_t qy_buf_offset = 0; + + bool src0_uma = false; + bool src1_uma = false; + + if (ctx->device->uma) { + ggml_vk_host_get(ctx, src0->data, d_Qx, qx_buf_offset); + ggml_vk_host_get(ctx, src1->data, d_Qy, qy_buf_offset); + src0_uma = d_Qx != nullptr; + src1_uma = d_Qy != nullptr; + } + + const bool x_non_contig = !ggml_vk_dim01_contiguous(src0); + const bool y_non_contig = !ggml_vk_dim01_contiguous(src1); + + const bool f16_f32_kernel = src1->type == GGML_TYPE_F32; + + const bool qx_needs_dequant = x_non_contig; + const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !f16_f32_kernel) || y_non_contig; + + // Not implemented + GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT + + const uint64_t x_ne = ne01 * ne00; + const uint64_t y_ne = ne11 * ne10; + const uint64_t d_ne = ne11 * ne01; + + const uint64_t qx_sz = ggml_vk_align_size(ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type), ctx->device->properties.limits.minStorageBufferOffsetAlignment); + const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type); + const uint64_t x_sz = x_non_contig ? ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment) : qx_sz; + const uint64_t y_sz = f16_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne; + const uint64_t d_sz = sizeof(float) * d_ne; + + vk_buffer d_D = extra->buffer_gpu.lock(); + const uint64_t d_buf_offset = extra->offset; + GGML_ASSERT(d_D != nullptr); + vk_buffer d_X; + uint64_t x_buf_offset = 0; + vk_buffer d_Y; + uint64_t y_buf_offset = 0; + if(!src0_uma) { + d_Qx = extra_src0->buffer_gpu.lock(); + qx_buf_offset = extra_src0->offset; + GGML_ASSERT(d_Qx != nullptr); + } + if(!src1_uma) { + d_Qy = extra_src1->buffer_gpu.lock(); + qy_buf_offset = extra_src1->offset; + GGML_ASSERT(d_Qy != nullptr); + } + if (qx_needs_dequant) { + d_X = ctx->prealloc_x; + } else { + d_X = d_Qx; + x_buf_offset = qx_buf_offset; + GGML_ASSERT(qx_sz == x_sz); + } + if (qy_needs_dequant) { + d_Y = ctx->prealloc_y; + } else { + d_Y = d_Qy; + y_buf_offset = qy_buf_offset; + GGML_ASSERT(qy_sz == y_sz); + } + + vk_pipeline to_fp16_vk_0 = nullptr; + vk_pipeline to_fp16_vk_1 = nullptr; + if (x_non_contig) { + to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0->type, src0->type); + } + if (y_non_contig) { + to_fp16_vk_1 = ggml_vk_get_cpy_pipeline(ctx, src1->type, src1->type); + } else { + to_fp16_vk_1 = ggml_vk_get_to_fp16(ctx, src1->type); + } + vk_pipeline dmmv = ggml_vk_get_dequantize_mul_mat_vec(ctx, src0->type, src1->type); + GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT + GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT + GGML_ASSERT(dmmv != nullptr); + + // Allocate descriptor sets + if (qx_needs_dequant) { + ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_0, 1); + } + if (qy_needs_dequant) { + ggml_pipeline_allocate_descriptor_sets(ctx, to_fp16_vk_1, y_non_contig ? 1 : ne12 * ne13); + } + ggml_pipeline_allocate_descriptor_sets(ctx, dmmv, ne12 * ne13); + + if (x_non_contig) { + GGML_ASSERT(x_sz == ggml_vk_align_size(ggml_type_size(src0->type) * x_ne, ctx->device->properties.limits.minStorageBufferOffsetAlignment)); + ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_0, src0, { d_Qx, qx_buf_offset, VK_WHOLE_SIZE }, { d_X, 0, VK_WHOLE_SIZE }); + } + if (y_non_contig) { + GGML_ASSERT(y_sz == ggml_type_size(src1->type) * y_ne); + ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }); + } + + uint32_t stride_batch_x = ne00*ne01; + uint32_t stride_batch_y = ne10*ne11; + + if (!ggml_vk_dim01_contiguous(src0) && !qx_needs_dequant) { + stride_batch_x = src0->nb[0] / ggml_type_size(src0->type); + } + + if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) { + stride_batch_y = src1->nb[0] / ggml_type_size(src1->type); + } + + // compute + const vk_mat_vec_push_constants pc = { + (uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01, + (uint32_t)ne02, (uint32_t)ne12, (uint32_t)r2, (uint32_t)r3, + stride_batch_x, stride_batch_y, (uint32_t)(ne20*ne21), + // 0, 0, 0, 0, 1 + }; + ggml_vk_sync_buffers(subctx); + ggml_vk_dispatch_pipeline(ctx, subctx, dmmv, { { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 }, { d_D, d_buf_offset, d_sz * ne22 * ne23} }, sizeof(vk_mat_vec_push_constants), &pc, { (uint32_t)ne01, (uint32_t)(ne12 * ne13), 1}); +}*/ static void ggml_vk_op_repeat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { // guaranteed to be an integer due to the check in ggml_can_repeat @@ -3178,14 +3829,15 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const } return nullptr; case GGML_OP_SOFT_MAX: -#pragma message("TODO: add ggml_vk_soft_max() F16 src1 and src2 support") -#pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/5021") - GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32); - GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F32); + GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); + GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F32 || src2->type == GGML_TYPE_F16); if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && (src2 == nullptr || src2->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) { return ctx->device->pipeline_soft_max_f32; } + if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16 && src2->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F32) { + return ctx->device->pipeline_soft_max_f32_f16; + } return nullptr; case GGML_OP_ROPE: { @@ -3233,6 +3885,21 @@ static ggml_vk_func_t ggml_vk_op_get_func(ggml_op op) { } } +static bool ggml_vk_op_supports_incontiguous(ggml_op op) { + switch (op) { + case GGML_OP_CPY: + case GGML_OP_GET_ROWS: + case GGML_OP_ADD: + case GGML_OP_MUL: + case GGML_OP_SCALE: + case GGML_OP_SQR: + case GGML_OP_CLAMP: + return true; + default: + return false; + } +} + template<typename PC> static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op, const PC&& pc) { #ifdef GGML_VULKAN_DEBUG @@ -3284,6 +3951,8 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c return; } + const bool op_supports_incontiguous = ggml_vk_op_supports_incontiguous(op); + ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra; ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra; ggml_tensor_extra_gpu * extra_src1 = use_src1 ? (ggml_tensor_extra_gpu *) src1->extra : nullptr; @@ -3345,7 +4014,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c GGML_ASSERT(d_Z != nullptr); } - if (op == GGML_OP_CPY || op == GGML_OP_GET_ROWS) { + if (op_supports_incontiguous) { x_sz = ggml_nbytes(src0); y_sz = use_src1 ? ggml_nbytes(src1) : 0; d_sz = ggml_nbytes(dst); @@ -3364,7 +4033,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c std::array<uint32_t, 3> elements; // Single call if dimension 2 is contiguous - if (op == GGML_OP_CPY || op == GGML_OP_GET_ROWS || (ggml_is_contiguous(src0) && (src1 == nullptr || ggml_is_contiguous(src1)))) { + if (op_supports_incontiguous || (ggml_is_contiguous(src0) && (src1 == nullptr || ggml_is_contiguous(src1)))) { ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, 1); switch (dst->op) { @@ -3385,7 +4054,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c break; } - if (op != GGML_OP_CPY && op != GGML_OP_GET_ROWS) { + if (!op_supports_incontiguous) { if (x_sz != VK_WHOLE_SIZE) { x_sz *= ne02 * ne03; } @@ -3403,14 +4072,14 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c if (use_src1) { subbuf_y = { d_Y, y_buf_offset, y_sz }; } else { - subbuf_y = { ctx->prealloc_y, 0, ctx->prealloc_y->size }; + subbuf_y = { d_X, 0, d_X->size }; } vk_subbuffer subbuf_z; if (use_src2) { subbuf_z = { d_Z, z_buf_offset, z_sz }; } else { - subbuf_z = { ctx->prealloc_y, 0, ctx->prealloc_y->size }; + subbuf_z = { d_X, 0, d_X->size }; } ggml_vk_sync_buffers(subctx); @@ -3582,7 +4251,9 @@ static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context * subctx, cons } static void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { - ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], 0.0f, 0.0f }); + float * op_params = (float *)dst->op_params; + + ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }); } static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) { @@ -3617,7 +4288,7 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx, ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, { ncols, - nrows_y, + src1 != nullptr ? nrows_y : (uint32_t)0, src2 != nullptr ? (uint32_t)1 : (uint32_t)0, scale, max_bias, m0, m1, @@ -3834,7 +4505,10 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); for (size_t i = 0; i < num_it; i++) { ggml_vk_ctx_begin(ctx, subctx); - ggml_vk_matmul(ctx, subctx, p, ggml_vk_subbuffer(d_X), ggml_vk_subbuffer(d_Y), ggml_vk_subbuffer(d_D), ggml_vk_subbuffer(ctx->prealloc_split_k), m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n); + ggml_vk_matmul( + ctx, subctx, p, ggml_vk_subbuffer(d_X), ggml_vk_subbuffer(d_Y), ggml_vk_subbuffer(d_D), ggml_vk_subbuffer(ctx->prealloc_split_k), + m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n, 0, 0, 0, 0, 1 + ); ggml_vk_ctx_end(subctx); } @@ -4339,7 +5013,10 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m, vk_context * subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue); for (size_t i = 0; i < num_it; i++) { ggml_vk_ctx_begin(ctx, subctx); - ggml_vk_matmul(ctx, subctx, p, ggml_vk_subbuffer(qx_buf), ggml_vk_subbuffer(y_buf), ggml_vk_subbuffer(d_buf), ggml_vk_subbuffer(ctx->prealloc_split_k), m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n); + ggml_vk_matmul( + ctx, subctx, p, ggml_vk_subbuffer(qx_buf), ggml_vk_subbuffer(y_buf), ggml_vk_subbuffer(d_buf), ggml_vk_subbuffer(ctx->prealloc_split_k), + m, n, k, k, k, m, split_k, batch, batch, batch, 1, 1, k*m, k*n, m*n, 0, 0, 0, 0, 1 + ); ggml_vk_ctx_end(subctx); } @@ -4590,6 +5267,8 @@ static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) { ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q5_K); ggml_vk_test_dequant(ctx, 7680, GGML_TYPE_Q6_K); + ggml_vk_test_matmul<ggml_fp16_t, ggml_fp16_t>(ctx, 512, 512, 100, 32, 100, 1, 2); + ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 0); ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 1); ggml_vk_test_matmul<float, float>(ctx, 128, 512, 512, 2, 100, 1, 2); @@ -4739,7 +5418,7 @@ static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) { } static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * node, bool last_node){ - if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU) { + if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(node)) { return; } @@ -5539,7 +6218,7 @@ GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backen int last_node = cgraph->n_nodes - 1; // If the last op in the cgraph isn't backend GPU, the command buffer doesn't get closed properly - while (last_node > 0 && cgraph->nodes[last_node]->backend != GGML_BACKEND_TYPE_GPU) { + while (last_node > 0 && (cgraph->nodes[last_node]->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(cgraph->nodes[last_node]))) { last_node -= 1; } @@ -5577,6 +6256,8 @@ GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backen } GGML_CALL static bool ggml_backend_vk_supports_op(ggml_backend_t backend, const ggml_tensor * op) { + // ggml_backend_vk_context * ctx = (ggml_backend_vk_context *) backend->context; + switch (op->op) { case GGML_OP_UNARY: switch (ggml_get_unary_op(op)) { @@ -6199,7 +6880,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_ tensor_clone = ggml_soft_max(ggml_ctx, src0_clone); } } else if (tensor->op == GGML_OP_DIAG_MASK_INF) { - tensor_clone = ggml_diag_mask_inf(ggml_ctx, src0_clone, *(float *)tensor->op_params); + tensor_clone = ggml_diag_mask_inf(ggml_ctx, src0_clone, *(int *)tensor->op_params); } else if (tensor->op == GGML_OP_ROPE) { const int n_dims = ((int32_t *) tensor->op_params)[1]; const int mode = ((int32_t *) tensor->op_params)[2]; @@ -6247,6 +6928,8 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_ tensor_clone = ggml_transpose(ggml_ctx, src0_clone); } else if (tensor->op == GGML_OP_GET_ROWS) { tensor_clone = ggml_get_rows(ggml_ctx, src0_clone, src1_clone); + } else if (tensor->op == GGML_OP_ARGSORT) { + tensor_clone = ggml_argsort(ggml_ctx, src0_clone, (ggml_sort_order) *(int *)tensor->op_params); } else { std::cerr << "Missing vk_check_results OP: " << ggml_op_name(tensor->op) << std::endl; GGML_ASSERT(false); @@ -6280,7 +6963,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_ free(src1_buffer); } if (src2 != nullptr) { - free(src1_buffer); + free(src2_buffer); } ggml_free(ggml_ctx); diff --git a/ggml_vk_generate_shaders.py b/ggml_vk_generate_shaders.py index 1d9a0cc82f704..162cf5c6ea9be 100644 --- a/ggml_vk_generate_shaders.py +++ b/ggml_vk_generate_shaders.py @@ -167,47 +167,54 @@ # Dequant functions shader_float_dequant_func = """ -#define DEQUANT_FUNC vec2 v = vec2(ib, ib); // data_a[ib], data_a[ib + 1]); +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + return vec2(data_a[a_offset + ib], data_a[a_offset + ib + 1]); +} """ shader_q4_0_dequant_func = """ -#define DEQUANT_FUNC const float d = float(data_a[ib].d); \ -const uint vui = uint(data_a[ib].qs[iqs]); \ -vec2 v = vec2(vui & 0xF, vui >> 4); \ -v = (v - 8.0f)*d; +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + const float d = float(data_a[a_offset + ib].d); + const uint vui = uint(data_a[a_offset + ib].qs[iqs]); + return (vec2(vui & 0xF, vui >> 4) - 8.0f) * d; +} """ shader_q4_1_dequant_func = """ -#define DEQUANT_FUNC const float d = float(data_a[ib].d); \ -const float m = float(data_a[ib].m); \ -const uint vui = uint(data_a[ib].qs[iqs]); \ -vec2 v = vec2(vui & 0xF, vui >> 4); \ -v = v*d + m; +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + const float d = float(data_a[a_offset + ib].d); + const float m = float(data_a[a_offset + ib].m); + const uint vui = uint(data_a[a_offset + ib].qs[iqs]); + return vec2(vui & 0xF, vui >> 4) * d + m; +} """ shader_q5_0_dequant_func = """ -#define DEQUANT_FUNC const float d = float(data_a[ib].d); \ -const uint uint_qh = uint(data_a[ib].qh[1]) << 16 | data_a[ib].qh[0]; \ -const ivec2 qh = ivec2(((uint_qh >> iqs) << 4) & 0x10, (uint_qh >> (iqs + 12)) & 0x10); \ -const uint vui = uint(data_a[ib].qs[iqs]); \ -vec2 v = vec2((vui & 0xF) | qh.x, (vui >> 4) | qh.y); \ -v = (v - 16.0f) * d; +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + const float d = float(data_a[a_offset + ib].d); + const uint uint_qh = uint(data_a[a_offset + ib].qh[1]) << 16 | data_a[a_offset + ib].qh[0]; + const ivec2 qh = ivec2(((uint_qh >> iqs) << 4) & 0x10, (uint_qh >> (iqs + 12)) & 0x10); + const uint vui = uint(data_a[a_offset + ib].qs[iqs]); + return (vec2((vui & 0xF) | qh.x, (vui >> 4) | qh.y) - 16.0f) * d; +} """ shader_q5_1_dequant_func = """ -#define DEQUANT_FUNC const float d = float(data_a[ib].d); \ -const float m = float(data_a[ib].m); \ -const uint uint_qh = data_a[ib].qh; \ -const ivec2 qh = ivec2(((uint_qh >> iqs) << 4) & 0x10, (uint_qh >> (iqs + 12)) & 0x10); \ -const uint vui = uint(data_a[ib].qs[iqs]); \ -vec2 v = vec2((vui & 0xF) | qh.x, (vui >> 4) | qh.y); \ -v = v*d + m; +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + const float d = float(data_a[a_offset + ib].d); + const float m = float(data_a[a_offset + ib].m); + const uint uint_qh = data_a[a_offset + ib].qh; + const ivec2 qh = ivec2(((uint_qh >> iqs) << 4) & 0x10, (uint_qh >> (iqs + 12)) & 0x10); + const uint vui = uint(data_a[a_offset + ib].qs[iqs]); + return vec2((vui & 0xF) | qh.x, (vui >> 4) | qh.y) * d + m; +} """ shader_q8_0_dequant_func = """ -#define DEQUANT_FUNC const float d = float(data_a[ib].d); \ -vec2 v = vec2(int(data_a[ib].qs[iqs]), int(data_a[ib].qs[iqs + 1])); \ -v = v * d; +vec2 dequantize(uint ib, uint iqs, uint a_offset) { + const float d = float(data_a[a_offset + ib].d); + return vec2(int(data_a[a_offset + ib].qs[iqs]), int(data_a[a_offset + ib].qs[iqs + 1])) * d; +} """ # MULMAT @@ -217,6 +224,15 @@ #extension GL_EXT_control_flow_attributes : enable #extension GL_EXT_shader_16bit_storage : require +#ifdef MUL_MAT_ID +#extension GL_EXT_buffer_reference2 : require +#extension GL_EXT_nonuniform_qualifier : require +#extension GL_EXT_scalar_block_layout : require +#extension GL_EXT_shader_explicit_arithmetic_types_int8 : require + +#define EXPERT_COUNT 8 +#endif + #ifndef LOAD_VEC_A #define LOAD_VEC_A 1 #endif @@ -232,6 +248,10 @@ layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; layout (binding = 2) writeonly buffer D {D_TYPE data_d[];}; +#ifdef MUL_MAT_ID +layout (binding = 3) readonly buffer IDS {int data_ids[];}; +#endif + layout (push_constant) uniform parameter { uint M; @@ -250,6 +270,21 @@ uint batch_stride_a; uint batch_stride_b; uint batch_stride_d; + +#ifdef MUL_MAT_ID + uint expert_stride_a; + uint expert_stride_b0; + uint expert_stride_b1; + uint expert_stride_d; + + uint ids_stride; + + uint n_as; + uint nei0; + uint nei1; + uint nbi1; + uint ne11; +#endif } p; layout (constant_id = 1) const uint BM = 64; @@ -265,9 +300,20 @@ shared FLOAT_TYPE buf_a[BM * (BK+1)]; shared FLOAT_TYPE buf_b[BN * (BK+1)]; +#ifdef MUL_MAT_ID +shared u8vec2 rowids[2048]; +#endif + void main() { - const uint i13 = gl_GlobalInvocationID.z / p.ne12; - const uint i12 = gl_GlobalInvocationID.z % p.ne12; +#ifdef MUL_MAT_ID + const uint batch_idx = gl_GlobalInvocationID.z / p.n_as; + const uint expert_idx = gl_GlobalInvocationID.z % p.n_as; +#else + const uint batch_idx = gl_GlobalInvocationID.z; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; const uint i03 = i13 / p.broadcast3; const uint i02 = i12 / p.broadcast2; @@ -299,11 +345,35 @@ const uint loadstride_a = gl_WorkGroupSize.x * LOAD_VEC_A / BK; const uint loadstride_b = gl_WorkGroupSize.x * LOAD_VEC_B / BK; +#ifdef MUL_MAT_ID + uint _ne1 = 0; + for (uint ii1 = 0; ii1 < p.nei1; ii1++) { + for (uint ii0 = 0; ii0 < p.nei0; ii0++) { + if (data_ids[ii1*p.nbi1 + ii0] == expert_idx) { + rowids[_ne1] = u8vec2(ii0, ii1); + _ne1++; + } + } + } + + const u8vec2 id = rowids[ir * BN + ic]; +#endif + const uint start_k = ik * p.k_split; const uint end_k = min(p.K, (ik + 1) * p.k_split); - uint pos_a = (batch_idx_a * p.batch_stride_a + ir * BM * p.stride_a + start_k) / LOAD_VEC_A; - uint pos_b = (gl_GlobalInvocationID.z * p.batch_stride_b + ic * BN * p.stride_b + start_k) / LOAD_VEC_B; + uint pos_a = ( +#ifdef MUL_MAT_ID + expert_idx * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a + ir * BM * p.stride_a + start_k) / LOAD_VEC_A; + uint pos_b = ( +#ifdef MUL_MAT_ID + id.y * p.expert_stride_b1 + + (id.x % p.ne11) * p.expert_stride_b0 + +#endif + batch_idx * p.batch_stride_b + + ic * BN * p.stride_b + start_k) / LOAD_VEC_B; float sums[WMITER * TM * WNITER * TN]; FLOAT_TYPE cache_a[WMITER * TM]; @@ -611,7 +681,11 @@ const uint dr = ir * BM + warp_r * WM; const uint dc = ic * BN + warp_c * WN; - const uint offsets = gl_GlobalInvocationID.z * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z; + const uint offsets = +#ifdef MUL_MAT_ID + expert_idx * p.expert_stride_d + +#endif + batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z; [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) { [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) { @@ -1077,21 +1151,54 @@ #extension GL_EXT_shader_16bit_storage : require #extension GL_EXT_shader_8bit_storage : require +#ifdef MUL_MAT_ID +#define EXPERT_COUNT 8 +#endif +""" + + +mul_mat_vec_layout = """ +layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; +layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; +layout (binding = 2) writeonly buffer D {D_TYPE data_d[];}; +#ifdef MUL_MAT_ID +layout (binding = 3) readonly buffer IDS {int data_ids[];}; +#endif + layout (push_constant) uniform parameter { uint ncols; - uint b_offset; - uint d_offset; + uint stride_a; + uint stride_b; + uint stride_d; + + uint ne02; + uint ne12; + uint broadcast2; + uint broadcast3; + + uint batch_stride_a; + uint batch_stride_b; + uint batch_stride_d; + +#ifdef MUL_MAT_ID + uint expert_stride_a; + uint expert_stride_b0; + uint expert_stride_b1; + uint expert_stride_d0; + uint expert_stride_d1; + + uint ne11; + uint nei0; + uint nbi1; + uint n_as; +#endif } p; """ mul_mat_vec_body = """ layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - layout (constant_id = 0) const uint BLOCK_SIZE = 32; shared FLOAT_TYPE tmp[BLOCK_SIZE]; @@ -1099,6 +1206,41 @@ void main() { const uint row = gl_WorkGroupID.x; const uint tid = gl_LocalInvocationID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint y_offset = QUANT_R == 1 ? 1 : QUANT_K/2; @@ -1110,11 +1252,11 @@ const uint iqs = (col%QUANT_K)/QUANT_R; // quant index const uint iybs = col - col%QUANT_K; // y block start index - DEQUANT_FUNC + vec2 v = dequantize(ib, iqs, a_offset / QUANT_K); // matrix multiplication - tmp[tid] += FLOAT_TYPE(v.x) * FLOAT_TYPE(data_b[p.b_offset + iybs + iqs + 0]) + - FLOAT_TYPE(v.y) * FLOAT_TYPE(data_b[p.b_offset + iybs + iqs + y_offset]); + tmp[tid] += FLOAT_TYPE(v.x) * FLOAT_TYPE(data_b[b_offset + iybs + iqs]) + + FLOAT_TYPE(v.y) * FLOAT_TYPE(data_b[b_offset + iybs + iqs + y_offset]); } // sum up partial sums and write back result @@ -1126,7 +1268,7 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ @@ -1135,17 +1277,48 @@ mul_mat_vec_q2_K_body = """ layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - shared FLOAT_TYPE tmp[32]; void main() { const uint row = gl_WorkGroupID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint num_blocks_per_row = p.ncols / QUANT_K; - const uint ib0 = row*num_blocks_per_row; + const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row; const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16 const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1 @@ -1171,22 +1344,22 @@ FLOAT_TYPE sum1 = FLOAT_TYPE(0.0); FLOAT_TYPE sum2 = FLOAT_TYPE(0.0); for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) { - sum1 += FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 0) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 16]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 1] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 0) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 2) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 48]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 3] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 2) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 4) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 80]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 5] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 4) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 6) & 3) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l +112]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 7] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 6) & 3); - sum2 += FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 0]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 0] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 16]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 1] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 32]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 2] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 48]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 3] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 64]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 4] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 80]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 5] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 96]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 6] >> 4) & 0xF) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l +112]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 7] >> 4) & 0xF); + sum1 += FLOAT_TYPE(data_b[b_offset + y_idx + l + 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 0) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 16]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 1] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 0) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 2) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 48]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 3] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 2) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 4) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 80]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 5] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 4) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l + 0] >> 6) & 3) + + FLOAT_TYPE(data_b[b_offset + y_idx + l +112]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 7] & 0xF) * FLOAT_TYPE((data_a[ib0 + i].qs[q_offset + l +16] >> 6) & 3); + sum2 += FLOAT_TYPE(data_b[b_offset + y_idx + l + 0]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 0] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 16]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 1] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 32]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 2] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 48]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 3] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 64]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 4] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 80]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 5] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 96]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 6] >> 4) & 0xF) + + FLOAT_TYPE(data_b[b_offset + y_idx + l +112]) * FLOAT_TYPE((data_a[ib0 + i].scales[s_offset + 7] >> 4) & 0xF); } tmp[16 * ix + tid] += dall * sum1 - dmin * sum2; } @@ -1200,24 +1373,55 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ mul_mat_vec_q3_K_body = """ layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - shared FLOAT_TYPE tmp[32]; void main() { const uint row = gl_WorkGroupID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint num_blocks_per_row = p.ncols / QUANT_K; - const uint ib0 = row*num_blocks_per_row; + const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row; const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16 const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1 @@ -1244,14 +1448,14 @@ FLOAT_TYPE sum = FLOAT_TYPE(0.0); for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) { - sum += FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 0]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[0] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 0)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 32]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[2] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 1)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 64]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[4] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 2)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 96]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[6] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 3)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 16]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[1] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 0)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 48]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[3] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 1)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l + 80]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[5] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 2)) != 0) ? 0 : 4)) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l +112]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[7] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 3)) != 0) ? 0 : 4)); + sum += FLOAT_TYPE(data_b[b_offset + y_idx + l + 0]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[0] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 0)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 32]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[2] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 1)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 64]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[4] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 8] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 2)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 96]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[6] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[10] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l ] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l ] & (m << 3)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 16]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[1] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] ) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 0)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 48]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[3] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 0) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 2) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 1)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l + 80]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[5] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[ 9] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 4) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 2)) != 0) ? 0 : 4)) + + FLOAT_TYPE(data_b[b_offset + y_idx + l +112]) * FLOAT_TYPE(int8_t(((data_a[ib0 + i].scales[7] >> s_shift) & 0xF) | ((data_a[ib0 + i].scales[11] >> (s_shift + 2) & 0x3) << 4)) - 32) * FLOAT_TYPE(((data_a[ib0 + i].qs[q_offset + l+16] >> 6) & 3) - (((data_a[ib0 + i].hmask[l0 + l+16] & (m << 3)) != 0) ? 0 : 4)); } tmp[16 * ix + tid] += d * sum; } @@ -1265,24 +1469,55 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ mul_mat_vec_q4_K_body = """ layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - shared FLOAT_TYPE tmp[32]; void main() { const uint row = gl_WorkGroupID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint num_blocks_per_row = p.ncols / QUANT_K; - const uint ib0 = row*num_blocks_per_row; + const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row; const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16 const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1 @@ -1336,15 +1571,15 @@ const uint8_t q4_14 = uint8_t(data_a[ib0 + i].qs[q_offset + 66] >> 4); const uint8_t q4_15 = uint8_t(data_a[ib0 + i].qs[q_offset + 67] >> 4); - const FLOAT_TYPE sx = FLOAT_TYPE(data_b[p.b_offset + y1_idx] * q4_0 + data_b[p.b_offset + y1_idx + 1] * q4_1 + data_b[p.b_offset + y1_idx + 2] * q4_2 + data_b[p.b_offset + y1_idx + 3] * q4_3); - const FLOAT_TYPE sy = FLOAT_TYPE(data_b[p.b_offset + y1_idx + 32] * q4_4 + data_b[p.b_offset + y1_idx + 33] * q4_5 + data_b[p.b_offset + y1_idx + 34] * q4_6 + data_b[p.b_offset + y1_idx + 35] * q4_7); - const FLOAT_TYPE sz = FLOAT_TYPE(data_b[p.b_offset + y2_idx] * q4_8 + data_b[p.b_offset + y2_idx + 1] * q4_9 + data_b[p.b_offset + y2_idx + 2] * q4_10 + data_b[p.b_offset + y2_idx + 3] * q4_11); - const FLOAT_TYPE sw = FLOAT_TYPE(data_b[p.b_offset + y2_idx + 32] * q4_12 + data_b[p.b_offset + y2_idx + 33] * q4_13 + data_b[p.b_offset + y2_idx + 34] * q4_14 + data_b[p.b_offset + y2_idx + 35] * q4_15); + const FLOAT_TYPE sx = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y1_idx]) * q4_0 + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) * q4_1 + FLOAT_TYPE(data_b[b_offset + y1_idx + 2]) * q4_2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 3]) * q4_3); + const FLOAT_TYPE sy = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) * q4_4 + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) * q4_5 + FLOAT_TYPE(data_b[b_offset + y1_idx + 34]) * q4_6 + FLOAT_TYPE(data_b[b_offset + y1_idx + 35]) * q4_7); + const FLOAT_TYPE sz = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y2_idx]) * q4_8 + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) * q4_9 + FLOAT_TYPE(data_b[b_offset + y2_idx + 2]) * q4_10 + FLOAT_TYPE(data_b[b_offset + y2_idx + 3]) * q4_11); + const FLOAT_TYPE sw = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) * q4_12 + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) * q4_13 + FLOAT_TYPE(data_b[b_offset + y2_idx + 34]) * q4_14 + FLOAT_TYPE(data_b[b_offset + y2_idx + 35]) * q4_15); const FLOAT_TYPE smin = FLOAT_TYPE( - data_b[p.b_offset + y1_idx ] * sc2 + data_b[p.b_offset + y1_idx + 32] * sc3 + data_b[p.b_offset + y2_idx ] * sc6 + data_b[p.b_offset + y2_idx + 32] * sc7 - + data_b[p.b_offset + y1_idx + 1] * sc2 + data_b[p.b_offset + y1_idx + 33] * sc3 + data_b[p.b_offset + y2_idx + 1] * sc6 + data_b[p.b_offset + y2_idx + 33] * sc7 - + data_b[p.b_offset + y1_idx + 2] * sc2 + data_b[p.b_offset + y1_idx + 34] * sc3 + data_b[p.b_offset + y2_idx + 2] * sc6 + data_b[p.b_offset + y2_idx + 34] * sc7 - + data_b[p.b_offset + y1_idx + 3] * sc2 + data_b[p.b_offset + y1_idx + 35] * sc3 + data_b[p.b_offset + y2_idx + 3] * sc6 + data_b[p.b_offset + y2_idx + 35] * sc7 + FLOAT_TYPE(data_b[b_offset + y1_idx ]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx ]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) * sc7 + + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) * sc7 + + FLOAT_TYPE(data_b[b_offset + y1_idx + 2]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 34]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx + 2]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 34]) * sc7 + + FLOAT_TYPE(data_b[b_offset + y1_idx + 3]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 35]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx + 3]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 35]) * sc7 ); tmp[16 * ix + tid] += FLOAT_TYPE(dall * (sx * sc0 + sy * sc1 + sz * sc4 + sw * sc5) - dmin * smin); #else @@ -1357,13 +1592,13 @@ const uint8_t q4_6 = uint8_t(data_a[ib0 + i].qs[q_offset + 64] >> 4); const uint8_t q4_7 = uint8_t(data_a[ib0 + i].qs[q_offset + 65] >> 4); - const FLOAT_TYPE sx = FLOAT_TYPE(data_b[p.b_offset + y1_idx ] * q4_0 + data_b[p.b_offset + y1_idx + 1] * q4_1); - const FLOAT_TYPE sy = FLOAT_TYPE(data_b[p.b_offset + y1_idx + 32] * q4_2 + data_b[p.b_offset + y1_idx + 33] * q4_3); - const FLOAT_TYPE sz = FLOAT_TYPE(data_b[p.b_offset + y2_idx ] * q4_4 + data_b[p.b_offset + y2_idx + 1] * q4_5); - const FLOAT_TYPE sw = FLOAT_TYPE(data_b[p.b_offset + y2_idx + 32] * q4_6 + data_b[p.b_offset + y2_idx + 33] * q4_7); + const FLOAT_TYPE sx = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y1_idx ]) * q4_0 + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) * q4_1); + const FLOAT_TYPE sy = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) * q4_2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) * q4_3); + const FLOAT_TYPE sz = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y2_idx ]) * q4_4 + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) * q4_5); + const FLOAT_TYPE sw = FLOAT_TYPE(FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) * q4_6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) * q4_7); const FLOAT_TYPE smin = FLOAT_TYPE( - data_b[p.b_offset + y1_idx] * sc2 + data_b[p.b_offset + y1_idx + 32] * sc3 + data_b[p.b_offset + y2_idx] * sc6 + data_b[p.b_offset + y2_idx + 32] * sc7 - + data_b[p.b_offset + y1_idx + 1] * sc2 + data_b[p.b_offset + y1_idx + 33] * sc3 + data_b[p.b_offset + y2_idx + 1] * sc6 + data_b[p.b_offset + y2_idx + 33] * sc7 + FLOAT_TYPE(data_b[b_offset + y1_idx]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) * sc7 + + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) * sc2 + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) * sc3 + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) * sc6 + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) * sc7 ); tmp[16 * ix + tid] += FLOAT_TYPE(dall * (sx * FLOAT_TYPE(data_a[ib0 + i].scales[v_im] & 0x3f) + sy * FLOAT_TYPE(data_a[ib0 + i].scales[v_im + 1] & 0x3f) + sz * FLOAT_TYPE((data_a[ib0 + i].scales[v_im + 4] & 0x0f) | ((data_a[ib0 + i].scales[v_im] & 0xc0) >> 2)) + sw * FLOAT_TYPE((data_a[ib0 + i].scales[v_im + 5] & 0x0f) | ((data_a[ib0 + i].scales[v_im + 1] & 0xc0) >> 2))) - dmin * smin); @@ -1379,24 +1614,55 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ mul_mat_vec_q5_K_body = """ layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - shared FLOAT_TYPE tmp[32]; void main() { const uint row = gl_WorkGroupID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint num_blocks_per_row = p.ncols / QUANT_K; - const uint ib0 = row*num_blocks_per_row; + const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row; const uint tid = gl_LocalInvocationID.x/2; // 0...31 or 0...16 const uint ix = gl_LocalInvocationID.x%2; // 0 or 0, 1 @@ -1450,32 +1716,32 @@ const uint8_t q4_15 = uint8_t(data_a[ib0 + i].qs[q_offset + 81] >> 4); const FLOAT_TYPE sx = FLOAT_TYPE( - data_b[p.b_offset + y1_idx ] * (q4_0 + (((data_a[ib0 + i].qh[l0 ] & hm1) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 1] * (q4_1 + (((data_a[ib0 + i].qh[l0 + 1] & hm1) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 16] * (q4_2 + (((data_a[ib0 + i].qh[l0 + 16] & hm1) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 17] * (q4_3 + (((data_a[ib0 + i].qh[l0 + 17] & hm1) != 0) ? 16 : 0)) + FLOAT_TYPE(data_b[b_offset + y1_idx ]) * (q4_0 + (((data_a[ib0 + i].qh[l0 ] & hm1) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) * (q4_1 + (((data_a[ib0 + i].qh[l0 + 1] & hm1) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 16]) * (q4_2 + (((data_a[ib0 + i].qh[l0 + 16] & hm1) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 17]) * (q4_3 + (((data_a[ib0 + i].qh[l0 + 17] & hm1) != 0) ? 16 : 0)) ); const FLOAT_TYPE sy = FLOAT_TYPE( - data_b[p.b_offset + y1_idx + 32] * (q4_4 + (((data_a[ib0 + i].qh[l0 ] & (hm1 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 33] * (q4_5 + (((data_a[ib0 + i].qh[l0 + 1] & (hm1 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 48] * (q4_6 + (((data_a[ib0 + i].qh[l0 + 16] & (hm1 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y1_idx + 49] * (q4_7 + (((data_a[ib0 + i].qh[l0 + 17] & (hm1 << 1)) != 0) ? 16 : 0)) + FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) * (q4_4 + (((data_a[ib0 + i].qh[l0 ] & (hm1 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) * (q4_5 + (((data_a[ib0 + i].qh[l0 + 1] & (hm1 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 48]) * (q4_6 + (((data_a[ib0 + i].qh[l0 + 16] & (hm1 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y1_idx + 49]) * (q4_7 + (((data_a[ib0 + i].qh[l0 + 17] & (hm1 << 1)) != 0) ? 16 : 0)) ); const FLOAT_TYPE sz = FLOAT_TYPE( - data_b[p.b_offset + y2_idx ] * (q4_8 + (((data_a[ib0 + i].qh[l0 ] & hm2) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 1] * (q4_9 + (((data_a[ib0 + i].qh[l0 + 1] & hm2) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 16] * (q4_10 + (((data_a[ib0 + i].qh[l0 + 16] & hm2) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 17] * (q4_11 + (((data_a[ib0 + i].qh[l0 + 17] & hm2) != 0) ? 16 : 0)) + FLOAT_TYPE(data_b[b_offset + y2_idx ]) * (q4_8 + (((data_a[ib0 + i].qh[l0 ] & hm2) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) * (q4_9 + (((data_a[ib0 + i].qh[l0 + 1] & hm2) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 16]) * (q4_10 + (((data_a[ib0 + i].qh[l0 + 16] & hm2) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 17]) * (q4_11 + (((data_a[ib0 + i].qh[l0 + 17] & hm2) != 0) ? 16 : 0)) ); const FLOAT_TYPE sw = FLOAT_TYPE( - data_b[p.b_offset + y2_idx + 32] * (q4_12 + (((data_a[ib0 + i].qh[l0 ] & (hm2 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 33] * (q4_13 + (((data_a[ib0 + i].qh[l0 + 1] & (hm2 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 48] * (q4_14 + (((data_a[ib0 + i].qh[l0 + 16] & (hm2 << 1)) != 0) ? 16 : 0)) - + data_b[p.b_offset + y2_idx + 49] * (q4_15 + (((data_a[ib0 + i].qh[l0 + 17] & (hm2 << 1)) != 0) ? 16 : 0)) + FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) * (q4_12 + (((data_a[ib0 + i].qh[l0 ] & (hm2 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) * (q4_13 + (((data_a[ib0 + i].qh[l0 + 1] & (hm2 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 48]) * (q4_14 + (((data_a[ib0 + i].qh[l0 + 16] & (hm2 << 1)) != 0) ? 16 : 0)) + + FLOAT_TYPE(data_b[b_offset + y2_idx + 49]) * (q4_15 + (((data_a[ib0 + i].qh[l0 + 17] & (hm2 << 1)) != 0) ? 16 : 0)) ); const FLOAT_TYPE smin = FLOAT_TYPE( - (data_b[p.b_offset + y1_idx] + data_b[p.b_offset + y1_idx + 1] + data_b[p.b_offset + y1_idx + 16] + data_b[p.b_offset + y1_idx + 17]) * sc2 + (data_b[p.b_offset + y1_idx + 32] + data_b[p.b_offset + y1_idx + 33] + data_b[p.b_offset + y1_idx + 48] + data_b[p.b_offset + y1_idx + 49]) * sc3 - + (data_b[p.b_offset + y2_idx] + data_b[p.b_offset + y2_idx + 1] + data_b[p.b_offset + y2_idx + 16] + data_b[p.b_offset + y2_idx + 17]) * sc6 + (data_b[p.b_offset + y2_idx + 32] + data_b[p.b_offset + y2_idx + 33] + data_b[p.b_offset + y2_idx + 48] + data_b[p.b_offset + y2_idx + 49]) * sc7 + (FLOAT_TYPE(data_b[b_offset + y1_idx]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 1]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 16]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 17])) * sc2 + (FLOAT_TYPE(data_b[b_offset + y1_idx + 32]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 33]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 48]) + FLOAT_TYPE(data_b[b_offset + y1_idx + 49])) * sc3 + + (FLOAT_TYPE(data_b[b_offset + y2_idx]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 1]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 16]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 17])) * sc6 + (FLOAT_TYPE(data_b[b_offset + y2_idx + 32]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 33]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 48]) + FLOAT_TYPE(data_b[b_offset + y2_idx + 49])) * sc7 ); tmp[16 * ix + tid] += FLOAT_TYPE(dall * (sx * sc0 + sy * sc1 + sz * sc4 + sw * sc5) - dmin * smin); } @@ -1489,25 +1755,55 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ mul_mat_vec_q6_K_body = """ layout(local_size_x = 32, local_size_y = 1, local_size_z = 1) in; -layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE dst[];}; - shared FLOAT_TYPE tmp[32]; void main() { - const uint block_size = gl_WorkGroupSize.x; const uint row = gl_WorkGroupID.x; + const uint batch_idx = gl_GlobalInvocationID.y; +#ifdef MUL_MAT_ID + const uint expert_idx1 = gl_GlobalInvocationID.z / p.nei0; + const uint expert_idx0 = gl_GlobalInvocationID.z % p.nei0; +#endif + + const uint i13 = batch_idx / p.ne12; + const uint i12 = batch_idx % p.ne12; + + const uint i03 = i13 / p.broadcast3; + const uint i02 = i12 / p.broadcast2; + + const uint batch_idx_a = i03 * p.ne02 + i02; + +#ifdef MUL_MAT_ID + const uint expert_id = data_ids[expert_idx1 * p.nbi1 + expert_idx0]; +#endif + + const uint a_offset = +#ifdef MUL_MAT_ID + expert_id * p.expert_stride_a + +#endif + batch_idx_a * p.batch_stride_a; + const uint b_offset = +#ifdef MUL_MAT_ID + (expert_idx0 % p.ne11) * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_b; + const uint d_offset = +#ifdef MUL_MAT_ID + expert_idx0 * p.expert_stride_b0 + + expert_idx1 * p.expert_stride_b1 + +#endif + batch_idx * p.batch_stride_d; const uint num_blocks_per_row = p.ncols / QUANT_K; - const uint ib0 = row*num_blocks_per_row; + const uint ib0 = a_offset / QUANT_K + row*num_blocks_per_row; const uint tid = gl_LocalInvocationID.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16 const uint ix = gl_LocalInvocationID.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1 @@ -1538,22 +1834,22 @@ const FLOAT_TYPE d = FLOAT_TYPE(data_a[ib0 + i].d); #if K_QUANTS_PER_ITERATION == 1 - FLOAT_TYPE sum = FLOAT_TYPE(data_b[p.b_offset + y_idx + 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 0] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x03) << 4)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 16]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 1]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 16] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x03) << 4)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 32] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x0c) << 2)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 48]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 3]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 48] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x0c) << 2)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 0] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x30) >> 0)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 80]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 5]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 16] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x30) >> 0)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + 96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 32] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0xc0) >> 2)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx +112]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 7]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 48] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0xc0) >> 2)) - 32); + FLOAT_TYPE sum = FLOAT_TYPE(data_b[b_offset + y_idx + 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 0] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x03) << 4)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 16]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 1]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 16] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x03) << 4)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 32] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x0c) << 2)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 48]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 3]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 48] & 0xF) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x0c) << 2)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 0] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0x30) >> 0)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 80]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 5]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 16] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0x30) >> 0)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + 96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 32] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 0] & 0xc0) >> 2)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx +112]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 7]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + 48] >> 4) | ((data_a[ib0 + i].qh[qh_offset + 16] & 0xc0) >> 2)) - 32); tmp[16 * ix + tid] += sum; #else FLOAT_TYPE sum = FLOAT_TYPE(0.0); [[unroll]] for (int l = 0; l < 4; ++l) { - sum += FLOAT_TYPE(data_b[p.b_offset + y_idx + l+ 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+ 0] & 0xF) | (((data_a[ib0 + i].qh[qh_offset + l] >> 0) & 3) << 4)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l+32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+32] & 0xF) | (((data_a[ib0 + i].qh[qh_offset + l] >> 2) & 3) << 4)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l+64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+ 0] >> 4) | (((data_a[ib0 + i].qh[qh_offset + l] >> 4) & 3) << 4)) - 32) - + FLOAT_TYPE(data_b[p.b_offset + y_idx + l+96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+32] >> 4) | (((data_a[ib0 + i].qh[qh_offset + l] >> 6) & 3) << 4)) - 32); + sum += FLOAT_TYPE(data_b[b_offset + y_idx + l+ 0]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 0]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+ 0] & 0xF) | (((data_a[ib0 + i].qh[qh_offset + l] >> 0) & 3) << 4)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + l+32]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 2]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+32] & 0xF) | (((data_a[ib0 + i].qh[qh_offset + l] >> 2) & 3) << 4)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + l+64]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 4]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+ 0] >> 4) | (((data_a[ib0 + i].qh[qh_offset + l] >> 4) & 3) << 4)) - 32) + + FLOAT_TYPE(data_b[b_offset + y_idx + l+96]) * FLOAT_TYPE(data_a[ib0 + i].scales[s_offset + 6]) * d * FLOAT_TYPE(int8_t((data_a[ib0 + i].ql[ql_offset + l+32] >> 4) | (((data_a[ib0 + i].qh[qh_offset + l] >> 6) & 3) << 4)) - 32); } tmp[16 * ix + tid] += sum; #endif @@ -1568,7 +1864,7 @@ barrier(); } if (tid == 0) { - dst[p.d_offset + row] = D_TYPE(tmp[0]); + data_d[d_offset + row] = D_TYPE(tmp[0]); } } """ @@ -1749,12 +2045,13 @@ float param1; float param2; } p;""" -generic_unary_op_funcs = """ +generic_unary_op_layout = """ layout(local_size_x = 512, local_size_y = 1, local_size_z = 1) in; layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; -layout (binding = 1) writeonly buffer D {D_TYPE data_d[];}; +layout (binding = 1) writeonly buffer D {D_TYPE data_d[];};""" +generic_unary_op_funcs = """ uint src0_idx(uint idx) { const uint i03 = idx / (p.ne02*p.ne01*p.ne00); const uint i03_offset = i03 * p.ne02*p.ne01*p.ne00; @@ -1782,7 +2079,7 @@ } """ -generic_unary_op_combined = f"{generic_unary_op_head}\n{generic_unary_op_funcs}\n{generic_unary_op_main}" +generic_unary_op_combined = f"{generic_unary_op_head}\n{generic_unary_op_layout}\n{generic_unary_op_funcs}\n{generic_unary_op_main}" generic_binary_op_head = """#version 450 @@ -1798,13 +2095,14 @@ float param1; float param2; } p;""" -generic_binary_op_funcs = """ +generic_binary_op_layout = """ layout(local_size_x = 512, local_size_y = 1, local_size_z = 1) in; layout (binding = 0) readonly buffer A {A_TYPE data_a[];}; layout (binding = 1) readonly buffer B {B_TYPE data_b[];}; -layout (binding = 2) writeonly buffer D {D_TYPE data_d[];}; +layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};""" +generic_binary_op_funcs = """ uint src0_idx(uint idx) { const uint i03 = idx / (p.ne02*p.ne01*p.ne00); const uint i03_offset = i03 * p.ne02*p.ne01*p.ne00; @@ -1843,7 +2141,7 @@ } """ -generic_binary_op_combined = f"{generic_binary_op_head}\n{generic_binary_op_funcs}\n{generic_binary_op_main}" +generic_binary_op_combined = f"{generic_binary_op_head}\n{generic_binary_op_layout}\n{generic_binary_op_funcs}\n{generic_binary_op_main}" # MUL F32 mul_body = """ @@ -1859,7 +2157,7 @@ # SCALE scale_body = """ - data_d[p.d_offset + dst_idx(gl_GlobalInvocationID.x)] = D_TYPE(FLOAT_TYPE(data_a[src0_idx(gl_GlobalInvocationID.x)]) + FLOAT_TYPE(p.param1)); + data_d[p.d_offset + dst_idx(gl_GlobalInvocationID.x)] = D_TYPE(FLOAT_TYPE(data_a[src0_idx(gl_GlobalInvocationID.x)]) * FLOAT_TYPE(p.param1)); } """ @@ -1934,7 +2232,7 @@ const uint iybs = i00 - i00%QUANT_K; // dst block start index const uint y_offset = QUANT_R == 1 ? 1 : QUANT_K/2; - DEQUANT_FUNC + vec2 v = dequantize(ib, iqs, 0); data_d[d_offset + iybs + iqs ] = D_TYPE(v.x); data_d[d_offset + iybs + iqs + y_offset] = D_TYPE(v.y); @@ -2033,7 +2331,11 @@ } const uint i = row*p.ncols + col; - data_d[i] = D_TYPE(data_a[i] - float(uint(col > p.n_past + row % p.rows_per_channel) * 0xFFFFFFFF)); + if (col > p.n_past + row % p.rows_per_channel) { + data_d[i] = D_TYPE(uintBitsToFloat(0xFF800000)); + } else { + data_d[i] = D_TYPE(data_a[i]); + } } """ @@ -2053,8 +2355,6 @@ const uint row = gl_WorkGroupID.x; const uint tid = gl_LocalInvocationID.x; - const float eps = 1e-5f; - sum[tid] = vec2(0.0f, 0.0f); [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) { @@ -2074,7 +2374,7 @@ const float mean = sum[0].x / p.KX; const float var = sum[0].y / p.KX - mean * mean; - const float inv_std = inversesqrt(var + 1e-5f); + const float inv_std = inversesqrt(var + p.param1); [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) { data_d[row*p.KX + col] = D_TYPE((float(data_a[row*p.KX + col]) - mean) * inv_std); @@ -2175,7 +2475,7 @@ vals[tid] = uintBitsToFloat(0xFF800000); [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) { - vals[tid] = max(vals[tid], FLOAT_TYPE(data_a[rowx * p.KX + col]) * p.scale + (p.KY > 0 ? FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)) + (p.KZ > 0 ? slope * data_c[col] : 0.0f)); + vals[tid] = max(vals[tid], FLOAT_TYPE(data_a[rowx * p.KX + col]) * p.scale + (p.KY > 0 ? FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)) + (p.KZ > 0 ? slope * FLOAT_TYPE(data_c[col]) : 0.0f)); } barrier(); @@ -2545,13 +2845,13 @@ async def main(): stream.clear() stream.extend((mulmat_head, shader_float_type, mulmat_body1, mulmat_load_scalar, mulmat_body2)) tasks.append(string_to_spv("matmul_f32", "".join(stream), {"A_TYPE": "float", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) - tasks.append(string_to_spv("matmul_f32_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + tasks.append(string_to_spv("matmul_f32_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) tasks.append(string_to_spv("matmul_f16", "".join(stream), {"A_TYPE": "float16_t", "B_TYPE": "float16_t", "D_TYPE": "float"}, fp16)) - tasks.append(string_to_spv("matmul_f16_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16)) + tasks.append(string_to_spv("matmul_f16_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float16_t", "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16)) tasks.append(string_to_spv("matmul_f16_f32", "".join(stream), {"A_TYPE": "float16_t", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) - tasks.append(string_to_spv("matmul_f16_f32_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + tasks.append(string_to_spv("matmul_f16_f32_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float16_t", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) stream.clear() stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q4_0_defines, mulmat_body1, mulmat_load_q4_0, mulmat_body2)) @@ -2603,6 +2903,68 @@ async def main(): tasks.append(string_to_spv("matmul_q6_k_f32", "".join(stream), {"LOAD_VEC_A": 2, "A_TYPE": "block_q6_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) tasks.append(string_to_spv("matmul_q6_k_f32_aligned", "".join(stream), {"LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q6_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + # MUL_MAT_ID + # stream.clear() + # stream.extend((mulmat_head, shader_float_type, mulmat_body1, mulmat_load_scalar, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_f32", "".join(stream), {"MUL_MAT_ID": "1", "A_TYPE": "float", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # tasks.append(string_to_spv("matmul_id_f16", "".join(stream), {"MUL_MAT_ID": "1", "A_TYPE": "float16_t", "B_TYPE": "float16_t", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_f16_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16)) + + # tasks.append(string_to_spv("matmul_id_f16_f32", "".join(stream), {"MUL_MAT_ID": "1", "A_TYPE": "float16_t", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_f16_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q4_0_defines, mulmat_body1, mulmat_load_q4_0, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q4_0_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q4_0", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q4_0_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q4_0", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q4_1_defines, mulmat_body1, mulmat_load_q4_1, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q4_1_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q4_1", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q4_1_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q4_1", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q5_0_defines, mulmat_body1, mulmat_load_q5_0, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q5_0_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q5_0", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q5_0_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q5_0", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q5_1_defines, mulmat_body1, mulmat_load_q5_1, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q5_1_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q5_1", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q5_1_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q5_1", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q8_0_defines, mulmat_body1, mulmat_load_q8_0, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q8_0_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q8_0", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q8_0_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q8_0", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q2_K_defines, mulmat_body1, mulmat_load_q2_K, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q2_k_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q2_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q2_k_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q2_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q3_K_defines, mulmat_body1, mulmat_load_q3_K, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q3_k_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q3_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q3_k_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q3_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q4_K_defines, mulmat_body1, mulmat_load_q4_K, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q4_k_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q4_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q4_k_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q4_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q5_K_defines, mulmat_body1, mulmat_load_q5_K, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q5_k_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q5_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q5_k_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q5_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + + # stream.clear() + # stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q6_K_defines, mulmat_body1, mulmat_load_q6_K, mulmat_body2)) + # tasks.append(string_to_spv("matmul_id_q6_k_f32", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "A_TYPE": "block_q6_K", "B_TYPE": "float", "D_TYPE": "float"}, fp16)) + # tasks.append(string_to_spv("matmul_id_q6_k_f32_aligned", "".join(stream), {"MUL_MAT_ID": "1", "LOAD_VEC_A": 2, "LOAD_VEC_B": load_vec, "A_TYPE": "block_q6_K", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16)) + # Shaders where precision is needed, so no fp16 version # mul mat vec @@ -2611,31 +2973,34 @@ async def main(): stream.extend((mul_mat_vec_head, shader_int8_ext, shader_f32)) if i == GGML_TYPE_F16: - stream.extend((shader_f16_defines, shader_float_dequant_func, mul_mat_vec_body)) + stream.extend((shader_f16_defines, mul_mat_vec_layout, shader_float_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q4_0: - stream.extend((shader_q4_0_defines, shader_q4_0_dequant_func, mul_mat_vec_body)) + stream.extend((shader_q4_0_defines, mul_mat_vec_layout, shader_q4_0_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q4_1: - stream.extend((shader_q4_1_defines, shader_q4_1_dequant_func, mul_mat_vec_body)) + stream.extend((shader_q4_1_defines, mul_mat_vec_layout, shader_q4_1_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q5_0: - stream.extend((shader_q5_0_defines, shader_q5_0_dequant_func, mul_mat_vec_body)) + stream.extend((shader_q5_0_defines, mul_mat_vec_layout, shader_q5_0_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q5_1: - stream.extend((shader_q5_1_defines, shader_q5_1_dequant_func, mul_mat_vec_body)) + stream.extend((shader_q5_1_defines, mul_mat_vec_layout, shader_q5_1_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q8_0: - stream.extend((shader_q8_0_defines, shader_q8_0_dequant_func, mul_mat_vec_body)) + stream.extend((shader_q8_0_defines, mul_mat_vec_layout, shader_q8_0_dequant_func, mul_mat_vec_body)) elif i == GGML_TYPE_Q2_K: - stream.extend((shader_q2_K_defines, mul_mat_vec_q2_K_body)) + stream.extend((shader_q2_K_defines, mul_mat_vec_layout, mul_mat_vec_q2_K_body)) elif i == GGML_TYPE_Q3_K: - stream.extend((shader_q3_K_defines, mul_mat_vec_q3_K_body)) + stream.extend((shader_q3_K_defines, mul_mat_vec_layout, mul_mat_vec_q3_K_body)) elif i == GGML_TYPE_Q4_K: - stream.extend((shader_q4_K_defines, mul_mat_vec_q4_K_body)) + stream.extend((shader_q4_K_defines, mul_mat_vec_layout, mul_mat_vec_q4_K_body)) elif i == GGML_TYPE_Q5_K: - stream.extend((shader_q5_K_defines, mul_mat_vec_q5_K_body)) + stream.extend((shader_q5_K_defines, mul_mat_vec_layout, mul_mat_vec_q5_K_body)) elif i == GGML_TYPE_Q6_K: - stream.extend((shader_q6_K_defines, mul_mat_vec_q6_K_body)) + stream.extend((shader_q6_K_defines, mul_mat_vec_layout, mul_mat_vec_q6_K_body)) else: continue - tasks.append(string_to_spv(f"mul_mat_vec_{type_names[i]}_f32", "".join(stream), {"B_TYPE": "float", "D_TYPE": "float", "K_QUANTS_PER_ITERATION": K_QUANTS_PER_ITERATION})) + tasks.append(string_to_spv(f"mul_mat_vec_{type_names[i]}_f32_f32", "".join(stream), {"B_TYPE": "float", "D_TYPE": "float", "K_QUANTS_PER_ITERATION": K_QUANTS_PER_ITERATION})) + tasks.append(string_to_spv(f"mul_mat_vec_{type_names[i]}_f16_f32", "".join(stream), {"B_TYPE": "float16_t", "D_TYPE": "float", "K_QUANTS_PER_ITERATION": K_QUANTS_PER_ITERATION})) + + # tasks.append(string_to_spv(f"mul_mat_vec_id_{type_names[i]}_f32", "".join(stream), {"MUL_MAT_ID": "1", "B_TYPE": "float", "D_TYPE": "float", "K_QUANTS_PER_ITERATION": K_QUANTS_PER_ITERATION})) # Dequant shaders for i in range(0, VK_NUM_TYPES): @@ -2677,20 +3042,20 @@ async def main(): optimization_workaround = False if i == GGML_TYPE_F32: - stream.extend((shader_f32_defines, generic_binary_op_funcs, get_rows_float_body)) + stream.extend((shader_f32_defines, generic_binary_op_layout, generic_binary_op_funcs, get_rows_float_body)) elif i == GGML_TYPE_F16: - stream.extend((shader_f16_defines, generic_binary_op_funcs, get_rows_float_body)) + stream.extend((shader_f16_defines, generic_binary_op_layout, generic_binary_op_funcs, get_rows_float_body)) optimization_workaround = True elif i == GGML_TYPE_Q4_0: - stream.extend((shader_q4_0_defines, shader_q4_0_dequant_func, generic_binary_op_funcs, get_rows_body)) + stream.extend((shader_q4_0_defines, generic_binary_op_layout, shader_q4_0_dequant_func, generic_binary_op_funcs, get_rows_body)) elif i == GGML_TYPE_Q4_1: - stream.extend((shader_q4_1_defines, shader_q4_1_dequant_func, generic_binary_op_funcs, get_rows_body)) + stream.extend((shader_q4_1_defines, generic_binary_op_layout, shader_q4_1_dequant_func, generic_binary_op_funcs, get_rows_body)) elif i == GGML_TYPE_Q5_0: - stream.extend((shader_q5_0_defines, shader_q5_0_dequant_func, generic_binary_op_funcs, get_rows_body)) + stream.extend((shader_q5_0_defines, generic_binary_op_layout, shader_q5_0_dequant_func, generic_binary_op_funcs, get_rows_body)) elif i == GGML_TYPE_Q5_1: - stream.extend((shader_q5_1_defines, shader_q5_1_dequant_func, generic_binary_op_funcs, get_rows_body)) + stream.extend((shader_q5_1_defines, generic_binary_op_layout, shader_q5_1_dequant_func, generic_binary_op_funcs, get_rows_body)) elif i == GGML_TYPE_Q8_0: - stream.extend((shader_q8_0_defines, shader_q8_0_dequant_func, generic_binary_op_funcs, get_rows_body)) + stream.extend((shader_q8_0_defines, generic_binary_op_layout, shader_q8_0_dequant_func, generic_binary_op_funcs, get_rows_body)) else: continue @@ -2729,6 +3094,7 @@ async def main(): tasks.append(string_to_spv("diag_mask_inf_f32", f"{diag_mask_inf_head}\n{shader_f32}\n{diag_mask_inf_body}", {"A_TYPE": "float", "D_TYPE": "float"})) tasks.append(string_to_spv("soft_max_f32", f"{soft_max_head}\n{shader_f32}\n{soft_max_body}", {"A_TYPE": "float", "B_TYPE": "float", "C_TYPE": "float", "D_TYPE": "float"})) + tasks.append(string_to_spv("soft_max_f32_f16", f"{soft_max_head}\n{shader_f32}\n{soft_max_body}", {"A_TYPE": "float", "B_TYPE": "float16_t", "C_TYPE": "float16_t", "D_TYPE": "float"})) tasks.append(string_to_spv("rope_f32", rope_src, {"A_TYPE": "float", "D_TYPE": "float"})) tasks.append(string_to_spv("rope_f16", rope_src, {"A_TYPE": "float16_t", "D_TYPE": "float16_t"})) From eaf4bd8b399a6ed4b834f91d22409d2a05c4d266 Mon Sep 17 00:00:00 2001 From: slaren <slarengh@gmail.com> Date: Fri, 10 May 2024 01:04:12 +0200 Subject: [PATCH 29/64] eval-callback : fix conversion to float (#7184) --- examples/eval-callback/eval-callback.cpp | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/examples/eval-callback/eval-callback.cpp b/examples/eval-callback/eval-callback.cpp index 29b5f3b3c12c8..e670d3769c7e8 100644 --- a/examples/eval-callback/eval-callback.cpp +++ b/examples/eval-callback/eval-callback.cpp @@ -52,15 +52,15 @@ static void ggml_print_tensor(uint8_t * data, ggml_type type, const int64_t * ne size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * nb[0]; float v; if (type == GGML_TYPE_F16) { - v = ggml_fp16_to_fp32(*(ggml_fp16_t *) data + i); + v = ggml_fp16_to_fp32(*(ggml_fp16_t *) &data[i]); } else if (type == GGML_TYPE_F32) { - v = *(float *) data + i; + v = *(float *) &data[i]; } else if (type == GGML_TYPE_I32) { - v = (float) *(int32_t *) data + i; + v = (float) *(int32_t *) &data[i]; } else if (type == GGML_TYPE_I16) { - v = (float) *(int16_t *) data + i; + v = (float) *(int16_t *) &data[i]; } else if (type == GGML_TYPE_I8) { - v = (float) *(int8_t *) data + i; + v = (float) *(int8_t *) &data[i]; } else { GGML_ASSERT(false); } From 8c570c9496212073079476651c7517c02581101f Mon Sep 17 00:00:00 2001 From: Ouadie EL FAROUKI <ouadie.elfarouki@codeplay.com> Date: Fri, 10 May 2024 01:32:15 +0100 Subject: [PATCH 30/64] Minor arithmetic improvement to mmvq wrapper kernel (#7172) --- ggml-sycl.cpp | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp index 57fe4ea3d4ac2..79aec4d9f02e1 100644 --- a/ggml-sycl.cpp +++ b/ggml-sycl.cpp @@ -8330,24 +8330,26 @@ static void mul_mat_vec_q(const void * __restrict__ vx, const void * __restrict_ const int blocks_per_row = ncols / qk; const int blocks_per_warp = vdr * WARP_SIZE / qi; -// partial sum for each thread + const int qi_vdr = (qi / vdr); // N_threads processing 1 qk block + + // partial sum for each thread float tmp = 0.0f; const block_q_t * x = (const block_q_t *) vx; const block_q8_1 * y = (const block_q8_1 *) vy; - for (int i = item_ct1.get_local_id(2) / (qi / vdr); i < blocks_per_row; + for (int i = item_ct1.get_local_id(2) / qi_vdr; i < blocks_per_row; i += blocks_per_warp) { - const int ibx = row*blocks_per_row + i; // x block index + const int ibx = row * blocks_per_row + i; // x block index - const int iby = i * (qk/QK8_1); // y block index that aligns with ibx + const int iby = i * (qk / QK8_1); // y block index that aligns with ibx - const int iqs = - vdr * - (item_ct1.get_local_id(2) % - (qi / vdr)); // x block quant index when casting the quants to int + const int iqs = + vdr * + (item_ct1.get_local_id(2) - + i * qi_vdr); // x block quant index when casting the quants to int - tmp += vec_dot_q_sycl(&x[ibx], &y[iby], iqs); + tmp += vec_dot_q_sycl(&x[ibx], &y[iby], iqs); } // sum up partial sums and write back result From d11afd665241c1b3910ab5f040d0216403019d87 Mon Sep 17 00:00:00 2001 From: Andrei <abetlen@gmail.com> Date: Fri, 10 May 2024 02:41:10 -0400 Subject: [PATCH 31/64] llava : fix moondream support (#7163) * Revert "Revert "llava : add support for moondream vision language model (#6899)"" This reverts commit 9da243b36ac0b9d609adfaaa4c8f1cc8c592f737. * Fix num_positions and embeddings initialization --- README.md | 1 + examples/llava/clip.cpp | 89 ++++++++++++++++++++++++++++++++--------- 2 files changed, 71 insertions(+), 19 deletions(-) diff --git a/README.md b/README.md index ff00f9966f2ef..9f2f8df64c127 100644 --- a/README.md +++ b/README.md @@ -140,6 +140,7 @@ Typically finetunes of the base models below are supported as well. - [x] [MobileVLM 1.7B/3B models](https://huggingface.co/models?search=mobileVLM) - [x] [Yi-VL](https://huggingface.co/models?search=Yi-VL) - [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM) +- [x] [Moondream](https://huggingface.co/vikhyatk/moondream2) **HTTP server** diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp index f568f470c8f5c..95fbe3d0216c4 100644 --- a/examples/llava/clip.cpp +++ b/examples/llava/clip.cpp @@ -104,6 +104,7 @@ static std::string format(const char * fmt, ...) { #define TN_POS_EMBD "%s.position_embd.weight" #define TN_CLASS_EMBD "v.class_embd" #define TN_PATCH_EMBD "v.patch_embd.weight" +#define TN_PATCH_BIAS "v.patch_embd.bias" #define TN_ATTN_K "%s.blk.%d.attn_k.%s" #define TN_ATTN_Q "%s.blk.%d.attn_q.%s" #define TN_ATTN_V "%s.blk.%d.attn_v.%s" @@ -425,6 +426,7 @@ struct clip_vision_model { // embeddings struct ggml_tensor * class_embedding; struct ggml_tensor * patch_embeddings; + struct ggml_tensor * patch_bias; struct ggml_tensor * position_embeddings; struct ggml_tensor * pre_ln_w; @@ -501,6 +503,11 @@ struct clip_ctx { bool use_gelu = false; int32_t ftype = 1; + bool has_class_embedding = true; + bool has_pre_norm = true; + bool has_post_norm = false; + bool has_patch_bias = false; + struct gguf_context * ctx_gguf; struct ggml_context * ctx_data; @@ -526,7 +533,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 const int patch_size = hparams.patch_size; const int num_patches = ((image_size / patch_size) * (image_size / patch_size)); const int num_patches_per_side = image_size / patch_size; GGML_UNUSED(num_patches_per_side); - const int num_positions = num_patches + 1; + const int num_positions = num_patches + (ctx->has_class_embedding ? 1 : 0); const int hidden_size = hparams.hidden_size; const int n_head = hparams.n_head; const int d_head = hidden_size / n_head; @@ -557,16 +564,23 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 inp = ggml_reshape_3d(ctx0, inp, num_patches, hidden_size, batch_size); inp = ggml_cont(ctx0, ggml_permute(ctx0, inp, 1, 0, 2, 3)); - // concat class_embeddings and patch_embeddings - struct ggml_tensor * embeddings = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, hidden_size, num_positions, batch_size); - ggml_set_name(embeddings, "embeddings"); - ggml_set_input(embeddings); + if (ctx->has_patch_bias) { + // inp = ggml_add(ctx0, inp, ggml_repeat(ctx0, model.patch_bias, inp)); + inp = ggml_add(ctx0, inp, model.patch_bias); + } - embeddings = ggml_acc(ctx0, embeddings, model.class_embedding, - embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], 0); + // concat class_embeddings and patch_embeddings + struct ggml_tensor * embeddings = inp; + if (ctx->has_class_embedding) { + embeddings = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, hidden_size, num_positions, batch_size); + ggml_set_name(embeddings, "embeddings"); + ggml_set_input(embeddings); + embeddings = ggml_acc(ctx0, embeddings, model.class_embedding, + embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], 0); + embeddings = ggml_acc(ctx0, embeddings, inp, + embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], model.class_embedding->nb[1]); + } - embeddings = ggml_acc(ctx0, embeddings, inp, - embeddings->nb[1], embeddings->nb[2], embeddings->nb[3], model.class_embedding->nb[1]); struct ggml_tensor * positions = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions); ggml_set_name(positions, "positions"); @@ -576,7 +590,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 ggml_add(ctx0, embeddings, ggml_get_rows(ctx0, model.position_embeddings, positions)); // pre-layernorm - { + if (ctx->has_pre_norm) { embeddings = ggml_norm(ctx0, embeddings, eps); ggml_set_name(embeddings, "pre_ln"); @@ -664,6 +678,14 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 embeddings = cur; } + // post-layernorm + if (ctx->has_post_norm) { + embeddings = ggml_norm(ctx0, embeddings, eps); + ggml_set_name(embeddings, "post_ln"); + + embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.post_ln_w), model.post_ln_b); + } + // llava projector { embeddings = ggml_reshape_2d(ctx0, embeddings, embeddings->ne[0], embeddings->ne[1]); @@ -1148,12 +1170,39 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { } + try { + vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); + new_clip->has_class_embedding = true; + } catch (const std::exception& e) { + new_clip->has_class_embedding = false; + } + + try { + vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); + vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); + new_clip->has_pre_norm = true; + } catch (std::exception & e) { + new_clip->has_pre_norm = false; + } + + try { + vision_model.post_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "weight")); + vision_model.post_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "bias")); + new_clip->has_post_norm = true; + } catch (std::exception & e) { + new_clip->has_post_norm = false; + } + + try { + vision_model.patch_bias = get_tensor(new_clip->ctx_data, TN_PATCH_BIAS); + new_clip->has_patch_bias = true; + } catch (std::exception & e) { + new_clip->has_patch_bias = false; + } + try { vision_model.patch_embeddings = get_tensor(new_clip->ctx_data, TN_PATCH_EMBD); - vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); vision_model.position_embeddings = get_tensor(new_clip->ctx_data, format(TN_POS_EMBD, "v")); - vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); - vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); } catch(const std::exception& e) { LOG_TEE("%s: failed to load vision model tensors\n", __func__); } @@ -1797,7 +1846,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima const int image_size = hparams.image_size; const int patch_size = hparams.patch_size; const int num_patches = ((image_size / patch_size) * (image_size / patch_size)); - const int num_positions = num_patches + 1; + const int num_positions = num_patches + (ctx->has_class_embedding ? 1 : 0); { struct ggml_tensor * inp_raw = ggml_graph_get_tensor(gf, "inp_raw"); @@ -1825,12 +1874,14 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima } { - struct ggml_tensor * embeddings = ggml_graph_get_tensor(gf, "embeddings"); + if (ctx->has_class_embedding) { + struct ggml_tensor * embeddings = ggml_graph_get_tensor(gf, "embeddings"); - void* zero_mem = malloc(ggml_nbytes(embeddings)); - memset(zero_mem, 0, ggml_nbytes(embeddings)); - ggml_backend_tensor_set(embeddings, zero_mem, 0, ggml_nbytes(embeddings)); - free(zero_mem); + void* zero_mem = malloc(ggml_nbytes(embeddings)); + memset(zero_mem, 0, ggml_nbytes(embeddings)); + ggml_backend_tensor_set(embeddings, zero_mem, 0, ggml_nbytes(embeddings)); + free(zero_mem); + } } { From f89fe2732c5709f6e86d5f4aee2e6d2a561f2eb2 Mon Sep 17 00:00:00 2001 From: HanishKVC <hanishkvc@gmail.com> Date: Fri, 10 May 2024 15:51:58 +0530 Subject: [PATCH 32/64] Main+: optionally allow special tokens from user in interactive mode (#7097) @hanishkvc added a new `--interactive-specials` flag which would allow for inserting special tokens from user side into the embedding stream. --- common/common.cpp | 6 ++++++ common/common.h | 1 + examples/main/main.cpp | 2 +- 3 files changed, 8 insertions(+), 1 deletion(-) diff --git a/common/common.cpp b/common/common.cpp index 0535508ba98df..484e673349071 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -901,6 +901,10 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa params.interactive = true; return true; } + if (arg == "--interactive-specials") { + params.interactive_specials = true; + return true; + } if (arg == "--embedding") { params.embedding = true; return true; @@ -1422,6 +1426,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { printf(" -h, --help show this help message and exit\n"); printf(" --version show version and build info\n"); printf(" -i, --interactive run in interactive mode\n"); + printf(" --interactive-specials allow special tokens in user text, in interactive mode\n"); printf(" --interactive-first run in interactive mode and wait for input right away\n"); printf(" -cnv, --conversation run in conversation mode (does not print special tokens and suffix/prefix)\n"); printf(" -ins, --instruct run in instruction mode (use with Alpaca models)\n"); @@ -2652,6 +2657,7 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l dump_string_yaml_multiline(stream, "in_suffix", params.input_prefix.c_str()); fprintf(stream, "instruct: %s # default: false\n", params.instruct ? "true" : "false"); fprintf(stream, "interactive: %s # default: false\n", params.interactive ? "true" : "false"); + fprintf(stream, "interactive_specials: %s # default: false\n", params.interactive_specials ? "true" : "false"); fprintf(stream, "interactive_first: %s # default: false\n", params.interactive_first ? "true" : "false"); fprintf(stream, "keep: %d # default: 0\n", params.n_keep); fprintf(stream, "logdir: %s # default: unset (no logging)\n", params.logdir.c_str()); diff --git a/common/common.h b/common/common.h index 6f00a2cca8883..d80344f2a61bb 100644 --- a/common/common.h +++ b/common/common.h @@ -140,6 +140,7 @@ struct gpt_params { bool random_prompt = false; // do not randomize prompt if none provided bool use_color = false; // use color to distinguish generations and inputs bool interactive = false; // interactive mode + bool interactive_specials = false; // whether to allow special tokens from user, during interactive mode bool conversation = false; // conversation mode (does not print special tokens and suffix/prefix) bool chatml = false; // chatml mode (used for models trained on chatml syntax) bool prompt_cache_all = false; // save user input and generations to prompt cache diff --git a/examples/main/main.cpp b/examples/main/main.cpp index 49acd6bab4074..f3e445c16d6a9 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -879,7 +879,7 @@ int main(int argc, char ** argv) { } const auto line_pfx = ::llama_tokenize(ctx, params.input_prefix, false, true); - const auto line_inp = ::llama_tokenize(ctx, buffer, false, false); + const auto line_inp = ::llama_tokenize(ctx, buffer, false, params.interactive_specials); const auto line_sfx = ::llama_tokenize(ctx, params.input_suffix, false, true); LOG("input tokens: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, line_inp).c_str()); From 4e3880978f8b1bf546dd4e6f3b524d6b8739c49c Mon Sep 17 00:00:00 2001 From: Justine Tunney <jtunney@mozilla.com> Date: Fri, 10 May 2024 07:01:08 -0400 Subject: [PATCH 33/64] Fix memory bug in grammar parser (#7194) The llama.cpp grammar parser had a bug where forgetting to add a closing quotation mark to strings would cause parsing to crash. Anyone running a server on a public endpoint is advised to upgrade. To reproduce this bug ./llamafile -m foo.gguf -p bar --grammar 'root::="' Credit for discovering and reporting this issue goes to Eclypsium Security Researcher Richard Johnson <Richard.johnson@eclypsium.com>. --- common/common.cpp | 8 +++----- common/grammar-parser.cpp | 9 +++++++++ examples/llava/llava-cli.cpp | 5 +++++ examples/main/main.cpp | 4 ++++ 4 files changed, 21 insertions(+), 5 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 484e673349071..ba1ecf0e59c8b 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1371,14 +1371,12 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) { if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) { std::replace(arg.begin(), arg.end(), '_', '-'); } - if (!gpt_params_find_arg(argc, argv, arg, params, i, invalid_param)) { throw std::invalid_argument("error: unknown argument: " + arg); } - } - - if (invalid_param) { - throw std::invalid_argument("error: invalid parameter for argument: " + arg); + if (invalid_param) { + throw std::invalid_argument("error: invalid parameter for argument: " + arg); + } } if (params.prompt_cache_all && diff --git a/common/grammar-parser.cpp b/common/grammar-parser.cpp index 2a1301569793a..fecb7cd713ea1 100644 --- a/common/grammar-parser.cpp +++ b/common/grammar-parser.cpp @@ -142,6 +142,9 @@ namespace grammar_parser { pos++; last_sym_start = out_elements.size(); while (*pos != '"') { + if (!*pos) { + throw std::runtime_error("unexpected end of input"); + } auto char_pair = parse_char(pos); pos = char_pair.second; out_elements.push_back({LLAMA_GRETYPE_CHAR, char_pair.first}); @@ -156,6 +159,9 @@ namespace grammar_parser { } last_sym_start = out_elements.size(); while (*pos != ']') { + if (!*pos) { + throw std::runtime_error("unexpected end of input"); + } auto char_pair = parse_char(pos); pos = char_pair.second; enum llama_gretype type = last_sym_start < out_elements.size() @@ -164,6 +170,9 @@ namespace grammar_parser { out_elements.push_back({type, char_pair.first}); if (pos[0] == '-' && pos[1] != ']') { + if (!pos[1]) { + throw std::runtime_error("unexpected end of input"); + } auto endchar_pair = parse_char(pos + 1); pos = endchar_pair.second; out_elements.push_back({LLAMA_GRETYPE_CHAR_RNG_UPPER, endchar_pair.first}); diff --git a/examples/llava/llava-cli.cpp b/examples/llava/llava-cli.cpp index 157a680b5ecdb..da60ddf2f057d 100644 --- a/examples/llava/llava-cli.cpp +++ b/examples/llava/llava-cli.cpp @@ -189,6 +189,11 @@ static void process_prompt(struct llava_context * ctx_llava, struct llava_image_ LOG_TEE("\n"); struct llama_sampling_context * ctx_sampling = llama_sampling_init(params->sparams); + if (!ctx_sampling) { + fprintf(stderr, "%s: failed to initialize sampling subsystem\n", __func__); + exit(1); + } + std::string response = ""; for (int i = 0; i < max_tgt_len; i++) { const char * tmp = sample(ctx_sampling, ctx_llava->ctx_llama, &n_past); diff --git a/examples/main/main.cpp b/examples/main/main.cpp index f3e445c16d6a9..9dee41001f12c 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -523,6 +523,10 @@ int main(int argc, char ** argv) { } struct llama_sampling_context * ctx_sampling = llama_sampling_init(sparams); + if (!ctx_sampling) { + fprintf(stderr, "%s: failed to initialize sampling subsystem\n", __func__); + exit(1); + } while ((n_remain != 0 && !is_antiprompt) || params.interactive) { // predict From 25c6e82e7a1ad25a42b0894e87d9b5c557409516 Mon Sep 17 00:00:00 2001 From: slaren <slarengh@gmail.com> Date: Fri, 10 May 2024 14:28:01 +0200 Subject: [PATCH 34/64] llama : use n_vocab to differentiate between mistral 7B and llama3 8B (#7200) --- llama.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama.cpp b/llama.cpp index e7b3fd8b433b4..2f1123d4e1678 100644 --- a/llama.cpp +++ b/llama.cpp @@ -3860,7 +3860,7 @@ static void llm_load_hparams( switch (hparams.n_layer) { case 22: model.type = e_model::MODEL_1B; break; case 26: model.type = e_model::MODEL_3B; break; - case 32: model.type = hparams.n_head == hparams.n_head_kv ? e_model::MODEL_7B : e_model::MODEL_8B; break; // LLaMa 8B v3 uses GQA + case 32: model.type = hparams.n_vocab < 40000 ? e_model::MODEL_7B : e_model::MODEL_8B; break; case 40: model.type = e_model::MODEL_13B; break; case 48: model.type = e_model::MODEL_34B; break; case 60: model.type = e_model::MODEL_30B; break; From 8c660242d708d3913a2adc2b6e4a9ee9cf5e4ce7 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Fri, 10 May 2024 17:53:04 +0300 Subject: [PATCH 35/64] convert : print "ignore_merges" field --- convert-hf-to-gguf-update.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index e6468772210f8..b5eb41eacdab7 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -161,6 +161,8 @@ def download_file_with_auth(url, token, save_path): logger.info("normalizer: " + json.dumps(normalizer, indent=4)) pre_tokenizer = cfg["pre_tokenizer"] logger.info("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4)) + if "ignore_merges" in cfg["model"]: + logger.info("ignore_merges: " + json.dumps(cfg["model"]["ignore_merges"], indent=4)) logger.info("") From 18e437665ce626dddbd79119aa7498493e7cb13b Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Fri, 10 May 2024 18:20:10 +0300 Subject: [PATCH 36/64] metal : fix flash attention kernel requirements (#7169) * metal : fix flash attention kernel requirements ggml-ci * metal : fix ggml_metal_supports_op ggml-ci --- ggml-metal.m | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/ggml-metal.m b/ggml-metal.m index c6817f01f2bdb..18ce5b88a1c01 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -633,14 +633,14 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){ GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_ASC, argsort_f32_i32_asc, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGSORT_F32_I32_DESC, argsort_f32_i32_desc, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_LEAKY_RELU_F32, leaky_relu_f32, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H64, flash_attn_ext_f16_h64, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H80, flash_attn_ext_f16_h80, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H96, flash_attn_ext_f16_h96, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H112, flash_attn_ext_f16_h112, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H128, flash_attn_ext_f16_h128, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H256, flash_attn_ext_f16_h256, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H128, flash_attn_ext_vec_f16_h128, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H256, flash_attn_ext_vec_f16_h256, true); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H64, flash_attn_ext_f16_h64, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H80, flash_attn_ext_f16_h80, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H96, flash_attn_ext_f16_h96, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H112, flash_attn_ext_f16_h112, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H128, flash_attn_ext_f16_h128, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H256, flash_attn_ext_f16_h256, ctx->support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H128, flash_attn_ext_vec_f16_h128, ctx->support_simdgroup_reduction); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H256, flash_attn_ext_vec_f16_h256, ctx->support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F16, cpy_f32_f16, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_F32, cpy_f32_f32, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q8_0, cpy_f32_q8_0, true); @@ -772,8 +772,9 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const case GGML_OP_TIMESTEP_EMBEDDING: case GGML_OP_ARGSORT: case GGML_OP_LEAKY_RELU: - case GGML_OP_FLASH_ATTN_EXT: return true; + case GGML_OP_FLASH_ATTN_EXT: + return ctx->support_simdgroup_mm; // TODO: over-restricted for vec-kernels case GGML_OP_MUL_MAT: case GGML_OP_MUL_MAT_ID: return ctx->support_simdgroup_reduction && From e849648888a11de13aaaa4cb2eda3f5a9c7b444d Mon Sep 17 00:00:00 2001 From: slaren <slarengh@gmail.com> Date: Fri, 10 May 2024 18:03:54 +0200 Subject: [PATCH 37/64] llama-bench : add pp+tg test type (#7199) --- examples/llama-bench/README.md | 18 +++++--- examples/llama-bench/llama-bench.cpp | 63 ++++++++++++++++++++++++---- scripts/compare-llama-bench.py | 8 +++- 3 files changed, 74 insertions(+), 15 deletions(-) diff --git a/examples/llama-bench/README.md b/examples/llama-bench/README.md index 10f37b4418897..8578405646af7 100644 --- a/examples/llama-bench/README.md +++ b/examples/llama-bench/README.md @@ -26,16 +26,21 @@ options: -m, --model <filename> (default: models/7B/ggml-model-q4_0.gguf) -p, --n-prompt <n> (default: 512) -n, --n-gen <n> (default: 128) - -b, --batch-size <n> (default: 512) - -ctk <t>, --cache-type-k <t> (default: f16) - -ctv <t>, --cache-type-v <t> (default: f16) - -t, --threads <n> (default: 112) + -pg <pp,tg> (default: 512,128) + -b, --batch-size <n> (default: 2048) + -ub, --ubatch-size <n> (default: 512) + -ctk, --cache-type-k <t> (default: f16) + -ctv, --cache-type-v <t> (default: f16) + -t, --threads <n> (default: 16) -ngl, --n-gpu-layers <n> (default: 99) -sm, --split-mode <none|layer|row> (default: layer) -mg, --main-gpu <i> (default: 0) -nkvo, --no-kv-offload <0|1> (default: 0) + -fa, --flash-attn <0|1> (default: 0) -mmp, --mmap <0|1> (default: 1) - -ts, --tensor_split <ts0/ts1/..> (default: 0) + --numa <distribute|isolate|numactl> (default: disabled) + -embd, --embeddings <0|1> (default: 0) + -ts, --tensor-split <ts0/ts1/..> (default: 0) -r, --repetitions <n> (default: 5) -o, --output <csv|json|md|sql> (default: md) -v, --verbose (default: 0) @@ -43,10 +48,11 @@ options: Multiple values can be given for each parameter by separating them with ',' or by specifying the parameter multiple times. ``` -llama-bench can perform two types of tests: +llama-bench can perform three types of tests: - Prompt processing (pp): processing a prompt in batches (`-p`) - Text generation (tg): generating a sequence of tokens (`-n`) +- Prompt processing + text generation (pg): processing a prompt followed by generating a sequence of tokens (`-pg`) With the exception of `-r`, `-o` and `-v`, all options can be specified multiple times to run multiple tests. Each pp and tg test is run with all combinations of the specified options. To specify multiple values for an option, the values can be separated by commas (e.g. `-n 16,32`), or the option can be specified multiple times (e.g. `-n 16 -n 32`). diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp index 40128ec444334..8b965e1990ba5 100644 --- a/examples/llama-bench/llama-bench.cpp +++ b/examples/llama-bench/llama-bench.cpp @@ -161,10 +161,17 @@ static const char * split_mode_str(llama_split_mode mode) { } } +static std::string pair_str(const std::pair<int, int> & p) { + static char buf[32]; + snprintf(buf, sizeof(buf), "%d,%d", p.first, p.second); + return buf; +} + struct cmd_params { std::vector<std::string> model; std::vector<int> n_prompt; std::vector<int> n_gen; + std::vector<std::pair<int, int>> n_pg; std::vector<int> n_batch; std::vector<int> n_ubatch; std::vector<ggml_type> type_k; @@ -188,6 +195,7 @@ static const cmd_params cmd_params_defaults = { /* model */ {"models/7B/ggml-model-q4_0.gguf"}, /* n_prompt */ {512}, /* n_gen */ {128}, + /* n_pg */ {{512, 128}}, /* n_batch */ {2048}, /* n_ubatch */ {512}, /* type_k */ {GGML_TYPE_F16}, @@ -215,10 +223,11 @@ static void print_usage(int /* argc */, char ** argv) { printf(" -m, --model <filename> (default: %s)\n", join(cmd_params_defaults.model, ",").c_str()); printf(" -p, --n-prompt <n> (default: %s)\n", join(cmd_params_defaults.n_prompt, ",").c_str()); printf(" -n, --n-gen <n> (default: %s)\n", join(cmd_params_defaults.n_gen, ",").c_str()); + printf(" -pg <pp,tg> (default: %s)\n", join(transform_to_str(cmd_params_defaults.n_pg, pair_str), ",").c_str()); printf(" -b, --batch-size <n> (default: %s)\n", join(cmd_params_defaults.n_batch, ",").c_str()); - printf(" -ub N, --ubatch-size <n> (default: %s)\n", join(cmd_params_defaults.n_ubatch, ",").c_str()); - printf(" -ctk <t>, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str()); - printf(" -ctv <t>, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str()); + printf(" -ub, --ubatch-size <n> (default: %s)\n", join(cmd_params_defaults.n_ubatch, ",").c_str()); + printf(" -ctk, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str()); + printf(" -ctv, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str()); printf(" -t, --threads <n> (default: %s)\n", join(cmd_params_defaults.n_threads, ",").c_str()); printf(" -ngl, --n-gpu-layers <n> (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str()); printf(" -sm, --split-mode <none|layer|row> (default: %s)\n", join(transform_to_str(cmd_params_defaults.split_mode, split_mode_str), ",").c_str()); @@ -304,6 +313,17 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { } auto p = split<int>(argv[i], split_delim); params.n_gen.insert(params.n_gen.end(), p.begin(), p.end()); + } else if (arg == "-pg") { + if (++i >= argc) { + invalid_param = true; + break; + } + auto p = split<std::string>(argv[i], ','); + if (p.size() != 2) { + invalid_param = true; + break; + } + params.n_pg.push_back({std::stoi(p[0]), std::stoi(p[1])}); } else if (arg == "-b" || arg == "--batch-size") { if (++i >= argc) { invalid_param = true; @@ -493,6 +513,7 @@ static cmd_params parse_cmd_params(int argc, char ** argv) { if (params.model.empty()) { params.model = cmd_params_defaults.model; } if (params.n_prompt.empty()) { params.n_prompt = cmd_params_defaults.n_prompt; } if (params.n_gen.empty()) { params.n_gen = cmd_params_defaults.n_gen; } + if (params.n_pg.empty()) { params.n_pg = cmd_params_defaults.n_pg; } if (params.n_batch.empty()) { params.n_batch = cmd_params_defaults.n_batch; } if (params.n_ubatch.empty()) { params.n_ubatch = cmd_params_defaults.n_ubatch; } if (params.type_k.empty()) { params.type_k = cmd_params_defaults.type_k; } @@ -632,6 +653,31 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param }; instances.push_back(instance); } + + for (const auto & n_pg : params.n_pg) { + if (n_pg.first == 0 && n_pg.second == 0) { + continue; + } + cmd_params_instance instance = { + /* .model = */ m, + /* .n_prompt = */ n_pg.first, + /* .n_gen = */ n_pg.second, + /* .n_batch = */ nb, + /* .n_ubatch = */ nub, + /* .type_k = */ tk, + /* .type_v = */ tv, + /* .n_threads = */ nt, + /* .n_gpu_layers = */ nl, + /* .split_mode = */ sm, + /* .main_gpu = */ mg, + /* .no_kv_offload= */ nkvo, + /* .flash_attn = */ fa, + /* .tensor_split = */ ts, + /* .use_mmap = */ mmp, + /* .embeddings = */ embd, + }; + instances.push_back(instance); + } } return instances; @@ -965,6 +1011,9 @@ struct markdown_printer : public printer { if (field == "n_gpu_layers") { return 3; } + if (field == "test") { + return 13; + } int width = std::max((int)field.length(), 10); @@ -1091,12 +1140,11 @@ struct markdown_printer : public printer { value = test::get_backend(); } else if (field == "test") { if (t.n_prompt > 0 && t.n_gen == 0) { - snprintf(buf, sizeof(buf), "pp %d", t.n_prompt); + snprintf(buf, sizeof(buf), "pp%d", t.n_prompt); } else if (t.n_gen > 0 && t.n_prompt == 0) { - snprintf(buf, sizeof(buf), "tg %d", t.n_gen); + snprintf(buf, sizeof(buf), "tg%d", t.n_gen); } else { - assert(false); - exit(1); + snprintf(buf, sizeof(buf), "pp%d+tg%d", t.n_prompt, t.n_gen); } value = buf; } else if (field == "t/s") { @@ -1297,6 +1345,7 @@ int main(int argc, char ** argv) { llama_kv_cache_clear(ctx); uint64_t t_start = get_time_ns(); + if (t.n_prompt > 0) { test_prompt(ctx, t.n_prompt, 0, t.n_batch, t.n_threads); } diff --git a/scripts/compare-llama-bench.py b/scripts/compare-llama-bench.py index fed3c1ee3d298..0ede9e67c2f15 100755 --- a/scripts/compare-llama-bench.py +++ b/scripts/compare-llama-bench.py @@ -325,8 +325,12 @@ def get_rows(properties): for row in rows_show: n_prompt = int(row[-4]) n_gen = int(row[-3]) - assert n_prompt == 0 or n_gen == 0 - test_name = f"tg{n_gen}" if n_prompt == 0 else f"pp{n_prompt}" + if n_prompt != 0 and n_gen == 0: + test_name = f"pp{n_prompt}" + elif n_prompt == 0 and n_gen != 0: + test_name = f"tg{n_gen}" + else: + test_name = f"pp{n_prompt}+tg{n_gen}" # Regular columns test name avg t/s values Speedup # VVVVVVVVVVVVV VVVVVVVVV VVVVVVVVVVVVVV VVVVVVV table.append(list(row[:-4]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])]) From 9cb317f77e53067f7a138cc89ef7657148eae8e6 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 10:32:41 +0300 Subject: [PATCH 38/64] ggml : full ALiBi support (#7192) * ggml : full ALiBi support * ggml : update ggml_soft_max_ext() CUDA, SYCL * ggml : ggml_flash_attn_ext() support ALiBi (CPU) * ggml : ggml_flash_attn_ext() support ALiBi (Metal) * ggml : fix warning * ggml : ggml_flash_attn_ext() support ALiBi (CUDA) ggml-ci * ggml : fix assert message * vulkan : add dev notes * ggml : require mask when using ALiBi ggml-ci * convert : fix convert for refact models --- convert-hf-to-gguf.py | 12 ++ ggml-cuda.cu | 5 - ggml-cuda/alibi.cu | 63 ------- ggml-cuda/alibi.cuh | 5 - ggml-cuda/fattn.cu | 72 ++++++-- ggml-cuda/softmax.cu | 55 +++--- ggml-kompute.cpp | 12 +- ggml-metal.m | 148 ++++++---------- ggml-metal.metal | 120 ++++++------- ggml-sycl.cpp | 138 ++------------- ggml-vulkan.cpp | 6 +- ggml.c | 309 +++++---------------------------- ggml.h | 18 +- gguf-py/gguf/tensor_mapping.py | 4 + llama.cpp | 178 +++++++------------ tests/test-backend-ops.cpp | 30 ++-- 16 files changed, 350 insertions(+), 825 deletions(-) delete mode 100644 ggml-cuda/alibi.cu delete mode 100644 ggml-cuda/alibi.cuh diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 1dc18b2a57721..3315ca74b044b 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -1013,6 +1013,18 @@ def set_gguf_parameters(self): class RefactModel(Model): model_arch = gguf.MODEL_ARCH.REFACT + def set_vocab(self): + super().set_vocab() + + # TODO: how to determine special FIM tokens automatically? + special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=False, + special_token_types = ['prefix', 'suffix', 'middle', 'fsep', 'eot']) + special_vocab._set_special_token("prefix", 1) + special_vocab._set_special_token("suffix", 3) + special_vocab._set_special_token("middle", 2) + special_vocab._set_special_token("fsep", 4) # is this correct? + special_vocab.add_to_gguf(self.gguf_writer) + def set_gguf_parameters(self): hidden_dim = self.hparams["n_embd"] inner_dim = 4 * hidden_dim diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 6f89a7cc3e900..c5c7787969f5f 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -4,7 +4,6 @@ #include "ggml-cuda/common.cuh" #include "ggml-cuda/acc.cuh" -#include "ggml-cuda/alibi.cuh" #include "ggml-cuda/arange.cuh" #include "ggml-cuda/argsort.cuh" #include "ggml-cuda/binbcast.cuh" @@ -2277,9 +2276,6 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg case GGML_OP_ROPE: ggml_cuda_op_rope(ctx, dst); break; - case GGML_OP_ALIBI: - ggml_cuda_op_alibi(ctx, dst); - break; case GGML_OP_IM2COL: ggml_cuda_op_im2col(ctx, dst); break; @@ -2829,7 +2825,6 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons case GGML_OP_DIAG_MASK_INF: case GGML_OP_SOFT_MAX: case GGML_OP_ROPE: - case GGML_OP_ALIBI: case GGML_OP_IM2COL: case GGML_OP_POOL_2D: case GGML_OP_SUM_ROWS: diff --git a/ggml-cuda/alibi.cu b/ggml-cuda/alibi.cu deleted file mode 100644 index 6c7f1fd9562e4..0000000000000 --- a/ggml-cuda/alibi.cu +++ /dev/null @@ -1,63 +0,0 @@ -#include "alibi.cuh" - -static __global__ void alibi_f32(const float * x, float * dst, const int ncols, const int k_rows, - const int n_heads_log2_floor, const float m0, const float m1) { - const int col = blockDim.x*blockIdx.x + threadIdx.x; - - if (col >= ncols) { - return; - } - - const int row = blockDim.y*blockIdx.y + threadIdx.y; - const int i = row*ncols + col; - - const int k = row/k_rows; - - float m_k; - if (k < n_heads_log2_floor) { - m_k = powf(m0, k + 1); - } else { - m_k = powf(m1, 2 * (k - n_heads_log2_floor) + 1); - } - - dst[i] = col * m_k + x[i]; -} - -static void alibi_f32_cuda(const float * x, float * dst, const int ncols, const int nrows, - const int k_rows, const int n_heads_log2_floor, const float m0, - const float m1, cudaStream_t stream) { - const dim3 block_dims(CUDA_ALIBI_BLOCK_SIZE, 1, 1); - const int num_blocks_x = (ncols + CUDA_ALIBI_BLOCK_SIZE - 1) / (CUDA_ALIBI_BLOCK_SIZE); - const dim3 block_nums(num_blocks_x, nrows, 1); - alibi_f32<<<block_nums, block_dims, 0, stream>>>(x, dst, ncols, k_rows, n_heads_log2_floor, m0, m1); -} - -void ggml_cuda_op_alibi(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { - const ggml_tensor * src0 = dst->src[0]; - const float * src0_d = (const float *)src0->data; - float * dst_d = (float *)dst->data; - cudaStream_t stream = ctx.stream(); - - GGML_ASSERT(src0->type == GGML_TYPE_F32); - GGML_ASSERT( dst->type == GGML_TYPE_F32); - - const int64_t ne00 = src0->ne[0]; - const int64_t ne01 = src0->ne[1]; - const int64_t ne02 = src0->ne[2]; - const int64_t nrows = ggml_nrows(src0); - - //const int n_past = ((int32_t *) dst->op_params)[0]; - const int n_head = ((int32_t *) dst->op_params)[1]; - float max_bias; - memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float)); - - //GGML_ASSERT(ne01 + n_past == ne00); - GGML_ASSERT(n_head == ne02); - - const int n_heads_log2_floor = 1 << (int) floor(log2(n_head)); - - const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor); - - alibi_f32_cuda(src0_d, dst_d, ne00, nrows, ne01, n_heads_log2_floor, m0, m1, stream); -} diff --git a/ggml-cuda/alibi.cuh b/ggml-cuda/alibi.cuh deleted file mode 100644 index 630adfc7f6396..0000000000000 --- a/ggml-cuda/alibi.cuh +++ /dev/null @@ -1,5 +0,0 @@ -#include "common.cuh" - -#define CUDA_ALIBI_BLOCK_SIZE 32 - -void ggml_cuda_op_alibi(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml-cuda/fattn.cu b/ggml-cuda/fattn.cu index 7c486f4829bdd..ac5d6672b30d3 100644 --- a/ggml-cuda/fattn.cu +++ b/ggml-cuda/fattn.cu @@ -23,6 +23,10 @@ static __global__ void flash_attn_vec_ext_f16( float * __restrict__ dst, float2 * __restrict__ dst_meta, const float scale, + const float max_bias, + const float m0, + const float m1, + const uint32_t n_head_log2, const int ne00, const int ne01, const int ne02, @@ -58,6 +62,18 @@ static __global__ void flash_attn_vec_ext_f16( const int stride_KV = nb11 / sizeof(half); const int stride_KV2 = nb11 / sizeof(half2); + half slopeh = __float2half(1.0f); + + // ALiBi + if (max_bias > 0.0f) { + const int h = blockIdx.y; + + const float base = h < n_head_log2 ? m0 : m1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + slopeh = __float2half(powf(base, exph)); + } + static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64."); constexpr int nwarps = D / WARP_SIZE; const int tid = WARP_SIZE*threadIdx.y + threadIdx.x; @@ -141,7 +157,7 @@ static __global__ void flash_attn_vec_ext_f16( for (int j = 0; j < ncols; ++j) { sum2[j] = warp_reduce_sum(sum2[j]); half sum = __low2half(sum2[j]) + __high2half(sum2[j]); - sum += mask ? maskh[j*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f); + sum += mask ? slopeh*maskh[j*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f); if (ncols == 1) { kqmax_new = ggml_cuda_hmax(kqmax_new, sum); @@ -249,6 +265,10 @@ static __global__ void flash_attn_ext_f16( float * __restrict__ dst, float2 * __restrict__ dst_meta, const float scale, + const float max_bias, + const float m0, + const float m1, + const uint32_t n_head_log2, const int ne00, const int ne01, const int ne02, @@ -305,6 +325,20 @@ static __global__ void flash_attn_ext_f16( const int stride_Q = nb01 / sizeof(float); const int stride_KV = nb11 / sizeof(half); + half slopeh = __float2half(1.0f); + half2 slope2 = make_half2(1.0f, 1.0f); + + // ALiBi + if (max_bias > 0.0f) { + const int h = blockIdx.y; + + const float base = h < n_head_log2 ? m0 : m1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + slopeh = __float2half(powf(base, exph)); + slope2 = make_half2(slopeh, slopeh); + } + frag_b Q_b[D/16][ncols/frag_n]; // A single buffer for temporarily holding tiles of KQ and VKQ parts: @@ -421,7 +455,7 @@ static __global__ void flash_attn_ext_f16( for (int k0 = 0; k0 < FATTN_KQ_STRIDE; k0 += WARP_SIZE) { const int k = k0 + threadIdx.x; - KQ_f_tmp[k0/WARP_SIZE] += mask ? __half2float(maskh[j*(nb31/sizeof(half)) + k_VKQ_0 + k]) : 0.0f; + KQ_f_tmp[k0/WARP_SIZE] += mask ? __half2float(slopeh*maskh[j*(nb31/sizeof(half)) + k_VKQ_0 + k]) : 0.0f; KQ_max_new = max(KQ_max_new, KQ_f_tmp[k0/WARP_SIZE]); } KQ_max_new = warp_reduce_max(KQ_max_new); @@ -464,7 +498,7 @@ static __global__ void flash_attn_ext_f16( for (int k0 = 0; k0 < FATTN_KQ_STRIDE/2; k0 += WARP_SIZE) { const int k = k0 + threadIdx.x; - KQ2_tmp[k0/WARP_SIZE] += mask ? mask2[(j*ne11 + k_VKQ_0)/2 + k] : make_half2(0.0f, 0.0f); + KQ2_tmp[k0/WARP_SIZE] += mask ? slope2*mask2[(j*ne11 + k_VKQ_0)/2 + k] : make_half2(0.0f, 0.0f); KQ_max_new = ggml_cuda_hmax2(KQ_max_new, KQ2_tmp[k0/WARP_SIZE]); } KQ_max_new = __half2half2(warp_reduce_max(ggml_cuda_hmax(__low2half(KQ_max_new), __high2half(KQ_max_new)))); @@ -710,8 +744,17 @@ template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_ const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]); const int shmem = 0; - float scale; - memcpy(&scale, KQV->op_params, sizeof(float)); + float scale = 1.0f; + float max_bias = 0.0f; + + memcpy(&scale, (float *) KQV->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float)); + + const uint32_t n_head = Q->ne[2]; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks> <<<blocks_num, block_dim, shmem, main_stream>>> ( @@ -720,7 +763,7 @@ template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_ (const char *) V->data, mask ? ((const char *) mask->data) : nullptr, parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr, - scale, + scale, max_bias, m0, m1, n_head_log2, Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], K->ne[0], K->ne[1], K->ne[2], K->ne[3], mask ? mask->ne[1] : 0, mask ? mask->nb[1] : 0, @@ -761,8 +804,17 @@ template <int D, int cols_per_block, int nwarps, int parallel_blocks, typename K const dim3 blocks_num(parallel_blocks*(Q->ne[1] + cols_per_block - 1) / cols_per_block, Q->ne[2], Q->ne[3]); const int shmem = 0; - float scale; - memcpy(&scale, KQV->op_params, sizeof(float)); + float scale = 1.0f; + float max_bias = 0.0f; + + memcpy(&scale, (float *) KQV->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float)); + + const uint32_t n_head = Q->ne[2]; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); flash_attn_ext_f16<D, cols_per_block, nwarps, get_VKQ_stride(D, nwarps, frag_m), parallel_blocks, KQ_acc_t> <<<blocks_num, block_dim, shmem, main_stream>>> ( @@ -771,7 +823,7 @@ template <int D, int cols_per_block, int nwarps, int parallel_blocks, typename K (const char *) V->data, mask ? ((const char *) mask->data) : nullptr, (parallel_blocks) == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr, - scale, + scale, max_bias, m0, m1, n_head_log2, Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], K->ne[0], K->ne[1], K->ne[2], K->ne[3], mask ? mask->ne[1] : 0, mask ? mask->nb[1] : 0, @@ -837,7 +889,7 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst const int cc = ggml_cuda_info().devices[ggml_cuda_get_device()].cc; const int nsm = ggml_cuda_info().devices[ggml_cuda_get_device()].nsm; - const int32_t precision = KQV->op_params[1]; + const int32_t precision = KQV->op_params[2]; if (!fp16_mma_available(cc)) { GGML_ASSERT(precision == GGML_PREC_DEFAULT); diff --git a/ggml-cuda/softmax.cu b/ggml-cuda/softmax.cu index 6ed225999bddf..ca85285a3f458 100644 --- a/ggml-cuda/softmax.cu +++ b/ggml-cuda/softmax.cu @@ -11,7 +11,7 @@ __device__ float __forceinline__ t2f32<half>(half val) { } template <bool vals_smem, int ncols_template, int block_size_template, typename T> -static __global__ void soft_max_f32(const float * x, const T * mask, const T * pos, float * dst, const int ncols_par, const int nrows_y, const float scale, const float max_bias, const float m0, const float m1, uint32_t n_head_log2) { +static __global__ void soft_max_f32(const float * x, const T * mask, float * dst, const int ncols_par, const int nrows_y, const float scale, const float max_bias, const float m0, const float m1, uint32_t n_head_log2) { const int ncols = ncols_template == 0 ? ncols_par : ncols_template; const int tid = threadIdx.x; @@ -23,16 +23,16 @@ static __global__ void soft_max_f32(const float * x, const T * mask, const T * p const int warp_id = threadIdx.x / WARP_SIZE; const int lane_id = threadIdx.x % WARP_SIZE; - float slope = 0.0f; + float slope = 1.0f; // ALiBi if (max_bias > 0.0f) { const int h = rowx/nrows_y; // head index const float base = h < n_head_log2 ? m0 : m1; - const int exp = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; - slope = powf(base, exp); + slope = powf(base, exph); } extern __shared__ float data_soft_max_f32[]; @@ -53,7 +53,7 @@ static __global__ void soft_max_f32(const float * x, const T * mask, const T * p const int64_t ix = (int64_t)rowx*ncols + col; const int64_t iy = (int64_t)rowy*ncols + col; - const float val = x[ix]*scale + (mask ? t2f32(mask[iy]) : 0.0f) + (pos ? slope*t2f32(pos[col]) : 0.0f); + const float val = x[ix]*scale + (mask ? slope*t2f32(mask[iy]) : 0.0f); vals[col] = val; max_val = max(max_val, val); @@ -125,7 +125,7 @@ static __global__ void soft_max_f32(const float * x, const T * mask, const T * p } template<typename T> -static void soft_max_f32_cuda(const float * x, const T * mask, const T * pos, float * dst, const int ncols_x, const int nrows_x, const int nrows_y, const float scale, const float max_bias, cudaStream_t stream) { +static void soft_max_f32_cuda(const float * x, const T * mask, float * dst, const int ncols_x, const int nrows_x, const int nrows_y, const float scale, const float max_bias, cudaStream_t stream) { int nth = WARP_SIZE; while (nth < ncols_x && nth < CUDA_SOFT_MAX_BLOCK_SIZE) nth *= 2; const dim3 block_dims(nth, 1, 1); @@ -133,8 +133,8 @@ static void soft_max_f32_cuda(const float * x, const T * mask, const T * pos, fl const size_t shmem = (GGML_PAD(ncols_x, WARP_SIZE) + WARP_SIZE)*sizeof(float); static_assert(CUDA_SOFT_MAX_BLOCK_SIZE == 1024, "These values need to be adjusted."); - const uint32_t n_head_kv = nrows_x/nrows_y; - const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head_kv)); + const uint32_t n_head = nrows_x/nrows_y; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); @@ -142,43 +142,42 @@ static void soft_max_f32_cuda(const float * x, const T * mask, const T * pos, fl if (shmem < ggml_cuda_info().devices[ggml_cuda_get_device()].smpb) { switch (ncols_x) { case 32: - soft_max_f32<true, 32, 32><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 32, 32><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 64: - soft_max_f32<true, 64, 64><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 64, 64><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 128: - soft_max_f32<true, 128, 128><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 128, 128><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 256: - soft_max_f32<true, 256, 256><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 256, 256><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 512: - soft_max_f32<true, 512, 512><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 512, 512><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 1024: - soft_max_f32<true, 1024, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 1024, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 2048: - soft_max_f32<true, 2048, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 2048, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; case 4096: - soft_max_f32<true, 4096, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 4096, 1024><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; default: - soft_max_f32<true, 0, 0><<<block_nums, block_dims, shmem, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<true, 0, 0><<<block_nums, block_dims, shmem, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); break; } } else { const size_t shmem_low = WARP_SIZE*sizeof(float); - soft_max_f32<false, 0, 0><<<block_nums, block_dims, shmem_low, stream>>>(x, mask, pos, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); + soft_max_f32<false, 0, 0><<<block_nums, block_dims, shmem_low, stream>>>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2); } } void ggml_cuda_op_soft_max(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; const ggml_tensor * src1 = dst->src[1]; - const ggml_tensor * src2 = dst->src[2]; const float * src0_d = (const float *)src0->data; const void * src1_d = src1 ? (const void *)src1->data : nullptr; @@ -190,7 +189,6 @@ void ggml_cuda_op_soft_max(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { GGML_ASSERT( dst->type == GGML_TYPE_F32); GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F16 || src1->type == GGML_TYPE_F32); // src1 contains mask and it is optional - GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F16 || src2->type == GGML_TYPE_F32); // src2 contains positions and it is optional const int64_t ne00 = src0->ne[0]; const int64_t nrows_x = ggml_nrows(src0); @@ -202,26 +200,15 @@ void ggml_cuda_op_soft_max(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { memcpy(&scale, (float *) dst->op_params + 0, sizeof(float)); memcpy(&max_bias, (float *) dst->op_params + 1, sizeof(float)); - // positions tensor - void * src2_d = nullptr; - - const bool use_src2 = src2 != nullptr; - - if (use_src2) { - src2_d = (void *)src2->data; - } - - const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16) || (src2 && src2->type == GGML_TYPE_F16); + const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16); if (use_f16) { const half * src1_dd = (const half *)src1_d; - const half * src2_dd = (const half *)src2_d; - soft_max_f32_cuda(src0_d, src1_dd, src2_dd, dst_d, ne00, nrows_x, nrows_y, scale, max_bias, stream); + soft_max_f32_cuda(src0_d, src1_dd, dst_d, ne00, nrows_x, nrows_y, scale, max_bias, stream); } else { const float * src1_dd = (const float *)src1_d; - const float * src2_dd = (const float *)src2_d; - soft_max_f32_cuda(src0_d, src1_dd, src2_dd, dst_d, ne00, nrows_x, nrows_y, scale, max_bias, stream); + soft_max_f32_cuda(src0_d, src1_dd, dst_d, ne00, nrows_x, nrows_y, scale, max_bias, stream); } } diff --git a/ggml-kompute.cpp b/ggml-kompute.cpp index 9a469821d8042..3f033d58be481 100644 --- a/ggml-kompute.cpp +++ b/ggml-kompute.cpp @@ -1559,12 +1559,18 @@ static void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml case GGML_OP_SOFT_MAX: { float scale; - memcpy(&scale, dst->op_params, sizeof(float)); + float max_bias; -#pragma message("TODO: add ggml_vk_soft_max() F16/F32 src1 and src2 support") + memcpy(&scale, (float *)dst->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *)dst->op_params + 1, sizeof(float)); + +#pragma message("TODO: add ggml_vk_soft_max() F16 src1 support") #pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/5021") GGML_ASSERT(!src1 || src1t == GGML_TYPE_F32); - GGML_ASSERT(src2 == nullptr); + +#pragma message("TODO: add ALiBi support") +#pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/7192") + GGML_ASSERT(max_bias == 0.0f); ggml_vk_soft_max(seq, id_src0, id_src1, id_dst, off_src0, off_src1, off_dst, ne00, ne01, ne02, ne03, scale); } break; diff --git a/ggml-metal.m b/ggml-metal.m index 18ce5b88a1c01..1bbb8fb4fefa1 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -169,7 +169,6 @@ GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_XS_F32, GGML_METAL_KERNEL_TYPE_ROPE_F32, GGML_METAL_KERNEL_TYPE_ROPE_F16, - GGML_METAL_KERNEL_TYPE_ALIBI_F32, GGML_METAL_KERNEL_TYPE_IM2COL_F16, GGML_METAL_KERNEL_TYPE_IM2COL_F32, GGML_METAL_KERNEL_TYPE_UPSCALE_F32, @@ -623,7 +622,6 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){ GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_IQ4_XS_F32, mul_mm_id_iq4_xs_f32, ctx->support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_F32, rope_f32, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ROPE_F16, rope_f16, true); - GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ALIBI_F32, alibi_f32, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_F16, im2col_f16, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_IM2COL_F32, im2col_f32, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_UPSCALE_F32, upscale_f32, true); @@ -759,7 +757,6 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const case GGML_OP_GROUP_NORM: return ctx->support_simdgroup_reduction; case GGML_OP_NORM: - case GGML_OP_ALIBI: case GGML_OP_ROPE: case GGML_OP_IM2COL: return true; @@ -1358,13 +1355,12 @@ static enum ggml_status ggml_metal_graph_compute( case GGML_OP_SOFT_MAX: { GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F16 || src1->type == GGML_TYPE_F32); - GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F16 || src2->type == GGML_TYPE_F32); int nth = 32; // SIMD width id<MTLComputePipelineState> pipeline = nil; - const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16) || (src2 && src2->type == GGML_TYPE_F16); + const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16); if (ne00%4 == 0) { while (nth < ne00/4 && nth < 256) { @@ -1395,8 +1391,8 @@ static enum ggml_status ggml_metal_graph_compute( const int64_t nrows_x = ggml_nrows(src0); const int64_t nrows_y = src0->ne[1]; - const uint32_t n_head_kv = nrows_x/nrows_y; - const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head_kv)); + const uint32_t n_head = nrows_x/nrows_y; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); @@ -1408,20 +1404,15 @@ static enum ggml_status ggml_metal_graph_compute( } else { [encoder setBuffer:id_src0 offset:offs_src0 atIndex:1]; } - if (id_src2) { - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - } else { - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:2]; - } - [encoder setBuffer:id_dst offset:offs_dst atIndex:3]; - [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:4]; - [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:5]; - [encoder setBytes:&ne02 length:sizeof(ne02) atIndex:6]; - [encoder setBytes:&scale length:sizeof(scale) atIndex:7]; - [encoder setBytes:&max_bias length:sizeof(max_bias) atIndex:8]; - [encoder setBytes:&m0 length:sizeof(m0) atIndex:9]; - [encoder setBytes:&m1 length:sizeof(m1) atIndex:10]; - [encoder setBytes:&n_head_log2 length:sizeof(n_head_log2) atIndex:11]; + [encoder setBuffer:id_dst offset:offs_dst atIndex:2]; + [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3]; + [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:4]; + [encoder setBytes:&ne02 length:sizeof(ne02) atIndex:5]; + [encoder setBytes:&scale length:sizeof(scale) atIndex:6]; + [encoder setBytes:&max_bias length:sizeof(max_bias) atIndex:7]; + [encoder setBytes:&m0 length:sizeof(m0) atIndex:8]; + [encoder setBytes:&m1 length:sizeof(m1) atIndex:9]; + [encoder setBytes:&n_head_log2 length:sizeof(n_head_log2) atIndex:10]; [encoder setThreadgroupMemoryLength:32*sizeof(float) atIndex:0]; [encoder dispatchThreadgroups:MTLSizeMake(ne01*ne02*ne03, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; @@ -2226,49 +2217,6 @@ static enum ggml_status ggml_metal_graph_compute( [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; } break; - case GGML_OP_ALIBI: - { - GGML_ASSERT((src0t == GGML_TYPE_F32)); - - const int nth = MIN(1024, ne00); - - //const int n_past = ((int32_t *) dst->op_params)[0]; - const int n_head = ((int32_t *) dst->op_params)[1]; - - float max_bias; - memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float)); - - const int n_heads_log2_floor = 1 << (int) floor(log2(n_head)); - const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor); - - id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_ALIBI_F32].pipeline; - - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2]; - [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3]; - [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4]; - [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5]; - [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6]; - [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7]; - [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8]; - [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9]; - [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10]; - [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11]; - [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12]; - [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13]; - [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14]; - [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15]; - [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16]; - [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17]; - [encoder setBytes:&m0 length:sizeof( float) atIndex:18]; - [encoder setBytes:&m1 length:sizeof( float) atIndex:19]; - [encoder setBytes:&n_heads_log2_floor length:sizeof(int) atIndex:20]; - - [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)]; - } break; case GGML_OP_ROPE: { GGML_ASSERT(ne10 == ne02); @@ -2566,7 +2514,7 @@ static enum ggml_status ggml_metal_graph_compute( "the Flash-Attention Metal kernel requires the mask to be padded to 8 and at least n_queries big"); const int64_t ne30 = src3 ? src3->ne[0] : 0; GGML_UNUSED(ne30); - const int64_t ne31 = src3 ? src3->ne[1] : 0; + //const int64_t ne31 = src3 ? src3->ne[1] : 0; const int64_t ne32 = src3 ? src3->ne[2] : 0; GGML_UNUSED(ne32); const int64_t ne33 = src3 ? src3->ne[3] : 0; GGML_UNUSED(ne33); @@ -2578,7 +2526,16 @@ static enum ggml_status ggml_metal_graph_compute( const enum ggml_type src2t = src2 ? src2->type : GGML_TYPE_COUNT; GGML_UNUSED(src2t); float scale; - memcpy(&scale, dst->op_params, sizeof(float)); + float max_bias; + + memcpy(&scale, ((int32_t *) dst->op_params) + 0, sizeof(scale)); + memcpy(&max_bias, ((int32_t *) dst->op_params) + 1, sizeof(max_bias)); + + const uint32_t n_head = src0->ne[2]; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); id<MTLComputePipelineState> pipeline = nil; @@ -2615,34 +2572,37 @@ static enum ggml_status ggml_metal_graph_compute( } [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; - [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; - [encoder setBuffer:id_src3 offset:offs_src3 atIndex:3]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:4]; - [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:5]; - [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:6]; - [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:7]; - [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:8]; - [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:9]; - [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:10]; - [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:11]; - [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:12]; - [encoder setBytes:&ne10 length:sizeof( int64_t) atIndex:13]; - [encoder setBytes:&ne11 length:sizeof( int64_t) atIndex:14]; - [encoder setBytes:&ne12 length:sizeof( int64_t) atIndex:15]; - [encoder setBytes:&ne13 length:sizeof( int64_t) atIndex:16]; - [encoder setBytes:&nb10 length:sizeof(uint64_t) atIndex:17]; - [encoder setBytes:&nb11 length:sizeof(uint64_t) atIndex:18]; - [encoder setBytes:&nb12 length:sizeof(uint64_t) atIndex:19]; - [encoder setBytes:&nb13 length:sizeof(uint64_t) atIndex:20]; - [encoder setBytes:&ne31 length:sizeof( int64_t) atIndex:21]; - [encoder setBytes:&nb31 length:sizeof(uint64_t) atIndex:22]; - [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:23]; - [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:24]; - [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:25]; - [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:26]; - [encoder setBytes:&scale length:sizeof( float) atIndex:27]; + [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; + [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1]; + [encoder setBuffer:id_src2 offset:offs_src2 atIndex:2]; + [encoder setBuffer:id_src3 offset:offs_src3 atIndex:3]; + [encoder setBuffer:id_dst offset:offs_dst atIndex:4]; + [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:5]; + [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:6]; + [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:7]; + [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:8]; + [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:9]; + [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:10]; + [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:11]; + [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:12]; + [encoder setBytes:&ne10 length:sizeof( int64_t) atIndex:13]; + [encoder setBytes:&ne11 length:sizeof( int64_t) atIndex:14]; + [encoder setBytes:&ne12 length:sizeof( int64_t) atIndex:15]; + [encoder setBytes:&ne13 length:sizeof( int64_t) atIndex:16]; + [encoder setBytes:&nb10 length:sizeof(uint64_t) atIndex:17]; + [encoder setBytes:&nb11 length:sizeof(uint64_t) atIndex:18]; + [encoder setBytes:&nb12 length:sizeof(uint64_t) atIndex:19]; + [encoder setBytes:&nb13 length:sizeof(uint64_t) atIndex:20]; + [encoder setBytes:&nb31 length:sizeof(uint64_t) atIndex:21]; + [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:22]; + [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:23]; + [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:24]; + [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:25]; + [encoder setBytes:&scale length:sizeof( float) atIndex:26]; + [encoder setBytes:&max_bias length:sizeof( float) atIndex:27]; + [encoder setBytes:&m0 length:sizeof(m0) atIndex:28]; + [encoder setBytes:&m1 length:sizeof(m1) atIndex:29]; + [encoder setBytes:&n_head_log2 length:sizeof(n_head_log2) atIndex:30]; if (!use_vec_kernel) { // half8x8 kernel diff --git a/ggml-metal.metal b/ggml-metal.metal index 46c7d503930a4..ee9de57a3a6f1 100644 --- a/ggml-metal.metal +++ b/ggml-metal.metal @@ -356,7 +356,6 @@ template<typename T> kernel void kernel_soft_max( device const char * src0, device const char * src1, - device const char * src2, device char * dst, constant int64_t & ne00, constant int64_t & ne01, @@ -378,10 +377,9 @@ kernel void kernel_soft_max( device const float * psrc0 = (device const float *) src0 + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00); device const T * pmask = src1 != src0 ? (device const T *) src1 + i01*ne00 : nullptr; - device const T * ppos = src2 != src0 ? (device const T *) src2 : nullptr; device float * pdst = (device float *) dst + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00); - float slope = 0.0f; + float slope = 1.0f; // ALiBi if (max_bias > 0.0f) { @@ -397,7 +395,7 @@ kernel void kernel_soft_max( float lmax = -INFINITY; for (int i00 = tpitg; i00 < ne00; i00 += ntg) { - lmax = MAX(lmax, psrc0[i00]*scale + (pmask ? pmask[i00] : 0.0f) + (ppos ? slope*ppos[i00] : 0.0f)); + lmax = MAX(lmax, psrc0[i00]*scale + (pmask ? slope*pmask[i00] : 0.0f)); } // find the max value in the block @@ -422,7 +420,7 @@ kernel void kernel_soft_max( // parallel sum float lsum = 0.0f; for (int i00 = tpitg; i00 < ne00; i00 += ntg) { - const float exp_psrc0 = exp((psrc0[i00]*scale + (pmask ? pmask[i00] : 0.0f) + (ppos ? slope*ppos[i00] : 0.0f)) - max_val); + const float exp_psrc0 = exp((psrc0[i00]*scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val); lsum += exp_psrc0; pdst[i00] = exp_psrc0; } @@ -461,7 +459,6 @@ template<typename T> kernel void kernel_soft_max_4( device const char * src0, device const char * src1, - device const char * src2, device char * dst, constant int64_t & ne00, constant int64_t & ne01, @@ -483,10 +480,9 @@ kernel void kernel_soft_max_4( device const float4 * psrc4 = (device const float4 *) src0 + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00)/4; device const T * pmask = src1 != src0 ? (device const T *) src1 + i01*ne00/4 : nullptr; - device const T * ppos = src2 != src0 ? (device const T *) src2 : nullptr; device float4 * pdst4 = (device float4 *) dst + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00)/4; - float slope = 0.0f; + float slope = 1.0f; if (max_bias > 0.0f) { const int64_t h = i02; @@ -501,7 +497,7 @@ kernel void kernel_soft_max_4( float4 lmax4 = -INFINITY; for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) { - lmax4 = fmax(lmax4, psrc4[i00]*scale + (float4)((pmask ? pmask[i00] : 0.0f) + (ppos ? slope*ppos[i00] : 0.0f))); + lmax4 = fmax(lmax4, psrc4[i00]*scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))); } const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3])); @@ -527,7 +523,7 @@ kernel void kernel_soft_max_4( // parallel sum float4 lsum4 = 0.0f; for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) { - const float4 exp_psrc4 = exp((psrc4[i00]*scale + (float4)((pmask ? pmask[i00] : 0.0f) + (ppos ? slope*ppos[i00] : 0.0f))) - max_val); + const float4 exp_psrc4 = exp((psrc4[i00]*scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val); lsum4 += exp_psrc4; pdst4[i00] = exp_psrc4; } @@ -1595,60 +1591,6 @@ kernel void kernel_mul_mv_f16_f32_l4( } } -kernel void kernel_alibi_f32( - device const float * src0, - device float * dst, - constant int64_t & ne00, - constant int64_t & ne01, - constant int64_t & ne02, - constant int64_t & ne03, - constant uint64_t & nb00, - constant uint64_t & nb01, - constant uint64_t & nb02, - constant uint64_t & nb03, - constant int64_t & ne0, - constant int64_t & ne1, - constant int64_t & ne2, - constant int64_t & ne3, - constant uint64_t & nb0, - constant uint64_t & nb1, - constant uint64_t & nb2, - constant uint64_t & nb3, - constant float & m0, - constant float & m1, - constant int & n_heads_log2_floor, - uint3 tgpig[[threadgroup_position_in_grid]], - uint3 tpitg[[thread_position_in_threadgroup]], - uint3 ntg[[threads_per_threadgroup]]) { - const int64_t i03 = tgpig[2]; - const int64_t i02 = tgpig[1]; - const int64_t i01 = tgpig[0]; - - const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; - - const int64_t i3 = n / (ne2*ne1*ne0); - const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); - const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; - //const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0); - - const int64_t k = i3*ne3 + i2; - - float m_k; - if (k < n_heads_log2_floor) { - m_k = pow(m0, k + 1); - } else { - m_k = pow(m1, 2 * (k - n_heads_log2_floor) + 1); - } - - device char * dst_row = (device char *) dst + i3*nb3 + i2*nb2 + i1*nb1; - device const char * src_row = (device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01; - for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { - const float src_v = *(device float *)(src_row + i00*nb00); - device float * dst_v = (device float *)(dst_row + i00*nb0); - *dst_v = i00 * m_k + src_v; - } -} - static float rope_yarn_ramp(const float low, const float high, const int i0) { const float y = (i0 / 2 - low) / max(0.001f, high - low); return 1.0f - min(1.0f, max(0.0f, y)); @@ -2116,13 +2058,16 @@ typedef void (flash_attn_ext_f16_t)( constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, - constant int64_t & ne31, constant uint64_t & nb31, constant int64_t & ne0, constant int64_t & ne1, constant int64_t & ne2, constant int64_t & ne3, constant float & scale, + constant float & max_bias, + constant float & m0, + constant float & m1, + constant uint32_t & n_head_log2, threadgroup half * shared, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -2154,13 +2099,16 @@ kernel void kernel_flash_attn_ext_f16( constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, - constant int64_t & ne31, constant uint64_t & nb31, constant int64_t & ne0, constant int64_t & ne1, constant int64_t & ne2, constant int64_t & ne3, constant float & scale, + constant float & max_bias, + constant float & m0, + constant float & m1, + constant uint32_t & n_head_log2, threadgroup half * shared [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -2257,6 +2205,19 @@ kernel void kernel_flash_attn_ext_f16( // prepare diagonal scale matrix simdgroup_float8x8 mscale(scale); + // prepare diagonal slope matrix + simdgroup_float8x8 mslope(1.0f); + + // ALiBi + if (max_bias > 0.0f) { + const short h = iq2; + + const float base = h < n_head_log2 ? m0 : m1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + mslope = simdgroup_float8x8(pow(base, exph)); + } + // loop over the KV cache // each simdgroup handles blocks of Q rows and C columns for (int ic0 = 0; ic0 < ne11; ic0 += C*nsg) { @@ -2279,9 +2240,10 @@ kernel void kernel_flash_attn_ext_f16( simdgroup_multiply_accumulate(mqk, mq[i], mk, mqk); } - // mqk = mqk*scale + mask + // mqk = mqk*scale + mask*slope simdgroup_half8x8 mm; simdgroup_load(mm, mp + ic + 8*cc, nb31/sizeof(half), 0, false); + simdgroup_multiply(mm, mslope, mm); simdgroup_multiply_accumulate(mqk, mqk, mscale, mm); simdgroup_store(mqk, ss + 8*cc, TF, 0, false); @@ -2472,13 +2434,16 @@ kernel void kernel_flash_attn_ext_vec_f16( constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, - constant int64_t & ne31, constant uint64_t & nb31, constant int64_t & ne0, constant int64_t & ne1, constant int64_t & ne2, constant int64_t & ne3, constant float & scale, + constant float & max_bias, + constant float & m0, + constant float & m1, + constant uint32_t & n_head_log2, threadgroup half * shared [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], @@ -2497,6 +2462,18 @@ kernel void kernel_flash_attn_ext_vec_f16( const short T = D + 2*nsg*SH; // shared memory size per query in (half) + float slope = 1.0f; + + // ALiBi + if (max_bias > 0.0f) { + const short h = iq2; + + const float base = h < n_head_log2 ? m0 : m1; + const int exp = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + slope = pow(base, exp); + } + //threadgroup half * sq = (threadgroup half *) (shared + 0*D); // holds the query data threadgroup half4 * sq4 = (threadgroup half4 *) (shared + 0*D); // same as above but in half4 threadgroup float * ss = (threadgroup float *) (shared + 2*sgitg*SH + 1*D); // scratch buffer for attention and diagonal matrix @@ -2603,10 +2580,10 @@ kernel void kernel_flash_attn_ext_vec_f16( mqk += simd_shuffle_down(mqk, 2); mqk += simd_shuffle_down(mqk, 1); - // mqk = mqk*scale + mask + // mqk = mqk*scale + mask*slope if (tiisg == 0) { float4 mm = (float4) mp4[ic/4 + cc]; - mqk = mqk*scale + mm; + mqk = mqk*scale + mm*slope; ss4[cc] = mqk; } @@ -2840,7 +2817,8 @@ kernel void kernel_cpy_f32_f16( for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); - dst_data[i00] = src[0]; + // TODO: is there a better way to handle -INFINITY? + dst_data[i00] = src[0] == -INFINITY ? -MAXHALF : src[0]; } } diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp index 79aec4d9f02e1..e93d2af631cc0 100644 --- a/ggml-sycl.cpp +++ b/ggml-sycl.cpp @@ -3154,7 +3154,6 @@ typedef float (*vec_dot_q_mul_mat_sycl_t)( #define SYCL_SCALE_BLOCK_SIZE 256 #define SYCL_CLAMP_BLOCK_SIZE 256 #define SYCL_ROPE_BLOCK_SIZE 256 -#define SYCL_ALIBI_BLOCK_SIZE 32 #define SYCL_DIAG_MASK_INF_BLOCK_SIZE 32 #define SYCL_QUANTIZE_BLOCK_SIZE 256 #define SYCL_DEQUANTIZE_BLOCK_SIZE 256 @@ -9316,32 +9315,6 @@ static void rope_glm_f32( dst[i + half_n_dims * 3] = x2*sin_block_theta + x3*cos_block_theta; } -static void alibi_f32(const float * x, float * dst, const int ncols, const int k_rows, - const int n_heads_log2_floor, const float m0, const float m1, - const sycl::nd_item<3> &item_ct1) { - const int col = item_ct1.get_local_range(2) * item_ct1.get_group(2) + - item_ct1.get_local_id(2); - - if (col >= ncols) { - return; - } - - const int row = item_ct1.get_local_range(1) * item_ct1.get_group(1) + - item_ct1.get_local_id(1); - const int i = row*ncols + col; - - const int k = row/k_rows; - - float m_k; - if (k < n_heads_log2_floor) { - m_k = dpct::pow(m0, k + 1); - } else { - m_k = dpct::pow(m1, 2 * (k - n_heads_log2_floor) + 1); - } - - dst[i] = col * m_k + x[i]; -} - static void k_sum_rows_f32(const float * x, float * dst, const int ncols, const sycl::nd_item<3> &item_ct1) { const int row = item_ct1.get_group(1); @@ -9443,7 +9416,7 @@ static void diag_mask_inf_f32(const float * x, float * dst, const int ncols, con template <bool vals_smem, int ncols_template, int block_size_template> -static void soft_max_f32(const float * x, const float * mask, const float *pos, float * dst, const int ncols_par, +static void soft_max_f32(const float * x, const float * mask, float * dst, const int ncols_par, const int nrows_y, const float scale, const float max_bias, const float m0, const float m1, uint32_t n_head_log2, const sycl::nd_item<3> &item_ct1, float *buf) { const int ncols = ncols_template == 0 ? ncols_par : ncols_template; @@ -9457,7 +9430,7 @@ static void soft_max_f32(const float * x, const float * mask, const float *pos, const int warp_id = item_ct1.get_local_id(2) / WARP_SIZE; const int lane_id = item_ct1.get_local_id(2) % WARP_SIZE; - float slope = 0.0f; + float slope = 1.0f; // ALiBi if (max_bias > 0.0f) { @@ -9482,7 +9455,7 @@ static void soft_max_f32(const float * x, const float * mask, const float *pos, const int ix = rowx*ncols + col; const int iy = rowy*ncols + col; - const float val = x[ix]*scale + (mask ? mask[iy] : 0.0f) + (pos ? slope*pos[col] : 0.0f); + const float val = x[ix]*scale + (mask ? slope*mask[iy] : 0.0f); vals[col] = val; max_val = sycl::max(max_val, val); @@ -12964,20 +12937,6 @@ static void rope_glm_f32_sycl(const float *x, float *dst, int ncols, int nrows, }); } -static void alibi_f32_sycl(const float *x, float *dst, const int ncols, - const int nrows, const int k_rows, - const int n_heads_log2_floor, const float m0, - const float m1, dpct::queue_ptr stream) { - const sycl::range<3> block_dims(1, 1, SYCL_ALIBI_BLOCK_SIZE); - const int num_blocks_x = (ncols + SYCL_ALIBI_BLOCK_SIZE - 1) / (SYCL_ALIBI_BLOCK_SIZE); - const sycl::range<3> block_nums(1, nrows, num_blocks_x); - stream->parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) { - alibi_f32(x, dst, ncols, k_rows, - n_heads_log2_floor, m0, m1, item_ct1); - }); -} - static void sum_rows_f32_sycl(const float *x, float *dst, const int ncols, const int nrows, dpct::queue_ptr stream) { const sycl::range<3> block_dims(1, 1, WARP_SIZE); @@ -13058,7 +13017,7 @@ static void diag_mask_inf_f32_sycl(const float *x, float *dst, } template <bool vals_smem, int ncols_template, int block_size_template> -static void soft_max_f32_submitter(const float * x, const float * mask, const float *pos, float * dst, const int ncols_par, +static void soft_max_f32_submitter(const float * x, const float * mask, float * dst, const int ncols_par, const int nrows_y, const float scale, const float max_bias, const float m0, const float m1, uint32_t n_head_log2, sycl::range<3> block_nums, sycl::range<3> block_dims, const size_t n_local_scratch, dpct::queue_ptr stream) { @@ -13068,7 +13027,7 @@ static void soft_max_f32_submitter(const float * x, const float * mask, const fl cgh.parallel_for( sycl::nd_range<3>(block_nums * block_dims, block_dims), [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - soft_max_f32<vals_smem, ncols_template, block_size_template>(x, mask, pos, dst, ncols_par, + soft_max_f32<vals_smem, ncols_template, block_size_template>(x, mask, dst, ncols_par, nrows_y, scale, max_bias, m0, m1, n_head_log2, item_ct1, local_buf_acc.get_pointer()); @@ -13076,7 +13035,7 @@ static void soft_max_f32_submitter(const float * x, const float * mask, const fl }); } -static void soft_max_f32_sycl(const float * x, const float * mask, const float * pos, +static void soft_max_f32_sycl(const float * x, const float * mask, float * dst, const int ncols_x, const int nrows_x, const int nrows_y, const float scale, const float max_bias, dpct::queue_ptr stream) { @@ -13098,60 +13057,60 @@ static void soft_max_f32_sycl(const float * x, const float * mask, const float * const size_t local_mem_size = stream->get_device().get_info<sycl::info::device::local_mem_size>(); if (n_local_scratch*sizeof(float) < local_mem_size) { if (ncols_x > max_block_size) { - soft_max_f32_submitter<true, 0, 0>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 0, 0>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); return; } switch (ncols_x) { case 32: - soft_max_f32_submitter<true, 32, 32>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 32, 32>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 64: - soft_max_f32_submitter<true, 64, 64>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 64, 64>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 128: - soft_max_f32_submitter<true, 128, 128>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 128, 128>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 256: - soft_max_f32_submitter<true, 256, 256>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 256, 256>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 512: - soft_max_f32_submitter<true, 512, 512>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 512, 512>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 1024: - soft_max_f32_submitter<true, 1024, 1024>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 1024, 1024>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 2048: - soft_max_f32_submitter<true, 2048, 1024>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 2048, 1024>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; case 4096: - soft_max_f32_submitter<true, 4096, 1024>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 4096, 1024>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; default: - soft_max_f32_submitter<true, 0, 0>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<true, 0, 0>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, n_local_scratch, stream); break; } } else { - soft_max_f32_submitter<false, 0, 0>(x, mask, pos, dst, ncols_x, nrows_y, scale, + soft_max_f32_submitter<false, 0, 0>(x, mask, dst, ncols_x, nrows_y, scale, max_bias, m0, m1, n_head_log2, block_nums, block_dims, WARP_SIZE, stream); } @@ -14562,36 +14521,6 @@ inline void ggml_sycl_op_rope(const ggml_tensor *src0, const ggml_tensor *src1, (void) src1_dd; } -inline void ggml_sycl_op_alibi(const ggml_tensor *src0, const ggml_tensor *src1, - ggml_tensor *dst, const float *src0_dd, - const float *src1_dd, float *dst_dd, - const dpct::queue_ptr &main_stream) { - - GGML_ASSERT(src0->type == GGML_TYPE_F32); - GGML_ASSERT( dst->type == GGML_TYPE_F32); - - GGML_TENSOR_LOCALS_3(int64_t, ne0, src0, ne); - const int64_t nrows = ggml_nrows(src0); - - //const int n_past = ((int32_t *) dst->op_params)[0]; - const int n_head = ((int32_t *) dst->op_params)[1]; - float max_bias; - memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float)); - - //GGML_ASSERT(ne01 + n_past == ne00); - GGML_ASSERT(n_head == ne02); - - const int n_heads_log2_floor = 1 << (int) floor(log2(n_head)); - - const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor); - - alibi_f32_sycl(src0_dd, dst_dd, ne00, nrows, ne01, n_heads_log2_floor, m0, m1, main_stream); - - (void) src1; - (void) src1_dd; -} - static void ggml_sycl_op_pool2d(const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst, const float *src0_dd, const float *src1_dd, @@ -14746,12 +14675,9 @@ inline void ggml_sycl_op_soft_max(const ggml_tensor *src0, GGML_ASSERT(src0->type == GGML_TYPE_F32); GGML_ASSERT( dst->type == GGML_TYPE_F32); - const ggml_tensor * src2 = dst->src[2]; - -#pragma message("TODO: add ggml_sycl_op_soft_max() F16 src1 and src2 support") +#pragma message("TODO: add ggml_sycl_op_soft_max() F16 src1 support") #pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/5021") GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32); // src1 contains mask and it is optional - GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F32); // src2 contains positions and it is optional const int64_t ne00 = src0->ne[0]; const int64_t nrows_x = ggml_nrows(src0); @@ -14763,25 +14689,7 @@ inline void ggml_sycl_op_soft_max(const ggml_tensor *src0, memcpy(&scale, dst->op_params + 0, sizeof(float)); memcpy(&max_bias, dst->op_params + 1, sizeof(float)); - // positions tensor - float * src2_dd = nullptr; - sycl_pool_alloc<float> src2_f; - - const bool use_src2 = src2 != nullptr; - - if (use_src2) { - const bool src2_on_device = src2->backend == GGML_BACKEND_TYPE_GPU; - - if (src2_on_device) { - ggml_tensor_extra_gpu * src2_extra = (ggml_tensor_extra_gpu *) src2->extra; - src2_dd = (float *) src2_extra->data_device[g_main_device]; - } else { - src2_dd = src2_f.alloc(ggml_nelements(src2)); - SYCL_CHECK(ggml_sycl_cpy_tensor_2d(src2_dd, src2, 0, 0, 0, 1, main_stream)); - } - } - - soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, src2_dd, dst_dd, ne00, + soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, dst_dd, ne00, nrows_x, nrows_y, scale, max_bias, main_stream); } @@ -16232,10 +16140,6 @@ static void ggml_sycl_rope(const ggml_tensor * src0, const ggml_tensor * src1, g ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_rope); } -static void ggml_sycl_alibi(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { - ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_alibi); -} - static void ggml_sycl_pool2d(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_pool2d); } @@ -16612,9 +16516,6 @@ bool ggml_sycl_compute_forward(struct ggml_compute_params * params, struct ggml_ case GGML_OP_ROPE: func = ggml_sycl_rope; break; - case GGML_OP_ALIBI: - func = ggml_sycl_alibi; - break; case GGML_OP_IM2COL: func = ggml_sycl_im2col; break; @@ -17744,7 +17645,6 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons case GGML_OP_DIAG_MASK_INF: case GGML_OP_SOFT_MAX: case GGML_OP_ROPE: - case GGML_OP_ALIBI: case GGML_OP_IM2COL: case GGML_OP_POOL_2D: case GGML_OP_SUM_ROWS: diff --git a/ggml-vulkan.cpp b/ggml-vulkan.cpp index 95f7189740539..b9449be0357b5 100644 --- a/ggml-vulkan.cpp +++ b/ggml-vulkan.cpp @@ -3830,9 +3830,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const return nullptr; case GGML_OP_SOFT_MAX: GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16); - GGML_ASSERT(!src2 || src2->type == GGML_TYPE_F32 || src2->type == GGML_TYPE_F16); - if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && (src2 == nullptr || src2->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) { + if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) { return ctx->device->pipeline_soft_max_f32; } if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16 && src2->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F32) { @@ -4286,6 +4285,9 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx, const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); +#pragma message("TODO: src2 is no longer used in soft_max - should be removed and ALiBi calculation should be updated") +#pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/7192") + ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, { ncols, src1 != nullptr ? nrows_y : (uint32_t)0, diff --git a/ggml.c b/ggml.c index 093d38d00ae35..4ee5d24af75d0 100644 --- a/ggml.c +++ b/ggml.c @@ -2185,7 +2185,6 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "SOFT_MAX_BACK", "ROPE", "ROPE_BACK", - "ALIBI", "CLAMP", "CONV_TRANSPOSE_1D", "IM2COL", @@ -2227,7 +2226,7 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "CROSS_ENTROPY_LOSS_BACK", }; -static_assert(GGML_OP_COUNT == 77, "GGML_OP_COUNT != 77"); +static_assert(GGML_OP_COUNT == 76, "GGML_OP_COUNT != 76"); static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "none", @@ -2276,7 +2275,6 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "soft_max_back(x)", "rope(x)", "rope_back(x)", - "alibi(x)", "clamp(x)", "conv_transpose_1d(x)", "im2col(x)", @@ -2318,7 +2316,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "cross_entropy_loss_back(x,y)", }; -static_assert(GGML_OP_COUNT == 77, "GGML_OP_COUNT != 77"); +static_assert(GGML_OP_COUNT == 76, "GGML_OP_COUNT != 76"); static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2"); @@ -5646,7 +5644,6 @@ static struct ggml_tensor * ggml_soft_max_impl( struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * mask, - struct ggml_tensor * pos, float scale, float max_bias, bool inplace) { @@ -5660,18 +5657,8 @@ static struct ggml_tensor * ggml_soft_max_impl( GGML_ASSERT(mask->ne[1] >= a->ne[1]); } - if (pos) { - GGML_ASSERT(ggml_is_vector(pos)); - GGML_ASSERT(pos->type == GGML_TYPE_F16 || pos->type == GGML_TYPE_F32); - GGML_ASSERT(pos->ne[0] == a->ne[0]); - } - - if (pos && mask) { - GGML_ASSERT(pos->type == mask->type); - } - if (max_bias > 0.0f) { - GGML_ASSERT(pos); + GGML_ASSERT(mask); } bool is_node = false; @@ -5689,7 +5676,6 @@ static struct ggml_tensor * ggml_soft_max_impl( result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL; result->src[0] = a; result->src[1] = mask; - result->src[2] = pos; return result; } @@ -5697,23 +5683,22 @@ static struct ggml_tensor * ggml_soft_max_impl( struct ggml_tensor * ggml_soft_max( struct ggml_context * ctx, struct ggml_tensor * a) { - return ggml_soft_max_impl(ctx, a, NULL, NULL, 1.0f, 0.0f, false); + return ggml_soft_max_impl(ctx, a, NULL, 1.0f, 0.0f, false); } struct ggml_tensor * ggml_soft_max_inplace( struct ggml_context * ctx, struct ggml_tensor * a) { - return ggml_soft_max_impl(ctx, a, NULL, NULL, 1.0f, 0.0f, true); + return ggml_soft_max_impl(ctx, a, NULL, 1.0f, 0.0f, true); } struct ggml_tensor * ggml_soft_max_ext( struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * mask, - struct ggml_tensor * pos, float scale, float max_bias) { - return ggml_soft_max_impl(ctx, a, mask, pos, scale, max_bias, false); + return ggml_soft_max_impl(ctx, a, mask, scale, max_bias, false); } // ggml_soft_max_back @@ -5928,37 +5913,6 @@ struct ggml_tensor * ggml_rope_back( return result; } -// ggml_alibi - -struct ggml_tensor * ggml_alibi( - struct ggml_context * ctx, - struct ggml_tensor * a, - int n_past, - int n_head, - float bias_max) { - GGML_ASSERT(n_past >= 0); - bool is_node = false; - - if (a->grad) { - GGML_ASSERT(false); // TODO: implement backward - is_node = true; - } - - // TODO: when implement backward, fix this: - //struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - struct ggml_tensor * result = ggml_view_tensor(ctx, a); - - int32_t op_params[3] = { n_past, n_head }; - memcpy(op_params + 2, &bias_max, sizeof(float)); - ggml_set_op_params(result, op_params, sizeof(op_params)); - - result->op = GGML_OP_ALIBI; - result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL; - result->src[0] = a; - - return result; -} - // ggml_clamp struct ggml_tensor * ggml_clamp( @@ -6486,9 +6440,11 @@ struct ggml_tensor * ggml_flash_attn_ext( struct ggml_tensor * k, struct ggml_tensor * v, struct ggml_tensor * mask, - float scale) { + float scale, + float max_bias) { GGML_ASSERT(ggml_can_mul_mat(k, q)); // TODO: check if vT can be multiplied by (k*qT) + if (mask) { GGML_ASSERT(ggml_is_contiguous(mask)); GGML_ASSERT(mask->ne[2] == 1); @@ -6498,6 +6454,10 @@ struct ggml_tensor * ggml_flash_attn_ext( //GGML_ASSERT(ggml_can_repeat_rows(mask, qk)); } + if (max_bias > 0.0f) { + GGML_ASSERT(mask); + } + bool is_node = false; if (q->grad || k->grad || v->grad) { @@ -6508,7 +6468,7 @@ struct ggml_tensor * ggml_flash_attn_ext( int64_t ne[4] = { q->ne[0], q->ne[2], q->ne[1], q->ne[3] }; struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne); - float params[] = { scale }; + float params[] = { scale, max_bias }; ggml_set_op_params(result, params, sizeof(params)); result->op = GGML_OP_FLASH_ATTN_EXT; @@ -6528,7 +6488,7 @@ void ggml_flash_attn_ext_set_prec( const int32_t prec_i32 = (int32_t) prec; - ggml_set_op_params_i32(a, 1, prec_i32); // scale is on first pos + ggml_set_op_params_i32(a, 2, prec_i32); // scale is on first pos, max_bias on second } // ggml_flash_ff @@ -13333,7 +13293,6 @@ static void ggml_compute_forward_soft_max_f32( const struct ggml_tensor * src0 = dst->src[0]; const struct ggml_tensor * src1 = dst->src[1]; - const struct ggml_tensor * src2 = dst->src[2]; assert(ggml_is_contiguous(dst)); assert(ggml_are_same_shape(src0, dst)); @@ -13359,8 +13318,8 @@ static void ggml_compute_forward_soft_max_f32( // TODO: is this supposed to be ceil instead of floor? // https://huggingface.co/mosaicml/mpt-7b/blob/main/attention.py#L370 - const uint32_t n_head_kv = ne02; - const uint32_t n_head_log2 = 1u << (uint32_t) floor(log2(n_head_kv)); + const uint32_t n_head = ne02; + const uint32_t n_head_log2 = 1u << (uint32_t) floor(log2(n_head)); const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); @@ -13377,13 +13336,13 @@ static void ggml_compute_forward_soft_max_f32( float * wp = (float *) params->wdata + (nc + CACHE_LINE_SIZE_F32) * ith; - // when max_bias <= 0.0f, src2 is not used and we default it to src0 to avoid branching - ggml_fp16_t * pos_f16 = src2 ? (ggml_fp16_t *) src2->data : src0->data; - float * pos_f32 = src2 ? (float *) src2->data : src0->data; - - const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16) || (src2 && src2->type == GGML_TYPE_F16); + const bool use_f16 = (src1 && src1->type == GGML_TYPE_F16); for (int i1 = ir0; i1 < ir1; i1++) { + // ALiBi + const uint32_t h = (i1/ne01)%ne02; // head + const float slope = (max_bias > 0.0f) ? h < n_head_log2 ? powf(m0, h + 1) : powf(m1, 2*(h - n_head_log2) + 1) : 1.0f; + float * sp = (float *)((char *) src0->data + i1*src0->nb[1]); float * dp = (float *)((char *) dst->data + i1*dst->nb[1]); @@ -13396,27 +13355,11 @@ static void ggml_compute_forward_soft_max_f32( if (mp_f32) { if (use_f16) { for (int i = 0; i < nc; ++i) { - wp[i] += GGML_FP16_TO_FP32(mp_f16[i]); + wp[i] += slope*GGML_FP16_TO_FP32(mp_f16[i]); } } else { for (int i = 0; i < nc; ++i) { - wp[i] += mp_f32[i]; - } - } - } - - // ALiBi bias - if (max_bias > 0.0f) { - const uint32_t h = (i1/ne01)%ne02; // head - const float slope = h < n_head_log2 ? powf(m0, h + 1) : powf(m1, 2*(h - n_head_log2) + 1); - - if (use_f16) { - for (int i = 0; i < nc; ++i) { - wp[i] += slope*GGML_FP16_TO_FP32(pos_f16[i]); - } - } else { - for (int i = 0; i < nc; ++i) { - wp[i] += slope*pos_f32[i]; + wp[i] += slope*mp_f32[i]; } } } @@ -13578,178 +13521,6 @@ static void ggml_compute_forward_soft_max_back( } } -// ggml_compute_forward_alibi - -static void ggml_compute_forward_alibi_f32( - const struct ggml_compute_params * params, - struct ggml_tensor * dst) { - - const struct ggml_tensor * src0 = dst->src[0]; - - assert(params->ith == 0); - - if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { - return; - } - - //const int n_past = ((int32_t *) dst->op_params)[0]; - const int n_head = ((int32_t *) dst->op_params)[1]; - float max_bias; - memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float)); - - const int64_t ne0 = src0->ne[0]; // all_seq_len = n_past + ne1 - const int64_t ne1 = src0->ne[1]; // seq_len_without_past - const int64_t ne2 = src0->ne[2]; // n_head -> this is k - //const int64_t ne3 = src0->ne[3]; // 1 -> bsz - - const int64_t n = ggml_nrows(src0); - const int64_t ne2_ne3 = n/ne1; // ne2*ne3 - - const size_t nb0 = src0->nb[0]; - const size_t nb1 = src0->nb[1]; - const size_t nb2 = src0->nb[2]; - //const int nb3 = src0->nb[3]; - - GGML_ASSERT(nb0 == sizeof(float)); - GGML_ASSERT(n_head == ne2); - - // add alibi to src0 (KQ_scaled) - const int n_heads_log2_floor = 1 << (int) floor(log2(n_head)); - - const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor); - - for (int64_t k = 0; k < ne2_ne3; k++) { - // TODO: k*nb2 or k*nb3 - float m_k; - - if (k < n_heads_log2_floor) { - m_k = powf(m0, k + 1); - } else { - m_k = powf(m1, 2 * (k - n_heads_log2_floor) + 1); - } - - for (int64_t i = 0; i < ne0; i++) { - for (int64_t j = 0; j < ne1; j++) { - float * const src = (float *)((char *) src0->data + i*nb0 + j*nb1 + k*nb2); - float * pdst = (float *)((char *) dst->data + i*nb0 + j*nb1 + k*nb2); - pdst[0] = i * m_k + src[0]; - } - } - } -} - -static void ggml_compute_forward_alibi_f16( - const struct ggml_compute_params * params, - struct ggml_tensor * dst) { - - const struct ggml_tensor * src0 = dst->src[0]; - - assert(params->ith == 0); - - if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { - return; - } - - //const int n_past = ((int32_t *) dst->op_params)[0]; - const int n_head = ((int32_t *) dst->op_params)[1]; - float max_bias; - memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float)); - - const int ne0 = src0->ne[0]; // all_seq_len = n_past + ne1 - const int ne1 = src0->ne[1]; // seq_len_without_past - const int ne2 = src0->ne[2]; // n_head -> this is k - //const int ne3 = src0->ne[3]; // 1 -> bsz - - const int n = ggml_nrows(src0); - const int ne2_ne3 = n/ne1; // ne2*ne3 - - const int nb0 = src0->nb[0]; - const int nb1 = src0->nb[1]; - const int nb2 = src0->nb[2]; - //const int nb3 = src0->nb[3]; - - GGML_ASSERT(nb0 == sizeof(ggml_fp16_t)); - //GGML_ASSERT(ne1 + n_past == ne0); (void) n_past; - GGML_ASSERT(n_head == ne2); - - // add alibi to src0 (KQ_scaled) - const int n_heads_log2_floor = 1 << (int) floor(log2(n_head)); - - const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor); - - for (int k = 0; k < ne2_ne3; k++) { - // TODO: k*nb2 or k*nb3 - float m_k; - - if (k < n_heads_log2_floor) { - m_k = powf(m0, k + 1); - } else { - m_k = powf(m1, 2 * (k - n_heads_log2_floor) + 1); - } - - for (int i = 0; i < ne0; i++) { - for (int j = 0; j < ne1; j++) { - ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i*nb0 + j*nb1 + k*nb2); - float * pdst = (float *)((char *) dst->data + i*nb0 + j*nb1 + k*nb2); - - // we return F32 - pdst[0] = i * m_k + GGML_FP16_TO_FP32(src[0]); - } - } - } -} - -static void ggml_compute_forward_alibi( - const struct ggml_compute_params * params, - struct ggml_tensor * dst) { - - const struct ggml_tensor * src0 = dst->src[0]; - - switch (src0->type) { - case GGML_TYPE_F16: - { - ggml_compute_forward_alibi_f16(params, dst); - } break; - case GGML_TYPE_F32: - { - ggml_compute_forward_alibi_f32(params, dst); - } break; - case GGML_TYPE_BF16: - case GGML_TYPE_Q4_0: - case GGML_TYPE_Q4_1: - case GGML_TYPE_Q5_0: - case GGML_TYPE_Q5_1: - case GGML_TYPE_Q8_0: - case GGML_TYPE_Q8_1: - case GGML_TYPE_Q2_K: - case GGML_TYPE_Q3_K: - case GGML_TYPE_Q4_K: - case GGML_TYPE_Q5_K: - case GGML_TYPE_Q6_K: - case GGML_TYPE_IQ2_XXS: - case GGML_TYPE_IQ2_XS: - case GGML_TYPE_IQ3_XXS: - case GGML_TYPE_IQ1_S: - case GGML_TYPE_IQ1_M: - case GGML_TYPE_IQ4_NL: - case GGML_TYPE_IQ4_XS: - case GGML_TYPE_IQ3_S: - case GGML_TYPE_IQ2_S: - case GGML_TYPE_Q8_K: - case GGML_TYPE_I8: - case GGML_TYPE_I16: - case GGML_TYPE_I32: - case GGML_TYPE_I64: - case GGML_TYPE_F64: - case GGML_TYPE_COUNT: - { - GGML_ASSERT(false); - } break; - } -} - // ggml_compute_forward_clamp static void ggml_compute_forward_clamp_f32( @@ -15763,8 +15534,17 @@ static void ggml_compute_forward_flash_attn_ext_f16( const int ir0 = dr*ith; const int ir1 = MIN(ir0 + dr, nr); - float scale = 1.0f; - memcpy(&scale, (float *) dst->op_params + 0, sizeof(float)); + float scale = 1.0f; + float max_bias = 0.0f; + + memcpy(&scale, (float *) dst->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *) dst->op_params + 1, sizeof(float)); + + const uint32_t n_head = neq2; + const uint32_t n_head_log2 = 1u << (uint32_t) floor(log2(n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); // loop over n_batch and n_head for (int ir = ir0; ir < ir1; ++ir) { @@ -15773,6 +15553,9 @@ static void ggml_compute_forward_flash_attn_ext_f16( const int iq2 = (ir - iq3*neq2*neq1)/neq1; const int iq1 = (ir - iq3*neq2*neq1 - iq2*neq1); + const uint32_t h = iq2; // head + const float slope = (max_bias > 0.0f) ? h < n_head_log2 ? powf(m0, h + 1) : powf(m1, 2*(h - n_head_log2) + 1) : 1.0f; + float S = 0.0f; float M = -INFINITY; @@ -15796,7 +15579,7 @@ static void ggml_compute_forward_flash_attn_ext_f16( // loop over n_kv and n_head_kv // ref: https://arxiv.org/pdf/2112.05682.pdf for (int64_t ic = 0; ic < nek1; ++ic) { - const float mv = mp ? GGML_FP16_TO_FP32(mp[ic]) : 0.0f; + const float mv = mp ? slope*GGML_FP16_TO_FP32(mp[ic]) : 0.0f; if (mv == -INFINITY) { continue; } @@ -15867,7 +15650,7 @@ static void ggml_compute_forward_flash_attn_ext( const struct ggml_tensor * v, const struct ggml_tensor * mask, struct ggml_tensor * dst) { - switch (dst->op_params[1]) { + switch (dst->op_params[2]) { case GGML_PREC_DEFAULT: case GGML_PREC_F32: { @@ -17630,10 +17413,6 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm { ggml_compute_forward_rope_back(params, tensor); } break; - case GGML_OP_ALIBI: - { - ggml_compute_forward_alibi(params, tensor); - } break; case GGML_OP_CLAMP: { ggml_compute_forward_clamp(params, tensor); @@ -18652,10 +18431,6 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor zero_table); } } break; - case GGML_OP_ALIBI: - { - GGML_ASSERT(false); // TODO: not implemented - } break; case GGML_OP_CLAMP: { GGML_ASSERT(false); // TODO: not implemented @@ -19428,10 +19203,6 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads, int n_cur_ { n_tasks = n_threads; } break; - case GGML_OP_ALIBI: - { - n_tasks = 1; //TODO - } break; case GGML_OP_CLAMP: { n_tasks = 1; //TODO diff --git a/ggml.h b/ggml.h index fe60538220680..76c3328315964 100644 --- a/ggml.h +++ b/ggml.h @@ -468,7 +468,6 @@ extern "C" { GGML_OP_SOFT_MAX_BACK, GGML_OP_ROPE, GGML_OP_ROPE_BACK, - GGML_OP_ALIBI, GGML_OP_CLAMP, GGML_OP_CONV_TRANSPOSE_1D, GGML_OP_IM2COL, @@ -1428,15 +1427,13 @@ extern "C" { struct ggml_context * ctx, struct ggml_tensor * a); - // fused soft_max(a*scale + mask + pos[i]*(ALiBi slope)) + // fused soft_max(a*scale + mask*(ALiBi slope)) // mask is optional - // pos is required when max_bias > 0.0f // max_bias = 0.0f for no ALiBi GGML_API struct ggml_tensor * ggml_soft_max_ext( struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * mask, - struct ggml_tensor * pos, float scale, float max_bias); @@ -1538,16 +1535,6 @@ extern "C" { float xpos_base, bool xpos_down); - // alibi position embedding - // in-place, returns view(a) - GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_alibi( - struct ggml_context * ctx, - struct ggml_tensor * a, - int n_past, - int n_head, - float bias_max), - "use ggml_soft_max_ext instead (will be removed in Mar 2024)"); - // clamp // in-place, returns view(a) GGML_API struct ggml_tensor * ggml_clamp( @@ -1744,7 +1731,8 @@ extern "C" { struct ggml_tensor * k, struct ggml_tensor * v, struct ggml_tensor * mask, - float scale); + float scale, + float max_bias); GGML_API void ggml_flash_attn_ext_set_prec( struct ggml_tensor * a, diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index e5750d4191f6b..990fe63c2acd1 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -137,6 +137,7 @@ class TensorNameMap: "layers.{bid}.attention.wk", # llama-pth "encoder.layer.{bid}.attention.self.key", # bert "transformer.h.{bid}.attn.k_proj", # gpt-j + "transformer.h.{bid}.attn.k", # refact "model.layers.layers.{bid}.self_attn.k_proj", # plamo "model.layers.{bid}.attention.wk", # internlm2 "transformer.decoder_layer.{bid}.multi_head_attention.key" # Grok @@ -148,6 +149,7 @@ class TensorNameMap: "layers.{bid}.attention.wv", # llama-pth "encoder.layer.{bid}.attention.self.value", # bert "transformer.h.{bid}.attn.v_proj", # gpt-j + "transformer.h.{bid}.attn.v", # refact "model.layers.layers.{bid}.self_attn.v_proj", # plamo "model.layers.{bid}.attention.wv", # internlm2 "transformer.decoder_layer.{bid}.multi_head_attention.value" # Grok @@ -229,6 +231,7 @@ class TensorNameMap: "layers.{bid}.feed_forward.w3", # llama-pth "encoder.layer.{bid}.intermediate.dense", # bert "transformer.h.{bid}.mlp.fc_in", # gpt-j + "transformer.h.{bid}.mlp.linear_3", # refact "language_model.encoder.layers.{bid}.mlp.dense_h_to_4h", # persimmon "model.layers.{bid}.mlp.dense_h_to_4h", # persimmon "transformer.h.{bid}.mlp.w1", # qwen @@ -266,6 +269,7 @@ class TensorNameMap: "model.layers.layers.{bid}.mlp.gate_proj", # plamo "model.layers.{bid}.feed_forward.w1", # internlm2 "encoder.layers.{bid}.mlp.fc12", # nomic-bert + "transformer.h.{bid}.mlp.linear_1", # refact ), MODEL_TENSOR.FFN_GATE_EXP: ( diff --git a/llama.cpp b/llama.cpp index 2f1123d4e1678..dede68cb5a3f9 100644 --- a/llama.cpp +++ b/llama.cpp @@ -1845,7 +1845,7 @@ struct llama_hparams { float f_logit_scale = 0.0f; bool causal_attn = true; - bool use_alibi = false; // currently, we need KQ_pos data for ALiBi-based models + bool use_alibi = false; enum llama_pooling_type pooling_type = LLAMA_POOLING_TYPE_NONE; enum llama_rope_type rope_type = LLAMA_ROPE_TYPE_NONE; @@ -2317,7 +2317,6 @@ struct llama_context { struct ggml_tensor * inp_pos; // I32 [n_batch] struct ggml_tensor * inp_out_ids; // I32 [n_outputs] struct ggml_tensor * inp_KQ_mask; // F32 [kv_size, n_batch] - struct ggml_tensor * inp_KQ_pos; // F32 [n_kv] struct ggml_tensor * inp_K_shift; // I32 [kv_size] struct ggml_tensor * inp_mean; // F32 [n_batch, n_batch] struct ggml_tensor * inp_cls; // I32 [n_batch] @@ -6500,7 +6499,6 @@ static struct ggml_tensor * llm_build_kqv( struct ggml_tensor * wo_b, struct ggml_tensor * q_cur, struct ggml_tensor * kq_mask, - struct ggml_tensor * kq_pos, int32_t n_tokens, int32_t n_kv, float kq_scale, @@ -6530,10 +6528,6 @@ static struct ggml_tensor * llm_build_kqv( GGML_UNUSED(model); GGML_UNUSED(n_ctx); - // note: if this assert triggers, then some check has failed earlier - // the idea is to detect during context creation that ALiBi would be used and disable Flash Attention - GGML_ASSERT(kq_pos == nullptr && "ALiBi is not yet supported with Flash Attention"); - // split cached v into n_head heads (not transposed) struct ggml_tensor * v = ggml_view_3d(ctx, kv.v_l[il], @@ -6543,7 +6537,7 @@ static struct ggml_tensor * llm_build_kqv( 0); cb(v, "v", il); - cur = ggml_flash_attn_ext(ctx, q, k, v, kq_mask, kq_scale); + cur = ggml_flash_attn_ext(ctx, q, k, v, kq_mask, kq_scale, hparams.f_max_alibi_bias); if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3) { ggml_flash_attn_ext_set_prec(cur, GGML_PREC_F32); @@ -6574,28 +6568,8 @@ static struct ggml_tensor * llm_build_kqv( kq = ggml_scale(ctx, kq, 30); } -#if defined(GGML_USE_KOMPUTE) -#pragma message("TODO: ALiBi support in ggml_soft_max_ext is not implemented for Kompute") -#pragma message(" Falling back to ggml_alibi(). Will become an error in Mar 2024") -#pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/5488") - if (hparams.use_alibi) { - kq = ggml_scale(ctx, kq, kq_scale); - cb(kq, "kq_scaled", il); - - kq = ggml_alibi(ctx, kq, /*n_past*/ 0, n_head, hparams.f_max_alibi_bias); - cb(kq, "kq_scaled_alibi", il); - - kq = ggml_add(ctx, kq, kq_mask); - cb(kq, "kq_masked", il); - - kq = ggml_soft_max(ctx, kq); - cb(kq, "kq_soft_max", il); - } else -#endif - { - kq = ggml_soft_max_ext(ctx, kq, kq_mask, kq_pos, kq_scale, hparams.f_max_alibi_bias); - cb(kq, "kq_soft_max_ext", il); - } + kq = ggml_soft_max_ext(ctx, kq, kq_mask, kq_scale, hparams.f_max_alibi_bias); + cb(kq, "kq_soft_max_ext", il); GGML_ASSERT(kv.size == n_ctx); @@ -6645,7 +6619,6 @@ static struct ggml_tensor * llm_build_kv( struct ggml_tensor * v_cur, struct ggml_tensor * q_cur, struct ggml_tensor * kq_mask, - struct ggml_tensor * kq_pos, int32_t n_tokens, int32_t kv_head, int32_t n_kv, @@ -6664,7 +6637,7 @@ static struct ggml_tensor * llm_build_kv( struct ggml_tensor * cur; cur = llm_build_kqv(ctx, model, hparams, cparams, kv, graph, wo, wo_b, - q_cur, kq_mask, kq_pos, n_tokens, n_kv, kq_scale, cb, il); + q_cur, kq_mask, n_tokens, n_kv, kq_scale, cb, il); cb(cur, "kqv_out", il); return cur; @@ -6771,18 +6744,17 @@ struct llm_build_context { ctx0 = ggml_init(params); - lctx.inp_tokens = nullptr; - lctx.inp_embd = nullptr; - lctx.inp_pos = nullptr; + lctx.inp_tokens = nullptr; + lctx.inp_embd = nullptr; + lctx.inp_pos = nullptr; lctx.inp_out_ids = nullptr; lctx.inp_KQ_mask = nullptr; - lctx.inp_KQ_pos = nullptr; lctx.inp_K_shift = nullptr; - lctx.inp_mean = nullptr; - lctx.inp_cls = nullptr; - lctx.inp_s_copy = nullptr; - lctx.inp_s_mask = nullptr; - lctx.inp_s_seq = nullptr; + lctx.inp_mean = nullptr; + lctx.inp_cls = nullptr; + lctx.inp_s_copy = nullptr; + lctx.inp_s_mask = nullptr; + lctx.inp_s_seq = nullptr; } void free() { @@ -6932,19 +6904,6 @@ struct llm_build_context { return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_mask, GGML_TYPE_F16) : lctx.inp_KQ_mask; } - struct ggml_tensor * build_inp_KQ_pos(bool causal = true) { - if (causal) { - lctx.inp_KQ_pos = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, n_kv); - } else { - // TODO: this will be needed for ALiBi-based BERT models - // https://github.com/ggerganov/llama.cpp/pull/6826 - lctx.inp_KQ_pos = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, n_tokens); - } - cb(lctx.inp_KQ_pos, "KQ_pos", -1); - ggml_set_input(lctx.inp_KQ_pos); - return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_pos, GGML_TYPE_F16) : lctx.inp_KQ_pos; - } - struct ggml_tensor * build_inp_mean() { lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, n_tokens); cb(lctx.inp_mean, "inp_mean", -1); @@ -7050,7 +7009,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -7143,9 +7102,6 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) struct ggml_tensor * KQ_mask = build_inp_KQ_mask(); - // positions of the tokens in the KV cache - struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); - for (int il = 0; il < n_layer; ++il) { struct ggml_tensor * inpSA = inpL; @@ -7190,7 +7146,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, KQ_pos, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -7260,9 +7216,6 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) struct ggml_tensor * KQ_mask = build_inp_KQ_mask(); - // positions of the tokens in the KV cache - struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); - for (int il = 0; il < n_layer; ++il) { struct ggml_tensor * inpSA = inpL; @@ -7297,7 +7250,7 @@ struct llm_build_context { cb(Kcur, "Kcur", il); cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, KQ_pos, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -7417,7 +7370,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -7542,7 +7495,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f, cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il); } if (il == n_layer - 1) { @@ -7694,7 +7647,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -7806,7 +7759,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8010,7 +7963,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Q, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Q, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8076,9 +8029,6 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) struct ggml_tensor * KQ_mask = build_inp_KQ_mask(); - // positions of the tokens in the KV cache - struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); - for (int il = 0; il < n_layer; ++il) { struct ggml_tensor * inpSA = inpL; @@ -8106,7 +8056,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, KQ_pos, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8246,7 +8196,7 @@ struct llm_build_context { struct ggml_tensor * kq = ggml_mul_mat(ctx0, k, q); cb(kq, "kq", il); - kq = ggml_soft_max_ext(ctx0, kq, KQ_mask, nullptr, 1.0f/sqrtf(float(n_embd_head)), hparams.f_max_alibi_bias); + kq = ggml_soft_max_ext(ctx0, kq, KQ_mask, 1.0f/sqrtf(float(n_embd_head)), hparams.f_max_alibi_bias); cb(kq, "kq_soft_max_ext", il); struct ggml_tensor * v = ggml_cont(ctx0, ggml_transpose(ctx0, ggml_reshape_2d(ctx0, Vcur, n_embd_gqa, n_tokens))); @@ -8363,9 +8313,6 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) struct ggml_tensor * KQ_mask = build_inp_KQ_mask(); - // positions of the tokens in the KV cache - struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); - inpL = llm_build_norm(ctx0, inpL, hparams, model.tok_norm, model.tok_norm_b, @@ -8399,7 +8346,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, KQ_pos, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8464,9 +8411,6 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) struct ggml_tensor * KQ_mask = build_inp_KQ_mask(); - // positions of the tokens in the KV cache - struct ggml_tensor * KQ_pos = build_inp_KQ_pos(); - if (model.pos_embd) { // inp_pos - contains the positions struct ggml_tensor * inp_pos = build_inp_pos(); @@ -8530,13 +8474,13 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } else { Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens); cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, KQ_pos, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } } @@ -8680,7 +8624,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8798,7 +8742,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -8911,7 +8855,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9025,7 +8969,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9180,7 +9124,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f, cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il); } if (il == n_layer - 1) { @@ -9297,7 +9241,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f, cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il); } if (il == n_layer - 1) { @@ -9410,7 +9354,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } struct ggml_tensor * sa_out = cur; @@ -9513,7 +9457,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9620,7 +9564,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9736,7 +9680,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9853,7 +9797,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -9983,7 +9927,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -10104,7 +10048,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f, cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il); } if (il == n_layer - 1) { @@ -10223,7 +10167,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -10513,7 +10457,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, model.layers[il].bo, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -10644,7 +10588,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, nullptr, - Kcur, Vcur, Qcur, KQ_mask, nullptr, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); + Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il); } if (il == n_layer - 1) { @@ -11032,11 +10976,21 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) { if (!lctx.kv_self.cells[i].has_seq_id(seq_id) || lctx.kv_self.cells[i].pos > pos) { f = -INFINITY; } else { - f = 0.0f; + if (hparams.use_alibi) { + f = -fabs(lctx.kv_self.cells[i].pos - pos); + } else { + f = 0.0f; + } } data[h*(n_kv*n_tokens) + j*n_kv + i] = f; } } + + for (int i = n_tokens; i < GGML_PAD(n_tokens, GGML_KQ_MASK_PAD); ++i) { + for (int j = 0; j < n_kv; ++j) { + data[h*(n_kv*n_tokens) + i*n_kv + j] = -INFINITY; + } + } } } else { // when using kv cache, the mask needs to match the kv cache size @@ -11055,7 +11009,11 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) { float f = -INFINITY; for (int s = 0; s < batch.n_seq_id[i]; ++s) { if (batch.seq_id[i][s] == seq_id) { - f = 0.0f; + if (hparams.use_alibi) { + f = -fabs(batch.pos[i] - batch.pos[j]); + } else { + f = 0.0f; + } break; } } @@ -11071,21 +11029,6 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) { } } - // ALiBi requires the KQ_pos tensor to provide the sequence position of each token in the batch - // this allows to process multiple sequences in parallel with ALiBi-based models - if (hparams.use_alibi) { - const int64_t n_kv = kv_self.n; - - GGML_ASSERT(lctx.inp_KQ_pos); - GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_KQ_pos->buffer)); - - float * data = (float *) lctx.inp_KQ_pos->data; - - for (int i = 0; i < n_kv; ++i) { - data[i] = float(lctx.kv_self.cells[i].pos); - } - } - if (cparams.pooling_type == LLAMA_POOLING_TYPE_MEAN) { const int64_t n_tokens = batch.n_tokens; @@ -15509,11 +15452,6 @@ struct llama_context * llama_new_context_with_model( } } - if (cparams.flash_attn && hparams.use_alibi) { - LLAMA_LOG_WARN("%s: flash_attn is not yet compatible with ALiBi - forcing off\n", __func__); - cparams.flash_attn = false; - } - if (cparams.flash_attn && model->arch == LLM_ARCH_GROK) { LLAMA_LOG_WARN("%s: flash_attn is not compatible with Grok - forcing off\n", __func__); cparams.flash_attn = false; diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 0d66de5d9d389..731788b958fca 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -1111,11 +1111,7 @@ struct test_soft_max : public test_case { if (this->mask) { mask = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, ne[0], ne[1]); } - ggml_tensor * pos = nullptr; - if (max_bias > 0.0f) { - pos = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, ne[0]); - } - ggml_tensor * out = ggml_soft_max_ext(ctx, a, mask, pos, scale, max_bias); + ggml_tensor * out = ggml_soft_max_ext(ctx, a, mask, scale, max_bias); return out; } }; @@ -1490,23 +1486,25 @@ struct test_flash_attn_ext : public test_case { const int64_t kv; // kv size const int64_t nb; // batch size + const float max_bias; // ALiBi + std::string vars() override { - return VARS_TO_STR4(hs, nh, kv, nb); + return VARS_TO_STR5(hs, nh, kv, nb, max_bias); } double max_nmse_err() override { return 5e-4; } - test_flash_attn_ext(int64_t hs = 128, int64_t nh = 32, int64_t kv = 96, int64_t nb = 8) - : hs(hs), nh(nh), kv(kv), nb(nb) {} + test_flash_attn_ext(int64_t hs = 128, int64_t nh = 32, int64_t kv = 96, int64_t nb = 8, float max_bias = 0.0f) + : hs(hs), nh(nh), kv(kv), nb(nb), max_bias(max_bias) {} ggml_tensor * build_graph(ggml_context * ctx) override { ggml_tensor * q = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, hs, nb, nh, 1); ggml_tensor * k = ggml_new_tensor_4d(ctx, GGML_TYPE_F16, hs, kv, nh, 1); ggml_tensor * v = ggml_new_tensor_4d(ctx, GGML_TYPE_F16, hs, kv, nh, 1); ggml_tensor * mask = ggml_new_tensor_4d(ctx, GGML_TYPE_F16, kv, GGML_PAD(nb, GGML_KQ_MASK_PAD), 1, 1); - ggml_tensor * out = ggml_flash_attn_ext(ctx, q, k, v, mask, 1.0f/sqrtf(hs)); + ggml_tensor * out = ggml_flash_attn_ext(ctx, q, k, v, mask, 1.0f/sqrtf(hs), max_bias); return out; } }; @@ -1611,7 +1609,7 @@ struct test_llm : public test_case { struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q); - kq = ggml_soft_max_ext(ctx, kq, kq_mask, nullptr, kq_scale, 0.0f); + kq = ggml_soft_max_ext(ctx, kq, kq_mask, kq_scale, 0.0f); // split cached v into n_head heads struct ggml_tensor * v = @@ -2128,6 +2126,7 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op #endif for (bool mask : {false, true}) { for (float max_bias : {0.0f, 8.0f}) { + if (!mask && max_bias > 0.0f) continue; for (float scale : {1.0f, 0.1f}) { for (int64_t ne0 : {16, 1024}) { for (int64_t ne1 : {16, 1024}) { @@ -2141,7 +2140,6 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, false, 0.1f, 0.0f)); test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, 0.1f, 0.0f)); - test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, false, 0.1f, 8.0f)); test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, 0.1f, 8.0f)); for (ggml_type type : {GGML_TYPE_F32, GGML_TYPE_F16}) { @@ -2180,10 +2178,12 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op #else for (int hs : { 64, 80, 128, 256, }) { #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) - for (int nh : { 32, }) { - for (int kv : { 512, 1024, }) { - for (int nb : { 1, 2, 4, 8, }) { - test_cases.emplace_back(new test_flash_attn_ext(hs, nh, kv, nb)); + for (float max_bias : {0.0f, 8.0f}) { + for (int nh : { 32, }) { + for (int kv : { 512, 1024, }) { + for (int nb : { 1, 2, 4, 8, }) { + test_cases.emplace_back(new test_flash_attn_ext(hs, nh, kv, nb, max_bias)); + } } } } From b83cc3f5b303ff30c52874b2d5864dc6385ebf9f Mon Sep 17 00:00:00 2001 From: Joan Fontanals <jfontanalsmartinez@gmail.com> Date: Sat, 11 May 2024 09:46:09 +0200 Subject: [PATCH 39/64] llama : add Jina Embeddings architecture (#6826) * feat: first things to do * feat: create tensors for Jina architecture * fix: use other tensors * feat: embedding gets results * fix: fix usage of ALIBI * fix: clean prints * fix: do some cleanup unused vars * fix: revert changes to Makefile and CMakeLists * fix: revert some changes * fix: fix small detail * fix: fix convert formatting * fix: fix linting and editor * feat: set proper vocab settings * fix: JinaBertForMaskedLM registration * feat: support q_normalization and k_normalization in Jina arch * feat: handle gpt2 tokenizer with Jina architecture * feat: example comments in embedding * feat: rename Jina Bert to Jina Bert V2 * fix: add some changes as per review * feat: proper KQ_pos for Jina embeddings * feat: add capacity to load models ES and DE for Spanish * llama : fix pre-tokenizers * ggml : full ALiBi support * ggml : update ggml_soft_max_ext() CUDA, SYCL * ggml : ggml_flash_attn_ext() support ALiBi (CPU) * ggml : ggml_flash_attn_ext() support ALiBi (Metal) * ggml : fix warning * ggml : ggml_flash_attn_ext() support ALiBi (CUDA) ggml-ci * minor : clean-up * embedding : add warning about missing SEP --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --- convert-hf-to-gguf-update.py | 3 + convert-hf-to-gguf.py | 48 +++++++- examples/embedding/embedding.cpp | 12 +- gguf-py/gguf/constants.py | 18 +++ gguf-py/gguf/tensor_mapping.py | 6 + llama.cpp | 190 ++++++++++++++++++++++++------- 6 files changed, 236 insertions(+), 41 deletions(-) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index b5eb41eacdab7..e757d5ccbc0b4 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -74,6 +74,9 @@ class TOKENIZER_TYPE(IntEnum): {"name": "qwen2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", }, {"name": "olmo", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", }, {"name": "dbrx", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", }, + {"name": "jina-en", "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-en", }, # WPM! + {"name": "jina-es", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", }, + {"name": "jina-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", }, ] # make directory "models/tokenizers" if it doesn't exist diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 3315ca74b044b..fbaed64da1cac 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -404,8 +404,17 @@ def get_vocab_base_pre(self, tokenizer) -> str: # ref: https://huggingface.co/allenai/OLMo-1.7-7B-hf res = "olmo" if chkhsh == "a8594e3edff7c29c003940395316294b2c623e09894deebbc65f33f1515df79e": - # ref: https://huggingface.co/databricks/dbrx-instruct + # ref: https://huggingface.co/databricks/dbrx-base res = "dbrx" + if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f": + # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-en + res = "jina-en" + if chkhsh == "171aeeedd6fb548d418a7461d053f11b6f1f1fc9b387bd66640d28a4b9f5c643": + # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-es + res = "jina-es" + if chkhsh == "27949a2493fc4a9f53f5b9b029c82689cfbe5d3a1929bb25e043089e28466de6": + # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-de + res = "jina-de" if res is None: logger.warning("\n") @@ -2289,6 +2298,43 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter return [(self.map_tensor_name(name), data_torch)] +@Model.register("JinaBertModel", "JinaBertForMaskedLM") +class JinaBertV2Model(BertModel): + model_arch = gguf.MODEL_ARCH.JINA_BERT_V2 + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.intermediate_size = self.hparams["intermediate_size"] + + def get_tensors(self): + for name, data in super().get_tensors(): + if 'gated_layers' in name: + d1 = data[:self.intermediate_size, :] + name1 = name.replace('gated_layers', 'gated_layers_w') + d2 = data[self.intermediate_size:, :] + name2 = name.replace('gated_layers', 'gated_layers_v') + yield name1, d1 + yield name2, d2 + continue + + yield name, data + + def set_vocab(self, *args, **kwargs): + tokenizer_class = 'BertTokenizer' + with open(self.dir_model / "tokenizer_config.json", "r", encoding="utf-8") as f: + tokenizer_class = json.load(f)['tokenizer_class'] + + if tokenizer_class == 'BertTokenizer': + super().set_vocab() + elif tokenizer_class == 'RobertaTokenizer': + self._set_vocab_gpt2() + self.gguf_writer.add_token_type_count(2) + else: + raise NotImplementedError(f'Tokenizer {tokenizer_class} is not supported for JinaBertModel') + self.gguf_writer.add_add_bos_token(True) + self.gguf_writer.add_add_eos_token(True) + + ###### CONVERSION LOGIC ###### diff --git a/examples/embedding/embedding.cpp b/examples/embedding/embedding.cpp index 6a93147d70e88..c85a2da53d129 100644 --- a/examples/embedding/embedding.cpp +++ b/examples/embedding/embedding.cpp @@ -49,6 +49,12 @@ static void batch_decode(llama_context * ctx, llama_batch & batch, float * outpu } float * out = output + batch.seq_id[i][0] * n_embd; + //TODO: I would also add a parameter here to enable normalization or not. + /*fprintf(stdout, "unnormalized_embedding:"); + for (int hh = 0; hh < n_embd; hh++) { + fprintf(stdout, "%9.6f ", embd[hh]); + } + fprintf(stdout, "\n");*/ llama_embd_normalize(embd, out, n_embd); } } @@ -123,10 +129,12 @@ int main(int argc, char ** argv) { inputs.push_back(inp); } - // add SEP if not present + // check if the last token is SEP + // it should be automatically added by the tokenizer when 'tokenizer.ggml.add_eos_token' is set to 'true' for (auto & inp : inputs) { if (inp.empty() || inp.back() != llama_token_sep(model)) { - inp.push_back(llama_token_sep(model)); + fprintf(stderr, "%s: warning: last token in the prompt is not SEP\n", __func__); + fprintf(stderr, "%s: 'tokenizer.ggml.add_eos_token' should be set to 'true' in the GGUF header\n", __func__); } } diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 5951c0bb0fb5e..a4fbfc5e09d06 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -118,6 +118,7 @@ class MODEL_ARCH(IntEnum): REFACT = auto() BERT = auto() NOMIC_BERT = auto() + JINA_BERT_V2 = auto() BLOOM = auto() STABLELM = auto() QWEN = auto() @@ -195,6 +196,7 @@ class MODEL_TENSOR(IntEnum): MODEL_ARCH.REFACT: "refact", MODEL_ARCH.BERT: "bert", MODEL_ARCH.NOMIC_BERT: "nomic-bert", + MODEL_ARCH.JINA_BERT_V2: "jina-bert-v2", MODEL_ARCH.BLOOM: "bloom", MODEL_ARCH.STABLELM: "stablelm", MODEL_ARCH.QWEN: "qwen", @@ -380,6 +382,22 @@ class MODEL_TENSOR(IntEnum): MODEL_TENSOR.FFN_UP, MODEL_TENSOR.LAYER_OUT_NORM, ], + MODEL_ARCH.JINA_BERT_V2: [ + MODEL_TENSOR.TOKEN_EMBD, + MODEL_TENSOR.TOKEN_EMBD_NORM, + MODEL_TENSOR.TOKEN_TYPES, + MODEL_TENSOR.ATTN_OUT_NORM, + MODEL_TENSOR.ATTN_Q, + MODEL_TENSOR.ATTN_Q_NORM, + MODEL_TENSOR.ATTN_K, + MODEL_TENSOR.ATTN_K_NORM, + MODEL_TENSOR.ATTN_V, + MODEL_TENSOR.ATTN_OUT, + MODEL_TENSOR.FFN_UP, + MODEL_TENSOR.FFN_GATE, + MODEL_TENSOR.FFN_DOWN, + MODEL_TENSOR.LAYER_OUT_NORM, + ], MODEL_ARCH.MPT: [ MODEL_TENSOR.TOKEN_EMBD, MODEL_TENSOR.OUTPUT_NORM, diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 990fe63c2acd1..8e1cac9152f55 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -243,6 +243,7 @@ class TensorNameMap: "model.layers.{bid}.feed_forward.w3", # internlm2 "encoder.layers.{bid}.mlp.fc11", # nomic-bert "model.layers.{bid}.mlp.c_fc", # starcoder2 + "encoder.layer.{bid}.mlp.gated_layers_v", # jina-bert-v2 ), MODEL_TENSOR.FFN_UP_EXP: ( @@ -269,6 +270,7 @@ class TensorNameMap: "model.layers.layers.{bid}.mlp.gate_proj", # plamo "model.layers.{bid}.feed_forward.w1", # internlm2 "encoder.layers.{bid}.mlp.fc12", # nomic-bert + "encoder.layer.{bid}.mlp.gated_layers_w", # jina-bert-v2 "transformer.h.{bid}.mlp.linear_1", # refact ), @@ -303,6 +305,7 @@ class TensorNameMap: "model.layers.{bid}.feed_forward.w2", # internlm2 "encoder.layers.{bid}.mlp.fc2", # nomic-bert "model.layers.{bid}.mlp.c_proj", # starcoder2 + "encoder.layer.{bid}.mlp.wo", # jina-bert-v2 ), MODEL_TENSOR.FFN_DOWN_EXP: ( @@ -321,6 +324,7 @@ class TensorNameMap: "model.layers.{bid}.self_attn.q_layernorm", # persimmon "model.layers.{bid}.self_attn.q_norm", # cohere "transformer.blocks.{bid}.attn.q_ln", # sea-lion + "encoder.layer.{bid}.attention.self.layer_norm_q" # jina-bert-v2 ), MODEL_TENSOR.ATTN_K_NORM: ( @@ -328,6 +332,7 @@ class TensorNameMap: "model.layers.{bid}.self_attn.k_layernorm", # persimmon "model.layers.{bid}.self_attn.k_norm", # cohere "transformer.blocks.{bid}.attn.k_ln", # sea-lion + "encoder.layer.{bid}.attention.self.layer_norm_k" # jina-bert-v2 ), MODEL_TENSOR.ROPE_FREQS: ( @@ -338,6 +343,7 @@ class TensorNameMap: "encoder.layer.{bid}.output.LayerNorm", # bert "encoder.layers.{bid}.norm2", # nomic-bert "transformer.decoder_layer.{bid}.rms_norm_3", # Grok + "encoder.layer.{bid}.mlp.layernorm", # jina-bert-v2 ), MODEL_TENSOR.SSM_IN: ( diff --git a/llama.cpp b/llama.cpp index dede68cb5a3f9..cdff28cdaa773 100644 --- a/llama.cpp +++ b/llama.cpp @@ -205,6 +205,7 @@ enum llm_arch { LLM_ARCH_REFACT, LLM_ARCH_BERT, LLM_ARCH_NOMIC_BERT, + LLM_ARCH_JINA_BERT_V2, LLM_ARCH_BLOOM, LLM_ARCH_STABLELM, LLM_ARCH_QWEN, @@ -228,39 +229,40 @@ enum llm_arch { }; static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = { - { LLM_ARCH_LLAMA, "llama" }, - { LLM_ARCH_FALCON, "falcon" }, - { LLM_ARCH_GROK, "grok" }, - { LLM_ARCH_GPT2, "gpt2" }, - { LLM_ARCH_GPTJ, "gptj" }, - { LLM_ARCH_GPTNEOX, "gptneox" }, - { LLM_ARCH_MPT, "mpt" }, - { LLM_ARCH_BAICHUAN, "baichuan" }, - { LLM_ARCH_STARCODER, "starcoder" }, - { LLM_ARCH_PERSIMMON, "persimmon" }, - { LLM_ARCH_REFACT, "refact" }, - { LLM_ARCH_BERT, "bert" }, - { LLM_ARCH_NOMIC_BERT, "nomic-bert" }, - { LLM_ARCH_BLOOM, "bloom" }, - { LLM_ARCH_STABLELM, "stablelm" }, - { LLM_ARCH_QWEN, "qwen" }, - { LLM_ARCH_QWEN2, "qwen2" }, - { LLM_ARCH_QWEN2MOE, "qwen2moe" }, - { LLM_ARCH_PHI2, "phi2" }, - { LLM_ARCH_PHI3, "phi3" }, - { LLM_ARCH_PLAMO, "plamo" }, - { LLM_ARCH_CODESHELL, "codeshell" }, - { LLM_ARCH_ORION, "orion" }, - { LLM_ARCH_INTERNLM2, "internlm2" }, - { LLM_ARCH_MINICPM, "minicpm" }, - { LLM_ARCH_GEMMA, "gemma" }, - { LLM_ARCH_STARCODER2, "starcoder2" }, - { LLM_ARCH_MAMBA, "mamba" }, - { LLM_ARCH_XVERSE, "xverse" }, - { LLM_ARCH_COMMAND_R, "command-r" }, - { LLM_ARCH_DBRX, "dbrx" }, - { LLM_ARCH_OLMO, "olmo" }, - { LLM_ARCH_UNKNOWN, "(unknown)" }, + { LLM_ARCH_LLAMA, "llama" }, + { LLM_ARCH_FALCON, "falcon" }, + { LLM_ARCH_GROK, "grok" }, + { LLM_ARCH_GPT2, "gpt2" }, + { LLM_ARCH_GPTJ, "gptj" }, + { LLM_ARCH_GPTNEOX, "gptneox" }, + { LLM_ARCH_MPT, "mpt" }, + { LLM_ARCH_BAICHUAN, "baichuan" }, + { LLM_ARCH_STARCODER, "starcoder" }, + { LLM_ARCH_PERSIMMON, "persimmon" }, + { LLM_ARCH_REFACT, "refact" }, + { LLM_ARCH_BERT, "bert" }, + { LLM_ARCH_NOMIC_BERT, "nomic-bert" }, + { LLM_ARCH_JINA_BERT_V2, "jina-bert-v2" }, + { LLM_ARCH_BLOOM, "bloom" }, + { LLM_ARCH_STABLELM, "stablelm" }, + { LLM_ARCH_QWEN, "qwen" }, + { LLM_ARCH_QWEN2, "qwen2" }, + { LLM_ARCH_QWEN2MOE, "qwen2moe" }, + { LLM_ARCH_PHI2, "phi2" }, + { LLM_ARCH_PHI3, "phi3" }, + { LLM_ARCH_PLAMO, "plamo" }, + { LLM_ARCH_CODESHELL, "codeshell" }, + { LLM_ARCH_ORION, "orion" }, + { LLM_ARCH_INTERNLM2, "internlm2" }, + { LLM_ARCH_MINICPM, "minicpm" }, + { LLM_ARCH_GEMMA, "gemma" }, + { LLM_ARCH_STARCODER2, "starcoder2" }, + { LLM_ARCH_MAMBA, "mamba" }, + { LLM_ARCH_XVERSE, "xverse" }, + { LLM_ARCH_COMMAND_R, "command-r" }, + { LLM_ARCH_DBRX, "dbrx" }, + { LLM_ARCH_OLMO, "olmo" }, + { LLM_ARCH_UNKNOWN, "(unknown)" }, }; enum llm_kv { @@ -691,6 +693,25 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" }, }, }, + { + LLM_ARCH_JINA_BERT_V2, + { + { LLM_TENSOR_TOKEN_EMBD, "token_embd" }, + { LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" }, + { LLM_TENSOR_TOKEN_TYPES, "token_types" }, + { LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" }, + { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" }, + { LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" }, + { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" }, + { LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" }, + { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" }, + { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" }, + { LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" }, + { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" }, + { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" }, + { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" }, + }, + }, { LLM_ARCH_BLOOM, { @@ -3778,6 +3799,12 @@ static void llm_load_hparams( // get hparams kv ml.get_key(LLM_KV_VOCAB_SIZE, hparams.n_vocab, false) || ml.get_arr_n(LLM_KV_TOKENIZER_LIST, hparams.n_vocab); + + // everything past this point is not vocab-related + if (hparams.vocab_only) { + return; + } + ml.get_key(LLM_KV_CONTEXT_LENGTH, hparams.n_ctx_train); ml.get_key(LLM_KV_EMBEDDING_LENGTH, hparams.n_embd); ml.get_key(LLM_KV_FEED_FORWARD_LENGTH, hparams.n_ff); @@ -3961,6 +3988,19 @@ static void llm_load_hparams( model.type = e_model::MODEL_335M; break; // bge-large } } break; + case LLM_ARCH_JINA_BERT_V2: + { + ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); + ml.get_key(LLM_KV_ATTENTION_CAUSAL, hparams.causal_attn); + ml.get_key(LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT, hparams.n_vocab_type); + ml.get_key(LLM_KV_POOLING_TYPE, hparams.pooling_type); + hparams.f_max_alibi_bias = 8.0f; + + switch (hparams.n_layer) { + case 4: model.type = e_model::MODEL_33M; break; // jina-embeddings-small + case 12: model.type = e_model::MODEL_137M; break; // jina-embeddings-base + } + } break; case LLM_ARCH_NOMIC_BERT: { ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); @@ -4382,7 +4422,9 @@ static void llm_load_vocab( tokenizer_pre == "starcoder") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STARCODER; } else if ( - tokenizer_pre == "gpt-2") { + tokenizer_pre == "gpt-2" || + tokenizer_pre == "jina-es" || + tokenizer_pre == "jina-de") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_GPT2; } else if ( tokenizer_pre == "refact") { @@ -5241,6 +5283,50 @@ static bool llm_load_tensors( layer.layer_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_LAYER_OUT_NORM, "bias", i), {n_embd}); } } break; + case LLM_ARCH_JINA_BERT_V2: + { + model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // word_embeddings + model.type_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_TYPES, "weight"), {n_embd, n_vocab_type}); //token_type_embeddings + model.tok_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight"), {n_embd}); // LayerNorm + model.tok_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD_NORM, "bias"), {n_embd}); //LayerNorm bias + + for (int i = 0; i < n_layer; ++i) { + ggml_context * ctx_layer = ctx_for_layer(i); + ggml_context * ctx_split = ctx_for_layer_split(i); + + auto & layer = model.layers[i]; // JinaBertLayer + + layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd}); + layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q, "bias", i), {n_embd}); + + layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, false); + layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, false); + + layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa}); + layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K, "bias", i), {n_embd_gqa}); + + layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, false); + layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, false); + + layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa}); + layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V, "bias", i), {n_embd_gqa}); + + layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}); //output_dens + layer.bo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd}); //output_dens + + layer.attn_out_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd}); //output_norm + layer.attn_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT_NORM, "bias", i), {n_embd}); + + layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}); + layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}); + + layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}); + layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i), {n_embd}); + + layer.layer_out_norm = ml.create_tensor(ctx_split, tn(LLM_TENSOR_LAYER_OUT_NORM, "weight", i), {n_embd}); + layer.layer_out_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_LAYER_OUT_NORM, "bias", i), {n_embd}); + } + } break; case LLM_ARCH_BLOOM: { model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); @@ -6317,7 +6403,7 @@ static struct ggml_tensor * llm_build_ffn( llm_ffn_gate_type type_gate, const llm_build_cb & cb, int il) { - struct ggml_tensor * tmp = ggml_mul_mat(ctx, up, cur); + struct ggml_tensor * tmp = up ? ggml_mul_mat(ctx, up, cur) : cur; cb(tmp, "ffn_up", il); if (up_b) { @@ -8118,8 +8204,11 @@ struct llm_build_context { struct ggml_tensor * cur; struct ggml_tensor * inpL; + struct ggml_tensor * inp_pos = nullptr; - struct ggml_tensor * inp_pos = build_inp_pos(); + if (model.arch != LLM_ARCH_JINA_BERT_V2) { + inp_pos = build_inp_pos(); + } struct ggml_tensor * inp_mean = build_inp_mean(); struct ggml_tensor * inp_cls = build_inp_cls(); @@ -8150,13 +8239,26 @@ struct llm_build_context { struct ggml_tensor * Vcur; // self-attention - if (model.arch == LLM_ARCH_BERT) { + if (model.arch == LLM_ARCH_BERT || model.arch == LLM_ARCH_JINA_BERT_V2) { Qcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wq, cur), model.layers[il].bq); cb(Qcur, "Qcur", il); + if (model.layers[il].attn_q_norm) { + Qcur = llm_build_norm(ctx0, Qcur, hparams, + model.layers[il].attn_q_norm, + model.layers[il].attn_q_norm_b, + LLM_NORM, cb, il); + } + Kcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wk, cur), model.layers[il].bk); cb(Kcur, "Kcur", il); + if (model.layers[il].attn_k_norm) { + Kcur = llm_build_norm(ctx0, Kcur, hparams, + model.layers[il].attn_k_norm, + model.layers[il].attn_k_norm_b, + LLM_NORM, cb, il); + } Vcur = ggml_add(ctx0, ggml_mul_mat(ctx0, model.layers[il].wv, cur), model.layers[il].bv); cb(Vcur, "Vcur", il); @@ -8247,6 +8349,13 @@ struct llm_build_context { model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL, LLM_FFN_GELU, LLM_FFN_SEQ, cb, il); + } else if (model.arch == LLM_ARCH_JINA_BERT_V2) { + cur = llm_build_ffn(ctx0, cur, + model.layers[il].ffn_up, NULL, + model.layers[il].ffn_gate, NULL, + model.layers[il].ffn_down, model.layers[il].ffn_down_b, + NULL, + LLM_FFN_GELU, LLM_FFN_PAR, cb, il); } else { cur = llm_build_ffn(ctx0, cur, model.layers[il].ffn_up, NULL, @@ -10769,6 +10878,7 @@ static struct ggml_cgraph * llama_build_graph( result = llm.build_refact(); } break; case LLM_ARCH_BERT: + case LLM_ARCH_JINA_BERT_V2: case LLM_ARCH_NOMIC_BERT: { result = llm.build_bert(); @@ -12695,7 +12805,10 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & } } - GGML_ASSERT(vocab.special_add_eos != 1); + if (add_special && vocab.special_add_eos == 1) { + GGML_ASSERT(vocab.special_add_eos != -1); + output.push_back(vocab.special_eos_id); + } } break; case LLAMA_VOCAB_TYPE_WPM: { @@ -15746,6 +15859,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) { case LLM_ARCH_REFACT: case LLM_ARCH_BLOOM: case LLM_ARCH_MAMBA: + case LLM_ARCH_JINA_BERT_V2: return LLAMA_ROPE_TYPE_NONE; // use what we call a normal RoPE, operating on pairs of consecutive head values From 5ae3426b0b64672991563d4c28b2018b9f961467 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= <johannesg@5d6.de> Date: Sat, 11 May 2024 10:11:28 +0200 Subject: [PATCH 40/64] server: fix reported top tokens for temperature 0 (#7203) --- common/sampling.cpp | 6 +++--- common/sampling.h | 2 +- examples/server/server.cpp | 6 +++--- 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/common/sampling.cpp b/common/sampling.cpp index 3715a798531ae..f0f1b92d37f59 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -35,7 +35,7 @@ struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_ result->prev.resize(params.n_prev); - result->n_considered = 0; + result->n_valid = 0; llama_sampling_set_rng_seed(result, params.seed); @@ -66,7 +66,7 @@ void llama_sampling_reset(llama_sampling_context * ctx) { std::fill(ctx->prev.begin(), ctx->prev.end(), 0); ctx->cur.clear(); - ctx->n_considered = 0; + ctx->n_valid = 0; } void llama_sampling_set_rng_seed(struct llama_sampling_context * ctx, uint32_t seed) { @@ -256,7 +256,7 @@ static llama_token llama_sampling_sample_impl( } } - ctx_sampling->n_considered = cur_p.size; + ctx_sampling->n_valid = temp == 0.0f ? 0 : cur_p.size; return id; } diff --git a/common/sampling.h b/common/sampling.h index 5b73ecdcdb37b..655732ad17206 100644 --- a/common/sampling.h +++ b/common/sampling.h @@ -81,7 +81,7 @@ struct llama_sampling_context { // TODO: replace with ring-buffer std::vector<llama_token> prev; std::vector<llama_token_data> cur; - size_t n_considered; + size_t n_valid; // Number of correct top tokens with correct probabilities. std::mt19937 rng; }; diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 305f79492a055..2bf4026d50842 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -2270,10 +2270,10 @@ struct server_context { const size_t n_probs = std::min(cur_p.size, (size_t) slot.sparams.n_probs); if (n_probs > 0) { - const size_t n_considered = slot.ctx_sampling->n_considered; + const size_t n_valid = slot.ctx_sampling->n_valid; // Make sure at least n_probs top tokens are at the front of the vector: - if (slot.sparams.temp == 0.0f && n_probs > n_considered) { + if (slot.sparams.temp == 0.0f && n_probs > n_valid) { llama_sample_top_k(ctx, &cur_p, n_probs, 0); } @@ -2289,7 +2289,7 @@ struct server_context { for (size_t i = 0; i < n_probs; ++i) { result.probs.push_back({ cur_p.data[i].id, - i >= n_considered ? 0.0f : cur_p.data[i].p // Tokens filtered out due to e.g. top_k have 0 probability. + i >= n_valid ? 0.0f : cur_p.data[i].p // Tokens filtered out due to e.g. top_k have 0 probability. }); } } From f99e1e456eaf69cc38c1982a2693ce41c0f897ef Mon Sep 17 00:00:00 2001 From: Haoxiang Fei <tonyfettes@tonyfettes.com> Date: Sat, 11 May 2024 16:12:06 +0800 Subject: [PATCH 41/64] llama : lookup word in vocab before doing BPE merges (#7193) * fix: llama-3 ignore_merges * test: add test for llama-3 bpe ignore_merges * fix: set ignore_merges only for llama-3 * fix: test-tokenizer-1-bpe --ingore-merges detection * fix: copy to fix fallthrough * fix: change ignore_merges to bool * fix: add ignore merges tests to cmake * llama : alternative merge ignore logic --------- Co-authored-by: Haoxiang Fei <feihaoxiang@idea.edu.cn> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --- llama.cpp | 14 ++++++++++++- models/ggml-vocab-llama-bpe.gguf.inp | 2 ++ models/ggml-vocab-llama-bpe.gguf.out | 1 + tests/CMakeLists.txt | 2 +- tests/test-tokenizer-1-bpe.cpp | 30 +++++++++++++++++++++++++--- 5 files changed, 44 insertions(+), 5 deletions(-) diff --git a/llama.cpp b/llama.cpp index cdff28cdaa773..e91ad7285da99 100644 --- a/llama.cpp +++ b/llama.cpp @@ -12253,13 +12253,14 @@ struct llm_tokenizer_bpe { void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) { int final_prev_index = -1; + bool ignore_merges = false; std::vector<std::string> word_collection; switch (vocab.type) { case LLAMA_VOCAB_TYPE_BPE: switch (vocab.type_pre) { case LLAMA_VOCAB_PRE_TYPE_LLAMA3: - case LLAMA_VOCAB_PRE_TYPE_DBRX: + ignore_merges = true; word_collection = unicode_regex_split(text, { // original regex from tokenizer.json //"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", @@ -12268,6 +12269,12 @@ struct llm_tokenizer_bpe { "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", }); break; + case LLAMA_VOCAB_PRE_TYPE_DBRX: + word_collection = unicode_regex_split(text, { + // same as llama3 + "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", + }); + break; case LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM: word_collection = unicode_regex_split(text, { "[\r\n]", @@ -12351,6 +12358,11 @@ struct llm_tokenizer_bpe { int index = 0; size_t offset = 0; + if (ignore_merges && vocab.token_to_id.find(word) != vocab.token_to_id.end()) { + symbols.emplace_back(llm_symbol{-1, -1, word.c_str(), word.size()}); + offset = word.size(); + } + while (offset < word.size()) { llm_symbol sym; size_t char_len = std::min(word.size() - offset, (size_t) ::utf8_len(word[offset])); diff --git a/models/ggml-vocab-llama-bpe.gguf.inp b/models/ggml-vocab-llama-bpe.gguf.inp index 0a89107c60d7f..9380bf355202a 100644 --- a/models/ggml-vocab-llama-bpe.gguf.inp +++ b/models/ggml-vocab-llama-bpe.gguf.inp @@ -104,3 +104,5 @@ __ggml_vocab_test__ 🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL __ggml_vocab_test__ + Việt +__ggml_vocab_test__ diff --git a/models/ggml-vocab-llama-bpe.gguf.out b/models/ggml-vocab-llama-bpe.gguf.out index 1f00e3812e227..1f3607fb6a378 100644 --- a/models/ggml-vocab-llama-bpe.gguf.out +++ b/models/ggml-vocab-llama-bpe.gguf.out @@ -41,3 +41,4 @@ 8765 8765 1644 8765 8765 8765 198 4815 15073 66597 8004 1602 2355 79772 11187 9468 248 222 320 8416 8 27623 114 102470 9468 234 104 31643 320 36773 100166 98634 8 26602 227 11410 99 247 9468 99 247 220 18 220 1644 220 8765 220 8765 18 220 8765 1644 220 8765 8765 220 8765 8765 18 220 8765 8765 1644 220 18 13 18 220 18 497 18 220 18 1131 18 220 21549 222 98629 241 45358 233 21549 237 45358 224 21549 244 21549 115 21549 253 45358 223 21549 253 21549 95 98629 227 76460 223 949 37046 101067 19000 23182 102301 9263 18136 16 36827 21909 56560 54337 19175 102118 13373 64571 34694 3114 112203 80112 3436 106451 14196 14196 74694 3089 3089 29249 17523 3001 27708 7801 358 3077 1027 364 83 820 568 596 1070 11 364 793 499 2771 30 364 44 539 2771 358 3358 1304 433 11 364 35 499 1093 1063 15600 30 1226 6 43712 264 64966 43 + 101798 diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt index d409a1d6b42ec..766a017524237 100644 --- a/tests/CMakeLists.txt +++ b/tests/CMakeLists.txt @@ -92,7 +92,7 @@ target_link_libraries(test-tokenizer-1-bpe PRIVATE common) install(TARGETS test-tokenizer-1-bpe RUNTIME) # TODO: disabled due to slowness -#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf) +#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf --ignore-merges) #llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) #llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-aquila ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf) #llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf) diff --git a/tests/test-tokenizer-1-bpe.cpp b/tests/test-tokenizer-1-bpe.cpp index a0e2caf9427eb..209a04ad6f77a 100644 --- a/tests/test-tokenizer-1-bpe.cpp +++ b/tests/test-tokenizer-1-bpe.cpp @@ -13,15 +13,27 @@ #include <vector> int main(int argc, char **argv) { - if (argc < 2) { - fprintf(stderr, "Usage: %s <vocab-file>\n", argv[0]); + if (argc < 2 || argc > 3) { + fprintf(stderr, "Usage: %s <vocab-file> [--ignore-merges]\n", argv[0]); return 1; } const std::string fname = argv[1]; + bool ignore_merges = false; + if (argc == 3) { + if (std::strcmp(argv[2], "--ignore-merges") != 0) { + fprintf(stderr, "Usage: %s <vocab-file> [--ignore-merges]\n", argv[0]); + return 1; + } + ignore_merges = true; + } fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str()); + if (ignore_merges) { + fprintf(stderr, "%s : ignoring merges for tokens inside vocab\n", __func__); + } + llama_model * model; llama_context * ctx; @@ -65,7 +77,19 @@ int main(int argc, char **argv) { std::string str = llama_detokenize_bpe(ctx, std::vector<int>(1, i)); try { auto cps = unicode_cpts_from_utf8(str); - std::vector<llama_token> tokens = llama_tokenize(ctx, str, false); + std::vector<llama_token> tokens = llama_tokenize(ctx, str, false, true); + if (ignore_merges && tokens.size() > 1) { + fprintf(stderr, + "%s : error: token %d detokenizes to '%s'(%zu) but " + "tokenization of this to multiple tokens: [", + __func__, i, str.c_str(), str.length()); + fprintf(stderr, "%d", tokens[0]); + for (size_t i = 1; i < tokens.size(); i++) { + fprintf(stderr, ", %d", tokens[i]); + } + fprintf(stderr, "]\n"); + return 2; + } std::string check = llama_detokenize_bpe(ctx, tokens); if (check != str) { fprintf(stderr, "%s : error: token %d detokenizes to '%s'(%zu) but tokenization of this detokenizes to '%s'(%zu)\n", From 988631335a20d06497f58be0b8ba13adb4323a22 Mon Sep 17 00:00:00 2001 From: Steve Grubb <ausearch.1@gmail.com> Date: Sat, 11 May 2024 04:13:02 -0400 Subject: [PATCH 42/64] server : free llama_batch on exit (#7212) * [server] Cleanup a memory leak on exit There are a couple memory leaks on exit of the server. This hides others. After cleaning this up, you can see leaks on slots. But that is another patch to be sent after this. * make tab into spaces --- examples/server/server.cpp | 2 ++ 1 file changed, 2 insertions(+) diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 2bf4026d50842..55c1d41298cd6 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -673,6 +673,8 @@ struct server_context { llama_free_model(model); model = nullptr; } + + llama_batch_free(batch); } bool load_model(const gpt_params & params_) { From 3292733f95d4632a956890a438af5192e7031c12 Mon Sep 17 00:00:00 2001 From: CrispStrobe <154636388+CrispStrobe@users.noreply.github.com> Date: Sat, 11 May 2024 10:18:35 +0200 Subject: [PATCH 43/64] convert : skip unaccessible HF repos (#7210) --- convert-hf-to-gguf-update.py | 22 ++++++++++++++++++++-- 1 file changed, 20 insertions(+), 2 deletions(-) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index e757d5ccbc0b4..cd2674a0ea97d 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -145,8 +145,17 @@ def download_file_with_auth(url, token, save_path): if tokt == TOKENIZER_TYPE.SPM: continue + # Skip if the tokenizer folder does not exist or there are other download issues previously + if not os.path.exists(f"models/tokenizers/{name}"): + logger.warning(f"Directory for tokenizer {name} not found. Skipping...") + continue + # create the tokenizer - tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}") + try: + tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}") + except OSError as e: + logger.error(f"Error loading tokenizer for model {name}. The model may not exist or is not accessible with the provided token. Error: {e}") + continue # Skip to the next model if the tokenizer can't be loaded chktok = tokenizer.encode(chktxt) chkhsh = sha256(str(chktok).encode()).hexdigest() @@ -287,8 +296,17 @@ def get_vocab_base_pre(self, tokenizer) -> str: name = model["name"] tokt = model["tokt"] + # Skip if the tokenizer folder does not exist or there are other download issues previously + if not os.path.exists(f"models/tokenizers/{name}"): + logger.warning(f"Directory for tokenizer {name} not found. Skipping...") + continue + # create the tokenizer - tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}") + try: + tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}") + except OSError as e: + logger.error(f"Failed to load tokenizer for model {name}. Error: {e}") + continue # Skip this model and continue with the next one in the loop with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f: for text in tests: From ef0d5e3ec9f99003af3ff326384816c02850ea3f Mon Sep 17 00:00:00 2001 From: Borislav Stanimirov <b.stanimirov@abv.bg> Date: Thu, 25 Apr 2024 17:24:07 +0300 Subject: [PATCH 44/64] build: fix and ignore msvc warnings (ggml/805) --- ggml-backend.c | 4 ++-- ggml-quants.c | 6 ++++++ 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/ggml-backend.c b/ggml-backend.c index f5bdcf07838aa..dd090a583f685 100644 --- a/ggml-backend.c +++ b/ggml-backend.c @@ -1182,9 +1182,9 @@ static int ggml_backend_sched_backend_id_from_cur(ggml_backend_sched_t sched, st static char * fmt_size(size_t size) { static char buffer[128]; if (size >= 1024*1024) { - sprintf(buffer, "%zuM", size/1024/1024); + snprintf(buffer, sizeof(buffer), "%zuM", size/1024/1024); } else { - sprintf(buffer, "%zuK", size/1024); + snprintf(buffer, sizeof(buffer), "%zuK", size/1024); } return buffer; } diff --git a/ggml-quants.c b/ggml-quants.c index 9883b6f8cabbb..00334c5feb3f3 100644 --- a/ggml-quants.c +++ b/ggml-quants.c @@ -14,6 +14,12 @@ #include <stdlib.h> // for qsort #include <stdio.h> // for GGML_ASSERT +#if defined(_MSC_VER) +// disable "possible loss of data" to avoid warnings for hundreds of casts +// we should just be careful :) +#pragma warning(disable: 4244 4267) +#endif + #define UNUSED GGML_UNUSED // some compilers don't provide _mm256_set_m128i, e.g. gcc 7 From f5ef34e428f3886544590ecb2d532e4d333c114c Mon Sep 17 00:00:00 2001 From: Justina Cho <justcho5@gmail.com> Date: Wed, 1 May 2024 14:44:26 -0700 Subject: [PATCH 45/64] feat: implemented sigmoid function (ggml/806) * added sigmoid function * implemented metal kernel for sigmoid * implemented cuda kernel for sigmoid * added sigmoid unary op and incremented count --- ggml-cuda.cu | 4 +++ ggml-cuda/unary.cu | 26 ++++++++++++++++ ggml-cuda/unary.cuh | 3 ++ ggml-metal.m | 15 ++++++++++ ggml-metal.metal | 7 +++++ ggml.c | 73 ++++++++++++++++++++++++++++++++++++++++++++- ggml.h | 9 ++++++ 7 files changed, 136 insertions(+), 1 deletion(-) diff --git a/ggml-cuda.cu b/ggml-cuda.cu index c5c7787969f5f..5b6c909192485 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -2204,6 +2204,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg case GGML_UNARY_OP_RELU: ggml_cuda_op_relu(ctx, dst); break; + case GGML_UNARY_OP_SIGMOID: + ggml_cuda_op_sigmoid(ctx, dst); + break; case GGML_UNARY_OP_HARDSIGMOID: ggml_cuda_op_hardsigmoid(ctx, dst); break; @@ -2716,6 +2719,7 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons case GGML_UNARY_OP_GELU: case GGML_UNARY_OP_SILU: case GGML_UNARY_OP_RELU: + case GGML_UNARY_OP_SIGMOID: case GGML_UNARY_OP_HARDSIGMOID: case GGML_UNARY_OP_HARDSWISH: case GGML_UNARY_OP_GELU_QUICK: diff --git a/ggml-cuda/unary.cu b/ggml-cuda/unary.cu index 1a7f0946972c1..ac03d5c6fce54 100644 --- a/ggml-cuda/unary.cu +++ b/ggml-cuda/unary.cu @@ -48,6 +48,15 @@ static __global__ void relu_f32(const float * x, float * dst, const int k) { dst[i] = fmaxf(x[i], 0); } +static __global__ void sigmoid_f32(const float * x, float * dst, const int k) { + const int i = blockDim.x*blockIdx.x + threadIdx.x; + + if (i >= k) { + return; + } + dst[i] = 1.0f / (1.0f + expf(-x[i])); +} + static __global__ void hardsigmoid_f32(const float * x, float * dst, const int k) { const int i = blockDim.x*blockIdx.x + threadIdx.x; @@ -108,6 +117,11 @@ static void relu_f32_cuda(const float * x, float * dst, const int k, cudaStream_ relu_f32<<<num_blocks, CUDA_RELU_BLOCK_SIZE, 0, stream>>>(x, dst, k); } +static void sigmoid_f32_cuda(const float * x, float * dst, const int k, cudaStream_t stream) { + const int num_blocks = (k + CUDA_SIGMOID_BLOCK_SIZE - 1) / CUDA_SIGMOID_BLOCK_SIZE; + sigmoid_f32<<<num_blocks, CUDA_SIGMOID_BLOCK_SIZE, 0, stream>>>(x, dst, k); +} + static void hardsigmoid_f32_cuda(const float * x, float * dst, const int k, cudaStream_t stream) { const int num_blocks = (k + CUDA_HARDSIGMOID_BLOCK_SIZE - 1) / CUDA_HARDSIGMOID_BLOCK_SIZE; hardsigmoid_f32<<<num_blocks, CUDA_HARDSIGMOID_BLOCK_SIZE, 0, stream>>>(x, dst, k); @@ -188,6 +202,18 @@ void ggml_cuda_op_relu(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { relu_f32_cuda(src0_d, dst_d, ggml_nelements(src0), stream); } +void ggml_cuda_op_sigmoid(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * src0 = dst->src[0]; + const float * src0_d = (const float *)src0->data; + float * dst_d = (float *)dst->data; + cudaStream_t stream = ctx.stream(); + + GGML_ASSERT(src0->type == GGML_TYPE_F32); + GGML_ASSERT( dst->type == GGML_TYPE_F32); + + sigmoid_f32_cuda(src0_d, dst_d, ggml_nelements(src0), stream); +} + void ggml_cuda_op_hardsigmoid(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; const float * src0_d = (const float *)src0->data; diff --git a/ggml-cuda/unary.cuh b/ggml-cuda/unary.cuh index 2002ed989209c..a1d07c04fcd43 100644 --- a/ggml-cuda/unary.cuh +++ b/ggml-cuda/unary.cuh @@ -4,6 +4,7 @@ #define CUDA_SILU_BLOCK_SIZE 256 #define CUDA_TANH_BLOCK_SIZE 256 #define CUDA_RELU_BLOCK_SIZE 256 +#define CUDA_SIGMOID_BLOCK_SIZE 256 #define CUDA_HARDSIGMOID_BLOCK_SIZE 256 #define CUDA_HARDSWISH_BLOCK_SIZE 256 #define CUDA_SQR_BLOCK_SIZE 256 @@ -18,6 +19,8 @@ void ggml_cuda_op_tanh(ggml_backend_cuda_context & ctx, ggml_tensor * dst); void ggml_cuda_op_relu(ggml_backend_cuda_context & ctx, ggml_tensor * dst); +void ggml_cuda_op_sigmoid(ggml_backend_cuda_context & ctx, ggml_tensor * dst); + void ggml_cuda_op_hardsigmoid(ggml_backend_cuda_context & ctx, ggml_tensor * dst); void ggml_cuda_op_hardswish(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml-metal.m b/ggml-metal.m index 1bbb8fb4fefa1..66c398d54fd28 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -40,6 +40,7 @@ GGML_METAL_KERNEL_TYPE_CLAMP, GGML_METAL_KERNEL_TYPE_TANH, GGML_METAL_KERNEL_TYPE_RELU, + GGML_METAL_KERNEL_TYPE_SIGMOID, GGML_METAL_KERNEL_TYPE_GELU, GGML_METAL_KERNEL_TYPE_GELU_4, GGML_METAL_KERNEL_TYPE_GELU_QUICK, @@ -493,6 +494,7 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){ GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CLAMP, clamp, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_TANH, tanh, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_RELU, relu, true); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SIGMOID, sigmoid, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU, gelu, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_4, gelu_4, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GELU_QUICK, gelu_quick, true); @@ -730,6 +732,7 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const switch (ggml_get_unary_op(op)) { case GGML_UNARY_OP_TANH: case GGML_UNARY_OP_RELU: + case GGML_UNARY_OP_SIGMOID: case GGML_UNARY_OP_GELU: case GGML_UNARY_OP_GELU_QUICK: case GGML_UNARY_OP_SILU: @@ -1237,6 +1240,18 @@ static enum ggml_status ggml_metal_graph_compute( const int64_t n = ggml_nelements(dst); + [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; + } break; + case GGML_UNARY_OP_SIGMOID: + { + id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SIGMOID].pipeline; + + [encoder setComputePipelineState:pipeline]; + [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; + [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; + + const int64_t n = ggml_nelements(dst); + [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; } break; case GGML_UNARY_OP_GELU: diff --git a/ggml-metal.metal b/ggml-metal.metal index ee9de57a3a6f1..0c6d327987652 100644 --- a/ggml-metal.metal +++ b/ggml-metal.metal @@ -229,6 +229,13 @@ kernel void kernel_relu( dst[tpig] = max(0.0f, src0[tpig]); } +kernel void kernel_sigmoid( + device const float * src0, + device float * dst, + uint tpig[[thread_position_in_grid]]) { + dst[tpig] = 1.0f / (1.0f + exp(-src0[tpig])); +} + kernel void kernel_tanh( device const float * src0, device float * dst, diff --git a/ggml.c b/ggml.c index 4ee5d24af75d0..4f3011583d2e7 100644 --- a/ggml.c +++ b/ggml.c @@ -1949,6 +1949,7 @@ inline static void ggml_vec_tanh_f32 (const int n, float * y, const float * x) { inline static void ggml_vec_elu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : expf(x[i])-1; } inline static void ggml_vec_relu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : 0.f; } inline static void ggml_vec_leaky_relu_f32 (const int n, float * y, const float * x, const float ns) { for (int i = 0; i < n; ++i) y[i] = ((x[i] > 0.f) ? x[i] : 0.f) + ns * ((x[i] < 0.0f) ? x[i] : 0.f); } +inline static void ggml_vec_sigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = 1.f / (1.f + expf(-x[i])); } // TODO: optimize performance inline static void ggml_vec_hardswish_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i] * fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); } inline static void ggml_vec_hardsigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); } @@ -2329,6 +2330,7 @@ static const char * GGML_UNARY_OP_NAME[GGML_UNARY_OP_COUNT] = { "TANH", "ELU", "RELU", + "SIGMOID", "GELU", "GELU_QUICK", "SILU", @@ -2336,7 +2338,7 @@ static const char * GGML_UNARY_OP_NAME[GGML_UNARY_OP_COUNT] = { "HARDSIGMOID", }; -static_assert(GGML_UNARY_OP_COUNT == 12, "GGML_UNARY_OP_COUNT != 12"); +static_assert(GGML_UNARY_OP_COUNT == 13, "GGML_UNARY_OP_COUNT != 13"); static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN"); @@ -4561,6 +4563,20 @@ struct ggml_tensor * ggml_leaky_relu( return result; } +// ggml_sigmoid + +struct ggml_tensor * ggml_sigmoid( + struct ggml_context * ctx, + struct ggml_tensor * a) { + return ggml_unary(ctx, a, GGML_UNARY_OP_SIGMOID); +} + +struct ggml_tensor * ggml_sigmoid_inplace( + struct ggml_context * ctx, + struct ggml_tensor * a) { + return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_SIGMOID); +} + // ggml_gelu struct ggml_tensor * ggml_gelu( @@ -10852,6 +10868,52 @@ static void ggml_compute_forward_relu( } } +// ggml_compute_forward_sigmoid + +static void ggml_compute_forward_sigmoid_f32( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + + assert(params->ith == 0); + assert(ggml_are_same_shape(src0, dst)); + + if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) { + return; + } + + const int n = ggml_nrows(src0); + const int nc = src0->ne[0]; + + assert(dst->nb[0] == sizeof(float)); + assert(src0->nb[0] == sizeof(float)); + + for (int i = 0; i < n; i++) { + ggml_vec_sigmoid_f32(nc, + (float *) ((char *) dst->data + i*( dst->nb[1])), + (float *) ((char *) src0->data + i*(src0->nb[1]))); + } +} + +static void ggml_compute_forward_sigmoid( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + + switch (src0->type) { + case GGML_TYPE_F32: + { + ggml_compute_forward_sigmoid_f32(params, dst); + } break; + default: + { + GGML_ASSERT(false); + } break; + } +} + // ggml_compute_forward_gelu static void ggml_compute_forward_gelu_f32( @@ -16617,6 +16679,10 @@ static void ggml_compute_forward_unary( { ggml_compute_forward_relu(params, dst); } break; + case GGML_UNARY_OP_SIGMOID: + { + ggml_compute_forward_sigmoid(params, dst); + } break; case GGML_UNARY_OP_GELU: { ggml_compute_forward_gelu(params, dst); @@ -18601,6 +18667,10 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor zero_table); } } break; + case GGML_UNARY_OP_SIGMOID: + { + GGML_ASSERT(false); // TODO: not implemented + } break; case GGML_UNARY_OP_GELU: { GGML_ASSERT(false); // TODO: not implemented @@ -19130,6 +19200,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads, int n_cur_ case GGML_UNARY_OP_TANH: case GGML_UNARY_OP_ELU: case GGML_UNARY_OP_RELU: + case GGML_UNARY_OP_SIGMOID: case GGML_UNARY_OP_HARDSWISH: // to opt for multiple threads case GGML_UNARY_OP_HARDSIGMOID: // to opt for multiple threads { diff --git a/ggml.h b/ggml.h index 76c3328315964..3fe95ed57633b 100644 --- a/ggml.h +++ b/ggml.h @@ -519,6 +519,7 @@ extern "C" { GGML_UNARY_OP_TANH, GGML_UNARY_OP_ELU, GGML_UNARY_OP_RELU, + GGML_UNARY_OP_SIGMOID, GGML_UNARY_OP_GELU, GGML_UNARY_OP_GELU_QUICK, GGML_UNARY_OP_SILU, @@ -1073,6 +1074,14 @@ extern "C" { struct ggml_context * ctx, struct ggml_tensor * a); + GGML_API struct ggml_tensor * ggml_sigmoid( + struct ggml_context * ctx, + struct ggml_tensor * a); + + GGML_API struct ggml_tensor * ggml_sigmoid_inplace( + struct ggml_context * ctx, + struct ggml_tensor * a); + GGML_API struct ggml_tensor * ggml_gelu( struct ggml_context * ctx, struct ggml_tensor * a); From fae9d234b6606693704eca62fe4aefbb6c6abb45 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 12:02:39 +0300 Subject: [PATCH 46/64] sync : ggml ggml-ci --- scripts/sync-ggml.last | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last index d4400695b1d40..c5bd3ef559ccc 100644 --- a/scripts/sync-ggml.last +++ b/scripts/sync-ggml.last @@ -1 +1 @@ -98875cdb7e9ceeb726d1c196d2fecb3cbb59b93a +8cd3975bf21657c6d1e80c7c61830977b962539e From 5a419926b0c4efab0531401aea91522aaea9fd07 Mon Sep 17 00:00:00 2001 From: compilade <git@compilade.net> Date: Sat, 11 May 2024 11:06:26 -0400 Subject: [PATCH 47/64] convert-hf : support bfloat16 conversion (#7158) * convert-hf : support bfloat16 conversion * gguf-py : flake8 fixes * convert-hf : add missing space after comma * convert-hf : get bit-exact same output as ./quantize The quantization version was missing. * convert-hf : don't round bf16 NANs * convert-hf : save some memory with np.int16 intermediate bf16 weights * convert-hf : more closely match llama.cpp with which weights to keep in f32 * convert-hf : add --outtype auto-f16 A reason for this to exist is for model quantizers who want an initial GGUF with the most fidelity to the original model while still using a 16-bit float type instead of 32-bit floats. * convert-hf : remove a semicolon because flake8 doesn't like it It's a reflex from when programming in C/C++, I guess. * convert-hf : support outtype templating in outfile name * convert-hf : rename --outtype auto-f16 to --outtype auto --- convert-hf-to-gguf.py | 269 ++++++++++++++++++------------------ gguf-py/gguf/__init__.py | 1 + gguf-py/gguf/constants.py | 44 ++++++ gguf-py/gguf/gguf_writer.py | 51 +------ gguf-py/gguf/lazy.py | 225 ++++++++++++++++++++++++++++++ 5 files changed, 406 insertions(+), 184 deletions(-) create mode 100644 gguf-py/gguf/lazy.py diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index fbaed64da1cac..ec7f4dd758c72 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -12,7 +12,7 @@ from enum import IntEnum from pathlib import Path from hashlib import sha256 -from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Sequence, TypeVar, cast, overload +from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Sequence, TypeVar, cast import numpy as np import torch @@ -48,7 +48,6 @@ class Model: dir_model: Path ftype: int - fname_out: Path is_big_endian: bool endianess: gguf.GGUFEndian use_temp_file: bool @@ -56,20 +55,20 @@ class Model: part_names: list[str] is_safetensors: bool hparams: dict[str, Any] - gguf_writer: gguf.GGUFWriter block_count: int tensor_map: gguf.TensorNameMap tensor_names: set[str] | None + fname_out: Path + gguf_writer: gguf.GGUFWriter # subclasses should define this! model_arch: gguf.MODEL_ARCH - def __init__(self, dir_model: Path, ftype: int, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool): - if self.__class__ == Model: - raise TypeError(f"{self.__class__.__name__!r} should not be directly instantiated") + def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, is_big_endian: bool, use_temp_file: bool, eager: bool): + if type(self) is Model: + raise TypeError(f"{type(self).__name__!r} should not be directly instantiated") self.dir_model = dir_model self.ftype = ftype - self.fname_out = fname_out self.is_big_endian = is_big_endian self.endianess = gguf.GGUFEndian.BIG if is_big_endian else gguf.GGUFEndian.LITTLE self.use_temp_file = use_temp_file @@ -79,10 +78,23 @@ def __init__(self, dir_model: Path, ftype: int, fname_out: Path, is_big_endian: if not self.is_safetensors: self.part_names = Model.get_model_part_names(self.dir_model, ".bin") self.hparams = Model.load_hparams(self.dir_model) - self.gguf_writer = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file) self.block_count = self.find_hparam(["n_layers", "num_hidden_layers", "n_layer"]) self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count) self.tensor_names = None + if self.ftype == gguf.LlamaFileType.GUESSED: + # NOTE: can't use field "torch_dtype" in config.json, because some finetunes lie. + _, first_tensor = next(self.get_tensors()) + if first_tensor.dtype == torch.float16: + logger.info(f"choosing --outtype f16 from first tensor type ({first_tensor.dtype})") + self.ftype = gguf.LlamaFileType.MOSTLY_F16 + else: + logger.info(f"choosing --outtype bf16 from first tensor type ({first_tensor.dtype})") + self.ftype = gguf.LlamaFileType.MOSTLY_BF16 + ftype_up: str = self.ftype.name.partition("_")[2].upper() + ftype_lw: str = ftype_up.lower() + # allow templating the file name with the output ftype, useful with the "auto" ftype + self.fname_out = fname_out.parent / fname_out.name.format(ftype_lw, outtype=ftype_lw, ftype=ftype_lw, OUTTYPE=ftype_up, FTYPE=ftype_up) + self.gguf_writer = gguf.GGUFWriter(self.fname_out, gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file) @classmethod def __init_subclass__(cls): @@ -142,14 +154,27 @@ def get_tensors(self) -> Iterator[tuple[str, Tensor]]: raise ValueError(f"Mismatch between weight map and model parts for tensor names: {sym_diff}") def format_tensor_name(self, key: gguf.MODEL_TENSOR, bid: int | None = None, suffix: str = ".weight") -> str: - name: str = gguf.TENSOR_NAMES[key] if key not in gguf.MODEL_TENSORS[self.model_arch]: raise ValueError(f"Missing {key!r} for MODEL_TENSORS of {self.model_arch!r}") + name: str = gguf.TENSOR_NAMES[key] if "{bid}" in name: assert bid is not None name = name.format(bid=bid) return name + suffix + def match_model_tensor_name(self, name: str, key: gguf.MODEL_TENSOR, bid: int | None, suffix: str = ".weight") -> bool: + if key not in gguf.MODEL_TENSORS[self.model_arch]: + return False + key_name: str = gguf.TENSOR_NAMES[key] + if "{bid}" in key_name: + if bid is None: + return False + key_name = key_name.format(bid=bid) + else: + if bid is not None: + return False + return name == (key_name + suffix) + def map_tensor_name(self, name: str, try_suffixes: Sequence[str] = (".weight", ".bias")) -> str: new_name = self.tensor_map.get_name(key=name, try_suffixes=try_suffixes) if new_name is None: @@ -215,6 +240,23 @@ def extra_f16_tensors(self, name: str, new_name: str, bid: int | None, n_dims: i return False def write_tensors(self): + # same as ggml_compute_fp32_to_bf16 in ggml-impl.h + def np_fp32_to_bf16(n: np.ndarray): + # force nan to quiet + n = np.where((n & 0x7fffffff) > 0x7f800000, (n & 0xffff0000) | (64 << 16), n) + # flush subnormals to zero + n = np.where((n & 0x7f800000) == 0, n & 0x80000000, n) + # round to nearest even + n = (n + (0x7fff + ((n >> 16) & 1))) >> 16 + return n.astype(np.int16) + + # Doing this row-wise is much, much faster than element-wise, hence the signature + v_fp32_to_bf16 = np.vectorize(np_fp32_to_bf16, otypes=[np.int16], signature="(n)->(n)") + if self.lazy: + # TODO: find a way to implicitly wrap np.vectorize functions + # NOTE: the type is changed to reflect otypes passed to np.vectorize above + v_fp32_to_bf16 = gguf.LazyNumpyTensor._wrap_fn(v_fp32_to_bf16, meta_noop=np.int16) + max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,") for name, data_torch in self.get_tensors(): @@ -239,35 +281,60 @@ def write_tensors(self): data: np.ndarray = data # type hint n_dims = len(data.shape) data_dtype = data.dtype - - # if f32 desired, convert any float16 to float32 - if self.ftype == 0 and data_dtype == np.float16: - data = data.astype(np.float32) + data_qtype: gguf.GGMLQuantizationType | None = None # when both are True, f32 should win extra_f32 = self.extra_f32_tensors(name, new_name, bid, n_dims) extra_f16 = self.extra_f16_tensors(name, new_name, bid, n_dims) # Most of the codebase that takes in 1D tensors or norms only handles F32 tensors - extra_f32 = extra_f32 or n_dims == 1 or new_name.endswith("_norm.weight") + # Conditions should closely match those in llama_model_quantize_internal in llama.cpp + extra_f32 = any(cond for cond in ( + extra_f32, + n_dims == 1, + new_name.endswith("_norm.weight"), + )) + + # Some tensor types are always in float32 + extra_f32 = extra_f32 or any(self.match_model_tensor_name(new_name, key, bid) for key in ( + gguf.MODEL_TENSOR.FFN_GATE_INP, + gguf.MODEL_TENSOR.POS_EMBD, + gguf.MODEL_TENSOR.TOKEN_TYPES, + )) # if f16 desired, convert any float32 2-dim weight tensors to float16 - extra_f16 = extra_f16 or (name.endswith(".weight") and n_dims >= 2) - - # when both extra_f32 and extra_f16 are False, convert to float32 by default - if self.ftype == 1 and data_dtype == np.float16 and (extra_f32 or not extra_f16): - data = data.astype(np.float32) - - if self.ftype == 1 and data_dtype == np.float32 and extra_f16 and not extra_f32: - data = data.astype(np.float16) + extra_f16 = any(cond for cond in ( + extra_f16, + (name.endswith(".weight") and n_dims >= 2), + )) + + if self.ftype != gguf.LlamaFileType.ALL_F32 and extra_f16 and not extra_f32: + if self.ftype == gguf.LlamaFileType.MOSTLY_F16: + if data_dtype != np.float16: + data = data.astype(np.float16) + data_qtype = gguf.GGMLQuantizationType.F16 + + elif self.ftype == gguf.LlamaFileType.MOSTLY_BF16: + if data_dtype != np.float32: + data = data.astype(np.float32) + data = v_fp32_to_bf16(data.view(np.int32)) + assert data.dtype == np.int16 + data_qtype = gguf.GGMLQuantizationType.BF16 + + else: # by default, convert to float32 + if data_dtype != np.float32: + data = data.astype(np.float32) + data_qtype = gguf.GGMLQuantizationType.F32 + + assert data_qtype is not None # reverse shape to make it similar to the internal ggml dimension order shape_str = f"{{{', '.join(str(n) for n in reversed(data.shape))}}}" # n_dims is implicit in the shape - logger.info(f"{f'%-{max_name_len}s' % f'{new_name},'} {old_dtype} --> {data.dtype}, shape = {shape_str}") + logger.info(f"{f'%-{max_name_len}s' % f'{new_name},'} {old_dtype} --> {data_qtype.name}, shape = {shape_str}") - self.gguf_writer.add_tensor(new_name, data) + self.gguf_writer.add_tensor(new_name, data, raw_dtype=data_qtype) def write(self): self.write_tensors() @@ -2044,12 +2111,6 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter return [(self.map_tensor_name(name), data_torch)] - def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool: - del new_name, bid, n_dims # unused - - # not used with get_rows, must be F32 - return name == "embeddings.token_type_embeddings.weight" - @Model.register("NomicBertModel") class NomicBertModel(BertModel): @@ -2339,92 +2400,40 @@ def set_vocab(self, *args, **kwargs): # tree of lazy tensors -class LazyTorchTensor: - _meta: Tensor - _data: Tensor | None - _args: tuple - _func: Callable[[tuple], Tensor] | None - - def __init__(self, *, meta: Tensor, data: Tensor | None = None, args: tuple = (), func: Callable[[tuple], Tensor] | None = None): - self._meta = meta - self._data = data - self._args = args - self._func = func - - @staticmethod - def _recurse_apply(o: Any, fn: Callable[[Any], Any]) -> Any: - # TODO: dict and set - if isinstance(o, (list, tuple)): - L = [] - for item in o: - L.append(LazyTorchTensor._recurse_apply(item, fn)) - if isinstance(o, tuple): - L = tuple(L) - return L - elif isinstance(o, LazyTorchTensor): - return fn(o) - else: - return o - - def _wrap_fn(self, fn: Callable, use_self: bool = False) -> Callable[[Any], LazyTorchTensor]: - def wrapped_fn(*args, **kwargs): - if kwargs is None: - kwargs = {} - args = ((self,) if use_self else ()) + args - - meta_args = LazyTorchTensor._recurse_apply(args, lambda t: t._meta) - - return LazyTorchTensor(meta=fn(*meta_args, **kwargs), args=args, func=lambda a: fn(*a, **kwargs)) - return wrapped_fn - - def __getattr__(self, __name: str) -> Any: - meta_attr = getattr(self._meta, __name) - if callable(meta_attr): - return self._wrap_fn(getattr(torch.Tensor, __name), use_self=True) - elif isinstance(meta_attr, torch.Tensor): - # for things like self.T - return self._wrap_fn(lambda s: getattr(s, __name))(self) - else: - return meta_attr +class LazyTorchTensor(gguf.LazyBase): + _tensor_type = torch.Tensor + # to keep the type-checker happy + dtype: torch.dtype + shape: torch.Size + # only used when converting a torch.Tensor to a np.ndarray _dtype_map: dict[torch.dtype, type] = { torch.float16: np.float16, torch.float32: np.float32, } - def numpy(self) -> gguf.LazyTensor: + def numpy(self) -> gguf.LazyNumpyTensor: dtype = self._dtype_map[self.dtype] - return gguf.LazyTensor(lambda: LazyTorchTensor.to_eager(self).numpy(), dtype=dtype, shape=self.shape) - - @overload - @staticmethod - def to_eager(t: Tensor | LazyTorchTensor) -> Tensor: ... - - @overload - @staticmethod - def to_eager(t: tuple) -> tuple: ... - - @staticmethod - def to_eager(t: Any) -> Any: - def simple_to_eager(_t: LazyTorchTensor) -> Tensor: - # wake up the lazy tensor - if _t._data is None and _t._func is not None: - # recurse into its arguments - _t._args = LazyTorchTensor.to_eager(_t._args) - _t._data = _t._func(_t._args) - if _t._data is not None: - return _t._data - else: - raise ValueError(f"Could not compute lazy tensor {_t!r} with args {_t._args!r}") - - # recurse into lists and/or tuples, keeping their structure - return LazyTorchTensor._recurse_apply(t, simple_to_eager) + return gguf.LazyNumpyTensor( + meta=np.lib.stride_tricks.as_strided(np.zeros(1, dtype), self.shape, (0 for _ in self.shape)), + lazy=self._lazy, + args=(self,), + func=(lambda s: s[0].numpy()) + ) - @staticmethod - def from_eager(t: Tensor) -> Tensor: - if (t.__class__ == LazyTorchTensor): + @classmethod + def eager_to_meta(cls, t: Tensor) -> Tensor: + if t.is_meta: return t - return LazyTorchTensor(meta=t.detach().to("meta"), data=t) # type: ignore + return t.detach().to("meta") + + @classmethod + def meta_with_dtype(cls, m: Tensor, dtype: torch.dtype) -> Tensor: + m = m.detach() + if not m.is_meta: + m = m.to("meta") + m.dtype = dtype + return m @classmethod def __torch_function__(cls, func, types, args=(), kwargs=None): @@ -2435,28 +2444,8 @@ def __torch_function__(cls, func, types, args=(), kwargs=None): if func is torch.Tensor.numpy: return args[0].numpy() - if func is torch.equal: - eager_args = LazyTorchTensor.to_eager(args) - return func(*eager_args, **kwargs) - return LazyTorchTensor._wrap_fn(args[0], func)(*args, **kwargs) - - # special methods bypass __getattr__, so they need to be added manually - # ref: https://docs.python.org/3/reference/datamodel.html#special-lookup - # NOTE: LazyTorchTensor can't be a subclass of Tensor (and then be used - # as self._meta is currently used), because then the following - # operations would by default not be wrapped, and so not propagated - # when the tensor is made eager. - # It's better to get non-silent errors for not-yet-supported operators. - # TODO: add more when needed to avoid clutter, or find a more concise way - def __neg__(self, *args): # mamba - return self._wrap_fn(torch.Tensor.__neg__)(self, *args) - - def __add__(self, *args): # gemma - return self._wrap_fn(torch.Tensor.__add__)(self, *args) - - def __getitem__(self, *args): # bloom falcon refact internlm2 - return self._wrap_fn(torch.Tensor.__getitem__)(self, *args) + return LazyTorchTensor._wrap_fn(func)(*args, **kwargs) def parse_args() -> argparse.Namespace: @@ -2472,11 +2461,11 @@ def parse_args() -> argparse.Namespace: ) parser.add_argument( "--outfile", type=Path, - help="path to write to; default: based on input", + help="path to write to; default: based on input. {ftype} will be replaced by the outtype.", ) parser.add_argument( - "--outtype", type=str, choices=["f32", "f16"], default="f16", - help="output format - use f32 for float32, f16 for float16", + "--outtype", type=str, choices=["f32", "f16", "bf16", "auto"], default="f16", + help="output format - use f32 for float32, f16 for float16, bf16 for bfloat16, auto for the highest-fidelity 16-bit float type depending on the first loaded tensor type", ) parser.add_argument( "--bigendian", action="store_true", @@ -2530,16 +2519,18 @@ def main() -> None: logger.error(f'Error: {args.model} is not a directory') sys.exit(1) - ftype_map = { - "f32": gguf.GGMLQuantizationType.F32, - "f16": gguf.GGMLQuantizationType.F16, + ftype_map: dict[str, gguf.LlamaFileType] = { + "f32": gguf.LlamaFileType.ALL_F32, + "f16": gguf.LlamaFileType.MOSTLY_F16, + "bf16": gguf.LlamaFileType.MOSTLY_BF16, + "auto": gguf.LlamaFileType.GUESSED, } if args.outfile is not None: fname_out = args.outfile else: # output in the same directory as the model by default - fname_out = dir_model / f'ggml-model-{args.outtype}.gguf' + fname_out = dir_model / 'ggml-model-{ftype}.gguf' logger.info(f"Loading model: {dir_model.name}") @@ -2555,14 +2546,16 @@ def main() -> None: logger.info("Set model tokenizer") model_instance.set_vocab() + model_instance.gguf_writer.add_quantization_version(gguf.GGML_QUANT_VERSION) + if args.vocab_only: - logger.info(f"Exporting model vocab to '{fname_out}'") + logger.info(f"Exporting model vocab to '{model_instance.fname_out}'") model_instance.write_vocab() else: - logger.info(f"Exporting model to '{fname_out}'") + logger.info(f"Exporting model to '{model_instance.fname_out}'") model_instance.write() - logger.info(f"Model successfully exported to '{fname_out}'") + logger.info(f"Model successfully exported to '{model_instance.fname_out}'") if __name__ == '__main__': diff --git a/gguf-py/gguf/__init__.py b/gguf-py/gguf/__init__.py index 110ab342ccd71..e5d5806c81e5e 100644 --- a/gguf-py/gguf/__init__.py +++ b/gguf-py/gguf/__init__.py @@ -1,4 +1,5 @@ from .constants import * +from .lazy import * from .gguf_reader import * from .gguf_writer import * from .tensor_mapping import * diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index a4fbfc5e09d06..978fcada3b42c 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -10,6 +10,7 @@ GGUF_MAGIC = 0x46554747 # "GGUF" GGUF_VERSION = 3 GGUF_DEFAULT_ALIGNMENT = 32 +GGML_QUANT_VERSION = 2 # GGML_QNT_VERSION from ggml.h # # metadata keys @@ -838,6 +839,49 @@ class GGMLQuantizationType(IntEnum): BF16 = 30 +# TODO: add GGMLFileType from ggml_ftype in ggml.h + + +# from llama_ftype in llama.h +# ALL VALUES SHOULD BE THE SAME HERE AS THEY ARE OVER THERE. +class LlamaFileType(IntEnum): + ALL_F32 = 0 + MOSTLY_F16 = 1 # except 1d tensors + MOSTLY_Q4_0 = 2 # except 1d tensors + MOSTLY_Q4_1 = 3 # except 1d tensors + MOSTLY_Q4_1_SOME_F16 = 4 # tok_embeddings.weight and output.weight are F16 + # MOSTLY_Q4_2 = 5 # support has been removed + # MOSTLY_Q4_3 = 6 # support has been removed + MOSTLY_Q8_0 = 7 # except 1d tensors + MOSTLY_Q5_0 = 8 # except 1d tensors + MOSTLY_Q5_1 = 9 # except 1d tensors + MOSTLY_Q2_K = 10 # except 1d tensors + MOSTLY_Q3_K_S = 11 # except 1d tensors + MOSTLY_Q3_K_M = 12 # except 1d tensors + MOSTLY_Q3_K_L = 13 # except 1d tensors + MOSTLY_Q4_K_S = 14 # except 1d tensors + MOSTLY_Q4_K_M = 15 # except 1d tensors + MOSTLY_Q5_K_S = 16 # except 1d tensors + MOSTLY_Q5_K_M = 17 # except 1d tensors + MOSTLY_Q6_K = 18 # except 1d tensors + MOSTLY_IQ2_XXS = 19 # except 1d tensors + MOSTLY_IQ2_XS = 20 # except 1d tensors + MOSTLY_Q2_K_S = 21 # except 1d tensors + MOSTLY_IQ3_XS = 22 # except 1d tensors + MOSTLY_IQ3_XXS = 23 # except 1d tensors + MOSTLY_IQ1_S = 24 # except 1d tensors + MOSTLY_IQ4_NL = 25 # except 1d tensors + MOSTLY_IQ3_S = 26 # except 1d tensors + MOSTLY_IQ3_M = 27 # except 1d tensors + MOSTLY_IQ2_S = 28 # except 1d tensors + MOSTLY_IQ2_M = 29 # except 1d tensors + MOSTLY_IQ4_XS = 30 # except 1d tensors + MOSTLY_IQ1_M = 31 # except 1d tensors + MOSTLY_BF16 = 32 # except 1d tensors + + GUESSED = 1024 # not specified in the model file + + class GGUFEndian(IntEnum): LITTLE = 0 BIG = 1 diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py index 8dcf9330b076f..96574358d66bb 100644 --- a/gguf-py/gguf/gguf_writer.py +++ b/gguf-py/gguf/gguf_writer.py @@ -7,7 +7,7 @@ import tempfile from enum import Enum, auto from io import BufferedWriter -from typing import IO, Any, Callable, Sequence, Mapping +from typing import IO, Any, Sequence, Mapping from string import ascii_letters, digits import numpy as np @@ -28,47 +28,6 @@ logger = logging.getLogger(__name__) -class LazyTensor: - data: Callable[[], np.ndarray[Any, Any]] - # to avoid too deep recursion - functions: list[Callable[[np.ndarray[Any, Any]], np.ndarray[Any, Any]]] - dtype: np.dtype[Any] - shape: tuple[int, ...] - - def __init__(self, data: Callable[[], np.ndarray[Any, Any]], *, dtype: type, shape: tuple[int, ...]): - self.data = data - self.functions = [] - self.dtype = np.dtype(dtype) - self.shape = shape - - def astype(self, dtype: type, **kwargs) -> LazyTensor: - self.functions.append(lambda n: n.astype(dtype, **kwargs)) - self.dtype = np.dtype(dtype) - return self - - @property - def nbytes(self) -> int: - size = 1 - for n in self.shape: - size *= n - return size * self.dtype.itemsize - - def tofile(self, *args, **kwargs) -> None: - data = self.data() - for f in self.functions: - data = f(data) - assert data.shape == self.shape - assert data.dtype == self.dtype - assert data.nbytes == self.nbytes - self.functions = [] - self.data = lambda: data - data.tofile(*args, **kwargs) - - def byteswap(self, *args, **kwargs) -> LazyTensor: - self.functions.append(lambda n: n.byteswap(*args, **kwargs)) - return self - - class WriterState(Enum): EMPTY = auto() HEADER = auto() @@ -79,7 +38,7 @@ class WriterState(Enum): class GGUFWriter: fout: BufferedWriter temp_file: tempfile.SpooledTemporaryFile[bytes] | None - tensors: list[np.ndarray[Any, Any] | LazyTensor] + tensors: list[np.ndarray[Any, Any]] _simple_value_packing = { GGUFValueType.UINT8: "B", GGUFValueType.INT8: "b", @@ -278,7 +237,7 @@ def add_tensor_info( self.ti_data_count += 1 def add_tensor( - self, name: str, tensor: np.ndarray[Any, Any] | LazyTensor, raw_shape: Sequence[int] | None = None, + self, name: str, tensor: np.ndarray[Any, Any], raw_shape: Sequence[int] | None = None, raw_dtype: GGMLQuantizationType | None = None, ) -> None: if self.endianess == GGUFEndian.BIG: @@ -303,7 +262,7 @@ def write_padding(self, fp: IO[bytes], n: int, align: int | None = None) -> None if pad != 0: fp.write(bytes([0] * pad)) - def write_tensor_data(self, tensor: np.ndarray[Any, Any] | LazyTensor) -> None: + def write_tensor_data(self, tensor: np.ndarray[Any, Any]) -> None: if self.state is not WriterState.TI_DATA: raise ValueError(f'Expected output file to contain tensor info, got {self.state}') @@ -391,7 +350,7 @@ def add_file_type(self, ftype: int) -> None: def add_name(self, name: str) -> None: self.add_string(Keys.General.NAME, name) - def add_quantization_version(self, quantization_version: GGMLQuantizationType) -> None: + def add_quantization_version(self, quantization_version: int) -> None: self.add_uint32( Keys.General.QUANTIZATION_VERSION, quantization_version) diff --git a/gguf-py/gguf/lazy.py b/gguf-py/gguf/lazy.py new file mode 100644 index 0000000000000..650bea11c9c58 --- /dev/null +++ b/gguf-py/gguf/lazy.py @@ -0,0 +1,225 @@ +from __future__ import annotations +from abc import ABC, ABCMeta, abstractmethod + +import logging +from typing import Any, Callable +from collections import deque + +import numpy as np +from numpy.typing import DTypeLike + + +logger = logging.getLogger(__name__) + + +class LazyMeta(ABCMeta): + + def __new__(cls, name: str, bases: tuple[type, ...], namespace: dict[str, Any], **kwargs): + def __getattr__(self, __name: str) -> Any: + meta_attr = getattr(self._meta, __name) + if callable(meta_attr): + return type(self)._wrap_fn( + (lambda s, *args, **kwargs: getattr(s, __name)(*args, **kwargs)), + use_self=self, + ) + elif isinstance(meta_attr, self._tensor_type): + # e.g. self.T with torch.Tensor should still be wrapped + return type(self)._wrap_fn(lambda s: getattr(s, __name))(self) + else: + # no need to wrap non-tensor properties, + # and they likely don't depend on the actual contents of the tensor + return meta_attr + + namespace["__getattr__"] = __getattr__ + + # need to make a builder for the wrapped wrapper to copy the name, + # or else it fails with very cryptic error messages, + # because somehow the same string would end up in every closures + def mk_wrap(op_name: str, *, meta_noop: bool = False): + # need to wrap the wrapper to get self + def wrapped_special_op(self, *args, **kwargs): + return type(self)._wrap_fn( + getattr(type(self)._tensor_type, op_name), + meta_noop=meta_noop, + )(self, *args, **kwargs) + return wrapped_special_op + + # special methods bypass __getattr__, so they need to be added manually + # ref: https://docs.python.org/3/reference/datamodel.html#special-lookup + # NOTE: doing this from a metaclass is very convenient + # TODO: make this even more comprehensive + for binary_op in ( + "lt", "le", "eq", "ne", "ge", "gt", "not" + "abs", "add", "and", "floordiv", "invert", "lshift", "mod", "mul", "matmul", + "neg", "or", "pos", "pow", "rshift", "sub", "truediv", "xor", + "iadd", "iand", "ifloordiv", "ilshift", "imod", "imul", "ior", "irshift", "isub", "ixor", + "radd", "rand", "rfloordiv", "rmul", "ror", "rpow", "rsub", "rtruediv", "rxor", + ): + attr_name = f"__{binary_op}__" + # the result of these operators usually has the same shape and dtype as the input, + # so evaluation on the meta tensor can be skipped. + namespace[attr_name] = mk_wrap(attr_name, meta_noop=True) + + for special_op in ( + "getitem", "setitem", "len", + ): + attr_name = f"__{special_op}__" + namespace[attr_name] = mk_wrap(attr_name, meta_noop=False) + + return super().__new__(cls, name, bases, namespace, **kwargs) + + +# Tree of lazy tensors +class LazyBase(ABC, metaclass=LazyMeta): + _tensor_type: type + _meta: Any + _data: Any | None + _lazy: deque[LazyBase] # shared within a graph, to avoid deep recursion when making eager + _args: tuple + _func: Callable[[tuple], Any] | None + + def __init__(self, *, meta: Any, data: Any | None = None, lazy: deque[LazyBase] | None = None, args: tuple = (), func: Callable[[tuple], Any] | None = None): + super().__init__() + self._meta = meta + self._data = data + self._lazy = lazy if lazy is not None else deque() + self._args = args + self._func = func + assert self._func is not None or self._data is not None + if self._data is None: + self._lazy.append(self) + + def __init_subclass__(cls) -> None: + if "_tensor_type" not in cls.__dict__: + raise TypeError(f"property '_tensor_type' must be defined for {cls!r}") + return super().__init_subclass__() + + @staticmethod + def _recurse_apply(o: Any, fn: Callable[[Any], Any]) -> Any: + # TODO: dict and set + if isinstance(o, (list, tuple)): + L = [] + for item in o: + L.append(LazyBase._recurse_apply(item, fn)) + if isinstance(o, tuple): + L = tuple(L) + return L + elif isinstance(o, LazyBase): + return fn(o) + else: + return o + + @classmethod + def _wrap_fn(cls, fn: Callable, *, use_self: LazyBase | None = None, meta_noop: bool | DTypeLike = False) -> Callable[[Any], Any]: + def wrapped_fn(*args, **kwargs): + if kwargs is None: + kwargs = {} + args = ((use_self,) if use_self is not None else ()) + args + + meta_args = LazyBase._recurse_apply(args, lambda t: t._meta) + + if isinstance(meta_noop, bool) and not meta_noop: + try: + res = fn(*meta_args, **kwargs) + except NotImplementedError: + # running some operations on PyTorch's Meta tensors can cause this exception + res = None + else: + # some operators don't need to actually run on the meta tensors + assert len(args) > 0 + res = args[0] + assert isinstance(res, cls) + res = res._meta + # allow operations to override the dtype + if meta_noop is not True: + res = cls.meta_with_dtype(res, meta_noop) + + if isinstance(res, cls._tensor_type): + def collect_replace(t: LazyBase): + if collect_replace.shared_lazy is None: + collect_replace.shared_lazy = t._lazy + else: + collect_replace.shared_lazy.extend(t._lazy) + t._lazy = collect_replace.shared_lazy + + # emulating a static variable + collect_replace.shared_lazy = None + + LazyBase._recurse_apply(args, collect_replace) + + shared_lazy = collect_replace.shared_lazy + + return cls(meta=cls.eager_to_meta(res), lazy=shared_lazy, args=args, func=lambda a: fn(*a, **kwargs)) + else: + del res # not needed + # non-tensor return likely relies on the contents of the args + # (e.g. the result of torch.equal) + eager_args = cls.to_eager(args) + return fn(*eager_args, **kwargs) + return wrapped_fn + + @classmethod + def to_eager(cls, t: Any) -> Any: + def simple_to_eager(_t: LazyBase) -> Any: + def already_eager_to_eager(_t: LazyBase) -> Any: + assert _t._data is not None + return _t._data + + while _t._data is None: + lt = _t._lazy.popleft() + if lt._data is not None: + raise ValueError(f"{lt} did not belong in the lazy queue") + assert lt._func is not None + lt._args = cls._recurse_apply(lt._args, already_eager_to_eager) + lt._data = lt._func(lt._args) + # sanity check + assert lt._data.dtype == lt._meta.dtype + assert lt._data.shape == lt._meta.shape + + return _t._data + + # recurse into lists and/or tuples, keeping their structure + return cls._recurse_apply(t, simple_to_eager) + + @classmethod + def eager_to_meta(cls, t: Any) -> Any: + return cls.meta_with_dtype(t, t.dtype) + + # must be overridden, meta tensor init is backend-specific + @classmethod + @abstractmethod + def meta_with_dtype(cls, m: Any, dtype: Any) -> Any: pass + + @classmethod + def from_eager(cls, t: Any) -> Any: + if type(t) is cls: + # already eager + return t + elif isinstance(t, cls._tensor_type): + return cls(meta=cls.eager_to_meta(t), data=t) + else: + return TypeError(f"{type(t)!r} is not compatible with {cls._tensor_type!r}") + + +class LazyNumpyTensor(LazyBase): + _tensor_type = np.ndarray + + @classmethod + def meta_with_dtype(cls, m: np.ndarray[Any, Any], dtype: DTypeLike) -> np.ndarray[Any, Any]: + # The initial idea was to use np.nan as the fill value, + # but non-float types like np.int16 can't use that. + # So zero it is. + cheat = np.zeros(1, dtype) + return np.lib.stride_tricks.as_strided(cheat, m.shape, (0 for _ in m.shape)) + + def astype(self, dtype, *args, **kwargs): + meta = type(self).meta_with_dtype(self._meta, dtype) + full_args = (self, dtype,) + args + # very important to pass the shared _lazy deque, or else there's an infinite loop somewhere. + return type(self)(meta=meta, args=full_args, lazy=self._lazy, func=(lambda a: a[0].astype(*a[1:], **kwargs))) + + def tofile(self, *args, **kwargs): + eager = LazyNumpyTensor.to_eager(self) + return eager.tofile(*args, **kwargs) + + # TODO: __array_function__ From 72c177c1f6c16693eee319d4ebd4eaab5e630dd2 Mon Sep 17 00:00:00 2001 From: Xuan Son Nguyen <thichthat@gmail.com> Date: Sat, 11 May 2024 17:28:10 +0200 Subject: [PATCH 48/64] fix system prompt handling (#7153) --- examples/server/server.cpp | 20 +++++++------------- 1 file changed, 7 insertions(+), 13 deletions(-) diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 55c1d41298cd6..ceaeb1f76dc3d 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -651,9 +651,6 @@ struct server_context { std::string system_prompt; std::vector<llama_token> system_tokens; - std::string name_user; // this should be the antiprompt - std::string name_assistant; - // slots / clients std::vector<server_slot> slots; json default_generation_settings_for_props; @@ -1100,15 +1097,11 @@ struct server_context { system_need_update = false; } - void system_prompt_set(const json & sys_props) { - system_prompt = sys_props.value("prompt", ""); - name_user = sys_props.value("anti_prompt", ""); - name_assistant = sys_props.value("assistant_name", ""); + bool system_prompt_set(const std::string & sys_prompt) { + system_prompt = sys_prompt; LOG_VERBOSE("system prompt process", { {"system_prompt", system_prompt}, - {"name_user", name_user}, - {"name_assistant", name_assistant}, }); // release all slots @@ -1117,6 +1110,7 @@ struct server_context { } system_need_update = true; + return true; } bool process_token(completion_token_output & result, server_slot & slot) { @@ -1536,7 +1530,8 @@ struct server_context { } if (task.data.contains("system_prompt")) { - system_prompt_set(task.data.at("system_prompt")); + std::string sys_prompt = json_value(task.data, "system_prompt", std::string()); + system_prompt_set(sys_prompt); for (server_slot & slot : slots) { slot.n_past = 0; @@ -2920,7 +2915,7 @@ int main(int argc, char ** argv) { server_params_parse(argc, argv, sparams, params); if (!sparams.system_prompt.empty()) { - ctx_server.system_prompt_set(json::parse(sparams.system_prompt)); + ctx_server.system_prompt_set(sparams.system_prompt); } if (params.model_alias == "unknown") { @@ -3409,8 +3404,7 @@ int main(int argc, char ** argv) { const auto handle_props = [&ctx_server](const httplib::Request & req, httplib::Response & res) { res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin")); json data = { - { "user_name", ctx_server.name_user.c_str() }, - { "assistant_name", ctx_server.name_assistant.c_str() }, + { "system_prompt", ctx_server.system_prompt.c_str() }, { "default_generation_settings", ctx_server.default_generation_settings_for_props }, { "total_slots", ctx_server.params.n_parallel } }; From fed0108491a3a3cbec6c6480dc8667ffff9d7659 Mon Sep 17 00:00:00 2001 From: Josh Ramer <josh.ramer@icloud.com> Date: Sat, 11 May 2024 12:26:35 -0500 Subject: [PATCH 49/64] Scripting & documenting debugging one test without anything else in the loop. (#7096) * A little documentation that shares my quick tips for working in the repository. * Update startup-testing-debugging.md * script that shows a menu of tests to pick from & run the debugger on * debug-test.sh: Refactor CLI help message * debug-test.sh: documentation update * debug-test.sh: CLI Help output corrections * debug-test.sh: minor doc fix --------- authored-by: Josh Ramer <ubuntu@ip-172-31-32-53.ec2.internal> Assisted-by: brian khuu <mofosyne@gmail.com> --- docs/debugging-tests.md | 88 ++++++++++++++++++++++++++++++ scripts/debug-test.sh | 117 ++++++++++++++++++++++++++++++++++++++++ 2 files changed, 205 insertions(+) create mode 100644 docs/debugging-tests.md create mode 100755 scripts/debug-test.sh diff --git a/docs/debugging-tests.md b/docs/debugging-tests.md new file mode 100644 index 0000000000000..51a125e191d84 --- /dev/null +++ b/docs/debugging-tests.md @@ -0,0 +1,88 @@ +# Debugging Tests Tips + +## How to run & debug a specific test without anything else to keep the feedback loop short? + +There is a script called debug-test.sh in the scripts folder whose parameter takes a REGEX and an optional test number. + +For example, running the following command will output an interactive list from which you can select a test. It takes this form: + +`debug-test.sh [OPTION]... <test_regex> <test_number>` + +It will then build & run in the debugger for you. + +```bash +./scripts/debug-test.sh test-tokenizer + +# Once in the debugger, i.e. at the chevrons prompt, setting a breakpoint could be as follows: +>>> b main +``` + +For further reference use `debug-test.sh -h` to print help. + +&nbsp; + +### How does the script work? +If you want to be able to use the concepts contained in the script separately, the important ones are briefly outlined below. + +#### Step 1: Reset and Setup folder context + +From base of this repository, let's create `build-ci-debug` as our build context. + +```bash +rm -rf build-ci-debug && mkdir build-ci-debug && cd build-ci-debug +``` + +#### Step 2: Setup Build Environment and Compile Test Binaries + +Setup and trigger a build under debug mode. You may adapt the arguments as needed, but in this case these are sane defaults. + +```bash +cmake -DCMAKE_BUILD_TYPE=Debug -DLLAMA_CUDA=1 -DLLAMA_FATAL_WARNINGS=ON .. +make -j +``` + +#### Step 3.1: Identify Test Command for Debugging + +The output of this command will give you the command & arguments needed to run GDB. + +* `-R test-tokenizer` : looks for all the test files named `test-tokenizer*` (R=Regex) +* `-N` : "show-only" disables test execution & shows test commands that you can feed to GDB. +* `-V` : Verbose Mode + +```bash +ctest -R "test-tokenizer" -V -N +``` + +This may return output similar to below (focusing on key lines to pay attention to): + +```bash +... +1: Test command: ~/llama.cpp/build-ci-debug/bin/test-tokenizer-0 "~/llama.cpp/tests/../models/ggml-vocab-llama-spm.gguf" +1: Working Directory: . +Labels: main + Test #1: test-tokenizer-0-llama-spm +... +4: Test command: ~/llama.cpp/build-ci-debug/bin/test-tokenizer-0 "~/llama.cpp/tests/../models/ggml-vocab-falcon.gguf" +4: Working Directory: . +Labels: main + Test #4: test-tokenizer-0-falcon +... +``` + +So for test #1 we can tell these two pieces of relevant information: +* Test Binary: `~/llama.cpp/build-ci-debug/bin/test-tokenizer-0` +* Test GGUF Model: `~/llama.cpp/tests/../models/ggml-vocab-llama-spm.gguf` + +#### Step 3.2: Run GDB on test command + +Based on the ctest 'test command' report above we can then run a gdb session via this command below: + +```bash +gdb --args ${Test Binary} ${Test GGUF Model} +``` + +Example: + +```bash +gdb --args ~/llama.cpp/build-ci-debug/bin/test-tokenizer-0 "~/llama.cpp/tests/../models/ggml-vocab-llama-spm.gguf" +``` diff --git a/scripts/debug-test.sh b/scripts/debug-test.sh new file mode 100755 index 0000000000000..231a23d694873 --- /dev/null +++ b/scripts/debug-test.sh @@ -0,0 +1,117 @@ +#!/bin/bash +test_suite=${1:-} +test_number=${2:-} + +PROG=${0##*/} +build_dir="build-ci-debug" + +if [ x"$1" = x"-h" ] || [ x"$1" = x"--help" ]; then + echo "Usage: $PROG [OPTION]... <test_regex> (test_number)" + echo "Debug specific ctest program." + echo + echo "Options:" + echo " -h, --help Display this help and exit" + echo + echo "Arguments:" + echo " <test_regex> (Mandatory) Supply one regex to the script to filter tests" + echo " (test_number) (Optional) Test number to run a specific test" + echo + echo "Example:" + echo " $PROG test-tokenizer" + echo " $PROG test-tokenizer 3" + echo + exit 0 +fi + +# Function to select and debug a test +function select_test() { + test_suite=${1:-test} + test_number=${2:-} + + # Sanity Check If Tests Is Detected + printf "\n\nGathering tests that fit REGEX: ${test_suite} ...\n" + tests=($(ctest -R ${test_suite} -V -N | grep -E " +Test +#[0-9]+*" | cut -d':' -f2 | awk '{$1=$1};1')) + if [ ${#tests[@]} -eq 0 ] + then + echo "No tests avaliable... check your compliation process..." + echo "Exiting." + exit 1 + fi + + if [ -z $test_number ] + then + # List out avaliable tests + printf "Which test would you like to debug?\n" + id=0 + for s in "${tests[@]}" + do + echo "Test# ${id}" + echo " $s" + ((id++)) + done + + # Prompt user which test they wanted to run + printf "\nRun test#? " + read test_number + else + printf "\nUser Already Requested #${test_number}" + fi + + # Start GDB with the requested test binary and arguments + printf "Debugging(GDB) test: ${tests[test_number]}\n" + # Change IFS (Internal Field Separator) + sIFS=$IFS + IFS=$'\n' + + # Get test args + gdb_args=($(ctest -R ${test_suite} -V -N | grep "Test command" | cut -d':' -f3 | awk '{$1=$1};1' )) + IFS=$sIFS + printf "Debug arguments: ${gdb_args[test_number]}\n\n" + + # Expand paths if needed + args=() + for x in $(echo ${gdb_args[test_number]} | sed -e 's/"\/\<//' -e 's/\>"//') + do + args+=($(echo $x | sed -e 's/.*\/..\//..\//')) + done + + # Execute debugger + echo "gdb args: ${args[@]}" + gdb --args ${args[@]} +} + +# Step 0: Check the args +if [ -z "$test_suite" ] +then + echo "Usage: $PROG [OPTION]... <test_regex> (test_number)" + echo "Supply one regex to the script to filter tests," + echo "and optionally a test number to run a specific test." + echo "Use --help flag for full instructions" + exit 1 +fi + +# Step 1: Reset and Setup folder context +## Sanity check that we are actually in a git repo +repo_root=$(git rev-parse --show-toplevel) +if [ ! -d "$repo_root" ]; then + echo "Error: Not in a Git repository." + exit 1 +fi + +## Reset folder to root context of git repo +pushd "$repo_root" || exit 1 + +## Create and enter build directory +rm -rf "$build_dir" && mkdir "$build_dir" || exit 1 + +# Step 2: Setup Build Environment and Compile Test Binaries +cmake -B "./$build_dir" -DCMAKE_BUILD_TYPE=Debug -DLLAMA_CUDA=1 -DLLAMA_FATAL_WARNINGS=ON || exit 1 +pushd "$build_dir" && make -j || exit 1 + +# Step 3: Debug the Test +select_test "$test_suite" "$test_number" + +# Step 4: Return to the directory from which the user ran the command. +popd || exit 1 +popd || exit 1 +popd || exit 1 From 325756d28df7d018a7bac424e1b3bc8acb4ecf07 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 16:25:50 +0300 Subject: [PATCH 50/64] ggml : resolve merge (ggml/0) ggml-ci --- ggml.c | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ggml.c b/ggml.c index 4f3011583d2e7..b96a82a41517d 100644 --- a/ggml.c +++ b/ggml.c @@ -4,7 +4,6 @@ #include "ggml-impl.h" #include "ggml-quants.h" #include "ggml.h" -#include "sgemm.h" #if defined(_MSC_VER) || defined(__MINGW32__) #include <malloc.h> // using malloc.h with MSC/MINGW @@ -37,6 +36,10 @@ #undef GGML_USE_LLAMAFILE #endif +#ifdef GGML_USE_LLAMAFILE +#include "sgemm.h" +#endif + #if defined(_MSC_VER) // disable "possible loss of data" to avoid hundreds of casts // we should just be careful :) From 6aeff24f8b91e145e92d17ec7ce3adc4ef60b8e9 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 16:57:53 +0300 Subject: [PATCH 51/64] metal : fix indent (ggml/0) --- ggml-metal.m | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/ggml-metal.m b/ggml-metal.m index 66c398d54fd28..28dec762a8a44 100644 --- a/ggml-metal.m +++ b/ggml-metal.m @@ -1195,24 +1195,24 @@ static enum ggml_status ggml_metal_graph_compute( [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; } break; case GGML_OP_CLAMP: - { - id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CLAMP].pipeline; + { + id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CLAMP].pipeline; - float min; - float max; - memcpy(&min, ((int32_t *) dst->op_params) + 0, sizeof(float)); - memcpy(&max, ((int32_t *) dst->op_params) + 1, sizeof(float)); + float min; + float max; + memcpy(&min, ((int32_t *) dst->op_params) + 0, sizeof(float)); + memcpy(&max, ((int32_t *) dst->op_params) + 1, sizeof(float)); - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; - [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; - [encoder setBytes:&min length:sizeof(min) atIndex:2]; - [encoder setBytes:&max length:sizeof(max) atIndex:3]; + [encoder setComputePipelineState:pipeline]; + [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0]; + [encoder setBuffer:id_dst offset:offs_dst atIndex:1]; + [encoder setBytes:&min length:sizeof(min) atIndex:2]; + [encoder setBytes:&max length:sizeof(max) atIndex:3]; - const int64_t n = ggml_nelements(dst); + const int64_t n = ggml_nelements(dst); - [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; - } break; + [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)]; + } break; case GGML_OP_UNARY: switch (ggml_get_unary_op(gf->nodes[i])) { // we are not taking into account the strides, so for now require contiguous tensors From 1622ac023f42e5e01c163321cd98c6596aa9402d Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 21:35:05 +0300 Subject: [PATCH 52/64] sync : ggml --- scripts/sync-ggml.last | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last index c5bd3ef559ccc..46b874c642dc3 100644 --- a/scripts/sync-ggml.last +++ b/scripts/sync-ggml.last @@ -1 +1 @@ -8cd3975bf21657c6d1e80c7c61830977b962539e +d2ad1793f45922665c99f5cf4244dcab77e16c00 From 7bd4ffb78062587e4012a1c24186223f09b1bc70 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sat, 11 May 2024 21:36:20 +0300 Subject: [PATCH 53/64] metal : fix warnings (skipme) (#0) --- ggml-metal.metal | 4 ++-- scripts/sync-ggml.last | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/ggml-metal.metal b/ggml-metal.metal index 0c6d327987652..7af4e8f9342e7 100644 --- a/ggml-metal.metal +++ b/ggml-metal.metal @@ -2217,7 +2217,7 @@ kernel void kernel_flash_attn_ext_f16( // ALiBi if (max_bias > 0.0f) { - const short h = iq2; + const uint32_t h = iq2; const float base = h < n_head_log2 ? m0 : m1; const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; @@ -2473,7 +2473,7 @@ kernel void kernel_flash_attn_ext_vec_f16( // ALiBi if (max_bias > 0.0f) { - const short h = iq2; + const uint32_t h = iq2; const float base = h < n_head_log2 ? m0 : m1; const int exp = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last index 46b874c642dc3..1ea32042927fc 100644 --- a/scripts/sync-ggml.last +++ b/scripts/sync-ggml.last @@ -1 +1 @@ -d2ad1793f45922665c99f5cf4244dcab77e16c00 +30f54cbb3ada3e4c5bc6924de3e5918e5be4ff11 From b228aba91ac2cd9eb90e9d423ba1d0d20e0117e2 Mon Sep 17 00:00:00 2001 From: slaren <slarengh@gmail.com> Date: Sun, 12 May 2024 02:29:33 +0200 Subject: [PATCH 54/64] remove convert-lora-to-ggml.py (#7204) --- CMakeLists.txt | 11 -- ci/run.sh | 95 ----------- convert-lora-to-ggml.py | 150 ------------------ requirements.txt | 1 - .../requirements-convert-lora-to-ggml.txt | 2 - 5 files changed, 259 deletions(-) delete mode 100755 convert-lora-to-ggml.py delete mode 100644 requirements/requirements-convert-lora-to-ggml.txt diff --git a/CMakeLists.txt b/CMakeLists.txt index aa65b0d6c3d04..362ab3673c77e 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -1281,17 +1281,6 @@ install( WORLD_READ WORLD_EXECUTE DESTINATION ${CMAKE_INSTALL_BINDIR}) -install( - FILES convert-lora-to-ggml.py - PERMISSIONS - OWNER_READ - OWNER_WRITE - OWNER_EXECUTE - GROUP_READ - GROUP_EXECUTE - WORLD_READ - WORLD_EXECUTE - DESTINATION ${CMAKE_INSTALL_BINDIR}) if (LLAMA_METAL) install( FILES ggml-metal.metal diff --git a/ci/run.sh b/ci/run.sh index e67c1a5ffa5cf..d5972480bc6c1 100755 --- a/ci/run.sh +++ b/ci/run.sh @@ -365,47 +365,6 @@ function gg_run_open_llama_3b_v2 { cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log - # lora - function compare_ppl { - qnt="$1" - ppl1=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1) - ppl2=$(echo "$3" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1) - - if [ $(echo "$ppl1 < $ppl2" | bc) -eq 1 ]; then - printf ' - %s @ %s (FAIL: %s > %s)\n' "$qnt" "$ppl" "$ppl1" "$ppl2" - return 20 - fi - - printf ' - %s @ %s %s OK\n' "$qnt" "$ppl1" "$ppl2" - return 0 - } - - path_lora="../models-mnt/open-llama/3B-v2/lora" - path_shakespeare="../models-mnt/shakespeare" - - shakespeare="${path_shakespeare}/shakespeare.txt" - lora_shakespeare="${path_lora}/ggml-adapter-model.bin" - - gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/adapter_config.json - gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/adapter_model.bin - gg_wget ${path_shakespeare} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/shakespeare.txt - - python3 ../convert-lora-to-ggml.py ${path_lora} - - # f16 - (time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log - (time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log - compare_ppl "f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-f16.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - - # q8_0 - (time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log - (time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log - compare_ppl "q8_0 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - - # q8_0 + f16 lora-base - (time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log - compare_ppl "q8_0 / f16 base shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - set +e } @@ -416,7 +375,6 @@ function gg_sum_open_llama_3b_v2 { gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)" gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)" gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)" - gg_printf '- lora:\n%s\n' "$(cat $OUT/${ci}-lora-ppl.log)" gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)" gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)" gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)" @@ -429,11 +387,6 @@ function gg_sum_open_llama_3b_v2 { gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)" gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)" gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)" - gg_printf '- shakespeare (f16):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-f16.log)" - gg_printf '- shakespeare (f16 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log)" - gg_printf '- shakespeare (q8_0):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log)" - gg_printf '- shakespeare (q8_0 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log)" - gg_printf '- shakespeare (q8_0 / f16 base lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log)" } # open_llama_7b_v2 @@ -549,48 +502,6 @@ function gg_run_open_llama_7b_v2 { cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log - # lora - function compare_ppl { - qnt="$1" - ppl1=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1) - ppl2=$(echo "$3" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1) - - if [ $(echo "$ppl1 < $ppl2" | bc) -eq 1 ]; then - printf ' - %s @ %s (FAIL: %s > %s)\n' "$qnt" "$ppl" "$ppl1" "$ppl2" - return 20 - fi - - printf ' - %s @ %s %s OK\n' "$qnt" "$ppl1" "$ppl2" - return 0 - } - - path_lora="../models-mnt/open-llama/7B-v2/lora" - path_shakespeare="../models-mnt/shakespeare" - - shakespeare="${path_shakespeare}/shakespeare.txt" - lora_shakespeare="${path_lora}/ggml-adapter-model.bin" - - gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/adapter_config.json - gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/adapter_model.bin - gg_wget ${path_shakespeare} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/shakespeare.txt - - python3 ../convert-lora-to-ggml.py ${path_lora} - - # f16 - (time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log - (time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log - compare_ppl "f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-f16.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - - # currently not supported by the CUDA backend - # q8_0 - #(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log - #(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log - #compare_ppl "q8_0 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - - # q8_0 + f16 lora-base - #(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log - #compare_ppl "q8_0 / f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log - set +e } @@ -601,7 +512,6 @@ function gg_sum_open_llama_7b_v2 { gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)" gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)" gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)" - gg_printf '- lora:\n%s\n' "$(cat $OUT/${ci}-lora-ppl.log)" gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)" gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)" gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)" @@ -614,11 +524,6 @@ function gg_sum_open_llama_7b_v2 { gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)" gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)" gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)" - gg_printf '- shakespeare (f16):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-f16.log)" - gg_printf '- shakespeare (f16 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log)" - #gg_printf '- shakespeare (q8_0):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log)" - #gg_printf '- shakespeare (q8_0 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log)" - #gg_printf '- shakespeare (q8_0 / f16 base lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log)" } # bge-small diff --git a/convert-lora-to-ggml.py b/convert-lora-to-ggml.py deleted file mode 100755 index f09fa85febef3..0000000000000 --- a/convert-lora-to-ggml.py +++ /dev/null @@ -1,150 +0,0 @@ -#!/usr/bin/env python3 -from __future__ import annotations - -import logging -import json -import os -import struct -import sys -from pathlib import Path -from typing import Any, BinaryIO, Sequence - -import numpy as np -import torch - -if 'NO_LOCAL_GGUF' not in os.environ: - sys.path.insert(1, str(Path(__file__).parent / 'gguf-py' / 'gguf')) -import gguf - -logging.basicConfig(level=logging.DEBUG) -logger = logging.getLogger("lora-to-gguf") - -NUMPY_TYPE_TO_FTYPE: dict[str, int] = {"float32": 0, "float16": 1} - - -def write_file_header(fout: BinaryIO, params: dict[str, Any]) -> None: - fout.write(b"ggla"[::-1]) # magic (ggml lora) - fout.write(struct.pack("i", 1)) # file version - fout.write(struct.pack("i", params["r"])) - # https://opendelta.readthedocs.io/en/latest/modules/deltas.html says that `lora_alpha` is an int - # but some models ship a float value instead - # let's convert to int, but fail if lossless conversion is not possible - assert ( - int(params["lora_alpha"]) == params["lora_alpha"] - ), "cannot convert float to int losslessly" - fout.write(struct.pack("i", int(params["lora_alpha"]))) - - -def write_tensor_header(fout: BinaryIO, name: str, shape: Sequence[int], data_type: np.dtype[Any]) -> None: - sname = name.encode("utf-8") - fout.write( - struct.pack( - "iii", - len(shape), - len(sname), - NUMPY_TYPE_TO_FTYPE[data_type.name], - ) - ) - fout.write(struct.pack("i" * len(shape), *shape[::-1])) - fout.write(sname) - fout.seek((fout.tell() + 31) & -32) - - -if __name__ == '__main__': - if len(sys.argv) < 2: - logger.info(f"Usage: python {sys.argv[0]} <path> [arch]") - logger.info("Path must contain HuggingFace PEFT LoRA files 'adapter_config.json' and 'adapter_model.bin'") - logger.info(f"Arch must be one of {list(gguf.MODEL_ARCH_NAMES.values())} (default: llama)") - sys.exit(1) - - input_json = os.path.join(sys.argv[1], "adapter_config.json") - input_model = os.path.join(sys.argv[1], "adapter_model.bin") - output_path = os.path.join(sys.argv[1], "ggml-adapter-model.bin") - - if os.path.exists(input_model): - model = torch.load(input_model, map_location="cpu") - else: - input_model = os.path.join(sys.argv[1], "adapter_model.safetensors") - # lazy import load_file only if lora is in safetensors format. - from safetensors.torch import load_file - model = load_file(input_model, device="cpu") - - arch_name = sys.argv[2] if len(sys.argv) == 3 else "llama" - - if arch_name not in gguf.MODEL_ARCH_NAMES.values(): - logger.error(f"Error: unsupported architecture {arch_name}") - sys.exit(1) - - arch = list(gguf.MODEL_ARCH_NAMES.keys())[list(gguf.MODEL_ARCH_NAMES.values()).index(arch_name)] - name_map = gguf.TensorNameMap(arch, 200) # 200 layers ought to be enough for anyone - - with open(input_json, "r") as f: - params = json.load(f) - - if params["peft_type"] != "LORA": - logger.error(f"Error: unsupported adapter type {params['peft_type']}, expected LORA") - sys.exit(1) - - if params["fan_in_fan_out"] is True: - logger.error("Error: param fan_in_fan_out is not supported") - sys.exit(1) - - if params["bias"] is not None and params["bias"] != "none": - logger.error("Error: param bias is not supported") - sys.exit(1) - - # TODO: these seem to be layers that have been trained but without lora. - # doesn't seem widely used but eventually should be supported - if params["modules_to_save"] is not None and len(params["modules_to_save"]) > 0: - logger.error("Error: param modules_to_save is not supported") - sys.exit(1) - - with open(output_path, "wb") as fout: - fout.truncate() - - write_file_header(fout, params) - for k, v in model.items(): - orig_k = k - if k.endswith(".default.weight"): - k = k.replace(".default.weight", ".weight") - if k in ["llama_proj.weight", "llama_proj.bias"]: - continue - if k.endswith("lora_A.weight"): - if v.dtype != torch.float16 and v.dtype != torch.float32: - v = v.float() - v = v.T - else: - v = v.float() - - t = v.detach().numpy() - - prefix = "base_model.model." - if k.startswith(prefix): - k = k[len(prefix) :] - - lora_suffixes = (".lora_A.weight", ".lora_B.weight") - if k.endswith(lora_suffixes): - suffix = k[-len(lora_suffixes[0]):] - k = k[: -len(lora_suffixes[0])] - else: - logger.error(f"Error: unrecognized tensor name {orig_k}") - sys.exit(1) - - tname = name_map.get_name(k) - if tname is None: - logger.error(f"Error: could not map tensor name {orig_k}") - logger.error(" Note: the arch parameter must be specified if the model is not llama") - sys.exit(1) - - if suffix == ".lora_A.weight": - tname += ".weight.loraA" - elif suffix == ".lora_B.weight": - tname += ".weight.loraB" - else: - assert False - - logger.info(f"{k} => {tname} {t.shape} {t.dtype} {t.nbytes/1024/1024:.2f}MB") - write_tensor_header(fout, tname, t.shape, t.dtype) - t.tofile(fout) - - logger.info(f"Converted {input_json} and {input_model} to {output_path}") diff --git a/requirements.txt b/requirements.txt index fc1e28278b695..e7d14e16ac73c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -9,5 +9,4 @@ -r ./requirements/requirements-convert-hf-to-gguf.txt -r ./requirements/requirements-convert-hf-to-gguf-update.txt -r ./requirements/requirements-convert-llama-ggml-to-gguf.txt --r ./requirements/requirements-convert-lora-to-ggml.txt -r ./requirements/requirements-convert-persimmon-to-gguf.txt diff --git a/requirements/requirements-convert-lora-to-ggml.txt b/requirements/requirements-convert-lora-to-ggml.txt deleted file mode 100644 index 6ac4026107fbe..0000000000000 --- a/requirements/requirements-convert-lora-to-ggml.txt +++ /dev/null @@ -1,2 +0,0 @@ --r ./requirements-convert.txt -torch~=2.1.1 From 6f1b63606fc68a09d62d1d74dbd156c35219026d Mon Sep 17 00:00:00 2001 From: Georgi Gerganov <ggerganov@gmail.com> Date: Sun, 12 May 2024 18:30:23 +0300 Subject: [PATCH 55/64] cmake : fix version cmp (#7227) --- CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 362ab3673c77e..1c3b5c8e423cc 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -296,7 +296,7 @@ if (LLAMA_BLAS) if (LLAMA_STATIC) set(BLA_STATIC ON) endif() - if ($(CMAKE_VERSION) VERSION_GREATER_EQUAL 3.22) + if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.22) set(BLA_SIZEOF_INTEGER 8) endif() From dc685be46622a8fabfd57cfa804237c8f15679b8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= <johannesg@5d6.de> Date: Sun, 12 May 2024 19:40:45 +0200 Subject: [PATCH 56/64] CUDA: add FP32 FlashAttention vector kernel (#7188) * CUDA: add FP32 FlashAttention vector kernel * fixup! CUDA: add FP32 FlashAttention vector kernel * fixup! fixup! CUDA: add FP32 FlashAttention vector kernel * fixup! fixup! fixup! CUDA: add FP32 FlashAttention vector kernel --- ggml-cuda.cu | 11 +- ggml-cuda/common.cuh | 4 + ggml-cuda/fattn-common.cuh | 47 ++++ ggml-cuda/fattn-vec-f16.cu | 430 +++++++++++++++++++++++++++++++++ ggml-cuda/fattn-vec-f16.cuh | 5 + ggml-cuda/fattn-vec-f32.cu | 384 +++++++++++++++++++++++++++++ ggml-cuda/fattn-vec-f32.cuh | 3 + ggml-cuda/fattn.cu | 468 ++---------------------------------- tests/test-backend-ops.cpp | 5 +- 9 files changed, 899 insertions(+), 458 deletions(-) create mode 100644 ggml-cuda/fattn-common.cuh create mode 100644 ggml-cuda/fattn-vec-f16.cu create mode 100644 ggml-cuda/fattn-vec-f16.cuh create mode 100644 ggml-cuda/fattn-vec-f32.cu create mode 100644 ggml-cuda/fattn-vec-f32.cuh diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 5b6c909192485..75a2ad480877d 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -2713,6 +2713,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t } GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, const ggml_tensor * op) { + ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *) backend->context; switch (op->op) { case GGML_OP_UNARY: switch (ggml_get_unary_op(op)) { @@ -2840,8 +2841,16 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons case GGML_OP_ARANGE: case GGML_OP_TIMESTEP_EMBEDDING: case GGML_OP_LEAKY_RELU: - case GGML_OP_FLASH_ATTN_EXT: return true; + case GGML_OP_FLASH_ATTN_EXT: +#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) + return op->src[0]->ne[0] == 64 || op->src[0]->ne[0] == 128; +#else + if (op->src[0]->ne[0] == 64 || op->src[0]->ne[0] == 128) { + return true; + } + return ggml_cuda_info().devices[cuda_ctx->device].cc >= CC_VOLTA; +#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) default: return false; } diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh index 44e67e040e16a..b6f0bc36a4f8a 100644 --- a/ggml-cuda/common.cuh +++ b/ggml-cuda/common.cuh @@ -321,6 +321,10 @@ static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) { #define FP16_MMA_AVAILABLE !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= CC_VOLTA +static bool fast_fp16_available(const int cc) { + return cc >= CC_PASCAL && cc != 610; +} + static bool fp16_mma_available(const int cc) { return cc < CC_OFFSET_AMD && cc >= CC_VOLTA; } diff --git a/ggml-cuda/fattn-common.cuh b/ggml-cuda/fattn-common.cuh new file mode 100644 index 0000000000000..33f640691ad7a --- /dev/null +++ b/ggml-cuda/fattn-common.cuh @@ -0,0 +1,47 @@ +#define FATTN_KQ_STRIDE 256 +#define HALF_MAX_HALF __float2half(65504.0f/2) // Use neg. of this instead of -INFINITY to initialize KQ max vals to avoid NaN upon subtraction. +#define SOFTMAX_FTZ_THRESHOLD -20.0f // Softmax exp. of values smaller than this are flushed to zero to avoid NaNs. + +template<int D, int parallel_blocks> // D == head size +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +__launch_bounds__(D, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +static __global__ void flash_attn_combine_results( + const float * __restrict__ VKQ_parts, + const float2 * __restrict__ VKQ_meta, + float * __restrict__ dst) { + VKQ_parts += parallel_blocks*D * gridDim.y*blockIdx.x; + VKQ_meta += parallel_blocks * gridDim.y*blockIdx.x; + dst += D * gridDim.y*blockIdx.x; + + const int tid = threadIdx.x; + __builtin_assume(tid < D); + + __shared__ float2 meta[parallel_blocks]; + if (tid < 2*parallel_blocks) { + ((float *) meta)[threadIdx.x] = ((const float *)VKQ_meta) [blockIdx.y*(2*parallel_blocks) + tid]; + } + + __syncthreads(); + + float kqmax = meta[0].x; +#pragma unroll + for (int l = 1; l < parallel_blocks; ++l) { + kqmax = max(kqmax, meta[l].x); + } + + float VKQ_numerator = 0.0f; + float VKQ_denominator = 0.0f; +#pragma unroll + for (int l = 0; l < parallel_blocks; ++l) { + const float diff = meta[l].x - kqmax; + const float KQ_max_scale = expf(diff); + const uint32_t ftz_mask = 0xFFFFFFFF * (diff > SOFTMAX_FTZ_THRESHOLD); + *((uint32_t *) &KQ_max_scale) &= ftz_mask; + + VKQ_numerator += KQ_max_scale * VKQ_parts[l*gridDim.y*D + blockIdx.y*D + tid]; + VKQ_denominator += KQ_max_scale * meta[l].y; + } + + dst[blockIdx.y*D + tid] = VKQ_numerator / VKQ_denominator; +} diff --git a/ggml-cuda/fattn-vec-f16.cu b/ggml-cuda/fattn-vec-f16.cu new file mode 100644 index 0000000000000..cbf5f7835f876 --- /dev/null +++ b/ggml-cuda/fattn-vec-f16.cu @@ -0,0 +1,430 @@ +#include "common.cuh" +#include "fattn-common.cuh" +#include "fattn-vec-f16.cuh" + +template<int D, int ncols, int parallel_blocks> // D == head size +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +__launch_bounds__(D, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +static __global__ void flash_attn_vec_ext_f16( + const char * __restrict__ Q, + const char * __restrict__ K, + const char * __restrict__ V, + const char * __restrict__ mask, + float * __restrict__ dst, + float2 * __restrict__ dst_meta, + const float scale, + const float max_bias, + const float m0, + const float m1, + const uint32_t n_head_log2, + const int ne00, + const int ne01, + const int ne02, + const int ne03, + const int ne10, + const int ne11, + const int ne12, + const int ne13, + const int ne31, + const int nb31, + const int nb01, + const int nb02, + const int nb03, + const int nb11, + const int nb12, + const int nb13, + const int ne0, + const int ne1, + const int ne2, + const int ne3) { +#if FP16_AVAILABLE + //In this kernel Q, K, V are matrices while i, j, k are matrix indices. + + const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on. + const int ip = blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel. + + const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. + const float2 * Q_f2 = (const float2 *) (Q + nb02* blockIdx.y + nb01*ic0); + const half2 * K_h2 = (const half2 *) (K + nb12*(blockIdx.y / gqa_ratio)); + const half * V_h = (const half *) (V + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape + const half * maskh = (const half *) mask + ne11*ic0; + + const int stride_KV = nb11 / sizeof(half); + const int stride_KV2 = nb11 / sizeof(half2); + + half slopeh = __float2half(1.0f); + + // ALiBi + if (max_bias > 0.0f) { + const int h = blockIdx.y; + + const float base = h < n_head_log2 ? m0 : m1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + slopeh = __float2half(powf(base, exph)); + } + + static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64."); + constexpr int nwarps = D / WARP_SIZE; + const int tid = WARP_SIZE*threadIdx.y + threadIdx.x; + __builtin_assume(tid < D); + + __shared__ half KQ[ncols*D]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + KQ[j*D + tid] = -HALF_MAX_HALF; + } + half2 * KQ2 = (half2 *) KQ; + + half kqmax[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax[j] = -HALF_MAX_HALF; + } + half kqsum[ncols] = {0.0f}; + + __shared__ half kqmax_shared[ncols][WARP_SIZE]; + __shared__ half kqsum_shared[ncols][WARP_SIZE]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + if (threadIdx.y == 0) { + kqmax_shared[j][threadIdx.x] = -HALF_MAX_HALF; + kqsum_shared[j][threadIdx.x] = 0.0f; + } + } + __syncthreads(); + + // Convert Q to half2 and store in registers: + half2 Q_h2[ncols][D/(2*WARP_SIZE)]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) { + const int i = i0 + threadIdx.x; + + const float2 tmp = Q_f2[j*(nb01/sizeof(float2)) + i]; + Q_h2[j][i0/WARP_SIZE] = make_half2(scale, scale) * make_half2(tmp.x, tmp.y); + } + } + + half2 VKQ[ncols] = {{0.0f, 0.0f}}; + + const int k_start = parallel_blocks == 1 ? 0 : ip*D; + for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*D) { + // Calculate KQ tile and keep track of new maximum KQ values: + + // For unknown reasons using a half array of size 1 for kqmax_new causes a performance regression, + // see https://github.com/ggerganov/llama.cpp/pull/7061 . + // Therefore this variable is defined twice but only used once (so that the compiler can optimize out the unused variable). + half kqmax_new = kqmax[0]; + half kqmax_new_arr[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax_new_arr[j] = kqmax[j]; + } + +#pragma unroll + for (int i_KQ_0 = 0; i_KQ_0 < D; i_KQ_0 += nwarps) { + const int i_KQ = i_KQ_0 + threadIdx.y; + + if ((i_KQ_0 + nwarps > D && i_KQ >= D) || (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + i_KQ >= ne11)) { + break; + } + + half2 sum2[ncols] = {{0.0f, 0.0f}}; +#pragma unroll + for (int k_KQ_0 = 0; k_KQ_0 < D/2; k_KQ_0 += WARP_SIZE) { + const int k_KQ = k_KQ_0 + threadIdx.x; + + const half2 K_ik = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum2[j] += K_ik * Q_h2[j][k_KQ_0/WARP_SIZE]; + } + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum2[j] = warp_reduce_sum(sum2[j]); + half sum = __low2half(sum2[j]) + __high2half(sum2[j]); + sum += mask ? slopeh*maskh[j*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f); + + if (ncols == 1) { + kqmax_new = ggml_cuda_hmax(kqmax_new, sum); + } else { + kqmax_new_arr[j] = ggml_cuda_hmax(kqmax_new_arr[j], sum); + } + + if (threadIdx.x == 0) { + KQ[j*D + i_KQ] = sum; + } + } + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + half kqmax_new_j = ncols == 1 ? kqmax_new : kqmax_new_arr[j]; + + kqmax_new_j = warp_reduce_max(kqmax_new_j); + if (threadIdx.x == 0) { + kqmax_shared[j][threadIdx.y] = kqmax_new_j; + } + } + + __syncthreads(); + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + half kqmax_new_j = kqmax_shared[j][threadIdx.x]; + kqmax_new_j = warp_reduce_max(kqmax_new_j); + + const half KQ_max_scale = hexp(kqmax[j] - kqmax_new_j); + kqmax[j] = kqmax_new_j; + + const half val = hexp(KQ[j*D + tid] - kqmax[j]); + kqsum[j] = kqsum[j]*KQ_max_scale + val; + KQ[j*D + tid] = val; + + VKQ[j] *= __half2half2(KQ_max_scale); + } + + __syncthreads(); + +#pragma unroll + for (int k0 = 0; k0 < D; k0 += 2) { + if (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + k0 >= ne11) { + break; + } + + half2 V_k; + reinterpret_cast<half&>(V_k.x) = V_h[(k_VKQ_0 + k0 + 0)*stride_KV + tid]; + reinterpret_cast<half&>(V_k.y) = V_h[(k_VKQ_0 + k0 + 1)*stride_KV + tid]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + VKQ[j] += V_k*KQ2[j*(D/2) + k0/2]; + } + } + + __syncthreads(); + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqsum[j] = warp_reduce_sum(kqsum[j]); + if (threadIdx.x == 0) { + kqsum_shared[j][threadIdx.y] = kqsum[j]; + } + } + + __syncthreads(); + +#pragma unroll + for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) { + kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x]; + kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]); + + half dst_val = (__low2half(VKQ[j_VKQ]) + __high2half(VKQ[j_VKQ])); + if (parallel_blocks == 1) { + dst_val /= kqsum[j_VKQ]; + } + const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip; + dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val; + } + + if (parallel_blocks != 1 && tid != 0) { +#pragma unroll + for (int j = 0; j < ncols; ++j) { + dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]); + } + } +#else + NO_DEVICE_CODE; +#endif // FP16_AVAILABLE +} + +template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f16( + const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask, + ggml_cuda_pool & pool, cudaStream_t main_stream +) { + ggml_cuda_pool_alloc<float> dst_tmp(pool); + ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool); + + if (parallel_blocks > 1) { + dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV)); + dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV)); + } + + constexpr int nwarps = (D + WARP_SIZE - 1) / WARP_SIZE; + const dim3 block_dim(WARP_SIZE, nwarps, 1); + const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]); + const int shmem = 0; + + float scale = 1.0f; + float max_bias = 0.0f; + + memcpy(&scale, (float *) KQV->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float)); + + const uint32_t n_head = Q->ne[2]; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); + + flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks> + <<<blocks_num, block_dim, shmem, main_stream>>> ( + (const char *) Q->data, + (const char *) K->data, + (const char *) V->data, + mask ? ((const char *) mask->data) : nullptr, + parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr, + scale, max_bias, m0, m1, n_head_log2, + Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], + K->ne[0], K->ne[1], K->ne[2], K->ne[3], + mask ? mask->ne[1] : 0, mask ? mask->nb[1] : 0, + Q->nb[1], Q->nb[2], Q->nb[3], + K->nb[1], K->nb[2], K->nb[3], + KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3] + ); + CUDA_CHECK(cudaGetLastError()); + + if (parallel_blocks == 1) { + return; + } + + const dim3 block_dim_combine(D, 1, 1); + const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z); + const int shmem_combine = 0; + + flash_attn_combine_results<D, parallel_blocks> + <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>> + (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data); + CUDA_CHECK(cudaGetLastError()); +} + +void ggml_cuda_flash_attn_ext_vec_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * Q = dst->src[0]; + const ggml_tensor * K = dst->src[1]; + const ggml_tensor * V = dst->src[2]; + + const ggml_tensor * mask = dst->src[3]; + + ggml_tensor * KQV = dst; + + const int32_t precision = KQV->op_params[2]; + GGML_ASSERT(precision == GGML_PREC_DEFAULT); + + constexpr int cols_per_block = 1; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 256: + launch_fattn_vec_f16<256, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } +} + +void ggml_cuda_flash_attn_ext_vec_f16_no_mma(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * Q = dst->src[0]; + const ggml_tensor * K = dst->src[1]; + const ggml_tensor * V = dst->src[2]; + + const ggml_tensor * mask = dst->src[3]; + + ggml_tensor * KQV = dst; + + const int32_t precision = KQV->op_params[2]; + GGML_ASSERT(precision == GGML_PREC_DEFAULT); + GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128."); + + if (Q->ne[1] == 1) { + constexpr int cols_per_block = 1; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] == 2) { + constexpr int cols_per_block = 2; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 4) { + constexpr int cols_per_block = 4; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 8) { + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 1; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } +} diff --git a/ggml-cuda/fattn-vec-f16.cuh b/ggml-cuda/fattn-vec-f16.cuh new file mode 100644 index 0000000000000..c7023610ab2d4 --- /dev/null +++ b/ggml-cuda/fattn-vec-f16.cuh @@ -0,0 +1,5 @@ +#include "common.cuh" + +void ggml_cuda_flash_attn_ext_vec_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst); + +void ggml_cuda_flash_attn_ext_vec_f16_no_mma(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml-cuda/fattn-vec-f32.cu b/ggml-cuda/fattn-vec-f32.cu new file mode 100644 index 0000000000000..40c336ce33252 --- /dev/null +++ b/ggml-cuda/fattn-vec-f32.cu @@ -0,0 +1,384 @@ +#include "common.cuh" +#include "fattn-common.cuh" +#include "fattn-vec-f32.cuh" + +template<int D, int ncols, int parallel_blocks> // D == head size +#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +__launch_bounds__(D, 1) +#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) +static __global__ void flash_attn_vec_ext_f32( + const char * __restrict__ Q, + const char * __restrict__ K, + const char * __restrict__ V, + const char * __restrict__ mask, + float * __restrict__ dst, + float2 * __restrict__ dst_meta, + const float scale, + const float max_bias, + const float m0, + const float m1, + const uint32_t n_head_log2, + const int ne00, + const int ne01, + const int ne02, + const int ne03, + const int ne10, + const int ne11, + const int ne12, + const int ne13, + const int ne31, + const int nb31, + const int nb01, + const int nb02, + const int nb03, + const int nb11, + const int nb12, + const int nb13, + const int ne0, + const int ne1, + const int ne2, + const int ne3) { + //In this kernel Q, K, V are matrices while i, j, k are matrix indices. + + const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on. + const int ip = blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel. + + const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. + const float2 * Q_f2 = (const float2 *) (Q + nb02* blockIdx.y + nb01*ic0); + const half2 * K_h2 = (const half2 *) (K + nb12*(blockIdx.y / gqa_ratio)); + const half * V_h = (const half *) (V + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape + const half * maskh = (const half *) mask + ne11*ic0; + + const int stride_KV = nb11 / sizeof(half); + const int stride_KV2 = nb11 / sizeof(half2); + + float slope = 1.0f; + + // ALiBi + if (max_bias > 0.0f) { + const int h = blockIdx.y; + + const float base = h < n_head_log2 ? m0 : m1; + const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; + + slope = powf(base, exph); + } + + static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64."); + constexpr int nwarps = D / WARP_SIZE; + const int tid = WARP_SIZE*threadIdx.y + threadIdx.x; + __builtin_assume(tid < D); + + __shared__ float KQ[ncols*D]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + KQ[j*D + tid] = -FLT_MAX/2.0f; + } + + float kqmax[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax[j] = -FLT_MAX/2.0f; + } + float kqsum[ncols] = {0.0f}; + + __shared__ float kqmax_shared[ncols][WARP_SIZE]; + __shared__ float kqsum_shared[ncols][WARP_SIZE]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + if (threadIdx.y == 0) { + kqmax_shared[j][threadIdx.x] = -FLT_MAX/2.0f; + kqsum_shared[j][threadIdx.x] = 0.0f; + } + } + __syncthreads(); + + // Convert Q to half2 and store in registers: + float2 Q_h2[ncols][D/(2*WARP_SIZE)]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { +#pragma unroll + for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) { + const int i = i0 + threadIdx.x; + + Q_h2[j][i0/WARP_SIZE] = Q_f2[j*(nb01/sizeof(float2)) + i]; + Q_h2[j][i0/WARP_SIZE].x *= scale; + Q_h2[j][i0/WARP_SIZE].y *= scale; + } + } + + float VKQ[ncols] = {0.0f}; + + const int k_start = parallel_blocks == 1 ? 0 : ip*D; + for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*D) { + // Calculate KQ tile and keep track of new maximum KQ values: + + float kqmax_new_arr[ncols]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqmax_new_arr[j] = kqmax[j]; + } + +#pragma unroll + for (int i_KQ_0 = 0; i_KQ_0 < D; i_KQ_0 += nwarps) { + const int i_KQ = i_KQ_0 + threadIdx.y; + + if ((i_KQ_0 + nwarps > D && i_KQ >= D) || (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + i_KQ >= ne11)) { + break; + } + + float sum[ncols] = {0.0f}; +#pragma unroll + for (int k_KQ_0 = 0; k_KQ_0 < D/2; k_KQ_0 += WARP_SIZE) { + const int k_KQ = k_KQ_0 + threadIdx.x; + + const half2 K_ik = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ]; +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum[j] += __low2float(K_ik) * Q_h2[j][k_KQ_0/WARP_SIZE].x; + sum[j] += __high2float(K_ik) * Q_h2[j][k_KQ_0/WARP_SIZE].y; + } + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + sum[j] = warp_reduce_sum(sum[j]); + sum[j] += mask ? slope*__half2float(maskh[j*ne11 + k_VKQ_0 + i_KQ]) : 0.0f; + + kqmax_new_arr[j] = fmaxf(kqmax_new_arr[j], sum[j]); + + if (threadIdx.x == 0) { + KQ[j*D + i_KQ] = sum[j]; + } + } + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + float kqmax_new_j = kqmax_new_arr[j]; + + kqmax_new_j = warp_reduce_max(kqmax_new_j); + if (threadIdx.x == 0) { + kqmax_shared[j][threadIdx.y] = kqmax_new_j; + } + } + + __syncthreads(); + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + float kqmax_new_j = kqmax_shared[j][threadIdx.x]; + kqmax_new_j = warp_reduce_max(kqmax_new_j); + + const float KQ_max_scale = expf(kqmax[j] - kqmax_new_j); + kqmax[j] = kqmax_new_j; + + const float val = expf(KQ[j*D + tid] - kqmax[j]); + kqsum[j] = kqsum[j]*KQ_max_scale + val; + KQ[j*D + tid] = val; + + VKQ[j] *= KQ_max_scale; + } + + __syncthreads(); + +#pragma unroll + for (int k = 0; k < D; ++k) { + if (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + k >= ne11) { + break; + } + + const float V_ki = __half2float(V_h[(k_VKQ_0 + k)*stride_KV + tid]); +#pragma unroll + for (int j = 0; j < ncols; ++j) { + VKQ[j] += V_ki*KQ[j*D + k]; + } + } + + __syncthreads(); + } + +#pragma unroll + for (int j = 0; j < ncols; ++j) { + kqsum[j] = warp_reduce_sum(kqsum[j]); + if (threadIdx.x == 0) { + kqsum_shared[j][threadIdx.y] = kqsum[j]; + } + } + + __syncthreads(); + +#pragma unroll + for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) { + kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x]; + kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]); + + float dst_val = VKQ[j_VKQ]; + if (parallel_blocks == 1) { + dst_val /= kqsum[j_VKQ]; + } + const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip; + dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val; + } + + if (parallel_blocks != 1 && tid != 0) { +#pragma unroll + for (int j = 0; j < ncols; ++j) { + dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]); + } + } +} + +template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f32( + const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask, + ggml_cuda_pool & pool, cudaStream_t main_stream +) { + ggml_cuda_pool_alloc<float> dst_tmp(pool); + ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool); + + if (parallel_blocks > 1) { + dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV)); + dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV)); + } + + constexpr int nwarps = (D + WARP_SIZE - 1) / WARP_SIZE; + const dim3 block_dim(WARP_SIZE, nwarps, 1); + const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]); + const int shmem = 0; + + float scale = 1.0f; + float max_bias = 0.0f; + + memcpy(&scale, (float *) KQV->op_params + 0, sizeof(float)); + memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float)); + + const uint32_t n_head = Q->ne[2]; + const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); + + const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); + const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); + + flash_attn_vec_ext_f32<D, cols_per_block, parallel_blocks> + <<<blocks_num, block_dim, shmem, main_stream>>> ( + (const char *) Q->data, + (const char *) K->data, + (const char *) V->data, + mask ? ((const char *) mask->data) : nullptr, + parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr, + scale, max_bias, m0, m1, n_head_log2, + Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], + K->ne[0], K->ne[1], K->ne[2], K->ne[3], + mask ? mask->ne[1] : 0, mask ? mask->nb[1] : 0, + Q->nb[1], Q->nb[2], Q->nb[3], + K->nb[1], K->nb[2], K->nb[3], + KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3] + ); + CUDA_CHECK(cudaGetLastError()); + + if (parallel_blocks == 1) { + return; + } + + const dim3 block_dim_combine(D, 1, 1); + const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z); + const int shmem_combine = 0; + + flash_attn_combine_results<D, parallel_blocks> + <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>> + (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data); + CUDA_CHECK(cudaGetLastError()); +} + +void ggml_cuda_flash_attn_ext_vec_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { + const ggml_tensor * Q = dst->src[0]; + const ggml_tensor * K = dst->src[1]; + const ggml_tensor * V = dst->src[2]; + + const ggml_tensor * mask = dst->src[3]; + + ggml_tensor * KQV = dst; + + GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128."); + + if (Q->ne[1] == 1) { + constexpr int cols_per_block = 1; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] == 2) { + constexpr int cols_per_block = 2; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 4) { + constexpr int cols_per_block = 4; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + if (Q->ne[1] <= 8) { + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 4; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } + return; + } + + constexpr int cols_per_block = 8; + constexpr int parallel_blocks = 1; + switch (Q->ne[0]) { + case 64: + launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + case 128: + launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); + break; + default: + GGML_ASSERT(false); + break; + } +} diff --git a/ggml-cuda/fattn-vec-f32.cuh b/ggml-cuda/fattn-vec-f32.cuh new file mode 100644 index 0000000000000..614d54ae39253 --- /dev/null +++ b/ggml-cuda/fattn-vec-f32.cuh @@ -0,0 +1,3 @@ +#include "common.cuh" + +void ggml_cuda_flash_attn_ext_vec_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst); diff --git a/ggml-cuda/fattn.cu b/ggml-cuda/fattn.cu index ac5d6672b30d3..419f8e752a778 100644 --- a/ggml-cuda/fattn.cu +++ b/ggml-cuda/fattn.cu @@ -1,4 +1,7 @@ #include "common.cuh" +#include "fattn-common.cuh" +#include "fattn-vec-f16.cuh" +#include "fattn-vec-f32.cuh" #include "fattn.cuh" #include <cstdint> @@ -7,251 +10,6 @@ #include <mma.h> #endif -#define FATTN_KQ_STRIDE 256 -#define HALF_MAX_HALF __float2half(65504.0f/2) // Use neg. of this instead of -INFINITY to initialize KQ max vals to avoid NaN upon subtraction. -#define SOFTMAX_FTZ_THRESHOLD -20.0f // Softmax exp. of values smaller than this are flushed to zero to avoid NaNs. - -template<int D, int ncols, int parallel_blocks> // D == head size -#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) -__launch_bounds__(D, 1) -#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) -static __global__ void flash_attn_vec_ext_f16( - const char * __restrict__ Q, - const char * __restrict__ K, - const char * __restrict__ V, - const char * __restrict__ mask, - float * __restrict__ dst, - float2 * __restrict__ dst_meta, - const float scale, - const float max_bias, - const float m0, - const float m1, - const uint32_t n_head_log2, - const int ne00, - const int ne01, - const int ne02, - const int ne03, - const int ne10, - const int ne11, - const int ne12, - const int ne13, - const int ne31, - const int nb31, - const int nb01, - const int nb02, - const int nb03, - const int nb11, - const int nb12, - const int nb13, - const int ne0, - const int ne1, - const int ne2, - const int ne3) { -#if FP16_AVAILABLE - //In this kernel Q, K, V are matrices while i, j, k are matrix indices. - - const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on. - const int ip = blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel. - - const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix. - const float2 * Q_f2 = (const float2 *) (Q + nb02* blockIdx.y + nb01*ic0); - const half2 * K_h2 = (const half2 *) (K + nb12*(blockIdx.y / gqa_ratio)); - const half * V_h = (const half *) (V + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape - const half * maskh = (const half *) mask + ne11*ic0; - - const int stride_KV = nb11 / sizeof(half); - const int stride_KV2 = nb11 / sizeof(half2); - - half slopeh = __float2half(1.0f); - - // ALiBi - if (max_bias > 0.0f) { - const int h = blockIdx.y; - - const float base = h < n_head_log2 ? m0 : m1; - const int exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1; - - slopeh = __float2half(powf(base, exph)); - } - - static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64."); - constexpr int nwarps = D / WARP_SIZE; - const int tid = WARP_SIZE*threadIdx.y + threadIdx.x; - __builtin_assume(tid < D); - - __shared__ half KQ[ncols*D]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - KQ[j*D + tid] = -HALF_MAX_HALF; - } - half2 * KQ2 = (half2 *) KQ; - - half kqmax[ncols]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - kqmax[j] = -HALF_MAX_HALF; - } - half kqsum[ncols] = {0.0f}; - - __shared__ half kqmax_shared[ncols][WARP_SIZE]; - __shared__ half kqsum_shared[ncols][WARP_SIZE]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - if (threadIdx.y == 0) { - kqmax_shared[j][threadIdx.x] = -HALF_MAX_HALF; - kqsum_shared[j][threadIdx.x] = 0.0f; - } - } - __syncthreads(); - - // Convert Q to half2 and store in registers: - half2 Q_h2[ncols][D/(2*WARP_SIZE)]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { -#pragma unroll - for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) { - const int i = i0 + threadIdx.x; - - const float2 tmp = Q_f2[j*(nb01/sizeof(float2)) + i]; - Q_h2[j][i0/WARP_SIZE] = make_half2(scale, scale) * make_half2(tmp.x, tmp.y); - } - } - - half2 VKQ[ncols] = {{0.0f, 0.0f}}; - - const int k_start = parallel_blocks == 1 ? 0 : ip*D; - for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*D) { - // Calculate KQ tile and keep track of new maximum KQ values: - - // For unknown reasons using a half array of size 1 for kqmax_new causes a performance regression, - // see https://github.com/ggerganov/llama.cpp/pull/7061 . - // Therefore this variable is defined twice but only used once (so that the compiler can optimize out the unused variable). - half kqmax_new = kqmax[0]; - half kqmax_new_arr[ncols]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - kqmax_new_arr[j] = kqmax[j]; - } - -#pragma unroll - for (int i_KQ_0 = 0; i_KQ_0 < D; i_KQ_0 += nwarps) { - const int i_KQ = i_KQ_0 + threadIdx.y; - - if ((i_KQ_0 + nwarps > D && i_KQ >= D) || (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + i_KQ >= ne11)) { - break; - } - - half2 sum2[ncols] = {{0.0f, 0.0f}}; -#pragma unroll - for (int k_KQ_0 = 0; k_KQ_0 < D/2; k_KQ_0 += WARP_SIZE) { - const int k_KQ = k_KQ_0 + threadIdx.x; - - const half2 K_ik = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - sum2[j] += K_ik * Q_h2[j][k_KQ_0/WARP_SIZE]; - } - } - -#pragma unroll - for (int j = 0; j < ncols; ++j) { - sum2[j] = warp_reduce_sum(sum2[j]); - half sum = __low2half(sum2[j]) + __high2half(sum2[j]); - sum += mask ? slopeh*maskh[j*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f); - - if (ncols == 1) { - kqmax_new = ggml_cuda_hmax(kqmax_new, sum); - } else { - kqmax_new_arr[j] = ggml_cuda_hmax(kqmax_new_arr[j], sum); - } - - if (threadIdx.x == 0) { - KQ[j*D + i_KQ] = sum; - } - } - } - -#pragma unroll - for (int j = 0; j < ncols; ++j) { - half kqmax_new_j = ncols == 1 ? kqmax_new : kqmax_new_arr[j]; - - kqmax_new_j = warp_reduce_max(kqmax_new_j); - if (threadIdx.x == 0) { - kqmax_shared[j][threadIdx.y] = kqmax_new_j; - } - } - - __syncthreads(); - -#pragma unroll - for (int j = 0; j < ncols; ++j) { - half kqmax_new_j = kqmax_shared[j][threadIdx.x]; - kqmax_new_j = warp_reduce_max(kqmax_new_j); - - const half KQ_max_scale = hexp(kqmax[j] - kqmax_new_j); - kqmax[j] = kqmax_new_j; - - const half val = hexp(KQ[j*D + tid] - kqmax[j]); - kqsum[j] = kqsum[j]*KQ_max_scale + val; - KQ[j*D + tid] = val; - - VKQ[j] *= __half2half2(KQ_max_scale); - } - - __syncthreads(); - -#pragma unroll - for (int k0 = 0; k0 < D; k0 += 2) { - if (FATTN_KQ_STRIDE % D != 0 && k_VKQ_0 + k0 >= ne11) { - break; - } - - half2 V_k; - reinterpret_cast<half&>(V_k.x) = V_h[(k_VKQ_0 + k0 + 0)*stride_KV + tid]; - reinterpret_cast<half&>(V_k.y) = V_h[(k_VKQ_0 + k0 + 1)*stride_KV + tid]; -#pragma unroll - for (int j = 0; j < ncols; ++j) { - VKQ[j] += V_k*KQ2[j*(D/2) + k0/2]; - } - } - - __syncthreads(); - } - -#pragma unroll - for (int j = 0; j < ncols; ++j) { - kqsum[j] = warp_reduce_sum(kqsum[j]); - if (threadIdx.x == 0) { - kqsum_shared[j][threadIdx.y] = kqsum[j]; - } - } - - __syncthreads(); - -#pragma unroll - for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) { - kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x]; - kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]); - - half dst_val = (__low2half(VKQ[j_VKQ]) + __high2half(VKQ[j_VKQ])); - if (parallel_blocks == 1) { - dst_val /= kqsum[j_VKQ]; - } - const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip; - dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val; - } - - if (parallel_blocks != 1 && tid != 0) { -#pragma unroll - for (int j = 0; j < ncols; ++j) { - dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]); - } - } -#else - NO_DEVICE_CODE; -#endif // FP16_AVAILABLE -} - // D == head size, VKQ_stride == num VKQ rows calculated in parallel: template<int D, int ncols, int nwarps, int VKQ_stride, int parallel_blocks, typename KQ_acc_t> #if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) @@ -655,54 +413,6 @@ static __global__ void flash_attn_ext_f16( #endif // FP16_MMA_AVAILABLE } -template<int D, int parallel_blocks> // D == head size -#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) -__launch_bounds__(D, 1) -#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) -static __global__ void flash_attn_combine_results( - const float * __restrict__ VKQ_parts, - const float2 * __restrict__ VKQ_meta, - float * __restrict__ dst) { -#if FP16_AVAILABLE - VKQ_parts += parallel_blocks*D * gridDim.y*blockIdx.x; - VKQ_meta += parallel_blocks * gridDim.y*blockIdx.x; - dst += D * gridDim.y*blockIdx.x; - - const int tid = threadIdx.x; - __builtin_assume(tid < D); - - __shared__ float2 meta[parallel_blocks]; - if (tid < 2*parallel_blocks) { - ((float *) meta)[threadIdx.x] = ((const float *)VKQ_meta) [blockIdx.y*(2*parallel_blocks) + tid]; - } - - __syncthreads(); - - float kqmax = meta[0].x; -#pragma unroll - for (int l = 1; l < parallel_blocks; ++l) { - kqmax = max(kqmax, meta[l].x); - } - - float VKQ_numerator = 0.0f; - float VKQ_denominator = 0.0f; -#pragma unroll - for (int l = 0; l < parallel_blocks; ++l) { - const float diff = meta[l].x - kqmax; - const float KQ_max_scale = expf(diff); - const uint32_t ftz_mask = 0xFFFFFFFF * (diff > SOFTMAX_FTZ_THRESHOLD); - *((uint32_t *) &KQ_max_scale) &= ftz_mask; - - VKQ_numerator += KQ_max_scale * VKQ_parts[l*gridDim.y*D + blockIdx.y*D + tid]; - VKQ_denominator += KQ_max_scale * meta[l].y; - } - - dst[blockIdx.y*D + tid] = VKQ_numerator / VKQ_denominator; -#else - NO_DEVICE_CODE; -#endif // FP16_AVAILABLE -} - constexpr int get_max_power_of_2(int x) { return x % 2 == 0 ? 2*get_max_power_of_2(x/2) : 1; } @@ -727,66 +437,6 @@ static_assert(get_VKQ_stride( 80, 1, 16) == 16, "Test failed."); static_assert(get_VKQ_stride( 80, 2, 16) == 16, "Test failed."); static_assert(get_VKQ_stride( 80, 4, 16) == 16, "Test failed."); -template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f16( - const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask, - ggml_cuda_pool & pool, cudaStream_t main_stream -) { - ggml_cuda_pool_alloc<float> dst_tmp(pool); - ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool); - - if (parallel_blocks > 1) { - dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV)); - dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV)); - } - - constexpr int nwarps = (D + WARP_SIZE - 1) / WARP_SIZE; - const dim3 block_dim(WARP_SIZE, nwarps, 1); - const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]); - const int shmem = 0; - - float scale = 1.0f; - float max_bias = 0.0f; - - memcpy(&scale, (float *) KQV->op_params + 0, sizeof(float)); - memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float)); - - const uint32_t n_head = Q->ne[2]; - const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head)); - - const float m0 = powf(2.0f, -(max_bias ) / n_head_log2); - const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2); - - flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks> - <<<blocks_num, block_dim, shmem, main_stream>>> ( - (const char *) Q->data, - (const char *) K->data, - (const char *) V->data, - mask ? ((const char *) mask->data) : nullptr, - parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr, - scale, max_bias, m0, m1, n_head_log2, - Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3], - K->ne[0], K->ne[1], K->ne[2], K->ne[3], - mask ? mask->ne[1] : 0, mask ? mask->nb[1] : 0, - Q->nb[1], Q->nb[2], Q->nb[3], - K->nb[1], K->nb[2], K->nb[3], - KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3] - ); - CUDA_CHECK(cudaGetLastError()); - - if (parallel_blocks == 1) { - return; - } - - const dim3 block_dim_combine(D, 1, 1); - const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z); - const int shmem_combine = 0; - - flash_attn_combine_results<D, parallel_blocks> - <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>> - (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data); - CUDA_CHECK(cudaGetLastError()); -} - template <int D, int cols_per_block, int nwarps, int parallel_blocks, typename KQ_acc_t> void launch_fattn_f16_impl( const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask, ggml_cuda_pool & pool, cudaStream_t main_stream @@ -891,95 +541,22 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst const int32_t precision = KQV->op_params[2]; - if (!fp16_mma_available(cc)) { - GGML_ASSERT(precision == GGML_PREC_DEFAULT); - GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128."); - - if (Q->ne[1] == 1) { - constexpr int cols_per_block = 1; - constexpr int parallel_blocks = 4; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } - return; - } - - if (Q->ne[1] == 2) { - constexpr int cols_per_block = 2; - constexpr int parallel_blocks = 4; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } - return; - } - - if (Q->ne[1] <= 4) { - constexpr int cols_per_block = 4; - constexpr int parallel_blocks = 4; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } - return; - } - - if (Q->ne[1] <= 8) { - constexpr int cols_per_block = 8; - constexpr int parallel_blocks = 4; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } - return; - } + if (!fast_fp16_available(cc)) { + ggml_cuda_flash_attn_ext_vec_f32(ctx, dst); + return; + } - constexpr int cols_per_block = 8; - constexpr int parallel_blocks = 1; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } + if (!fp16_mma_available(cc)) { + ggml_cuda_flash_attn_ext_vec_f16_no_mma(ctx, dst); return; } if (precision != GGML_PREC_DEFAULT) { + if (Q->ne[1] == 1 && (Q->ne[0] == 64 || Q->ne[0] == 128)) { + ggml_cuda_flash_attn_ext_vec_f32(ctx, dst); + return; + } + if (Q->ne[1] <= 32 || Q->ne[0] > 128) { constexpr int cols_per_block = 16; constexpr int nwarps = 4; @@ -1037,22 +614,7 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst } if (Q->ne[1] == 1 && Q->ne[0] % (2*WARP_SIZE) == 0) { - constexpr int cols_per_block = 1; - constexpr int parallel_blocks = 4; - switch (Q->ne[0]) { - case 64: - launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 128: - launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - case 256: - launch_fattn_vec_f16<256, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream()); - break; - default: - GGML_ASSERT(false); - break; - } + ggml_cuda_flash_attn_ext_vec_f16(ctx, dst); return; } diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 731788b958fca..45a2cb85a4efa 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -2,6 +2,7 @@ #include <ggml-alloc.h> #include <ggml-backend.h> #include <ggml-backend-impl.h> + #include <algorithm> #include <array> #include <cfloat> @@ -2173,11 +2174,7 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op test_cases.emplace_back(new test_timestep_embedding()); test_cases.emplace_back(new test_leaky_relu()); -#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) - for (int hs : { 64, 128, }) { // other head sizes not implemented -#else for (int hs : { 64, 80, 128, 256, }) { -#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__) for (float max_bias : {0.0f, 8.0f}) { for (int nh : { 32, }) { for (int kv : { 512, 1024, }) { From 0d5cef78aeafae4d4e6d56e2d4bcda771af58cc9 Mon Sep 17 00:00:00 2001 From: Neo Zhang <14088817+arthw@users.noreply.github.com> Date: Mon, 13 May 2024 08:02:55 +0800 Subject: [PATCH 57/64] [SYCL] update CI with oneapi 2024.1 (#7235) Co-authored-by: Zhang <jianyu.zhang@intel.com> --- .github/workflows/build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 2d747e688437a..3408b74ac3efc 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -898,7 +898,7 @@ jobs: shell: bash env: - WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/62641e01-1e8d-4ace-91d6-ae03f7f8a71f/w_BaseKit_p_2024.0.0.49563_offline.exe + WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/7dff44ba-e3af-4448-841c-0d616c8da6e7/w_BaseKit_p_2024.1.0.595_offline.exe WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel steps: From cbf75894d256f1861f6409565db599365de3d4b8 Mon Sep 17 00:00:00 2001 From: Neo Zhang <14088817+arthw@users.noreply.github.com> Date: Mon, 13 May 2024 08:04:29 +0800 Subject: [PATCH 58/64] [SYCL] Add oneapi runtime dll files to win release package (#7241) * add oneapi running time dlls to release package * fix path * fix path * fix path * fix path * fix path --------- Co-authored-by: Zhang <jianyu.zhang@intel.com> --- .github/workflows/build.yml | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 3408b74ac3efc..8c338534dc5cc 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -900,7 +900,7 @@ jobs: env: WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/7dff44ba-e3af-4448-841c-0d616c8da6e7/w_BaseKit_p_2024.1.0.595_offline.exe WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel - + ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI" steps: - name: Clone id: checkout @@ -932,6 +932,17 @@ jobs: id: pack_artifacts if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }} run: | + echo "cp oneAPI running time dll files in ${{ env.ONEAPI_ROOT }} to ./build/bin" + cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_sycl_blas.4.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_core.2.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_tbb_thread.2.dll" ./build/bin + + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/pi_win_proxy_loader.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/pi_level_zero.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl7.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin + cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin + echo "cp oneAPI running time dll files to ./build/bin done" 7z a llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip ./build/bin/* - name: Upload artifacts From e586ee42595500c53938e937b6b6ad5353ad76dc Mon Sep 17 00:00:00 2001 From: Benjamin Findley <39356821+Kartoffelsaft@users.noreply.github.com> Date: Sun, 12 May 2024 19:40:08 -0700 Subject: [PATCH 59/64] change default temperature of OAI compat API from 0 to 1 (#7226) * change default temperature of OAI compat API from 0 to 1 * make tests explicitly send temperature to OAI API --- examples/server/tests/features/steps/steps.py | 7 +++++-- examples/server/utils.hpp | 2 +- 2 files changed, 6 insertions(+), 3 deletions(-) diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py index f4b1ac1d71840..577b87af34195 100644 --- a/examples/server/tests/features/steps/steps.py +++ b/examples/server/tests/features/steps/steps.py @@ -887,6 +887,7 @@ async def oai_chat_completions(user_prompt, base_path, async_client, debug=False, + temperature=None, model=None, n_predict=None, enable_streaming=None, @@ -913,7 +914,8 @@ async def oai_chat_completions(user_prompt, "model": model, "max_tokens": n_predict, "stream": enable_streaming, - "seed": seed + "temperature": temperature if temperature is not None else 0.0, + "seed": seed, } if response_format is not None: payload['response_format'] = response_format @@ -978,7 +980,8 @@ async def oai_chat_completions(user_prompt, max_tokens=n_predict, stream=enable_streaming, response_format=payload.get('response_format'), - seed=seed + seed=seed, + temperature=payload['temperature'] ) except openai.error.AuthenticationError as e: if expect_api_error is not None and expect_api_error: diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index d872b63f537f4..d8a2286e4b1df 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -371,7 +371,7 @@ static json oaicompat_completion_params_parse( llama_params["presence_penalty"] = json_value(body, "presence_penalty", 0.0); llama_params["seed"] = json_value(body, "seed", LLAMA_DEFAULT_SEED); llama_params["stream"] = json_value(body, "stream", false); - llama_params["temperature"] = json_value(body, "temperature", 0.0); + llama_params["temperature"] = json_value(body, "temperature", 1.0); llama_params["top_p"] = json_value(body, "top_p", 1.0); // Apply chat template to the list of messages From b1f8af1886e8187db6bb2a9b87cfc1c0f175f629 Mon Sep 17 00:00:00 2001 From: Brian <mofosyne@gmail.com> Date: Mon, 13 May 2024 12:56:47 +1000 Subject: [PATCH 60/64] convert.py: Outfile default name change and additional metadata support (#4858) * convert.py: Outfile default name change and additional metadata support * convert.py: don't stringify Metadata load method output * convert.py: typo fix * convert.py: fix metadata format to sync with LLM_KV_NAMES in llama.cpp --- convert.py | 180 +++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 155 insertions(+), 25 deletions(-) diff --git a/convert.py b/convert.py index 148bfd66ad65b..e2e6423516d15 100755 --- a/convert.py +++ b/convert.py @@ -24,7 +24,7 @@ from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Any, Callable, ClassVar, IO, Iterable, Literal, Protocol, TypeVar, runtime_checkable +from typing import TYPE_CHECKING, Any, Callable, ClassVar, IO, Iterable, Literal, Protocol, TypeVar, runtime_checkable, Optional import numpy as np from sentencepiece import SentencePieceProcessor @@ -344,10 +344,47 @@ def load(model_plus: ModelPlus) -> Params: return params +@dataclass +class Metadata: + name: Optional[str] = None + author: Optional[str] = None + version: Optional[str] = None + url: Optional[str] = None + description: Optional[str] = None + licence: Optional[str] = None + source_url: Optional[str] = None + source_hf_repo: Optional[str] = None + + @staticmethod + def load(metadata_path: Path) -> Metadata: + if metadata_path is None or not metadata_path.exists(): + return Metadata() + + with open(metadata_path, 'r') as file: + data = json.load(file) + + # Create a new Metadata instance + metadata = Metadata() + + # Assigning values to Metadata attributes if they exist in the JSON file + # This is based on LLM_KV_NAMES mapping in llama.cpp + metadata.name = data.get("general.name") + metadata.author = data.get("general.author") + metadata.version = data.get("general.version") + metadata.url = data.get("general.url") + metadata.description = data.get("general.description") + metadata.license = data.get("general.license") + metadata.source_url = data.get("general.source.url") + metadata.source_hf_repo = data.get("general.source.huggingface.repository") + + return metadata + + # # vocab # + @runtime_checkable class BaseVocab(Protocol): tokenizer_model: ClassVar[str] @@ -1066,21 +1103,42 @@ class OutputFile: def __init__(self, fname_out: Path, endianess:gguf.GGUFEndian = gguf.GGUFEndian.LITTLE): self.gguf = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[ARCH], endianess=endianess) - def add_meta_arch(self, params: Params) -> None: + def add_meta_model(self, params: Params, metadata: Metadata) -> None: + # Metadata About The Model And Its Provenence name = "LLaMA" - - # TODO: better logic to determine model name - if params.n_ctx == 4096: - name = "LLaMA v2" + if metadata is not None and metadata.name is not None: + name = metadata.name elif params.path_model is not None: - name = str(params.path_model.parent).split('/')[-1] - - self.gguf.add_name (name) - self.gguf.add_vocab_size (params.n_vocab) - self.gguf.add_context_length (params.n_ctx) - self.gguf.add_embedding_length (params.n_embd) - self.gguf.add_block_count (params.n_layer) - self.gguf.add_feed_forward_length (params.n_ff) + name = str(params.path_model.parent).split("/")[-1] + elif params.n_ctx == 4096: + # Heuristic detection of LLaMA v2 model + name = "LLaMA v2" + + self.gguf.add_name(name) + + if metadata is not None: + if metadata.author is not None: + self.gguf.add_author(metadata.author) + if metadata.version is not None: + self.gguf.add_version(metadata.version) + if metadata.url is not None: + self.gguf.add_url(metadata.url) + if metadata.description is not None: + self.gguf.add_description(metadata.description) + if metadata.licence is not None: + self.gguf.add_licence(metadata.licence) + if metadata.source_url is not None: + self.gguf.add_source_url(metadata.source_url) + if metadata.source_hf_repo is not None: + self.gguf.add_source_hf_repo(metadata.source_hf_repo) + + def add_meta_arch(self, params: Params) -> None: + # Metadata About The Neural Architecture Itself + self.gguf.add_vocab_size(params.n_vocab) + self.gguf.add_context_length(params.n_ctx) + self.gguf.add_embedding_length(params.n_embd) + self.gguf.add_block_count(params.n_layer) + self.gguf.add_feed_forward_length(params.n_ff) self.gguf.add_rope_dimension_count(params.n_embd // params.n_head) self.gguf.add_head_count (params.n_head) self.gguf.add_head_count_kv (params.n_head_kv) @@ -1183,13 +1241,14 @@ def close(self) -> None: @staticmethod def write_vocab_only( fname_out: Path, params: Params, vocab: Vocab, svocab: gguf.SpecialVocab, - endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, + endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, metadata: Metadata = None, ) -> None: check_vocab_size(params, vocab, pad_vocab=pad_vocab) of = OutputFile(fname_out, endianess=endianess) # meta data + of.add_meta_model(params, metadata) of.add_meta_arch(params) of.add_meta_vocab(vocab) of.add_meta_special_vocab(svocab) @@ -1216,12 +1275,14 @@ def write_all( fname_out: Path, ftype: GGMLFileType, params: Params, model: LazyModel, vocab: BaseVocab, svocab: gguf.SpecialVocab, concurrency: int = DEFAULT_CONCURRENCY, endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, + metadata: Metadata = None, ) -> None: check_vocab_size(params, vocab, pad_vocab=pad_vocab) of = OutputFile(fname_out, endianess=endianess) # meta data + of.add_meta_model(params, metadata) of.add_meta_arch(params) if isinstance(vocab, Vocab): of.add_meta_vocab(vocab) @@ -1257,6 +1318,37 @@ def pick_output_type(model: LazyModel, output_type_str: str | None) -> GGMLFileT raise ValueError(f"Unexpected combination of types: {name_to_type}") +def model_parameter_count(model: LazyModel) -> int: + total_model_parameters = 0 + for i, (name, lazy_tensor) in enumerate(model.items()): + sum_weights_in_tensor = 1 + for dim in lazy_tensor.shape: + sum_weights_in_tensor *= dim + total_model_parameters += sum_weights_in_tensor + return total_model_parameters + + +def model_parameter_count_rounded_notation(model_params_count: int) -> str: + if model_params_count > 1e12 : + # Trillions Of Parameters + scaled_model_params = model_params_count * 1e-12 + scale_suffix = "T" + elif model_params_count > 1e9 : + # Billions Of Parameters + scaled_model_params = model_params_count * 1e-9 + scale_suffix = "B" + elif model_params_count > 1e6 : + # Millions Of Parameters + scaled_model_params = model_params_count * 1e-6 + scale_suffix = "M" + else: + # Thousands Of Parameters + scaled_model_params = model_params_count * 1e-3 + scale_suffix = "K" + + return f"{round(scaled_model_params)}{scale_suffix}" + + def convert_to_output_type(model: LazyModel, output_type: GGMLFileType) -> LazyModel: return {name: tensor.astype(output_type.type_for_tensor(name, tensor)) for (name, tensor) in model.items()} @@ -1436,13 +1528,35 @@ def load_vocab(self, vocab_types: list[str] | None, model_parent_path: Path) -> return vocab, special_vocab -def default_outfile(model_paths: list[Path], file_type: GGMLFileType) -> Path: - namestr = { - GGMLFileType.AllF32: "f32", - GGMLFileType.MostlyF16: "f16", - GGMLFileType.MostlyQ8_0:"q8_0", +def default_convention_outfile(file_type: GGMLFileType, params: Params, model_params_count: int, metadata: Metadata) -> str: + quantization = { + GGMLFileType.AllF32: "F32", + GGMLFileType.MostlyF16: "F16", + GGMLFileType.MostlyQ8_0: "Q8_0", }[file_type] - ret = model_paths[0].parent / f"ggml-model-{namestr}.gguf" + + parameters = model_parameter_count_rounded_notation(model_params_count) + + expert_count = "" + if params.n_experts is not None: + expert_count = f"{params.n_experts}x" + + version = "" + if metadata is not None and metadata.version is not None: + version = f"-{metadata.version}" + + name = "ggml-model" + if metadata is not None and metadata.name is not None: + name = metadata.name + elif params.path_model is not None: + name = params.path_model.name + + return f"{name}{version}-{expert_count}{parameters}-{quantization}" + + +def default_outfile(model_paths: list[Path], file_type: GGMLFileType, params: Params, model_params_count: int, metadata: Metadata) -> Path: + default_filename = default_convention_outfile(file_type, params, model_params_count, metadata) + ret = model_paths[0].parent / f"{default_filename}.gguf" if ret in model_paths: logger.error( f"Error: Default output path ({ret}) would overwrite the input. " @@ -1480,17 +1594,30 @@ def main(args_in: list[str] | None = None) -> None: parser.add_argument("--pad-vocab", action="store_true", help="add pad tokens when model vocab expects more than tokenizer metadata provides") parser.add_argument("--skip-unknown", action="store_true", help="skip unknown tensor names instead of failing") parser.add_argument("--verbose", action="store_true", help="increase output verbosity") + parser.add_argument("--metadata", type=Path, help="Specify the path for a metadata file") + parser.add_argument("--get-outfile", action="store_true", help="get calculated default outfile name") args = parser.parse_args(args_in) if args.verbose: logging.basicConfig(level=logging.DEBUG) - elif args.dump_single or args.dump: + elif args.dump_single or args.dump or args.get_outfile: # Avoid printing anything besides the dump output logging.basicConfig(level=logging.WARNING) else: logging.basicConfig(level=logging.INFO) + metadata = Metadata.load(args.metadata) + + if args.get_outfile: + model_plus = load_some_model(args.model) + params = Params.load(model_plus) + model = convert_model_names(model_plus.model, params, args.skip_unknown) + model_params_count = model_parameter_count(model_plus.model) + ftype = pick_output_type(model, args.outtype) + print(f"{default_convention_outfile(ftype, params, model_params_count, metadata)}") # noqa: NP100 + return + if args.no_vocab and args.vocab_only: raise ValueError("--vocab-only does not make sense with --no-vocab") @@ -1504,6 +1631,9 @@ def main(args_in: list[str] | None = None) -> None: else: model_plus = ModelPlus(model = {}, paths = [args.model / 'dummy'], format = 'none', vocab = None) + model_params_count = model_parameter_count(model_plus.model) + logger.info(f"model parameters count : {model_params_count} ({model_parameter_count_rounded_notation(model_params_count)})") + if args.dump: do_dump_model(model_plus) return @@ -1557,7 +1687,7 @@ def main(args_in: list[str] | None = None) -> None: f_norm_eps = 1e-5, ) OutputFile.write_vocab_only(outfile, params, vocab, special_vocab, - endianess=endianess, pad_vocab=args.pad_vocab) + endianess=endianess, pad_vocab=args.pad_vocab, metadata=metadata) logger.info(f"Wrote {outfile}") return @@ -1570,13 +1700,13 @@ def main(args_in: list[str] | None = None) -> None: model = convert_model_names(model, params, args.skip_unknown) ftype = pick_output_type(model, args.outtype) model = convert_to_output_type(model, ftype) - outfile = args.outfile or default_outfile(model_plus.paths, ftype) + outfile = args.outfile or default_outfile(model_plus.paths, ftype, params, model_params_count, metadata) params.ftype = ftype logger.info(f"Writing {outfile}, format {ftype}") OutputFile.write_all(outfile, ftype, params, model, vocab, special_vocab, - concurrency=args.concurrency, endianess=endianess, pad_vocab=args.pad_vocab) + concurrency=args.concurrency, endianess=endianess, pad_vocab=args.pad_vocab, metadata=metadata) logger.info(f"Wrote {outfile}") From 9aa672490c848e45eaa704a554e0f1f6df995fc8 Mon Sep 17 00:00:00 2001 From: Joan Fontanals <joan.fontanals.martinez@jina.ai> Date: Mon, 13 May 2024 10:35:14 +0200 Subject: [PATCH 61/64] llama : rename jina tokenizers to v2 (#7249) * refactor: rename jina tokenizers to v2 * refactor: keep refactoring non-breaking --- convert-hf-to-gguf-update.py | 6 +++--- convert-hf-to-gguf.py | 6 +++--- llama.cpp | 4 +++- 3 files changed, 9 insertions(+), 7 deletions(-) diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py index cd2674a0ea97d..14aa0c45a6a87 100755 --- a/convert-hf-to-gguf-update.py +++ b/convert-hf-to-gguf-update.py @@ -74,9 +74,9 @@ class TOKENIZER_TYPE(IntEnum): {"name": "qwen2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", }, {"name": "olmo", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", }, {"name": "dbrx", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", }, - {"name": "jina-en", "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-en", }, # WPM! - {"name": "jina-es", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", }, - {"name": "jina-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", }, + {"name": "jina-v2-en", "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-en", }, # WPM! + {"name": "jina-v2-es", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", }, + {"name": "jina-v2-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", }, ] # make directory "models/tokenizers" if it doesn't exist diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index ec7f4dd758c72..d6e5dece0a2c3 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -475,13 +475,13 @@ def get_vocab_base_pre(self, tokenizer) -> str: res = "dbrx" if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f": # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-en - res = "jina-en" + res = "jina-v2-en" if chkhsh == "171aeeedd6fb548d418a7461d053f11b6f1f1fc9b387bd66640d28a4b9f5c643": # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-es - res = "jina-es" + res = "jina-v2-es" if chkhsh == "27949a2493fc4a9f53f5b9b029c82689cfbe5d3a1929bb25e043089e28466de6": # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-de - res = "jina-de" + res = "jina-v2-de" if res is None: logger.warning("\n") diff --git a/llama.cpp b/llama.cpp index e91ad7285da99..adbcc07e20fc5 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4424,7 +4424,9 @@ static void llm_load_vocab( } else if ( tokenizer_pre == "gpt-2" || tokenizer_pre == "jina-es" || - tokenizer_pre == "jina-de") { + tokenizer_pre == "jina-de" || + tokenizer_pre == "jina-v2-es" || + tokenizer_pre == "jina-v2-de") { vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_GPT2; } else if ( tokenizer_pre == "refact") { From 948f4ec7c5bff92b18e63303f2b2d1645bccd943 Mon Sep 17 00:00:00 2001 From: Neo Zhang <14088817+arthw@users.noreply.github.com> Date: Mon, 13 May 2024 18:11:26 +0800 Subject: [PATCH 62/64] [SYCL] rm wait() (#7233) --- ggml-sycl.cpp | 25 +------------------------ 1 file changed, 1 insertion(+), 24 deletions(-) diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp index e93d2af631cc0..724070eb91080 100644 --- a/ggml-sycl.cpp +++ b/ggml-sycl.cpp @@ -15564,26 +15564,6 @@ static void ggml_sycl_mul_mat_batched_sycl(const ggml_tensor *src0, const int64_t r2 = ne12/ne02; const int64_t r3 = ne13/ne03; -#if 0 - // use syclGemmEx - { - for (int i13 = 0; i13 < ne13; ++i13) { - for (int i12 = 0; i12 < ne12; ++i12) { - int i03 = i13 / r3; - int i02 = i12 / r2; - - SYCL_CHECK( - syclGemmEx(g_sycl_handles[g_main_device], CUBLAS_OP_T, CUBLAS_OP_N, - ne01, ne11, ne10, - alpha, (const char *) src0_as_f16 + i02*src0->nb[2] + i03*src0->nb[3] , SYCL_R_16F, nb01/sizeof(half), - (const char *) src1_as_f16 + i12*src1->nb[2]/2 + i13*src1->nb[3]/2, SYCL_R_16F, nb11/sizeof(float), - beta, ( char *) dst_t + i12*nbd2 + i13*nbd3, cu_data_type, ne01, - cu_compute_type, - CUBLAS_GEMM_DEFAULT_TENSOR_OP)); - } - } - } -#else if (r2 == 1 && r3 == 1 && src0->nb[2]*src0->ne[2] == src0->nb[3] && src1->nb[2]*src1->ne[2] == src1->nb[3]) { // there is no broadcast and src0, src1 are contiguous across dims 2, 3 SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch( @@ -15595,7 +15575,6 @@ static void ggml_sycl_mul_mat_batched_sycl(const ggml_tensor *src0, nb11 / nb10, nb12 / nb10, beta, (char *)dst_t, cu_data_type, ne01, nb2 / nb0, ne12 * ne13, cu_compute_type))); - g_sycl_handles[g_main_device]->wait(); } else { const int ne23 = ne12*ne13; @@ -15626,7 +15605,7 @@ static void ggml_sycl_mul_mat_batched_sycl(const ggml_tensor *src0, nb02, nb03, nb12_scaled, nb13_scaled, nbd2, nbd3, r2, r3, item_ct1); }); - }).wait(); + }); } SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch( *g_sycl_handles[g_main_device], oneapi::mkl::transpose::trans, @@ -15637,9 +15616,7 @@ static void ggml_sycl_mul_mat_batched_sycl(const ggml_tensor *src0, dpct::library_data_t::real_half, nb11 / nb10, beta, (void **)(ptrs_dst.get() + 0 * ne23), cu_data_type, ne01, ne23, cu_compute_type))); - g_sycl_handles[g_main_device]->wait(); } -#endif if (no_mixed_dtypes) { const to_fp32_sycl_t to_fp32_sycl = ggml_get_to_fp32_sycl(GGML_TYPE_F16); From 1c570d8beeebad95872dc738ea542a4a0022f78a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20G=C3=A4=C3=9Fler?= <johannesg@5d6.de> Date: Mon, 13 May 2024 13:03:27 +0200 Subject: [PATCH 63/64] perplexity: add BF16 vs. FP16 results (#7150) --- examples/perplexity/README.md | 60 ++++++++++++++++++++++++++++++++++- 1 file changed, 59 insertions(+), 1 deletion(-) diff --git a/examples/perplexity/README.md b/examples/perplexity/README.md index c5e2bc5de9690..c2a3c5ce9fdb9 100644 --- a/examples/perplexity/README.md +++ b/examples/perplexity/README.md @@ -7,6 +7,8 @@ Also note that finetunes typically result in a higher perplexity value even thou Within llama.cpp the perplexity of base models is used primarily to judge the quality loss from e.g. quantized models vs. FP16. The convention among contributors is to use the Wikitext-2 test set for testing unless noted otherwise (can be obtained with `scripts/get-wikitext-2.sh`). +When numbers are listed all command line arguments and compilation options are left at their defaults unless noted otherwise. +llama.cpp numbers are **not** directly comparable to those of other projects because the exact values depend strongly on the implementation details. By default only the mean perplexity value and the corresponding uncertainty is calculated. The uncertainty is determined empirically by assuming a Gaussian distribution of the "correct" logits per and then applying error propagation. @@ -32,7 +34,13 @@ In addition to the KL divergence the following statistics are calculated with `- ## LLaMA 3 8b Scoreboard -Results are sorted by Kullback-Leibler divergence relative to FP16. +| Revision | f364eb6f | +|:---------|:-------------------| +| Backend | CUDA | +| CPU | AMD Epyc 7742 | +| GPU | 1x NVIDIA RTX 4090 | + +Results were generated using the CUDA backend and are sorted by Kullback-Leibler divergence relative to FP16. The "WT" importance matrices were created using varying numbers of Wikitext tokens and can be found [here](https://huggingface.co/JohannesGaessler/llama.cpp_importance_matrices/blob/main/imatrix-llama_3-8b-f16-2.7m_tokens.dat). | Quantization | imatrix | Model size [GiB] | PPL | ΔPPL | KLD | Mean Δp | RMS Δp | @@ -89,6 +97,12 @@ K-quants score better on mean Δp than the legacy quants than e.g. KL divergence ## LLaMA 2 vs. LLaMA 3 Quantization comparison +| Revision | f364eb6f | +|:---------|:-------------------| +| Backend | CUDA | +| CPU | AMD Epyc 7742 | +| GPU | 1x NVIDIA RTX 4090 | + | Metric | L2 7b q2_K | L3 8b q2_K | L2 7b q4_K_M | L3 8b q4_K_M | L2 7b q6_K | L3 8b q6_K | L2 7b q8_0 | L3 8b q8_0 | |-----------------|---------------------|---------------------|---------------------|---------------------|---------------------|---------------------|---------------------|---------------------| | Mean PPL | 5.794552 ± 0.032298 | 9.751568 ± 0.063312 | 5.877078 ± 0.032781 | 6.407115 ± 0.039119 | 5.808494 ± 0.032425 | 6.253382 ± 0.038078 | 5.798542 ± 0.032366 | 6.234284 ± 0.037878 | @@ -107,6 +121,50 @@ K-quants score better on mean Δp than the legacy quants than e.g. KL divergence | RMS Δp | 9.762 ± 0.053 % | 21.421 ± 0.079 % | 3.252 ± 0.024 % | 5.519 ± 0.050 % | 1.339 ± 0.010 % | 2.295 ± 0.019 % | 0.618 ± 0.011 % | 1.198 ± 0.007 % | | Same top p | 85.584 ± 0.086 % | 71.138 ± 0.119 % | 94.665 ± 0.055 % | 91.901 ± 0.072 % | 97.520 ± 0.038 % | 96.031 ± 0.051 % | 98.846 ± 0.026 % | 97.674 ± 0.040 % | +## LLaMA 3 BF16 vs. FP16 comparison + +| Revision | 83330d8c | +|:---------|:--------------| +| Backend | CPU | +| CPU | AMD Epyc 7742 | +| GPU | N/A | + +Results were calculated with LLaMA 3 8b BF16 as `--kl-divergence-base` and LLaMA 3 8b FP16 as the `--model` for comparison. + +| Metric | Value | +|--------------------------------|--------------------------| +| Mean PPL(Q) | 6.227711 ± 0.037833 | +| Mean PPL(base) | 6.225194 ± 0.037771 | +| Cor(ln(PPL(Q)), ln(PPL(base))) | 99.990% | +| Mean ln(PPL(Q)/PPL(base)) | 0.000404 ± 0.000086 | +| Mean PPL(Q)/PPL(base) | 1.000404 ± 0.000086 | +| Mean PPL(Q)-PPL(base) | 0.002517 ± 0.000536 | +| Mean KLD | 0.00002515 ± 0.00000020 | +| Maximum KLD | 0.012206 | +| 99.9% KLD | 0.000799 | +| 99.0% KLD | 0.000222 | +| 99.0% KLD | 0.000222 | +| Median KLD | 0.000013 | +| 10.0% KLD | -0.000002 | +| 5.0% KLD | -0.000008 | +| 1.0% KLD | -0.000023 | +| Minimum KLD | -0.000059 | +| Mean Δp | -0.0000745 ± 0.0003952 % | +| Maximum Δp | 4.186% | +| 99.9% Δp | 1.049% | +| 99.0% Δp | 0.439% | +| 95.0% Δp | 0.207% | +| 90.0% Δp | 0.125% | +| 75.0% Δp | 0.029% | +| Median Δp | 0.000% | +| 25.0% Δp | -0.030% | +| 10.0% Δp | -0.126% | +| 5.0% Δp | -0.207% | +| 1.0% Δp | -0.434% | +| 0.1% Δp | -1.016% | +| Minimum Δp | -4.672% | +| RMS Δp | 0.150 ± 0.001 % | +| Same top p | 99.739 ± 0.013 % | ## Old Numbers From 29d5012042e9e68b017747200db8871fc3d22b0e Mon Sep 17 00:00:00 2001 From: Srihari-mcw <srihari@multicorewareinc.com> Date: Mon, 13 May 2024 06:05:29 -0700 Subject: [PATCH 64/64] Add provisions for windows support for BF16 code including CMake provision for enabling AVX512_BF16 --- CMakeLists.txt | 8 ++++++++ ggml-impl.h | 12 ++++++++++++ ggml.c | 24 ++++++++++++++++-------- ggml.h | 1 + llama.cpp | 1 + 5 files changed, 38 insertions(+), 8 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 1c3b5c8e423cc..e432b0c4a77cd 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -77,6 +77,7 @@ option(LLAMA_AVX2 "llama: enable AVX2" option(LLAMA_AVX512 "llama: enable AVX512" OFF) option(LLAMA_AVX512_VBMI "llama: enable AVX512-VBMI" OFF) option(LLAMA_AVX512_VNNI "llama: enable AVX512-VNNI" OFF) +option(LLAMA_AVX512_BF16 "llama: enable AVX512-BF16" OFF) option(LLAMA_FMA "llama: enable FMA" ${INS_ENB}) # in MSVC F16C is implied with AVX2/AVX512 if (NOT MSVC) @@ -1047,6 +1048,10 @@ elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LW add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VNNI__>) add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VNNI__>) endif() + if (LLAMA_AVX512_BF16) + add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512BF16__>) + add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512BF16__>) + endif() elseif (LLAMA_AVX2) list(APPEND ARCH_FLAGS /arch:AVX2) elseif (LLAMA_AVX) @@ -1078,6 +1083,9 @@ elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LW if (LLAMA_AVX512_VNNI) list(APPEND ARCH_FLAGS -mavx512vnni) endif() + if (LLAMA_AVX512_BF16) + list(APPEND ARCH_FLAGS -mavx512bf16) + endif() endif() elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64") message(STATUS "PowerPC detected") diff --git a/ggml-impl.h b/ggml-impl.h index d85b152bf16ea..3f1fcbba655a0 100644 --- a/ggml-impl.h +++ b/ggml-impl.h @@ -17,6 +17,18 @@ #define MIN(a, b) ((a) < (b) ? (a) : (b)) #define MAX(a, b) ((a) > (b) ? (a) : (b)) +#if defined(_WIN32) + +#define m512bh(p) p +#define m512i(p) p + +#else + +#define m512bh(p) (__m512bh)(p) +#define m512i(p) (__m512i)(p) + +#endif + /** * Converts brain16 to float32. * diff --git a/ggml.c b/ggml.c index b96a82a41517d..d60e701b5249f 100644 --- a/ggml.c +++ b/ggml.c @@ -413,10 +413,10 @@ void ggml_fp32_to_bf16_row(const float * x, ggml_bf16_t * y, int64_t n) { int i = 0; #if defined(__AVX512BF16__) for (; i + 32 <= n; i += 32) { - _mm512_storeu_ps( - (__m512 *)(y + i), - (__m512)_mm512_cvtne2ps_pbh(_mm512_loadu_ps(x + i + 16), - _mm512_loadu_ps(x + i))); + _mm512_storeu_si512( + (__m512i *)(y + i), + m512i(_mm512_cvtne2ps_pbh(_mm512_loadu_ps(x + i + 16), + _mm512_loadu_ps(x + i)))); } #endif for (; i < n; i++) { @@ -1618,10 +1618,10 @@ static void ggml_vec_dot_bf16(int n, float * restrict s, size_t bs, ggml_bf16_t __m512 c1 = _mm512_setzero_ps(); __m512 c2 = _mm512_setzero_ps(); for (; i + 64 <= n; i += 64) { - c1 = _mm512_dpbf16_ps(c1, (__m512bh)_mm512_loadu_ps((const float *)(x + i)), - (__m512bh)_mm512_loadu_ps((const float *)(y + i))); - c2 = _mm512_dpbf16_ps(c2, (__m512bh)_mm512_loadu_ps((const float *)(x + i + 32)), - (__m512bh)_mm512_loadu_ps((const float *)(y + i + 32))); + c1 = _mm512_dpbf16_ps(c1, m512bh(_mm512_loadu_si512((x + i))), + m512bh(_mm512_loadu_si512((y + i)))); + c2 = _mm512_dpbf16_ps(c2, m512bh(_mm512_loadu_si512((x + i + 32))), + m512bh(_mm512_loadu_si512((y + i + 32)))); } sumf += (ggml_float)_mm512_reduce_add_ps(c1); sumf += (ggml_float)_mm512_reduce_add_ps(c2); @@ -22873,6 +22873,14 @@ int ggml_cpu_has_avx512_vnni(void) { #endif } +int ggml_cpu_has_avx512_bf16(void) { +#if defined(__AVX512BF16__) + return 1; +#else + return 0; +#endif +} + int ggml_cpu_has_fma(void) { #if defined(__FMA__) return 1; diff --git a/ggml.h b/ggml.h index 3fe95ed57633b..b51d649b1a051 100644 --- a/ggml.h +++ b/ggml.h @@ -2376,6 +2376,7 @@ extern "C" { GGML_API int ggml_cpu_has_avx512 (void); GGML_API int ggml_cpu_has_avx512_vbmi(void); GGML_API int ggml_cpu_has_avx512_vnni(void); + GGML_API int ggml_cpu_has_avx512_bf16(void); GGML_API int ggml_cpu_has_fma (void); GGML_API int ggml_cpu_has_neon (void); GGML_API int ggml_cpu_has_arm_fma (void); diff --git a/llama.cpp b/llama.cpp index adbcc07e20fc5..b43e43020ffcf 100644 --- a/llama.cpp +++ b/llama.cpp @@ -17976,6 +17976,7 @@ const char * llama_print_system_info(void) { s += "AVX512 = " + std::to_string(ggml_cpu_has_avx512()) + " | "; s += "AVX512_VBMI = " + std::to_string(ggml_cpu_has_avx512_vbmi()) + " | "; s += "AVX512_VNNI = " + std::to_string(ggml_cpu_has_avx512_vnni()) + " | "; + s += "AVX512_BF16 = " + std::to_string(ggml_cpu_has_avx512_bf16()) + " | "; s += "FMA = " + std::to_string(ggml_cpu_has_fma()) + " | "; s += "NEON = " + std::to_string(ggml_cpu_has_neon()) + " | "; s += "ARM_FMA = " + std::to_string(ggml_cpu_has_arm_fma()) + " | ";

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