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MKLDNN 1.0.2 #2102

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MKLDNN 1.0.2 #2102

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544a883
MKLDNN 1.0.2
sreekanth-yalachigere Oct 11, 2019
225726a
adding back MKL-ML
sreekanth-yalachigere Oct 11, 2019
da2f192
mklml for v0.20
sreekanth-yalachigere Oct 12, 2019
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6 changes: 3 additions & 3 deletions cmake/external/mkldnn.cmake
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ include (ExternalProject)

set(MKLDNN_URL https://github.com/intel/mkl-dnn.git)
# If MKLDNN_TAG is updated, check if MKLML_VERSION and platform.cmake.patch need to be updated.
set(MKLDNN_TAG v0.18.1)
set(MKLDNN_TAG v1.0.2)
set(MKLML_VERSION 2019.0.5.20190502)

if(WIN32)
Expand Down Expand Up @@ -62,9 +62,9 @@ if (onnxruntime_USE_MKLDNN)
endif()
set(MKLDNN_INCLUDE_DIR ${MKLDNN_INSTALL}/include)
set(MKLDNN_CMAKE_EXTRA_ARGS)
set(MKLDNN_PATCH_COMMAND1 git apply ${CMAKE_SOURCE_DIR}/patches/mkldnn/mem-patch.cmake.patch)
# set(MKLDNN_PATCH_COMMAND1 git apply ${CMAKE_SOURCE_DIR}/patches/mkldnn/mem-patch.cmake.patch)
# discard prior changes due to patching in mkldnn source to unblock incremental builds.
set(MKLDNN_PATCH_DISCARD_COMMAND cd ${MKLDNN_SOURCE} && git checkout -- .)
# set(MKLDNN_PATCH_DISCARD_COMMAND cd ${MKLDNN_SOURCE} && git checkout -- .)
if(NOT onnxruntime_BUILD_FOR_NATIVE_MACHINE)
# pre-v1.0
list(APPEND MKLDNN_CMAKE_EXTRA_ARGS "-DARCH_OPT_FLAGS=")
Expand Down
195 changes: 0 additions & 195 deletions onnxruntime/core/providers/mkldnn/activation/activations.cc
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20 changes: 0 additions & 20 deletions onnxruntime/core/providers/mkldnn/activation/activations.h
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23 changes: 11 additions & 12 deletions onnxruntime/core/providers/mkldnn/math/gemm.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
#include "core/providers/cpu/math/gemm_helper.h"
#include "core/util/math_cpuonly.h"
#include "mkldnn.h"
#include "mkldnn.hpp"
#include "core/providers/mkldnn/mkldnn_fwd.h"

namespace onnxruntime {
Expand All @@ -28,9 +29,9 @@ Status Gemm<float>::Compute(OpKernelContext* ctx) const {
if (!helper.State().IsOK())
return helper.State();

int M = gsl::narrow_cast<int>(helper.M());
int N = gsl::narrow_cast<int>(helper.N());
int K = gsl::narrow_cast<int>(helper.K());
mkldnn::memory::dim M = gsl::narrow_cast<int>(helper.M());
mkldnn::memory::dim N = gsl::narrow_cast<int>(helper.N());
mkldnn::memory::dim K = gsl::narrow_cast<int>(helper.K());
auto Y = ctx->Output(0, TensorShape({M, N}));

if (beta_ != 0) {
Expand Down Expand Up @@ -77,15 +78,13 @@ Status Gemm<float>::Compute(OpKernelContext* ctx) const {
}
}

// mkldnn_sgemm expects col major matrices, so we need to swap the operands A and B
auto status = mkldnn_sgemm(trans_B_ ? "T" : "N",
trans_A_ ? "T" : "N",
&N, &M, &K,
&alpha_, W->template Data<float>(),
trans_B_ ? &K : &N,
X->template Data<float>(),
trans_A_ ? &M : &K,
&beta_, Y->template MutableData<float>(), &N);
// mkldnn_sgemm expects row major matrices, so no need to swap the operands A and B
auto status = mkldnn_sgemm(trans_A_ ? 'T' : 'N',
trans_B_ ? 'T' : 'N',
M, N, K,
alpha_, X->template Data<float>() , trans_A_ ? M : K,
W->template Data<float>(), trans_B_ ? K : N,
beta_, Y->template MutableData<float>(), N);
if (status == mkldnn_success) {
return Status::OK();
} else {
Expand Down
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