add embed test, trigger pnnx ci for ncnn layer changes

.ci/pnnx.yml

@@ -4,12 +4,14 @@ on:
     branches: [master]
     paths:
     - '.ci/pnnx.yml'
+    - 'src/layer/*'
     - 'tools/pnnx/**'
     - '!tools/pnnx/README.md'
   mr:
     target-branches: [master]
     paths:
     - '.ci/pnnx.yml'
+    - 'src/layer/*'
     - 'tools/pnnx/**'
     - '!tools/pnnx/README.md'
 concurrency:

tests/CMakeLists.txt

@@ -101,6 +101,7 @@ ncnn_add_layer_test(Dropout)
 ncnn_add_layer_test(Einsum)
 ncnn_add_layer_test(Eltwise)
 ncnn_add_layer_test(ELU)
+ncnn_add_layer_test(Embed)
 ncnn_add_layer_test(Erf)
 ncnn_add_layer_test(ExpandDims)
 ncnn_add_layer_test(Flatten)

tests/test_embed.cpp

@@ -0,0 +1,108 @@
+// Tencent is pleased to support the open source community by making ncnn available.
+//
+// Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved.
+//
+// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+// in compliance with the License. You may obtain a copy of the License at
+//
+// https://opensource.org/licenses/BSD-3-Clause
+//
+// Unless required by applicable law or agreed to in writing, software distributed
+// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+// CONDITIONS OF ANY KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations under the License.
+
+#include "testutil.h"
+
+static int test_embed(int words, int num_output, int input_dim, int bias)
+{
+    ncnn::ParamDict pd;
+    pd.set(0, num_output);
+    pd.set(1, input_dim);
+    pd.set(2, bias);
+    pd.set(3, num_output * input_dim);
+
+    std::vector<ncnn::Mat> weights(bias ? 2 : 1);
+    weights[0] = RandomMat(num_output * input_dim);
+    if (bias)
+        weights[1] = RandomMat(num_output);
+
+    ncnn::Mat a(words);
+    RandomizeInt(a, 0, input_dim);
+
+    int ret = test_layer("Embed", pd, weights, a);
+    if (ret != 0)
+    {
+        fprintf(stderr, "test_embed failed words=%d num_output=%d input_dim=%d bias=%d\n", words, num_output, input_dim, bias);
+    }
+
+    return ret;
+}
+
+static int test_embed_0()
+{
+    return 0
+           || test_embed(128, 128, 128, 0)
+           || test_embed(128, 128, 128, 1)
+           || test_embed(127, 127, 127, 0)
+           || test_embed(127, 127, 127, 1)
+           || test_embed(124, 124, 124, 0)
+           || test_embed(124, 124, 124, 1);
+}
+
+#if NCNN_INT8
+static int test_embed_int8(int words, int num_output, int input_dim, int bias)
+{
+    ncnn::ParamDict pd;
+    pd.set(0, num_output);
+    pd.set(1, input_dim);
+    pd.set(2, bias);
+    pd.set(3, num_output * input_dim);
+    pd.set(18, 2);
+
+    std::vector<ncnn::Mat> weights(bias ? 3 : 2);
+    weights[0] = RandomS8Mat(num_output * input_dim);
+    if (bias)
+    {
+        weights[1] = RandomMat(num_output);
+        weights[2] = RandomMat(1, 100.f, 200.f);
+    }
+    else
+    {
+        weights[1] = RandomMat(1, 100.f, 200.f);
+    }
+
+    ncnn::Mat a(words);
+    RandomizeInt(a, 0, input_dim);
+
+    int ret = test_layer("Embed", pd, weights, a);
+    if (ret != 0)
+    {
+        fprintf(stderr, "test_embed_int8 failed words=%d num_output=%d input_dim=%d bias=%d\n", words, num_output, input_dim, bias);
+    }
+
+    return ret;
+}
+
+static int test_embed_1()
+{
+    return 0
+           || test_embed_int8(128, 128, 128, 0)
+           || test_embed_int8(128, 128, 128, 1)
+           || test_embed_int8(127, 127, 127, 0)
+           || test_embed_int8(127, 127, 127, 1)
+           || test_embed_int8(124, 124, 124, 0)
+           || test_embed_int8(124, 124, 124, 1);
+}
+#endif // NCNN_INT8
+
+int main()
+{
+    SRAND(7767517);
+
+#if NCNN_INT8
+    return test_embed_0() || test_embed_1();
+#else
+    return test_embed_0();
+#endif
+}