add test resnet squeezenet ssd(mobilenet)

src/common/types.h

@@ -95,17 +95,23 @@ static const std::string G_OP_TYPE_FETCH = "fetch";
 
 static std::unordered_map<
     std::string, std::pair<std::vector<std::string>, std::vector<std::string>>>
-    op_input_output_key = {{G_OP_TYPE_CONV, {{"Input"}, {"Output"}}},
-                           {G_OP_TYPE_RELU, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_SOFTMAX, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_MUL, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_ELEMENTWISE_ADD, {{"X", "Y"}, {"Out"}}},
-                           {G_OP_TYPE_POOL2D, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_BATCHNORM, {{"X"}, {"Y"}}},
-                           {G_OP_TYPE_LRN, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_CONCAT, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_SPLIT, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_FEED, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_FETCH, {{"X"}, {"Out"}}},
-                           {G_OP_TYPE_RESHAPE, {{"X"}, {"Out"}}}};
+    op_input_output_key = {
+        {G_OP_TYPE_CONV, {{"Input"}, {"Output"}}},
+        {G_OP_TYPE_RELU, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_SOFTMAX, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_MUL, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_ELEMENTWISE_ADD, {{"X", "Y"}, {"Out"}}},
+        {G_OP_TYPE_POOL2D, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_BATCHNORM, {{"X"}, {"Y"}}},
+        {G_OP_TYPE_LRN, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_CONCAT, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_SPLIT, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_FEED, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_FETCH, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_TRANSPOSE, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_BOX_CODER,
+         {{"PriorBox", "PriorBoxVar", "TargetBox"}, {"OutputBox"}}},
+        {G_OP_TYPE_PRIOR_BOX, {{"Image", "Input"}, {"Boxes", "Variances"}}},
+        {G_OP_TYPE_MULTICLASS_NMS, {{"BBoxes", "Scores"}, {"Out"}}},
+        {G_OP_TYPE_RESHAPE, {{"X"}, {"Out"}}}};
 }  // namespace paddle_mobile

src/io.cpp

@@ -220,7 +220,7 @@ const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
       }
     }
   }
-  //  originProgramDesc->Description("program: ");
+  originProgramDesc->Description("program: ");
 
   if (optimize) {
     framework::ProgramOptimize program_optimize;

test/CMakeLists.txt

@@ -96,6 +96,17 @@ target_link_libraries(test-googlenet paddle-mobile)
 ADD_EXECUTABLE(test-mobilenet net/test_mobilenet.cpp test_helper.h  test_include.h executor_for_test.h)
 target_link_libraries(test-mobilenet paddle-mobile)
 
+# gen test
+ADD_EXECUTABLE(test-resnet net/test_resnet.cpp test_helper.h  test_include.h executor_for_test.h)
+target_link_libraries(test-resnet paddle-mobile)
+# gen test
+ADD_EXECUTABLE(test-mobilenetssd net/test_mobilenet+ssd.cpp test_helper.h  test_include.h executor_for_test.h)
+target_link_libraries(test-mobilenetssd paddle-mobile)
+
+# gen test
+ADD_EXECUTABLE(test-squeezenet net/test_squeezenet.cpp test_helper.h  test_include.h executor_for_test.h)
+target_link_libraries(test-squeezenet paddle-mobile)
+
 # gen test
 ADD_EXECUTABLE(test-sigmoid operators/test_sigmoid_op.cpp  test_include.h)
 target_link_libraries(test-sigmoid paddle-mobile)

test/net/test_mobilenet+ssd.cpp

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+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 <fstream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+int main() {
+  paddle_mobile::Loader<paddle_mobile::CPU> loader;
+  auto time1 = time();
+  auto program = loader.Load(g_mobilenet_ssd, false);
+  auto time2 = time();
+  DLOG << "load cost :" << time_diff(time1, time1) << "ms";
+  paddle_mobile::Executor<paddle_mobile::CPU> executor(program, 1, false);
+
+  std::vector<int64_t> dims{1, 3, 300, 300};
+  Tensor input_tensor;
+  SetupTensor<float>(&input_tensor, {1, 3, 300, 300}, static_cast<float>(0),
+                     static_cast<float>(1));
+
+  std::vector<float> input(input_tensor.data<float>(),
+                           input_tensor.data<float>() + input_tensor.numel());
+  auto time3 = time();
+  executor.Predict(input, dims);
+  auto time4 = time();
+  DLOG << "predict cost :" << time_diff(time3, time4) << "ms";
+  return 0;
+}

test/net/test_resnet.cpp

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+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 <fstream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+int main() {
+  paddle_mobile::Loader<paddle_mobile::CPU> loader;
+  auto time1 = time();
+  auto program = loader.Load(g_resnet, false);
+  auto time2 = time();
+  DLOG << "load cost :" << time_diff(time1, time1) << "ms";
+  paddle_mobile::Executor<paddle_mobile::CPU> executor(program, 1, false);
+
+  std::vector<int64_t> dims{1, 3, 32, 32};
+  Tensor input_tensor;
+  SetupTensor<float>(&input_tensor, {1, 3, 32, 32}, static_cast<float>(0),
+                     static_cast<float>(1));
+
+  std::vector<float> input(input_tensor.data<float>(),
+                           input_tensor.data<float>() + input_tensor.numel());
+  auto time3 = time();
+  executor.Predict(input, dims);
+  auto time4 = time();
+  DLOG << "predict cost :" << time_diff(time3, time4) << "ms";
+  return 0;
+}

test/net/test_squeezenet.cpp

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+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 <fstream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+int main() {
+  paddle_mobile::Loader<paddle_mobile::CPU> loader;
+  //  ../../../test/models/googlenet
+  //  ../../../test/models/mobilenet
+  auto time1 = time();
+  auto program = loader.Load(g_squeezenet, false);
+  auto time2 = time();
+  DLOG << "load cost :" << time_diff(time1, time1) << "ms";
+  paddle_mobile::Executor<paddle_mobile::CPU> executor(program, 1, false);
+
+  std::vector<int64_t> dims{1, 3, 227, 227};
+  Tensor input_tensor;
+  SetupTensor<float>(&input_tensor, {1, 3, 227, 227}, static_cast<float>(0),
+                     static_cast<float>(1));
+
+  std::vector<float> input(input_tensor.data<float>(),
+                           input_tensor.data<float>() + input_tensor.numel());
+  auto time3 = time();
+  executor.Predict(input, dims);
+  auto time4 = time();
+  DLOG << "predict cost :" << time_diff(time3, time4) << "ms";
+  return 0;
+}