提交 680868a9 编写于 作者: E eclipsess

add test resnet squeezenet ssd(mobilenet)

上级 410e5bdf
......@@ -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
......@@ -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;
......
......@@ -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)
......
/* 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;
}
/* 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;
}
/* 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;
}
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