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rewrite unittest of trt_activation_op

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wangkuiyi-patch-1
Luo Tao 7 years ago
parent df87e63baa
commit e116129f03
4 changed files with 36 additions and 94 deletions
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3
cmake/configure.cmake
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@ -92,6 +92,9 @@ if(WITH_GPU)
if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7)
message(FATAL_ERROR "TensorRT needs CUDNN >= 7.0 to compile")
endif()
if(${TENSORRT_MAJOR_VERSION} VERSION_LESS 4)
message(FATAL_ERROR "Paddle needs TensorRT >= 4.0 to compile")
endif()
include_directories(${TENSORRT_INCLUDE_DIR})
endif()
elseif(WITH_AMD_GPU)

7
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
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@ -1,12 +1,9 @@
# Add TRT tests
nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES} tensorrt_engine)
# This test is not stable
# See https://paddleci.ngrok.io/viewLog.html?tab=buildLog&buildTypeId=Paddle_PrCi2&buildId=36834&_focus=8828
#nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc io_converter.cc
# DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine
# SERIAL)
nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor)
nv_test(test_trt_mul_op SRCS test_mul_op.cc mul_op.cc
DEPS ${FLUID_CORE_MODULES} tensorrt_engine mul_op SERIAL)
nv_test(test_trt_fc_op SRCS test_fc_op.cc fc_op.cc
DEPS ${FLUID_CORE_MODULES} tensorrt_engine mul_op SERIAL)
nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
DEPS ${FLUID_CORE_MODULES} tensorrt_engine activation_op SERIAL)

5
paddle/fluid/inference/tensorrt/convert/activation_op.cc
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@ -21,7 +21,8 @@ namespace tensorrt {
class ReluOpConverter : public OpConverter {
public:
ReluOpConverter() {}
void operator()(const framework::proto::OpDesc& op) override {
void operator()(const framework::proto::OpDesc& op,
const framework::Scope& scope) override {
// Here the two nullptr looks strange, that's because the
// framework::OpDesc's constructor is strange.
framework::OpDesc op_desc(op, nullptr);
@ -32,7 +33,7 @@ class ReluOpConverter : public OpConverter {
nvinfer1::IActivationLayer* layer = TRT_ENGINE_ADD_LAYER(
engine_, Activation, *const_cast<nvinfer1::ITensor*>(input_tensor),
nvinfer1::ActivationType::kRELU);
engine_->SetITensor(op_desc.Output("Out")[0], layer->getOutput(0));
engine_->DeclareOutput(layer, 0, op_desc.Output("Out")[0]);
}
};

115
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
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@ -1,106 +1,47 @@
/* 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
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
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. */
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 <gtest/gtest.h>
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/inference/tensorrt/convert/io_converter.h"
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/place.h"
USE_OP(relu);
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace paddle {
namespace inference {
namespace tensorrt {
void Compare(const std::string op_type, float input, float expect) {
TEST(ReluOpConverter, main) {
framework::Scope scope;
platform::CUDAPlace place;
platform::CUDADeviceContext ctx(place);
// init fluid op and variable
auto x_var = scope.Var("X");
auto x_tensor = x_var->GetMutable<framework::LoDTensor>();
x_tensor->Resize({1, 1});
x_tensor->mutable_data<float>(place);
std::vector<float> init;
init.push_back(input);
framework::TensorFromVector(init, ctx, x_tensor);
auto out_var = scope.Var("Out");
auto out_tensor = out_var->GetMutable<framework::LoDTensor>();
out_tensor->Resize({1, 1});
out_tensor->mutable_data<float>(place);
framework::OpDesc op_desc;
op_desc.SetType(op_type);
op_desc.SetInput("X", {"X"});
op_desc.SetOutput("Out", {"Out"});
auto op = framework::OpRegistry::CreateOp(*op_desc.Proto());
// run fluid op
op->Run(scope, place);
// get fluid output
std::vector<float> out1;
framework::TensorToVector(*out_tensor, ctx, &out1);
// init tensorrt op
cudaStream_t stream;
ASSERT_EQ(0, cudaStreamCreate(&stream));
TensorRTEngine* engine = new TensorRTEngine(1, 1 << 10, &stream);
engine->InitNetwork();
engine->DeclareInput("X", nvinfer1::DataType::kFLOAT,
nvinfer1::DimsCHW{1, 1, 1});
// convert op
OpConverter op_converter;
op_converter.ConvertOp(*op_desc.Proto(), engine);
engine->DeclareOutput("Out");
engine->FreezeNetwork();
// convert LoDTensor to ITensor
size_t size = x_tensor->memory_size();
EngineIOConverter::ConvertInput(op_type, *x_tensor,
engine->buffer("X").buffer, size, &stream);
// run tensorrt Outp
engine->Execute(1);
// convert ITensor to LoDTensor
EngineIOConverter::ConvertOutput(op_type, engine->buffer("Out").buffer,
out_tensor, size, &stream);
// get tensorrt output
std::vector<float> out2;
framework::TensorToVector(*out_tensor, ctx, &out2);
// compare
ASSERT_EQ(out1[0], out2[0]);
ASSERT_EQ(out1[0], expect);
delete engine;
cudaStreamDestroy(stream);
}
TEST(OpConverter, ConvertRelu) {
Compare("relu", 1, 1); // relu(1) = 1
Compare("relu", -5, 0); // relu(-5) = 0
std::unordered_set<std::string> parameters;
TRTConvertValidation validator(10, parameters, scope, 1000);
validator.DeclInputVar("relu-X", nvinfer1::Dims2(10, 6));
validator.DeclOutputVar("relu-Out", nvinfer1::Dims2(10, 6));
// Prepare Op description
framework::OpDesc desc;
desc.SetType("relu");
desc.SetInput("X", {"relu-X"});
desc.SetOutput("Out", {"relu-Out"});
LOG(INFO) << "set OP";
validator.SetOp(*desc.Proto());
LOG(INFO) << "execute";
validator.Execute(10);
}
} // namespace tensorrt
} // namespace inference
} // namespace paddle
USE_OP(activation);
USE_OP(relu);

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