Merge pull request #10956 from panyx0718/infer2

paddle inference interface implementation
release/0.13.0
Xin Pan 7 years ago committed by GitHub
commit 7323be175d
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GPG Key ID: 4AEE18F83AFDEB23

@ -13,10 +13,45 @@
# limitations under the License. # limitations under the License.
# #
function(inference_api_test TARGET_NAME TEST_SRC DEP_TEST)
set(options "")
set(oneValueArgs "")
set(multiValueArgs ARGS)
cmake_parse_arguments(inference_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
set(arg_list "")
if(inference_test_ARGS)
foreach(arg ${inference_test_ARGS})
list(APPEND arg_list "_${arg}")
endforeach()
else()
list(APPEND arg_list "_")
endif()
foreach(arg ${arg_list})
string(REGEX REPLACE "^_$" "" arg "${arg}")
cc_test(${TARGET_NAME}
SRCS ${TEST_SRC}
DEPS paddle_fluid_api paddle_inference_api paddle_inference_api_impl
ARGS --dirname=${PYTHON_TESTS_DIR}/book/)
# set_tests_properties(${TARGET_NAME}
# PROPERTIES DEPENDS ${DEP_TEST})
endforeach()
endfunction(inference_api_test)
cc_library(paddle_inference_api cc_library(paddle_inference_api
SRCS paddle_inference_api.cc SRCS paddle_inference_api.cc
DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB}) DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
cc_library(paddle_inference_api_impl
SRCS paddle_inference_api_impl.cc
DEPS paddle_inference_api paddle_fluid_api)
cc_test(test_paddle_inference_api cc_test(test_paddle_inference_api
SRCS test_paddle_inference_api.cc SRCS test_paddle_inference_api.cc
DEPS paddle_inference_api) DEPS paddle_inference_api)
inference_api_test(test_paddle_inference_api_impl
test_paddle_inference_api_impl.cc
test_word2vec)

@ -27,29 +27,38 @@
namespace paddle { namespace paddle {
enum PaddleDType {
FLOAT32,
INT64,
};
struct PaddleBuf {
void* data; // pointer to the data memory.
size_t length; // number of memory bytes.
};
struct PaddleTensor { struct PaddleTensor {
std::string name; // variable name. std::string name; // variable name.
std::vector<int> shape; std::vector<int> shape;
std::vector<unsigned char> data; // bytes of data. PaddleBuf data; // blob of data.
size_t type{typeid(float).hash_code()}; // hash of type PaddleDType dtype;
}; };
/* /*
* A simple Inference API for Paddle. Currently this API might just be used by * A simple Inference API for Paddle. Currently this API might just be used by
* non-sequence scenerios. * non-sequence scenerios.
* TODO(Superjomn) Prepare another API for NLP-related usages. * TODO(Superjomn) Prepare another API for NLP-related usages.
*/ */
class PaddlePredictor { class PaddlePredictor {
public: public:
struct Config; struct Config;
PaddlePredictor() = default; PaddlePredictor() = default;
PaddlePredictor(const PaddlePredictor&) = delete; PaddlePredictor(const PaddlePredictor&) = delete;
// One drived class should has such a constructor
// PaddlePredictor(const XConfig& config);
// The XConfig is a derived class of Config.
// Predict an record. // Predict an record.
// The caller should be responsible for allocating and releasing the memory of
// `inputs`. `inputs` should be alive until Run returns. caller should be
// responsible for releasing the memory of `output_data`.
virtual bool Run(const std::vector<PaddleTensor>& inputs, virtual bool Run(const std::vector<PaddleTensor>& inputs,
std::vector<PaddleTensor>* output_data) = 0; std::vector<PaddleTensor>* output_data) = 0;

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@ -0,0 +1,76 @@
/* 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. */
#pragma once
#include <glog/logging.h>
#include <memory>
#include <string>
#include <vector>
#include "paddle/contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/framework/init.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/io.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
struct VisConfig : public PaddlePredictor::Config {
int device;
float fraction_of_gpu_memory;
std::string prog_file;
std::string param_file;
bool share_variables;
};
/*
* Do not use this, just a demo indicating how to customize a Predictor.
*/
class PaddlePredictorImpl : public PaddlePredictor {
public:
explicit PaddlePredictorImpl(const VisConfig &config) : config_(config) {}
bool Init();
bool Run(const std::vector<PaddleTensor> &inputs,
std::vector<PaddleTensor> *output_data) override;
std::unique_ptr<PaddlePredictor> Clone() override;
~PaddlePredictorImpl() override{};
private:
bool InitShared(PaddlePredictorImpl *cls);
bool SetFeed(const std::vector<PaddleTensor> &input_datas,
std::vector<paddle::framework::LoDTensor> *feeds);
bool GetFetch(const std::vector<paddle::framework::LoDTensor> &fetchs,
std::vector<PaddleTensor> *output_data);
VisConfig config_;
paddle::platform::Place place_;
std::unique_ptr<paddle::framework::Executor> executor_;
std::unique_ptr<paddle::framework::Scope> scope_;
std::unique_ptr<paddle::framework::ExecutorPrepareContext> ctx_;
std::unique_ptr<paddle::framework::ProgramDesc> inference_program_;
std::vector<std::string> feed_target_names_;
std::vector<std::string> fetch_target_names_;
};
std::unique_ptr<PaddlePredictorImpl> CreatePaddlePredictorImpl(
const VisConfig &config);
} // namespace paddle

@ -0,0 +1,83 @@
/* 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 <glog/logging.h>
#include <gtest/gtest.h>
#include "gflags/gflags.h"
#include "paddle/contrib/inference/paddle_inference_api_impl.h"
#include "paddle/fluid/inference/tests/test_helper.h"
DEFINE_string(dirname, "", "Directory of the inference model.");
namespace paddle {
PaddleTensor LodTensorToPaddleTensor(framework::LoDTensor* t) {
PaddleTensor pt;
pt.data.data = t->data<void>();
if (t->type() == typeid(int64_t)) {
pt.data.length = t->numel() * sizeof(int64_t);
pt.dtype = PaddleDType::INT64;
} else if (t->type() == typeid(float)) {
pt.data.length = t->numel() * sizeof(float);
pt.dtype = PaddleDType::FLOAT32;
} else {
LOG(FATAL) << "unsupported type.";
}
pt.shape = framework::vectorize2int(t->dims());
return pt;
}
TEST(paddle_inference_api_impl, word2vec) {
VisConfig config;
config.model_dir = FLAGS_dirname + "word2vec.inference.model";
LOG(INFO) << "dirname " << config.model_dir;
config.fraction_of_gpu_memory = 0.85;
config.device = 0;
config.share_variables = true;
std::unique_ptr<PaddlePredictorImpl> predictor =
CreatePaddlePredictorImpl(config);
framework::LoDTensor first_word, second_word, third_word, fourth_word;
framework::LoD lod{{0, 1}};
int64_t dict_size = 2073; // The size of dictionary
SetupLoDTensor(&first_word, lod, static_cast<int64_t>(0), dict_size - 1);
SetupLoDTensor(&second_word, lod, static_cast<int64_t>(0), dict_size - 1);
SetupLoDTensor(&third_word, lod, static_cast<int64_t>(0), dict_size - 1);
SetupLoDTensor(&fourth_word, lod, static_cast<int64_t>(0), dict_size - 1);
std::vector<PaddleTensor> cpu_feeds;
cpu_feeds.push_back(LodTensorToPaddleTensor(&first_word));
cpu_feeds.push_back(LodTensorToPaddleTensor(&second_word));
cpu_feeds.push_back(LodTensorToPaddleTensor(&third_word));
cpu_feeds.push_back(LodTensorToPaddleTensor(&fourth_word));
std::vector<PaddleTensor> outputs;
ASSERT_TRUE(predictor->Run(cpu_feeds, &outputs));
ASSERT_EQ(outputs.size(), 1);
for (size_t i = 0; i < outputs.size(); ++i) {
size_t len = outputs[i].data.length;
float* data = static_cast<float*>(outputs[i].data.data);
for (int j = 0; j < len / sizeof(float); ++j) {
ASSERT_LT(data[j], 1.0);
ASSERT_GT(data[j], -1.0);
}
free(outputs[i].data.data);
}
}
} // namespace paddle

@ -1,5 +1,6 @@
set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor init) set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor init)
# TODO(panyx0718): Should this be called paddle_fluid_inference_api_internal?
cc_library(paddle_fluid_api cc_library(paddle_fluid_api
SRCS io.cc SRCS io.cc
DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB}) DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})

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