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93 lines
3.2 KiB
93 lines
3.2 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/naive_executor.h"
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#include "paddle/fluid/inference/analysis/analyzer.h"
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#include "paddle/fluid/inference/api/api_impl.h"
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#include "paddle/fluid/inference/api/paddle_inference_api.h"
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#include "paddle/fluid/string/printf.h"
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namespace paddle {
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using inference::analysis::Argument;
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using inference::analysis::Analyzer;
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using framework::proto::ProgramDesc;
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using framework::NaiveExecutor;
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using contrib::AnalysisConfig;
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/* This predictor is based on the original native predictor with IR and Analysis
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* support. It will optimize IR and Parameters in the runtime.
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* TODO(Superjomn) Replace the Navive predictor?
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*/
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class AnalysisPredictor : public PaddlePredictor {
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public:
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explicit AnalysisPredictor(const AnalysisConfig &config) : config_(config) {}
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bool Init(const std::shared_ptr<framework::Scope> &parent_scope,
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const std::shared_ptr<framework::ProgramDesc> &program = nullptr);
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bool Run(const std::vector<PaddleTensor> &inputs,
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std::vector<PaddleTensor> *output_data,
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int batch_size = -1) override;
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std::unique_ptr<ZeroCopyTensor> GetInputTensor(
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const std::string &name) override;
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std::unique_ptr<ZeroCopyTensor> GetOutputTensor(
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const std::string &name) override;
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bool ZeroCopyRun() override;
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void PrepareFeedFetch();
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void OptimizeInferenceProgram();
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Argument &analysis_argument() { return argument_; }
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std::unique_ptr<PaddlePredictor> Clone() override;
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framework::Scope *scope() { return executor_->scope(); }
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framework::ProgramDesc &program() { return *inference_program_; }
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protected:
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bool LoadProgramDesc();
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bool SetFeed(const std::vector<PaddleTensor> &input_datas,
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framework::Scope *scope);
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bool GetFetch(std::vector<PaddleTensor> *output_data,
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framework::Scope *scope);
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template <typename T>
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void GetFetchOne(const framework::LoDTensor &fetchs,
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PaddleTensor *output_data);
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private:
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contrib::AnalysisConfig config_;
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Argument argument_;
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std::unique_ptr<NaiveExecutor> executor_;
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platform::Place place_;
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std::shared_ptr<framework::Scope> scope_;
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framework::Scope *sub_scope_{nullptr};
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std::shared_ptr<framework::ProgramDesc> inference_program_;
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std::vector<framework::OpDesc *> feeds_;
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std::map<std::string, size_t> feed_names_;
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std::vector<framework::OpDesc *> fetchs_;
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// Memory buffer for feed inputs. The temporary LoDTensor will cause serious
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// concurrency problems, so cache them.
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std::vector<framework::LoDTensor> feed_tensors_;
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};
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} // namespace paddle
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