paddle_pass_builder.h 4.3 KB
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// 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 <sstream>
#include <string>
#include <vector>

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/*! \file */

/*! \namespace paddle */
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namespace paddle {
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/** This is a pass builder based on string. It is part of inference API.
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 */
class PaddlePassBuilder {
 public:
  explicit PaddlePassBuilder(const std::vector<std::string> &passes)
      : passes_(passes) {}

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  void SetPasses(std::initializer_list<std::string> passes) {
    passes_ = passes;
  }

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  /** Append a pass to the end of the passes. */
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  void AppendPass(const std::string &pass_type);

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  /** Insert a pass to a specific position.
   * @param idx the position to insert.
   * @param pass_type the pass key.
   */
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  void InsertPass(size_t idx, const std::string &pass_type);

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  /** Delete the `idx`-th pass. */
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  void DeletePass(size_t idx);

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  /** Delete all the passes that has type `pass_type`. */
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  void DeletePass(const std::string &pass_type);

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  void ClearPasses();
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  /** Append an analysis pass. */
  void AppendAnalysisPass(const std::string &pass);

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  /** Visualize the computation graph after each pass by generating a DOT
   * language file, one can draw them with the Graphviz toolkit.
   */
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  void TurnOnDebug();

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  /** Human-readible information. */
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  std::string DebugString();

  const std::vector<std::string> &AllPasses() const { return passes_; }
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  std::vector<std::string> AnalysisPasses() const {
    auto passes = analysis_passes_;
    // To make sure the ir_graph_to_program should be the last pass so any
    // modication of IR will persist to the program.
    passes.push_back("ir_graph_to_program_pass");
    return passes;
  }
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 protected:
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  std::vector<std::string> analysis_passes_{
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      {"ir_graph_build_pass", "ir_graph_clean_pass", "ir_analysis_pass",
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       "ir_params_sync_among_devices_pass", "adjust_cudnn_workspace_size_pass",
       "inference_op_replace_pass"}};
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  std::vector<std::string> passes_;
};

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/**Pass strategy to help control the IR passes.
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 */
class PassStrategy : public PaddlePassBuilder {
 public:
  explicit PassStrategy(const std::vector<std::string> &passes)
      : PaddlePassBuilder(passes) {}

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  /** The MKLDNN control exists in both CPU and GPU mode, because there can be
   * still some CPU kernels running in CPU mode.
   */
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  virtual void EnableMKLDNN() {}
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  /** Enable NGRAPH optimization
   */
  virtual void EnableNgraph() {}

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  /** Enable MKLDNN quantize optimization
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   */
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  virtual void EnableMkldnnQuantizer() {}
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  bool use_gpu() const { return use_gpu_; }

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  virtual ~PassStrategy() = default;
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 protected:
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  bool use_ngraph_{false};
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  bool use_gpu_{false};
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  bool use_mkldnn_{false};
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};

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/** The CPU passes controller, it is used in AnalysisPredictor with CPU mode.
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 */
class CpuPassStrategy : public PassStrategy {
 public:
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  CpuPassStrategy();
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  explicit CpuPassStrategy(const CpuPassStrategy &other)
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      : PassStrategy(other.AllPasses()) {
    use_gpu_ = other.use_gpu_;
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    use_ngraph_ = other.use_ngraph_;
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    use_mkldnn_ = other.use_mkldnn_;
    use_mkldnn_quantizer_ = other.use_mkldnn_quantizer_;
  }
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  virtual ~CpuPassStrategy() = default;

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  void EnableNgraph() override;
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  void EnableMKLDNN() override;
  void EnableMkldnnQuantizer() override;
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 protected:
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  bool use_ngraph_{false};
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  bool use_mkldnn_quantizer_{false};
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};

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/** The GPU passes strategy, it is used in AnalysisPredictor with GPU mode.
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 */
class GpuPassStrategy : public PassStrategy {
 public:
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  GpuPassStrategy();
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  explicit GpuPassStrategy(const GpuPassStrategy &other)
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      : PassStrategy(other.AllPasses()) {
    use_gpu_ = true;
  }
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  void EnableNgraph() override;
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  void EnableMKLDNN() override;
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  void EnableMkldnnQuantizer() override;
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  virtual ~GpuPassStrategy() = default;
};

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extern const std::vector<std::string> kTRTSubgraphPasses;
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extern const std::vector<std::string> kAnakinSubgraphPasses;

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}  // namespace paddle