op_lite.h 5.4 KB
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// Copyright (c) 2019 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 <map>
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#include <memory>
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#include <string>
#include "paddle/fluid/framework/variable.h"
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#include "paddle/fluid/lite/core/context.h"
#include "paddle/fluid/lite/core/kernel.h"
#include "paddle/fluid/lite/core/scope.h"
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#include "paddle/fluid/lite/model_parser/compatible_pb.h"
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namespace paddle {
namespace lite {

// For registry factory.
struct Registry {
  void Touch() {}
};

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namespace mir {
class Node;
class SSAGraph;
}

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class OpInfo;

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/**
 * The base class of an light-weight operators, currently just used in inference
 * to eliminate overhead of some operations in current framework.
 *
 * The Operator are designed as follows:
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 * - it can has some members to hold the argument and some other computation
 * resources,
 * - it should act like a function call, no more logic included.
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 */
class OpLite : public Registry {
 public:
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  OpLite() = default;
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  OpLite(const std::string &type) : op_type_(type) {}
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  OpLite(const std::vector<Place> &valid_places)
      : valid_places_(valid_places) {}
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  void SetValidPlaces(const std::vector<Place> &places) {
    valid_places_ = places;
  }
  const std::vector<Place> &valid_places() const { return valid_places_; }
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  // Check the shape.
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  virtual bool CheckShape() const { return true; }
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  // Inference the outputs' shape.
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  virtual bool InferShape() const { return true; }
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  // Run this operator.
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  virtual bool Run();
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  // Link the external execution environ to internal context.
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  bool Attach(const OpDesc &opdesc, lite::Scope *scope);
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  const OpInfo *op_info() const { return op_info_.get(); }
  OpInfo *mutable_op_info() { return op_info_.get(); }
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  // Human-readable information.
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  virtual std::string DebugString() const = 0;

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  const Place &kernel_place() const { return kernel_place_; }

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  // Create all the kernels for the valid targets.
  std::vector<std::unique_ptr<KernelBase>> CreateKernels(
      const std::vector<Place> &places, const std::string &kernel_type = "");

  lite::Scope *scope() { return scope_; }

  // Assign op param to kernel.
  virtual void AttachKernel(KernelBase *kernel) = 0;

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  virtual ~OpLite() = default;

 protected:
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  // Attach it with the runtime environment.
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  virtual bool AttachImpl(const OpDesc &opdesc, lite::Scope *scope) = 0;
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  // Specify the kernel to run by default. This will specify the value of
  // `kernel_place_`.
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  virtual void StaticPickKernel(const std::vector<Place> &valid_targets) {
    auto kernels = CreateKernels(valid_targets);
    kernel_ = std::move(kernels.front());
  }
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  // Wait until all the inputs' events are ready.
  void SyncInputEvents() {}

  // Record the output events, and that will tell all the dependent operators
  // some inputs are ready.
  void RecordOutputEvents() {}
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  const Tensor *GetTensor(lite::Scope *scope, const std::string &name) const;
  Tensor *GetMutableTensor(lite::Scope *scope, const std::string &name) const;

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  friend class mir::Node;
  friend class mir::SSAGraph;

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 protected:
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  lite::Scope *scope_{};
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  std::unique_ptr<KernelBase> kernel_;
  std::string op_type_;
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  std::vector<Place> valid_places_;
  Place kernel_place_{TARGET(kHost), PRECISION(kFloat)};
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  std::unique_ptr<OpInfo> op_info_;
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};

/*
 * Operator Information, such as some description. It will be shared by all the
 * kernels of the same operator.
 */
class OpInfo {
 public:
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  // To avoid the bugs from legancy framework::OpDesc, we use the ProtoBuf
  // message instead.
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  void Build(const framework::proto::OpDesc &desc);
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  const framework::proto::OpDesc &desc() const;
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  framework::proto::OpDesc *mutable_desc() { return desc_.get(); }
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  const std::list<std::string> &input_names() const { return input_names_; }
  const std::list<std::string> &output_names() const { return output_names_; }
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  const std::map<std::string, std::list<std::string>> &input_argument() const;
  const std::map<std::string, std::list<std::string>> &output_argument() const;
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  bool GetInputArgname(const std::string &value_name, std::string *out) const;
  bool GetOutputArgname(const std::string &value_name, std::string *out) const;
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  const std::list<std::string> &input_argnames() const;
  const std::list<std::string> &output_argnames() const;
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 private:
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  void ExtractInputsAndOutputs(const framework::proto::OpDesc &opdesc);
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  void CollectInputAndOutputArgnames(const framework::proto::OpDesc &opdesc);
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  void CollectArguments(const framework::proto::OpDesc &opdesc);
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 private:
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  std::list<std::string> input_names_;
  std::list<std::string> output_names_;
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  std::list<std::string> input_argnames_;
  std::list<std::string> output_argnames_;
  std::map<std::string, std::list<std::string>> input_argument_;
  std::map<std::string, std::list<std::string>> output_argument_;
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  // NOTE too heavy.
  std::unique_ptr<framework::proto::OpDesc> desc_;
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};

}  // namespace lite
}  // namespace paddle