op_registry.h 4.6 KB
Newer Older
1
/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserved.
2

L
Luo Tao 已提交
3 4 5
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
6

L
Luo Tao 已提交
7
    http://www.apache.org/licenses/LICENSE-2.0
8

L
Luo Tao 已提交
9 10 11 12 13
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. */
14 15 16

#pragma once

17 18 19
#include <string>
#include <tuple>
#include <vector>
Y
Yi Wang 已提交
20 21 22 23 24
#include "paddle/fluid/framework/grad_op_desc_maker.h"
#include "paddle/fluid/framework/op_info.h"
#include "paddle/fluid/framework/op_proto_maker.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/var_type_inference.h"
25 26 27 28 29 30 31 32

namespace paddle {
namespace framework {
namespace details {

enum OpInfoFillType {
  kOperator = 0,
  kOpProtoAndCheckerMaker = 1,
Y
Yu Yang 已提交
33
  kGradOpDescMaker = 2,
34 35
  kVarTypeInference = 3,
  kShapeInference = 4
36 37 38 39 40 41 42 43 44 45 46
};

template <typename T>
struct OpInfoFillTypeID {
  static constexpr OpInfoFillType ID() {
    return std::is_base_of<OperatorBase, T>::value
               ? kOperator
               : (std::is_base_of<OpProtoAndCheckerMaker, T>::value
                      ? kOpProtoAndCheckerMaker
                      : (std::is_base_of<GradOpDescMakerBase, T>::value
                             ? kGradOpDescMaker
Y
Yu Yang 已提交
47 48
                             : (std::is_base_of<VarTypeInference, T>::value
                                    ? kVarTypeInference
49 50 51 52
                                    : (std::is_base_of<InferShapeBase, T>::value
                                           ? kShapeInference
                                           : static_cast<OpInfoFillType>(
                                                 -1)))));
53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
  }
};

template <typename T, OpInfoFillType = OpInfoFillTypeID<T>::ID()>
struct OpInfoFiller;

template <size_t I, bool at_end, typename... ARGS>
class OperatorRegistrarRecursive;

template <size_t I, typename... ARGS>
class OperatorRegistrarRecursive<I, false, ARGS...> {
 public:
  using T = typename std::tuple_element<I, std::tuple<ARGS...>>::type;
  OperatorRegistrarRecursive(const char* op_type, OpInfo* info) {
    OpInfoFiller<T> fill;
    fill(op_type, info);
    constexpr auto size = sizeof...(ARGS);
    OperatorRegistrarRecursive<I + 1, I + 1 == size, ARGS...> reg(op_type,
                                                                  info);
    (void)(reg);
  }
};

template <size_t I, typename... ARGS>
class OperatorRegistrarRecursive<I, true, ARGS...> {
 public:
  OperatorRegistrarRecursive(const char* op_type, OpInfo* info) {}
};

template <typename T>
struct OpInfoFiller<T, kOperator> {
  void operator()(const char* op_type, OpInfo* info) const {
    info->creator_ = [](const std::string& type, const VariableNameMap& inputs,
                        const VariableNameMap& outputs,
                        const AttributeMap& attrs) {
      return new T(type, inputs, outputs, attrs);
    };
  }
};

template <typename T>
struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
  void operator()(const char* op_type, OpInfo* info) const {
96
    info->proto_ = new proto::OpProto;
97 98 99 100 101 102 103 104 105 106 107 108 109 110
    info->checker_ = new OpAttrChecker();
    auto maker = T(info->proto_, info->checker_);
    maker.Validate();
    info->proto_->set_type(op_type);
    PADDLE_ENFORCE(
        info->proto_->IsInitialized(),
        "Fail to initialize %s's OpProto, because %s is not initialized",
        op_type, info->proto_->InitializationErrorString());
  }
};

template <typename T>
struct OpInfoFiller<T, kGradOpDescMaker> {
  void operator()(const char* op_type, OpInfo* info) const {
111
    info->grad_op_maker_ = [](
Y
Yu Yang 已提交
112
        const OpDesc& fwd_op,
113
        const std::unordered_set<std::string>& no_grad_set,
Y
Yu Yang 已提交
114
        std::unordered_map<std::string, std::string>* grad_to_var,
Y
Yu Yang 已提交
115
        const std::vector<BlockDesc*>& grad_block) {
Y
Yu Yang 已提交
116
      T maker(fwd_op, no_grad_set, grad_to_var, grad_block);
117 118
      return maker();
    };
119 120
  }
};
Y
Yu Yang 已提交
121 122 123 124

template <typename T>
struct OpInfoFiller<T, kVarTypeInference> {
  void operator()(const char* op_type, OpInfo* info) const {
Y
Yu Yang 已提交
125
    info->infer_var_type_ = [](const OpDesc& fwd_op, BlockDesc* block) {
Y
Yu Yang 已提交
126 127 128 129 130 131
      T inference;
      inference(fwd_op, block);
    };
  }
};

132 133 134 135 136 137 138 139 140 141
template <typename T>
struct OpInfoFiller<T, kShapeInference> {
  void operator()(const char* op_type, OpInfo* info) const {
    info->infer_shape_ = [](InferShapeContext* ctx) {
      T inference;
      inference(ctx);
    };
  }
};

142 143 144 145
}  // namespace details

}  // namespace framework
}  // namespace paddle