op_registry.h

/* Copyright (c) 2017 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 <map>
#include <memory>
#include <string>
#include <tuple>
#include <type_traits>
#include <unordered_map>
#include <unordered_set>
#include <vector>

#include "paddle/fluid/framework/grad_op_desc_maker.h"
#include "paddle/fluid/framework/inplace_op_inference.h"
#include "paddle/fluid/framework/no_need_buffer_vars_inference.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"
#include "paddle/fluid/imperative/dygraph_grad_maker.h"
#include "paddle/fluid/imperative/type_defs.h"

namespace paddle {
namespace framework {
namespace details {

enum OpInfoFillType {
  kOperator = 0,
  kOpProtoAndCheckerMaker = 1,
  kGradOpDescMaker = 2,
  kVarTypeInference = 3,
  kShapeInference = 4,
  kInplaceOpInference = 5,
  kNoNeedBufferVarsInference = 6,
  kGradOpBaseMaker = 7,
  kUnknown = -1
};

namespace internal {
template <typename T, OpInfoFillType kType>
struct TypePair {
  using Type = T;
  static constexpr OpInfoFillType kFillType = kType;
};

using OpRegistryClasses = std::tuple<                                // NOLINT
    TypePair<OperatorBase, kOperator>,                               // NOLINT
    TypePair<OpProtoAndCheckerMaker, kOpProtoAndCheckerMaker>,       // NOLINT
    TypePair<GradOpDescMakerBase, kGradOpDescMaker>,                 // NOLINT
    TypePair<imperative::GradOpBaseMakerBase, kGradOpBaseMaker>,     // NOLINT
    TypePair<VarTypeInference, kVarTypeInference>,                   // NOLINT
    TypePair<InferShapeBase, kShapeInference>,                       // NOLINT
    TypePair<InplaceOpInference, kInplaceOpInference>,               // NOLINT
    TypePair<NoNeedBufferVarsInference, kNoNeedBufferVarsInference>  // NOLINT
    >;

static constexpr int kOpRegistryClassNumber =
    std::tuple_size<OpRegistryClasses>::value;

template <typename T, int kPos, bool kIsBounded /* = true*/>
struct IsMatchedBaseTypeImpl {
  using PairType = typename std::tuple_element<kPos, OpRegistryClasses>::type;
  static constexpr bool kValue =
      std::is_base_of<typename PairType::Type, T>::value;
};

template <typename T, int kPos>
struct IsMatchedBaseTypeImpl<T, kPos, false> {
  static constexpr bool kValue = false;
};

template <typename T, int kPos>
static inline constexpr bool IsMatchedBaseType() {
  return IsMatchedBaseTypeImpl<
      T, kPos, (kPos >= 0 && kPos < kOpRegistryClassNumber)>::kValue;
}

template <typename T, int kStart, int kEnd, bool kIsEnd, bool kIsMatched>
struct OpInfoFillTypeGetterImpl {};

// This case should not happen
template <typename T, int kStart, int kEnd>
struct OpInfoFillTypeGetterImpl<T, kStart, kEnd, true, true> {};

template <typename T, int kStart, int kEnd>
struct OpInfoFillTypeGetterImpl<T, kStart, kEnd, true, false> {
  static constexpr OpInfoFillType kType = kUnknown;
};

template <typename T, int kStart, int kEnd>
struct OpInfoFillTypeGetterImpl<T, kStart, kEnd, false, false> {
  static constexpr OpInfoFillType kType =
      OpInfoFillTypeGetterImpl<T, kStart + 1, kEnd, kStart + 1 == kEnd,
                               IsMatchedBaseType<T, kStart + 1>()>::kType;
};

template <typename T, int kStart, int kEnd>
struct OpInfoFillTypeGetterImpl<T, kStart, kEnd, false, true> {
  using PairType = typename std::tuple_element<kStart, OpRegistryClasses>::type;
  static constexpr OpInfoFillType kType = PairType::kFillType;
};

template <typename T>
using OpInfoFillTypeGetter =
    OpInfoFillTypeGetterImpl<T, 0, kOpRegistryClassNumber,
                             kOpRegistryClassNumber == 0,
                             IsMatchedBaseType<T, 0>()>;

}  // namespace internal

template <typename T>
struct OpInfoFillTypeID {
  static constexpr OpInfoFillType ID() {
    return internal::OpInfoFillTypeGetter<T>::kType;
  }
};

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 {
    PADDLE_ENFORCE_EQ(info->creator_, nullptr,
                      platform::errors::AlreadyExists(
                          "OpCreator of %s has been registered", op_type));
    info->creator_ = [](const std::string& type, const VariableNameMap& inputs,
                        const VariableNameMap& outputs,
                        const AttributeMap& attrs) {
      return new T(type, inputs, outputs, attrs);
    };

    if (std::is_base_of<OperatorWithKernel, T>::value) {
      PADDLE_ENFORCE_EQ(
          info->infer_shape_, nullptr,
          platform::errors::AlreadyExists(
              "Duplicate InferShapeFN of %s has been registered", op_type));

      OperatorWithKernel* op = dynamic_cast<OperatorWithKernel*>(info->creator_(
          std::string{}, VariableNameMap{}, VariableNameMap{}, AttributeMap{}));
      PADDLE_ENFORCE_NOT_NULL(op, platform::errors::InvalidArgument(
                                      "%s should have kernels", op_type));
      info->infer_shape_ = [op](InferShapeContext* ctx) {
        op->InferShape(ctx);
      };
    }
  }
};

template <typename T>
struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(info->proto_, nullptr,
                      platform::errors::AlreadyExists(
                          "OpProto of %s has been registered.", op_type));
    PADDLE_ENFORCE_EQ(info->checker_, nullptr,
                      platform::errors::AlreadyExists(
                          "OpAttrChecker of %s has been registered.", op_type));
    info->proto_ = new proto::OpProto;
    info->checker_ = new OpAttrChecker();
    T maker;
    maker(info->proto_, info->checker_);
    info->proto_->set_type(op_type);
    PADDLE_ENFORCE_EQ(
        info->proto_->IsInitialized(), true,
        platform::errors::PreconditionNotMet(
            "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 {
    PADDLE_ENFORCE_EQ(
        info->grad_op_maker_, nullptr,
        platform::errors::AlreadyExists(
            "GradOpDescMaker of %s has been registered", op_type));

    info->grad_op_maker_ = [](
        const OpDesc& fwd_op,
        const std::unordered_set<std::string>& no_grad_set,
        std::unordered_map<std::string, std::string>* grad_to_var,
        const std::vector<BlockDesc*>& grad_block) {
      T maker(fwd_op, no_grad_set, grad_to_var, grad_block);
      return maker();
    };

    info->use_default_grad_op_desc_maker_ =
        std::is_base_of<DefaultGradOpMaker<OpDesc, true>, T>::value ||
        std::is_base_of<DefaultGradOpMaker<OpDesc, false>, T>::value ||
        std::is_base_of<DefaultGradOpMaker<imperative::OpBase, true>,
                        T>::value ||
        std::is_base_of<DefaultGradOpMaker<imperative::OpBase, false>,
                        T>::value;

    info->use_empty_grad_op_desc_maker_ =
        std::is_base_of<EmptyGradOpMaker<OpDesc>, T>::value ||
        std::is_base_of<EmptyGradOpMaker<imperative::OpBase>, T>::value;
  }
};

template <typename T>
struct OpInfoFiller<T, kGradOpBaseMaker> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(
        info->dygraph_grad_op_maker_, nullptr,
        platform::errors::AlreadyExists(
            "GradOpBaseMaker of %s has been registered", op_type));

    info->dygraph_grad_op_maker_ = [](
        const std::string& type,
        const imperative::NameVarBaseMap& var_base_map_in,
        const imperative::NameVarBaseMap& var_base_map_out,
        const framework::AttributeMap& attrs,
        const framework::AttributeMap& default_attrs,
        const std::map<std::string, std::string>& inplace_map) {
      T maker(type, var_base_map_in, var_base_map_out, attrs, inplace_map);
      maker.SetDygraphDefaultAttrsMap(default_attrs);
      return maker();
    };
  }
};

template <typename T>
struct OpInfoFiller<T, kVarTypeInference> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(
        info->infer_var_type_, nullptr,
        platform::errors::AlreadyExists(
            "VarTypeInference of %s has been registered", op_type));
    info->infer_var_type_ = [](InferVarTypeContext* context) {
      T inference;
      inference(context);
    };
  }
};

template <typename T>
struct OpInfoFiller<T, kShapeInference> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(
        info->infer_shape_, nullptr,
        platform::errors::AlreadyExists(
            "Duplicate InferShapeFN of %s has been registered", op_type));
    info->infer_shape_ = [](InferShapeContext* ctx) {
      T inference;
      inference(ctx);
    };
  }
};

template <typename T>
struct OpInfoFiller<T, kInplaceOpInference> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(
        info->infer_inplace_, nullptr,
        platform::errors::AlreadyExists(
            "InplaceOpInference of %s has been registered", op_type));
    info->infer_inplace_ = [](bool use_cuda) {
      T infer;
      return infer(use_cuda);
    };
  }
};

template <typename T>
struct OpInfoFiller<T, kNoNeedBufferVarsInference> {
  void operator()(const char* op_type, OpInfo* info) const {
    PADDLE_ENFORCE_EQ(
        info->infer_no_need_buffer_vars_, nullptr,
        platform::errors::AlreadyExists(
            "NoNeedBufferVarsInference of %s has been registered", op_type));
    info->infer_no_need_buffer_vars_.Reset(std::make_shared<T>());
  }
};

// A fake OpInfoFiller of void
template <>
struct OpInfoFiller<void, kUnknown> {
  void operator()(const char* op_type, OpInfo* info) const {}
};

}  // namespace details

}  // namespace framework
}  // namespace paddle