/* 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 "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" namespace paddle { namespace framework { namespace details { enum OpInfoFillType { kOperator = 0, kOpProtoAndCheckerMaker = 1, kGradOpDescMaker = 2, kVarTypeInference = 3, kShapeInference = 4 }; template struct OpInfoFillTypeID { static constexpr OpInfoFillType ID() { return std::is_base_of::value ? kOperator : (std::is_base_of::value ? kOpProtoAndCheckerMaker : (std::is_base_of::value ? kGradOpDescMaker : (std::is_base_of::value ? kVarTypeInference : (std::is_base_of::value ? kShapeInference : static_cast( -1))))); } }; template ::ID()> struct OpInfoFiller; template class OperatorRegistrarRecursive; template class OperatorRegistrarRecursive { public: using T = typename std::tuple_element>::type; OperatorRegistrarRecursive(const char* op_type, OpInfo* info) { OpInfoFiller fill; fill(op_type, info); constexpr auto size = sizeof...(ARGS); OperatorRegistrarRecursive reg(op_type, info); (void)(reg); } }; template class OperatorRegistrarRecursive { public: OperatorRegistrarRecursive(const char* op_type, OpInfo* info) {} }; template struct OpInfoFiller { 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 struct OpInfoFiller { void operator()(const char* op_type, OpInfo* info) const { info->proto_ = new proto::OpProto; 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 struct OpInfoFiller { void operator()(const char* op_type, OpInfo* info) const { info->grad_op_maker_ = []( const OpDesc& fwd_op, const std::unordered_set& no_grad_set, std::unordered_map* grad_to_var, const std::vector& grad_block) { T maker(fwd_op, no_grad_set, grad_to_var, grad_block); return maker(); }; } }; template struct OpInfoFiller { void operator()(const char* op_type, OpInfo* info) const { info->infer_var_type_ = [](const OpDesc& fwd_op, BlockDesc* block) { T inference; inference(fwd_op, block); }; } }; template struct OpInfoFiller { void operator()(const char* op_type, OpInfo* info) const { info->infer_shape_ = [](InferShapeContext* ctx) { T inference; inference(ctx); }; } }; } // namespace details } // namespace framework } // namespace paddle