// 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 #include #include #include #include #include #include #include "paddle/fluid/imperative/backward_strategy.h" #include "paddle/fluid/imperative/gradient_accumulator.h" #include "paddle/fluid/imperative/layer.h" namespace paddle { namespace imperative { // It seems there is no need for Engine to be an // singleton, we can have multi-engine to run // mutil-graoh. For future use we may expose a interface // to Python to support class Engine { public: virtual ~Engine() = default; virtual void Execute() = 0; virtual void Init(VarBase* var, const detail::BackwardStrategy& strategy) = 0; }; class BasicEngine : public Engine { public: void Init(VarBase* var, const detail::BackwardStrategy& strategy) override; void Execute() override; private: void PrepareDeps(); void CheckBackwardInputs(OpBase* op); void PrepareGradAccumulators(OpBase* op); void SumGradient(OpBase* op, std::shared_ptr src, VariableWrapper* dst); // TODO(jiabin): maybe we can optimize the performance of engine by cache the // result void Clear() { init_ops_.clear(); op_deps_.clear(); accumulators_.clear(); } std::vector> init_ops_; detail::BackwardStrategy backward_strategy_; std::unordered_map op_deps_; std::unordered_map> accumulators_; std::vector>> need_accu_var_list_; }; } // namespace imperative } // namespace paddle