// 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 "paddle/fluid/framework/details/build_strategy.h" #include "paddle/fluid/framework/details/multi_devices_helper.h" #include "paddle/fluid/framework/ir/graph.h" namespace paddle { namespace platform { class NCCLContextMap; } namespace framework { class Scope; namespace details { class MultiDevSSAGraphBuilder : public ir::Pass { protected: std::unique_ptr ApplyImpl( std::unique_ptr graph) const override; private: void CreateOpHandleIOs(ir::Graph *result, ir::Node *node, size_t device_id) const; void Init() const; private: mutable std::string loss_var_name_; mutable std::vector places_; mutable std::vector local_scopes_; mutable std::unordered_set grad_names_; #ifdef PADDLE_WITH_CUDA mutable platform::NCCLContextMap *nccl_ctxs_; #endif int GetVarDeviceID(const ir::Graph &graph, const std::string &varname) const; bool IsScaleLossOp(ir::Node *node) const; void CreateRPCOp(ir::Graph *result, ir::Node *node) const; void CreateDistTrainOp(ir::Graph *result, ir::Node *node) const; /** * Is this operator as the end-point operator before/after send operator. */ bool IsDistTrainOp(ir::Node *node, const std::vector &send_vars, const std::vector &recv_vars) const; std::vector FindDistTrainSendVars( const std::vector &nodes) const; std::vector FindDistTrainRecvVars( const std::vector &nodes) const; void CreateComputationalOps(ir::Graph *result, ir::Node *node, size_t num_places) const; void CreateScaleLossGradOp(ir::Graph *result, const std::string &loss_grad_name) const; VarHandle *CreateReduceOp(ir::Graph *result, const std::string &og, int dst_dev_id) const; void CreateComputationalOp(ir::Graph *result, ir::Node *node, int dev_id) const; int GetOpDeviceID(const ir::Graph &graph, ir::Node *node) const; void InsertAllReduceOp(ir::Graph *result, const std::string &og) const; void InsertDataBalanceOp(ir::Graph *result, const std::vector &datas) const; void CreateBroadcastOp(ir::Graph *result, const std::string &p_name, size_t src_dev_id) const; bool IsSparseGradient(const std::string &og) const; size_t GetAppropriateDeviceID( const std::vector &var_names) const; private: mutable BuildStrategy strategy_; mutable std::unordered_map all_vars_; mutable std::vector balance_vars_; void SetCommunicationContext(OpHandleBase *op_handle, const platform::Place &p) const; }; } // namespace details } // namespace framework } // namespace paddle