/* 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. */ #include "paddle/fluid/framework/details/build_strategy.h" #include "paddle/fluid/framework/details/multi_devices_graph_check_pass.h" #include "paddle/fluid/framework/details/multi_devices_graph_print_pass.h" #include "paddle/fluid/framework/details/reduce_op_handle.h" #include "paddle/fluid/framework/details/sequential_execution_pass.h" #include "paddle/fluid/framework/ir/graph.h" #include "paddle/fluid/framework/ir/graph_viz_pass.h" namespace paddle { namespace framework { namespace details { static inline bool SeqOnlyAllReduceOps(const BuildStrategy &strategy) { return (!strategy.enable_sequential_execution_ && strategy.num_trainers_ > 1); } class ParallelExecutorPassBuilder : public ir::PassBuilder { public: explicit ParallelExecutorPassBuilder(const BuildStrategy &strategy) : ir::PassBuilder(), strategy_(strategy) { if (strategy_.enable_sequential_execution_) { AppendPass("sequential_execution_pass"); } // Add a graph viz pass to record a graph. if (!strategy_.debug_graphviz_path_.empty()) { auto viz_pass = AppendPass("graph_viz_pass"); const std::string graph_path = string::Sprintf( "%s%s", strategy_.debug_graphviz_path_.c_str(), "_original_graph"); viz_pass->Set("graph_viz_path", new std::string(graph_path)); } // Add op fusion. if (strategy.fuse_elewise_add_act_ops_) { auto fuse_elewise_add_act_pass = AppendPass("fuse_elewise_add_act_pass"); // Add a graph viz pass to record a graph. if (!strategy.debug_graphviz_path_.empty()) { auto viz_pass = AppendPass("graph_viz_pass"); const std::string graph_path = string::Sprintf( "%s%s", strategy.debug_graphviz_path_.c_str(), "_fused_graph"); viz_pass->Set("graph_viz_path", new std::string(graph_path)); } } // Convert graph to run on multi-devices. auto multi_devices_pass = AppendPass("multi_devices_pass"); multi_devices_pass->SetNotOwned("strategy", &strategy_); // Add a graph print pass to record a graph with device info. if (!strategy_.debug_graphviz_path_.empty()) { auto multi_devices_print_pass = AppendPass("multi_devices_print_pass"); multi_devices_print_pass->SetNotOwned( "debug_graphviz_path", &strategy_.debug_graphviz_path_); multi_devices_print_pass->Set( "graph_printer", new details::GraphvizSSAGraphPrinter); } // Verify that the graph is correct for multi-device executor. AppendPass("multi_devices_check_pass"); if (SeqOnlyAllReduceOps(strategy)) { AppendPass("all_reduce_deps_pass"); } if (strategy_.remove_unnecessary_lock_) { AppendPass("modify_op_lock_and_record_event_pass"); } } private: BuildStrategy strategy_; }; std::shared_ptr BuildStrategy::CreatePassesFromStrategy( bool finalize_strategy) const { if (is_finalized_) { return pass_builder_; } pass_builder_.reset(new ParallelExecutorPassBuilder(*this)); if (finalize_strategy) { is_finalized_ = true; } return pass_builder_; } std::unique_ptr BuildStrategy::Apply( const ProgramDesc &main_program, const std::vector &places, const std::string &loss_var_name, const std::unordered_set ¶m_names, const std::vector &local_scopes, #if defined(PADDLE_WITH_CUDA) && !defined(_WIN32) const bool use_cuda, platform::NCCLContextMap *nccl_ctxs) const { #else const bool use_cuda) const { #endif // Create a default one if not finalized by user. CreatePassesFromStrategy(false); std::unique_ptr graph(new ir::Graph(main_program)); for (std::shared_ptr &pass : pass_builder_->AllPasses()) { if (pass->Type() == "multi_devices_pass") { pass->Erase("places"); pass->SetNotOwned>("places", &places); pass->Erase("loss_var_name"); pass->SetNotOwned("loss_var_name", &loss_var_name); pass->Erase("params"); pass->SetNotOwned>("params", ¶m_names); pass->Erase("local_scopes"); pass->SetNotOwned>("local_scopes", &local_scopes); #if defined(PADDLE_WITH_CUDA) && !defined(_WIN32) platform::NCCLContextMap *nctx = use_cuda ? nccl_ctxs : nullptr; pass->Erase("nccl_ctxs"); pass->SetNotOwned("nccl_ctxs", nctx); #endif } else if (pass->Type() == "sequential_execution_pass") { VLOG(1) << "set enable_sequential_execution:" << enable_sequential_execution_; pass->Erase(kAllOpDescs); pass->Set>( kAllOpDescs, new std::vector(main_program.Block(0).AllOps())); } else if (pass->Type() == "all_reduce_deps_pass") { VLOG(1) << "SeqOnlyAllReduceOps:" << SeqOnlyAllReduceOps(*this) << ", num_trainers:" << num_trainers_; pass->Erase(kAllOpDescs); pass->Set>( kAllOpDescs, new std::vector(main_program.Block(0).AllOps())); } graph = pass->Apply(std::move(graph)); } return graph; } } // namespace details } // namespace framework } // namespace paddle USE_PASS(fuse_elewise_add_act_pass); USE_PASS(graph_viz_pass); USE_PASS(multi_batch_merge_pass); USE_PASS(multi_devices_pass); USE_PASS(multi_devices_check_pass); USE_PASS(multi_devices_print_pass); USE_PASS(sequential_execution_pass); USE_PASS(all_reduce_deps_pass); USE_PASS(modify_op_lock_and_record_event_pass);