// 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 #include #include #include "paddle/fluid/framework/details/eager_deletion_op_handle.h" #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h" #include "paddle/fluid/framework/lod_tensor_array.h" #include "paddle/fluid/framework/scope.h" #include "paddle/fluid/framework/selected_rows.h" #include "paddle/fluid/platform/profiler.h" #ifdef PADDLE_WITH_CUDA #include "paddle/fluid/platform/cuda_device_guard.h" #endif namespace paddle { namespace framework { namespace details { EagerDeletionOpHandle::EagerDeletionOpHandle( ir::Node *node, Scope *scope, const platform::Place &place, const std::unordered_set &vars, GarbageCollector *gc) : OpHandleBase(node), scope_(scope), place_(place), var_infos_(vars.begin(), vars.end()), gc_(gc) { #ifdef PADDLE_WITH_CUDA if (platform::is_gpu_place(place)) { dev_ctx_ = reinterpret_cast( platform::DeviceContextPool::Instance().Get(place)); if (dynamic_cast(gc_)) { platform::CUDADeviceGuard guard( boost::get(place).device); PADDLE_ENFORCE(cudaEventCreateWithFlags(&event_, cudaEventDisableTiming)); PADDLE_ENFORCE_NOT_NULL(event_); } } #endif PADDLE_ENFORCE(!vars.empty(), "Var names cannot be empty"); for (auto *var : var_infos_) { PADDLE_ENFORCE_NOT_NULL(var); } } EagerDeletionOpHandle::~EagerDeletionOpHandle() { #ifdef PADDLE_WITH_CUDA if (event_) { auto gpu_place = boost::get(dev_ctx_->GetPlace()); platform::CUDADeviceGuard guard(gpu_place.device); PADDLE_ENFORCE(cudaEventDestroy(event_)); } #endif } void EagerDeletionOpHandle::InitCUDA() { #ifdef PADDLE_WITH_CUDA int dev_id = boost::get(dev_ctxes_.begin()->first).device; events_[dev_id] = nullptr; #endif } void EagerDeletionOpHandle::CallOnce() { PADDLE_ENFORCE(vars_.empty(), "vars_ must be initialized here"); Scope *exec_scope = local_exec_scopes_[0]; for (auto *var_info : var_infos_) { auto *var = exec_scope->FindVar(var_info->Name()); PADDLE_ENFORCE_NOT_NULL(var, "Variable %s should not be nullptr", var_info->Name()); vars_.emplace_back(var); } } std::string EagerDeletionOpHandle::Name() const { return "eager_deletion"; } void EagerDeletionOpHandle::RunImpl() { if (vars_.size() != var_infos_.size()) { CallOnce(); } platform::RecordEvent record_event(Name()); std::deque> garbages; for (size_t i = 0; i < var_infos_.size(); ++i) { auto *var_info = var_infos_[i]; if (var_info->IsSkippedAllMemoryOptimization() || !var_info->DecreaseRefCnt()) { continue; } VLOG(2) << "Erase variable " << var_info->Name() << " on " << place_; Variable *var = vars_[i]; if (var->IsType()) { garbages.emplace_back(var->GetMutable()->MoveMemoryHolder()); } else if (var->IsType()) { garbages.emplace_back( var->GetMutable()->mutable_value()->MoveMemoryHolder()); } else if (var->IsType()) { auto *tensor_arr = var->GetMutable(); for (auto &t : *tensor_arr) { garbages.emplace_back(t.MoveMemoryHolder()); } } else { PADDLE_THROW("Type %s of %s is not supported eager deletion", framework::ToTypeName(var->Type()), var_info->Name()); } } if (!garbages.empty()) { ClearGarbages(&garbages); } } void EagerDeletionOpHandle::ClearGarbages( std::deque> *garbages) { #ifdef PADDLE_WITH_CUDA if (event_) { auto compute_stream = dev_ctx_->stream(); auto callback_stream = reinterpret_cast(gc_)->stream(); auto callback_func = [=]() { PADDLE_ENFORCE(cudaEventRecord(event_, compute_stream)); PADDLE_ENFORCE(cudaStreamWaitEvent(callback_stream, event_, 0)); }; gc_->Add(std::move(*garbages), callback_func); } else { #endif gc_->Add(std::move(*garbages)); #ifdef PADDLE_WITH_CUDA } #endif } } // namespace details } // namespace framework } // namespace paddle