// 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/fetch_op_handle.h" #include #include #include "paddle/fluid/platform/profiler.h" namespace paddle { namespace framework { namespace details { FetchOpHandle::FetchOpHandle(ir::Node *node, FeedFetchList *data, size_t offset, std::vector *local_scopes, std::vector *local_exec_scopes) : OpHandleBase(node), data_(data), offset_(offset), local_scopes_(local_scopes), local_exec_scopes_(local_exec_scopes) {} FetchOpHandle::~FetchOpHandle() {} void FetchOpHandle::RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) { PADDLE_THROW("Nobody should wait FetchOp. Unexpceted Error"); } void FetchOpHandle::WaitAndMergeCPUTensors() const { std::vector tensors_ptr; tensors_ptr.reserve(tensors_.size()); for (auto &t : tensors_) { tensors_ptr.emplace_back(&t); } data_->at(offset_).MergeLoDTensor(tensors_ptr, platform::CPUPlace()); } void FetchOpHandle::RunImpl() { platform::RecordEvent record_event(Name()); WaitInputVarGenerated(platform::CPUPlace()); tensors_.resize(inputs_.size()); platform::CPUPlace cpu; auto &scopes = *local_exec_scopes_; for (size_t i = 0; i < inputs_.size(); ++i) { auto *var_handle = static_cast(inputs_[i]); auto &scope = scopes.at(var_handle->scope_idx()); auto *var = scope->FindVar(var_handle->name()); PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope", var_handle->name()); auto &t = var->Get(); if (t.IsInitialized() && t.numel() > 0) { if (platform::is_gpu_place(t.place())) { #ifdef PADDLE_WITH_CUDA TensorCopy(t, cpu, &tensors_[i]); #endif } else { tensors_[i].ShareDataWith(t); } } else { tensors_[i].clear(); tensors_[i].Resize({0}); } tensors_[i].set_lod(t.lod()); } this->WaitAndMergeCPUTensors(); } void FetchOpHandle::WaitInputVarGenerated(const platform::Place &place) { auto cpu_ctx = platform::DeviceContextPool::Instance().Get(place); for (auto *input : inputs_) { if (input->GeneratedOp()) { input->GeneratedOp()->RecordWaitEventOnCtx(cpu_ctx); } } } bool FetchOpHandle::IsMultiDeviceTransfer() { return true; } std::string FetchOpHandle::Name() const { return "Fetch"; } } // namespace details } // namespace framework } // namespace paddle