// 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/broadcast_op_handle.h" namespace paddle { namespace framework { namespace details { BroadcastOpHandle::BroadcastOpHandle(const std::vector &local_scopes, const std::vector &places) : local_scopes_(local_scopes), places_(places) {} void BroadcastOpHandle::RunImpl() { PADDLE_ENFORCE_EQ(this->inputs_.size(), 1, "The number of input should be one."); PADDLE_ENFORCE_EQ( this->outputs_.size(), places_.size(), "The number of output should equal to the number of places."); // Wait input done, this Wait is asynchronous operation auto in_var_handle = static_cast(this->inputs_[0]); auto &in_place = in_var_handle->place_; if (inputs_[0]->generated_op_) { inputs_[0]->generated_op_->Wait(dev_ctxes_[in_place]); for (auto *out : outputs_) { auto out_handle = static_cast(out); auto &out_p = out_handle->place_; inputs_[0]->generated_op_->Wait(dev_ctxes_[out_p]); } } auto in_scope_idx = in_var_handle->scope_idx_; PADDLE_ENFORCE_LT(in_scope_idx, local_scopes_.size(), "The input(%s) is not in the local_scopes.", in_var_handle->name_); auto in_var = local_scopes_[in_scope_idx]->FindVar(in_var_handle->name_); Tensor *in_tensor = GetTensorFromVar(in_var); for (auto *out : outputs_) { auto out_handle = static_cast(out); auto &out_p = out_handle->place_; auto out_scope_idx = out_handle->scope_idx_; PADDLE_ENFORCE_LT(out_scope_idx, local_scopes_.size(), "%s is not in the local_scopes ", out_handle->name_); auto *s = local_scopes_[out_scope_idx]; auto out_var = s->FindVar(out_handle->name_); PADDLE_ENFORCE_EQ(out_p.which(), in_place.which(), "The place of input and output should be the same."); if (in_var->IsType()) { auto &in_sr = in_var->Get(); auto out_sr = out_var->GetMutable(); if (&in_sr == out_sr) continue; out_sr->set_height(in_sr.height()); out_sr->set_rows(in_sr.rows()); out_sr->mutable_value()->Resize(in_sr.value().dims()); out_sr->mutable_value()->mutable_data(out_p, in_sr.value().type()); } else if (in_var->IsType()) { auto in_lod = in_var->Get(); auto out_lod = out_var->GetMutable(); if (&in_lod == out_lod) continue; out_lod->set_lod(in_lod.lod()); out_lod->Resize(in_lod.dims()); out_lod->mutable_data(out_p, in_lod.type()); } else { PADDLE_THROW("Var should be LoDTensor or SelectedRows."); } Tensor *out_tensor = GetTensorFromVar(out_var); if (platform::is_cpu_place(in_place)) { paddle::framework::TensorCopy(*in_tensor, out_p, *(dev_ctxes_[in_place]), out_tensor); } else if (platform::is_gpu_place(in_place)) { #ifdef PADDLE_WITH_CUDA auto src_gpu_place = boost::get(in_place); auto dst_gpu_place = boost::get(out_p); void *dst_ptr = out_tensor->mutable_data(out_p); void *src_ptr = in_tensor->data(); int64_t size = in_tensor->numel(); memory::Copy( dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, reinterpret_cast(dev_ctxes_[out_p]) ->stream()); #else PADDLE_THROW("CUDAPlace is not supported in CPU device."); #endif } } } std::string BroadcastOpHandle::Name() const { return "broadcast"; } } // namespace details } // namespace framework } // namespace paddle