// 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/gather_op_handle.h" #include "paddle/fluid/framework/details/container_cast.h" #include "paddle/fluid/framework/details/variable_visitor.h" namespace paddle { namespace framework { namespace details { GatherOpHandle::GatherOpHandle(const std::vector &local_scopes, const std::vector &places) : local_scopes_(local_scopes), places_(places) {} void GatherOpHandle::RunImpl() { if (places_.size() == 1) return; // the input and output may have dummy var. auto in_var_handles = DynamicCast(inputs_); PADDLE_ENFORCE_EQ( in_var_handles.size(), places_.size(), "The number of output should equal to the number of places."); VarHandle *out_var_handle; { auto out_var_handles = DynamicCast(outputs_); PADDLE_ENFORCE_EQ(out_var_handles.size(), 1, "The number of output should be one."); out_var_handle = out_var_handles.front(); } std::vector var_scopes; for (auto *s : local_scopes_) { var_scopes.emplace_back(s->FindVar(kLocalExecScopeName)->Get()); } auto in_0_handle = in_var_handles[0]; auto pre_in_var = var_scopes.at(in_0_handle->scope_idx_)->FindVar(in_0_handle->name_); PADDLE_ENFORCE_NOT_NULL(pre_in_var); PADDLE_ENFORCE(pre_in_var->IsType(), "Currently, gather_op only can gather SelectedRows."); // Wait input done, this Wait is asynchronous operation WaitInputVarGenerated(); auto &pre_in_value = pre_in_var->Get(); std::vector out_rows; std::vector in_tensors; // Gather the inputs for (auto *in_handle : in_var_handles) { auto *in_var = var_scopes.at(in_handle->scope_idx_)->FindVar(in_handle->name_); PADDLE_ENFORCE_NOT_NULL(in_var); VariableVisitor::EnforceShapeAndDTypeEQ(*in_var, *pre_in_var); auto &in_sr_value = in_var->Get(); auto &in_sr_rows = in_sr_value.rows(); out_rows.insert(out_rows.end(), in_sr_rows.begin(), in_sr_rows.end()); in_tensors.emplace_back(in_sr_value.value()); } // NOTE: The Places of all input tensor must be all on CPU or all on GPU. platform::Place t_out_p = out_var_handle->place_; if (platform::is_gpu_place(pre_in_value.place())) { PADDLE_ENFORCE(platform::is_gpu_place(t_out_p), "Places of input and output must be all on GPU."); } else { t_out_p = platform::CPUPlace(); } auto out_var = var_scopes.at(out_var_handle->scope_idx_)->FindVar(out_var_handle->name_); PADDLE_ENFORCE_NOT_NULL(out_var); auto out_value = out_var->GetMutable(); out_value->set_height(pre_in_value.height()); out_value->set_rows(out_rows); size_t rows = out_rows.size(); DDim out_dim = pre_in_value.GetCompleteDims(); out_dim[0] = static_cast(rows); out_value->mutable_value()->Resize(out_dim).mutable_data( t_out_p, pre_in_value.value().type()); Tensor *out_tensor = out_value->mutable_value(); // copy auto dev_ctx = dev_ctxes_[out_var_handle->place_]; RunAndRecordEvent(out_var_handle->place_, [in_tensors, out_tensor, &dev_ctx, t_out_p] { int s = 0, e = 0; for (size_t j = 0; j < in_tensors.size(); ++j) { e += in_tensors[j].dims()[0]; auto sub_out = out_tensor->Slice(s, e); paddle::framework::TensorCopy(in_tensors[j], t_out_p, *dev_ctx, &sub_out); s = e; } }); } std::string GatherOpHandle::Name() const { return "gather"; } } // namespace details } // namespace framework } // namespace paddle