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119 lines
4.3 KiB
119 lines
4.3 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/framework/details/gather_op_handle.h"
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#include "paddle/fluid/framework/details/container_cast.h"
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#include "paddle/fluid/framework/details/variable_visitor.h"
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namespace paddle {
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namespace framework {
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namespace details {
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GatherOpHandle::GatherOpHandle(ir::Node *node,
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const std::vector<Scope *> &local_scopes,
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const std::vector<platform::Place> &places)
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: OpHandleBase(node), local_scopes_(local_scopes), places_(places) {}
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void GatherOpHandle::RunImpl() {
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if (places_.size() == 1) return;
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// the input and output may have dummy var.
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auto in_var_handles = DynamicCast<VarHandle>(inputs_);
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PADDLE_ENFORCE_EQ(
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in_var_handles.size(), places_.size(),
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"The number of output should equal to the number of places.");
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VarHandle *out_var_handle;
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{
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auto out_var_handles = DynamicCast<VarHandle>(this->Outputs());
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PADDLE_ENFORCE_EQ(out_var_handles.size(), 1,
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"The number of output should be one.");
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out_var_handle = out_var_handles.front();
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}
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std::vector<const Scope *> var_scopes;
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for (auto *s : local_scopes_) {
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var_scopes.emplace_back(s->FindVar(kLocalExecScopeName)->Get<Scope *>());
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}
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auto in_0_handle = in_var_handles[0];
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auto pre_in_var =
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var_scopes.at(in_0_handle->scope_idx())->FindVar(in_0_handle->name());
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PADDLE_ENFORCE_NOT_NULL(pre_in_var);
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PADDLE_ENFORCE(pre_in_var->IsType<framework::SelectedRows>(),
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"Currently, gather_op only can gather SelectedRows.");
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// Wait input done, this Wait is asynchronous operation
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WaitInputVarGenerated();
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auto &pre_in_value = pre_in_var->Get<framework::SelectedRows>();
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std::vector<int64_t> out_rows;
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std::vector<Tensor> in_tensors;
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// Gather the inputs
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for (auto *in_handle : in_var_handles) {
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auto *in_var =
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var_scopes.at(in_handle->scope_idx())->FindVar(in_handle->name());
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PADDLE_ENFORCE_NOT_NULL(in_var);
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VariableVisitor::EnforceShapeAndDTypeEQ(*in_var, *pre_in_var);
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auto &in_sr_value = in_var->Get<framework::SelectedRows>();
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auto &in_sr_rows = in_sr_value.rows();
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out_rows.insert(out_rows.end(), in_sr_rows.begin(), in_sr_rows.end());
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in_tensors.emplace_back(in_sr_value.value());
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}
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// NOTE: The Places of all input tensor must be all on CPU or all on GPU.
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platform::Place t_out_p = out_var_handle->place();
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if (platform::is_gpu_place(pre_in_value.place())) {
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PADDLE_ENFORCE(platform::is_gpu_place(t_out_p),
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"Places of input and output must be all on GPU.");
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} else {
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t_out_p = platform::CPUPlace();
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}
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auto out_var = var_scopes.at(out_var_handle->scope_idx())
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->FindVar(out_var_handle->name());
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PADDLE_ENFORCE_NOT_NULL(out_var);
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auto out_value = out_var->GetMutable<framework::SelectedRows>();
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out_value->set_height(pre_in_value.height());
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out_value->set_rows(out_rows);
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size_t rows = out_rows.size();
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DDim out_dim = pre_in_value.GetCompleteDims();
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out_dim[0] = static_cast<int64_t>(rows);
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out_value->mutable_value()->Resize(out_dim).mutable_data(
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t_out_p, pre_in_value.value().type());
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Tensor *out_tensor = out_value->mutable_value();
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// copy
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auto dev_ctx = dev_ctxes_.at(out_var_handle->place());
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RunAndRecordEvent(out_var_handle->place(), [in_tensors, out_tensor, &dev_ctx,
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t_out_p] {
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int s = 0, e = 0;
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for (size_t j = 0; j < in_tensors.size(); ++j) {
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e += in_tensors[j].dims()[0];
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auto sub_out = out_tensor->Slice(s, e);
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paddle::framework::TensorCopy(in_tensors[j], t_out_p, *dev_ctx, &sub_out);
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s = e;
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}
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});
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}
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std::string GatherOpHandle::Name() const { return "gather"; }
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} // namespace details
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} // namespace framework
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} // namespace paddle
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