Paddle/paddle/fluid/framework/details/broadcast_op_handle.cc

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3.5 KiB

// 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<Scope *> &local_scopes,
const std::vector<platform::Place> &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<VarHandle *>(this->inputs_[0]);
auto &in_place = in_var_handle->place_;
if (inputs_[0]->generated_op_)
inputs_[0]->generated_op_->Wait(dev_ctxes_[in_place]);
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<VarHandle *>(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<framework::SelectedRows>()) {
auto &in_sr = in_var->Get<framework::SelectedRows>();
auto out_sr = out_var->GetMutable<framework::SelectedRows>();
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<framework::LoDTensor>()) {
auto in_lod = in_var->Get<framework::LoDTensor>();
auto out_lod = out_var->GetMutable<framework::LoDTensor>();
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);
paddle::framework::TensorCopy(*in_tensor, out_p, *(dev_ctxes_[in_place]),
out_tensor);
}
}
std::string BroadcastOpHandle::Name() const { return "broadcast"; }
} // namespace details
} // namespace framework
} // namespace paddle