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

140 lines
5.2 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/gather_op_handle.h"
#include "paddle/fluid/framework/details/container_cast.h"
#include "paddle/fluid/framework/details/variable_visitor.h"
namespace paddle {
namespace framework {
class Tensor;
} // namespace framework
} // namespace paddle
namespace paddle {
namespace framework {
namespace details {
GatherOpHandle::GatherOpHandle(ir::Node *node,
const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places)
: OpHandleBase(node), 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<VarHandle>(inputs_);
PADDLE_ENFORCE_EQ(
in_var_handles.size(), places_.size(),
platform::errors::InvalidArgument(
"The number of input variables should be equal "
"to the number of places, but got the number of input variables is "
"%d and the number of places is %d.",
in_var_handles.size(), places_.size()));
VarHandle *out_var_handle;
{
auto out_var_handles = DynamicCast<VarHandle>(this->Outputs());
PADDLE_ENFORCE_EQ(
out_var_handles.size(), 1,
platform::errors::InvalidArgument(
"The number of output variables should be 1, but got %d.",
out_var_handles.size()));
out_var_handle = out_var_handles.front();
}
auto &var_scopes = local_exec_scopes_;
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,
platform::errors::NotFound("The variable '%s' is not found in the scope.",
in_0_handle->name()));
PADDLE_ENFORCE_EQ(pre_in_var->IsType<framework::SelectedRows>(), true,
platform::errors::Unimplemented(
"Currently, gather_op only supports SelectedRows."));
// Wait input done, this Wait is asynchronous operation
WaitInputVarGenerated();
auto &pre_in_value = pre_in_var->Get<framework::SelectedRows>();
std::vector<int64_t> out_rows;
std::vector<Tensor> 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,
platform::errors::NotFound(
"The variable '%s' is not found in the scope.", in_handle->name()));
VariableVisitor::EnforceShapeAndDTypeEQ(*in_var, *pre_in_var);
auto &in_sr_value = in_var->Get<framework::SelectedRows>();
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_EQ(platform::is_gpu_place(t_out_p), true,
platform::errors::PreconditionNotMet(
"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,
platform::errors::NotFound("The variable '%s' is not found in the scope.",
out_var_handle->name()));
auto out_value = out_var->GetMutable<framework::SelectedRows>();
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<int64_t>(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_.at(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