You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
104 lines
3.7 KiB
104 lines
3.7 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 <string>
|
|
#include <vector>
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
class ExtractRowsOpInferShape : public framework::InferShapeBase {
|
|
public:
|
|
void operator()(framework::InferShapeContext *ctx) const override {
|
|
PADDLE_ENFORCE(ctx->HasInput("X"),
|
|
"Input(X) of ExtractRowsOp should not be null.");
|
|
PADDLE_ENFORCE(ctx->HasOutput("Out"),
|
|
"Output(Out) of ExtractRowsOp should not be null.");
|
|
PADDLE_ENFORCE_EQ(ctx->GetInputsVarType("X")[0],
|
|
framework::proto::VarType::SELECTED_ROWS,
|
|
"The type of input(X) must be SelectedRows.");
|
|
auto in_dims = ctx->GetInputDim("X");
|
|
|
|
ctx->SetOutputDim(
|
|
"Out", framework::make_ddim(std::vector<int64_t>{in_dims[0], 1}));
|
|
}
|
|
};
|
|
|
|
class ExtractRowsOp : public framework::OperatorBase {
|
|
public:
|
|
ExtractRowsOp(const std::string &type,
|
|
const framework::VariableNameMap &inputs,
|
|
const framework::VariableNameMap &outputs,
|
|
const framework::AttributeMap &attrs)
|
|
: framework::OperatorBase(type, inputs, outputs, attrs) {}
|
|
|
|
private:
|
|
void RunImpl(const framework::Scope &scope,
|
|
const platform::Place &place) const override {
|
|
auto &in = scope.FindVar(Input("X"))->Get<framework::SelectedRows>();
|
|
auto out = scope.FindVar(Output("Out"))->GetMutable<framework::LoDTensor>();
|
|
|
|
auto in_rows = in.rows();
|
|
auto out_dim = framework::make_ddim(
|
|
std::vector<int64_t>{static_cast<int64_t>(in_rows.size()), 1});
|
|
auto dst_ptr = out->mutable_data<int64_t>(out_dim, in.place());
|
|
|
|
if (paddle::platform::is_gpu_place(in.place())) {
|
|
#ifdef PADDLE_WITH_CUDA
|
|
platform::DeviceContextPool &pool =
|
|
platform::DeviceContextPool::Instance();
|
|
auto *dev_ctx = pool.Get(in.place());
|
|
auto src_ptr = in_rows.Data(in.place());
|
|
auto stream =
|
|
reinterpret_cast<const platform::CUDADeviceContext &>(*dev_ctx)
|
|
.stream();
|
|
memory::Copy(boost::get<platform::CUDAPlace>(out->place()), dst_ptr,
|
|
boost::get<platform::CUDAPlace>(in.place()), src_ptr,
|
|
in_rows.size() * sizeof(int64_t), stream);
|
|
#else
|
|
PADDLE_THROW("Not compiled with CUDA.");
|
|
#endif
|
|
} else {
|
|
memory::Copy(platform::CPUPlace(), dst_ptr, platform::CPUPlace(),
|
|
in_rows.data(), in_rows.size() * sizeof(int64_t));
|
|
}
|
|
}
|
|
};
|
|
|
|
class ExtractRowsOpMaker : public framework::OpProtoAndCheckerMaker {
|
|
public:
|
|
void Make() override {
|
|
AddInput("X",
|
|
"(SelectedRows). The input tensor of extract_rows operator,"
|
|
" and its type is SelectedRows.");
|
|
AddOutput("Out", "(Tensor). The the rows of input(X).");
|
|
|
|
AddComment(R"DOC(
|
|
ExtractRows Operator.
|
|
|
|
The function of extract_rows_op is extracting the rows from the input(X)
|
|
whose type is SelectedRows.
|
|
|
|
)DOC");
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OPERATOR(extract_rows, ops::ExtractRowsOp, ops::ExtractRowsOpMaker,
|
|
ops::ExtractRowsOpInferShape);
|