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.
100 lines
3.1 KiB
100 lines
3.1 KiB
/* Copyright (c) 2016 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/operators/split_selected_rows_op.h"
|
|
|
|
#include <memory>
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
class SplitSelectedRowsOpMaker : public framework::OpProtoAndCheckerMaker {
|
|
public:
|
|
void Make() override {
|
|
AddInput("X", "The input SelectedRows.");
|
|
AddOutput("Out", "The outputs of the input SelectedRows.").AsDuplicable();
|
|
AddAttr<std::vector<int64_t>>("height_sections",
|
|
"Height for each output SelectedRows.")
|
|
.SetDefault(std::vector<int64_t>({}));
|
|
|
|
AddComment(R"DOC(
|
|
Split a SelectedRows with a specified rows section.
|
|
height_sections is only needed when need to split the dims of the original tensor.
|
|
|
|
Example:
|
|
Input:
|
|
X.rows = {7, 5}
|
|
X.height = 12
|
|
Attr:
|
|
height_sections = {4, 8}
|
|
Out:
|
|
out0.rows = {}
|
|
out0.height = 4
|
|
|
|
out1.rows = {5, 7}
|
|
out2.height = 8
|
|
|
|
)DOC");
|
|
}
|
|
};
|
|
|
|
class SplitSelectedRowsOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
|
|
void InferShape(framework::InferShapeContext *ctx) const override {
|
|
PADDLE_ENFORCE(ctx->HasInput("X"), "SplitSelectedRowsOp must has input X.");
|
|
PADDLE_ENFORCE(ctx->HasOutputs("Out"),
|
|
"SplitSelectedRowsOp must has output Out.");
|
|
}
|
|
};
|
|
|
|
class SplitSelectedRowsOpInferVarType : public framework::VarTypeInference {
|
|
public:
|
|
void operator()(framework::InferVarTypeContext *ctx) const override {
|
|
for (auto &out_var : ctx->Output("Out")) {
|
|
ctx->SetType(out_var, framework::proto::VarType::SELECTED_ROWS);
|
|
}
|
|
}
|
|
};
|
|
|
|
template <typename T>
|
|
class SplitSelectedRowsGradMaker : public framework::SingleGradOpMaker<T> {
|
|
public:
|
|
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
|
|
|
|
protected:
|
|
std::unique_ptr<T> Apply() const override {
|
|
auto *grad_op = new T();
|
|
grad_op->SetType("sum");
|
|
grad_op->SetInput("X", this->OutputGrad("Out"));
|
|
grad_op->SetOutput("Out", this->InputGrad("X"));
|
|
grad_op->SetAttrMap(this->Attrs());
|
|
return std::unique_ptr<T>(grad_op);
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OPERATOR(split_selected_rows, ops::SplitSelectedRowsOp,
|
|
ops::SplitSelectedRowsOpMaker,
|
|
ops::SplitSelectedRowsGradMaker<paddle::framework::OpDesc>,
|
|
ops::SplitSelectedRowsGradMaker<paddle::imperative::OpBase>,
|
|
ops::SplitSelectedRowsOpInferVarType);
|
|
REGISTER_OP_CPU_KERNEL(
|
|
split_selected_rows,
|
|
ops::SplitSelectedRowsOpKernel<paddle::platform::CPUPlace, float>);
|