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.
127 lines
4.2 KiB
127 lines
4.2 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/transpose_op.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using framework::Tensor;
|
|
|
|
class TransposeOp : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
|
|
void InferShape(framework::InferShapeContext* ctx) const override {
|
|
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
|
|
PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
|
|
auto x_dims = ctx->GetInputDim("X");
|
|
std::vector<int> axis = ctx->Attrs().Get<std::vector<int>>("axis");
|
|
size_t x_rank = x_dims.size();
|
|
size_t axis_size = axis.size();
|
|
|
|
PADDLE_ENFORCE_EQ(x_rank, axis_size,
|
|
"The input tensor's rank(%d) "
|
|
"should be equal to the axis's size(%d)",
|
|
x_rank, axis_size);
|
|
|
|
std::vector<int> count(axis_size, 0);
|
|
for (size_t i = 0; i < axis_size; i++) {
|
|
PADDLE_ENFORCE(
|
|
axis[i] < static_cast<int>(axis_size) && ++count[axis[i]] == 1,
|
|
"Each element of Attribute axis should be a unique value "
|
|
"range from 0 to (dims - 1), "
|
|
"where the dims is the axis's size");
|
|
}
|
|
|
|
framework::DDim out_dims(x_dims);
|
|
for (size_t i = 0; i < axis_size; i++) {
|
|
out_dims[i] = x_dims[axis[i]];
|
|
}
|
|
ctx->SetOutputDim("Out", out_dims);
|
|
}
|
|
};
|
|
|
|
class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
|
|
public:
|
|
TransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
|
|
: OpProtoAndCheckerMaker(proto, op_checker) {
|
|
AddInput(
|
|
"X",
|
|
"(Tensor) The input tensor, tensors with rank up to 6 are supported.");
|
|
AddOutput("Out", "(Tensor)The output tensor.");
|
|
AddAttr<std::vector<int>>(
|
|
"axis",
|
|
"(vector<int>) A list of values, and the size of the list should be "
|
|
"the same with the input tensor rank. This operator permutes the input "
|
|
"tensor's axes according to the values given.");
|
|
AddComment(R"DOC(
|
|
Transpose Operator.
|
|
|
|
The input tensor will be permuted according to the axes given.
|
|
The behavior of this operator is similar to how `numpy.transpose` works.
|
|
|
|
- suppose the input `X` is a 2-D tensor:
|
|
$$
|
|
X = \begin{pmatrix}
|
|
0 &1 &2 \\
|
|
3 &4 &5
|
|
\end{pmatrix}$$
|
|
|
|
the given `axes` is: $[1, 0]$, and $Y$ = transpose($X$, axis)
|
|
|
|
then the output $Y$ is:
|
|
|
|
$$
|
|
Y = \begin{pmatrix}
|
|
0 &3 \\
|
|
1 &4 \\
|
|
2 &5
|
|
\end{pmatrix}$$
|
|
|
|
- Given a input tensor with shape $(N, C, H, W)$ and the `axes` is
|
|
$[0, 2, 3, 1]$, then shape of the output tensor will be: $(N, H, W, C)$.
|
|
|
|
)DOC");
|
|
}
|
|
};
|
|
|
|
class TransposeOpGrad : public framework::OperatorWithKernel {
|
|
public:
|
|
using framework::OperatorWithKernel::OperatorWithKernel;
|
|
|
|
void InferShape(framework::InferShapeContext* ctx) const override {
|
|
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
|
|
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
|
|
"Input(Out@GRAD) should not be null");
|
|
auto x_dims = ctx->GetInputDim("X");
|
|
ctx->SetOutputDim(framework::GradVarName("X"), x_dims);
|
|
if (ctx->HasOutput(framework::GradVarName("X"))) {
|
|
ctx->SetOutputDim(framework::GradVarName("X"), x_dims);
|
|
}
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OP(transpose, ops::TransposeOp, ops::TransposeOpMaker, transpose_grad,
|
|
ops::TransposeOpGrad);
|
|
REGISTER_OP_CPU_KERNEL(
|
|
transpose, ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>);
|
|
REGISTER_OP_CPU_KERNEL(
|
|
transpose_grad,
|
|
ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>);
|