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652f182d
编写于
10月 13, 2017
作者:
Z
zchen0211
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电子邮件补丁
差异文件
deconv
上级
da399ae6
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
141 addition
and
81 deletion
+141
-81
paddle/operators/deconv2d_op.cc
paddle/operators/deconv2d_op.cc
+66
-81
paddle/operators/deconv2d_op.cu
paddle/operators/deconv2d_op.cu
+23
-0
paddle/operators/deconv2d_op.h
paddle/operators/deconv2d_op.h
+52
-0
未找到文件。
paddle/operators/deconv2d_op.cc
浏览文件 @
652f182d
...
...
@@ -12,97 +12,82 @@
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/gemm_conv2d_op.h"
#include "paddle/operators/deconv2d_op.h"
#include "paddle/operators/conv2d_op.h"
namespace
paddle
{
namespace
operators
{
class
Deconv2DOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Input"
),
"Input(Input) of Deconv2DOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Filter"
),
"Input(Filter) of Deconv2DOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Output"
),
"Output(Output) of Deconv2DOp should not be null."
);
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
auto
filter_dims
=
ctx
->
GetInputDim
(
"Filter"
);
std
::
vector
<
int
>
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
int
groups
=
ctx
->
Attrs
().
Get
<
int
>
(
"groups"
);
int
input_channels
=
in_dims
[
1
];
int
output_channels
=
filter_dims
[
0
];
PADDLE_ENFORCE_EQ
(
in_dims
.
size
(),
4
,
"Conv2DOp input should be 4-D."
);
PADDLE_ENFORCE_EQ
(
filter_dims
.
size
(),
4
,
"Conv2DOp filter should be 4-D."
);
PADDLE_ENFORCE_EQ
(
input_channels
,
filter_dims
[
1
]
*
groups
,
"The number of input channels should be equal to filter "
"channels * groups."
);
PADDLE_ENFORCE_EQ
(
output_channels
%
groups
,
0
,
"The number of output channels should be divided by groups."
);
auto
output_height
=
(
in_dims
[
2
]
-
1
)
*
strides
[
0
]
+
filter_dims
[
2
];
auto
output_width
=
(
in_dims
[
3
]
-
1
)
*
strides
[
1
]
+
filter_dims
[
3
];
ctx
->
SetOutputDim
(
"Output"
,
{
in_dims
[
0
],
filter_dims
[
0
],
output_height
,
output_width
});
}
};
class
Deconv2DOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Deconv2DOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"Input"
,
"The input tensor of deconvolution operator. "
"The format of input tensor is NCHW. Where N is batch size, C is the "
"number of channels, H and W is the height and width of image."
);
AddInput
(
"Filter"
,
"The filter tensor of deconvolution operator."
"The format of the filter tensor is MCHW, where M is the number of "
"output image channels, C is the number of input image channels, "
"H and W is height and width of filter. "
"We enforce groups number == 1 and padding == 0 in our deconvolution
Scenario."
);
AddOutput
(
"Output"
,
"The output tensor of deconvolution operator."
"The format of output tensor is also NCHW."
);
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
"strides of deconvolution operator."
)
.
SetDefault
({
1
,
1
});
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
"paddings of deconvolution operator."
)
.
SetDefault
({
0
,
0
});
AddComment
(
R"DOC(
void
Deconv2DOp
::
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Input"
),
"Input(Input) of Deconv2DOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Filter"
),
"Input(Filter) of Deconv2DOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Output"
),
"Output(Output) of Deconv2DOp should not be null."
);
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
auto
filter_dims
=
ctx
->
GetInputDim
(
"Filter"
);
std
::
vector
<
int
>
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
int
groups
=
ctx
->
Attrs
().
Get
<
int
>
(
"groups"
);
int
input_channels
=
in_dims
[
1
];
int
output_channels
=
filter_dims
[
0
];
PADDLE_ENFORCE_EQ
(
in_dims
.
size
(),
4
,
"Conv2DOp input should be 4-D."
);
PADDLE_ENFORCE_EQ
(
filter_dims
.
size
(),
4
,
"Conv2DOp filter should be 4-D."
);
PADDLE_ENFORCE_EQ
(
input_channels
,
filter_dims
[
1
]
*
groups
,
"The number of input channels should be equal to filter "
"channels * groups."
);
PADDLE_ENFORCE_EQ
(
output_channels
%
groups
,
0
,
"The number of output channels should be divided by groups."
);
auto
output_height
=
(
in_dims
[
2
]
-
1
)
*
strides
[
0
]
+
filter_dims
[
2
];
auto
output_width
=
(
in_dims
[
3
]
-
1
)
*
strides
[
1
]
+
filter_dims
[
3
];
ctx
->
SetOutputDim
(
"Output"
,
{
in_dims
[
0
],
filter_dims
[
0
],
output_height
,
output_width
});
}
Deconv2DOpMaker
::
Deconv2DOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"Input"
,
"The input tensor of deconvolution operator. "
"The format of input tensor is NCHW. Where N is batch size, C is the "
"number of channels, H and W is the height and width of image."
);
AddInput
(
"Filter"
,
"The filter tensor of deconvolution operator."
"The format of the filter tensor is MCHW, where M is the number of "
"output image channels, C is the number of input image channels, "
"H and W is height and width of filter. "
"We enforce groups number == 1 and padding == 0 in our "
"deconvolution Scenario."
);
AddOutput
(
"Output"
,
"The output tensor of deconvolution operator."
"The format of output tensor is also NCHW."
);
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
"strides of deconvolution operator."
)
.
SetDefault
({
1
,
1
});
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
"paddings of deconvolution operator."
)
.
SetDefault
({
0
,
0
});
AddComment
(
R"DOC(
The deconvolution operation calculates the output based on the input, filter
and strides, paddings, groups parameters. The size of each dimension of the
parameters is checked in the infer-shape.
)DOC"
);
}
};
}
class
Deconv2DOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
auto
filter_dims
=
ctx
->
GetInputDim
(
"Filter"
);
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Input"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Input"
),
in_dims
);
}
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Filter"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Filter"
),
filter_dims
);
}
void
Deconv2DOpGrad
::
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
{
auto
in_dims
=
ctx
->
GetInputDim
(
"Input"
);
auto
filter_dims
=
ctx
->
GetInputDim
(
"Filter"
);
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Input"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Input"
),
in_dims
);
}
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Filter"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Filter"
),
filter_dims
);
}
}
;
}
}
// namespace operators
}
// namespace paddle
...
...
paddle/operators/deconv2d_op.cu
0 → 100644
浏览文件 @
652f182d
/* Copyright (c) 2016 PaddlePaddle Authors All Rights Reserve.
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/operators/conv2d_op.h"
#include "paddle/operators/deconv2d_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_GPU_KERNEL
(
deconv2d
,
ops
::
GemmConvGrad2DKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
deconv2d_grad
,
ops
::
GemmConv2DKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
paddle/operators/deconv2d_op.h
0 → 100644
浏览文件 @
652f182d
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#pragma once
#include "paddle/framework/eigen.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/math/im2col.h"
#include "paddle/operators/math/math_function.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
// Define Op classes in .h file so that other deconv
// operator implementations can reuse the code.
class
Deconv2DOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Deconv2DOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
);
};
class
Deconv2DOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
;
};
class
Deconv2DOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
;
};
}
// namespace operators
}
// namespace paddle
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