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体验新版 GitCode,发现更多精彩内容 >>
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b756063c
编写于
6月 27, 2018
作者:
Q
qingqing01
提交者:
GitHub
6月 27, 2018
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电子邮件补丁
差异文件
Speed depthwise transposed conv2d. (#11740)
* Speed depthwise transposed conv2d.
上级
8630ba2e
变更
5
显示空白变更内容
内联
并排
Showing
5 changed file
with
135 addition
and
24 deletion
+135
-24
paddle/fluid/operators/conv_transpose_op.cc
paddle/fluid/operators/conv_transpose_op.cc
+18
-0
paddle/fluid/operators/conv_transpose_op.cu.cc
paddle/fluid/operators/conv_transpose_op.cu.cc
+24
-21
paddle/fluid/operators/conv_transpose_op.h
paddle/fluid/operators/conv_transpose_op.h
+70
-0
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+10
-3
python/paddle/fluid/tests/unittests/test_conv2d_transpose_op.py
.../paddle/fluid/tests/unittests/test_conv2d_transpose_op.py
+13
-0
未找到文件。
paddle/fluid/operators/conv_transpose_op.cc
浏览文件 @
b756063c
...
...
@@ -302,6 +302,7 @@ framework::OpKernelType ConvTransposeOpGrad::GetExpectedKernelType(
namespace
ops
=
paddle
::
operators
;
// conv2d_transpose
REGISTER_OPERATOR
(
conv2d_transpose
,
ops
::
ConvTransposeOp
,
ops
::
Conv2DTransposeOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
...
...
@@ -317,6 +318,7 @@ REGISTER_OP_CPU_KERNEL(
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
// conv3d_transpose
REGISTER_OPERATOR
(
conv3d_transpose
,
ops
::
ConvTransposeOp
,
ops
::
Conv3DTransposeOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
...
...
@@ -331,3 +333,19 @@ REGISTER_OP_CPU_KERNEL(
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
// depthwise conv2d_transpose
REGISTER_OPERATOR
(
depthwise_conv2d_transpose
,
ops
::
ConvTransposeOp
,
ops
::
Conv2DTransposeOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
depthwise_conv2d_transpose_grad
,
ops
::
ConvTransposeOpGrad
);
REGISTER_OP_CPU_KERNEL
(
depthwise_conv2d_transpose
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
depthwise_conv2d_transpose_grad
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/fluid/operators/conv_transpose_op.cu.cc
浏览文件 @
b756063c
...
...
@@ -15,25 +15,28 @@ limitations under the License. */
#include "paddle/fluid/operators/conv_transpose_op.h"
namespace
ops
=
paddle
::
operators
;
using
CUDA
=
paddle
::
platform
::
CUDADeviceContext
;
REGISTER_OP_CUDA_KERNEL
(
conv2d_transpose
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
conv2d_transpose_grad
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
conv3d_transpose
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
GemmConvTransposeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
conv3d_transpose_grad
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
// conv2d
REGISTER_OP_CUDA_KERNEL
(
conv2d_transpose
,
ops
::
GemmConvTransposeKernel
<
CUDA
,
float
>
,
ops
::
GemmConvTransposeKernel
<
CUDA
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
conv2d_transpose_grad
,
ops
::
GemmConvTransposeGradKernel
<
CUDA
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
CUDA
,
double
>
);
// conv3d
REGISTER_OP_CUDA_KERNEL
(
conv3d_transpose
,
ops
::
GemmConvTransposeKernel
<
CUDA
,
float
>
,
ops
::
GemmConvTransposeKernel
<
CUDA
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
conv3d_transpose_grad
,
ops
::
GemmConvTransposeGradKernel
<
CUDA
,
float
>
,
ops
::
GemmConvTransposeGradKernel
<
CUDA
,
double
>
);
// depthwise conv2d
REGISTER_OP_CUDA_KERNEL
(
depthwise_conv2d_transpose
,
ops
::
DepthwiseConvTransposeKernel
<
CUDA
,
float
>
,
ops
::
DepthwiseConvTransposeKernel
<
CUDA
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
depthwise_conv2d_transpose_grad
,
ops
::
DepthwiseConvTransposeGradKernel
<
CUDA
,
float
>
,
ops
::
DepthwiseConvTransposeGradKernel
<
CUDA
,
double
>
);
paddle/fluid/operators/conv_transpose_op.h
浏览文件 @
b756063c
...
...
@@ -17,6 +17,7 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/depthwise_conv.h"
#include "paddle/fluid/operators/math/im2col.h"
#include "paddle/fluid/operators/math/vol2col.h"
...
...
@@ -316,5 +317,74 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
}
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
DepthwiseConvTransposeKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
Tensor
*
input
=
context
.
Input
<
Tensor
>
(
"Input"
);
Tensor
filter
=
*
context
.
Input
<
Tensor
>
(
"Filter"
);
Tensor
*
output
=
context
.
Output
<
Tensor
>
(
"Output"
);
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
groups
=
context
.
Attr
<
int
>
(
"groups"
);
PADDLE_ENFORCE_EQ
(
groups
,
filter
.
dims
()[
0
]);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
dilations
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"dilations"
);
for
(
auto
v
:
dilations
)
{
PADDLE_ENFORCE_EQ
(
v
,
1
);
}
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
&
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
math
::
SetConstant
<
DeviceContext
,
T
>
set_zero
;
set_zero
(
dev_ctx
,
output
,
static_cast
<
T
>
(
0
));
math
::
DepthwiseConvInputGradFunctor
<
DeviceContext
,
T
>
depthwiseConvInputGrad
;
depthwiseConvInputGrad
(
dev_ctx
,
*
output
,
filter
,
*
input
,
strides
,
paddings
,
output
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
DepthwiseConvTransposeGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
Tensor
*
input
=
context
.
Input
<
Tensor
>
(
"Input"
);
const
Tensor
*
output_grad
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Output"
));
Tensor
*
input_grad
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Input"
));
Tensor
*
filter_grad
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Filter"
));
Tensor
filter
=
*
context
.
Input
<
Tensor
>
(
"Filter"
);
if
(
!
input_grad
&&
!
filter_grad
)
return
;
auto
&
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
input_grad
)
{
math
::
DepthwiseConvFunctor
<
DeviceContext
,
T
>
depthwiseConv
;
depthwiseConv
(
dev_ctx
,
*
output_grad
,
filter
,
strides
,
paddings
,
input_grad
);
}
if
(
filter_grad
)
{
math
::
SetConstant
<
DeviceContext
,
T
>
set_zero
;
filter_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
set_zero
(
dev_ctx
,
filter_grad
,
static_cast
<
T
>
(
0
));
math
::
DepthwiseConvFilterGradFunctor
<
DeviceContext
,
T
>
depthwiseConvFilterGrad
;
depthwiseConvFilterGrad
(
dev_ctx
,
*
output_grad
,
*
input
,
strides
,
paddings
,
filter_grad
);
}
}
};
}
// namespace operators
}
// namespace paddle
python/paddle/fluid/layers/nn.py
浏览文件 @
b756063c
...
...
@@ -2334,10 +2334,17 @@ def conv2d_transpose(input,
data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32')
conv2d_transpose = fluid.layers.conv2d_transpose(input=data, num_filters=2, filter_size=3)
"""
helper
=
LayerHelper
(
"conv2d_transpose"
,
**
locals
())
input_channel
=
input
.
shape
[
1
]
op_type
=
'conv2d_transpose'
if
(
input_channel
==
groups
and
num_filters
==
input_channel
and
not
use_cudnn
):
op_type
=
'depthwise_conv2d_transpose'
helper
=
LayerHelper
(
op_type
,
**
locals
())
if
not
isinstance
(
input
,
Variable
):
raise
TypeError
(
"Input of conv2d_transpose must be Variable"
)
input_channel
=
input
.
shape
[
1
]
padding
=
utils
.
convert_to_list
(
padding
,
2
,
'padding'
)
stride
=
utils
.
convert_to_list
(
stride
,
2
,
'stride'
)
...
...
@@ -2371,7 +2378,7 @@ def conv2d_transpose(input,
pre_bias
=
helper
.
create_tmp_variable
(
dtype
=
input
.
dtype
)
helper
.
append_op
(
type
=
'conv2d_transpose'
,
type
=
op_type
,
inputs
=
{
'Input'
:
[
input
],
'Filter'
:
[
img_filter
]},
outputs
=
{
'Output'
:
pre_bias
},
...
...
python/paddle/fluid/tests/unittests/test_conv2d_transpose_op.py
浏览文件 @
b756063c
...
...
@@ -242,6 +242,19 @@ class TestCUDNNWithGroups(TestWithGroups):
self
.
op_type
=
"conv2d_transpose"
class
TestDepthwiseConvTranspose
(
TestConv2dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
dilations
=
[
1
,
1
]
self
.
input_size
=
[
2
,
8
,
16
,
16
]
# NCHW
self
.
groups
=
8
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
/
self
.
groups
self
.
filter_size
=
[
self
.
input_size
[
1
],
f_c
,
4
,
4
]
self
.
op_type
=
"depthwise_conv2d_transpose"
# Please Don't remove the following code.
# Currently, CI use cudnn V5.0 which not support dilation conv.
# class TestCUDNNWithDilation(TestWithDilation):
...
...
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