Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
271fc9c1
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
大约 1 年 前同步成功
通知
694
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
271fc9c1
编写于
11月 10, 2017
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add dilation for vol2col
上级
93551bd2
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
189 addition
and
70 deletion
+189
-70
paddle/operators/conv_op.h
paddle/operators/conv_op.h
+8
-7
paddle/operators/conv_transpose_op.h
paddle/operators/conv_transpose_op.h
+8
-5
paddle/operators/math/im2col.cu
paddle/operators/math/im2col.cu
+1
-0
paddle/operators/math/vol2col.cc
paddle/operators/math/vol2col.cc
+64
-16
paddle/operators/math/vol2col.cu
paddle/operators/math/vol2col.cu
+101
-38
paddle/operators/math/vol2col.h
paddle/operators/math/vol2col.h
+2
-0
paddle/operators/math/vol2col_test.cc
paddle/operators/math/vol2col_test.cc
+5
-4
未找到文件。
paddle/operators/conv_op.h
浏览文件 @
271fc9c1
...
...
@@ -165,9 +165,9 @@ class GemmConvKernel : public framework::OpKernel<T> {
}
else
if
(
filter_shape_vec
.
size
()
==
3
)
{
// vol2col
math
::
Vol2ColFunctor
<
Place
,
T
>
vol2col
;
vol2col
(
context
.
device_context
(),
in_slice
,
col
,
stride
s
[
0
],
strides
[
1
],
strides
[
2
],
paddings
[
0
],
padding
s
[
1
],
paddings
[
2
]);
vol2col
(
context
.
device_context
(),
in_slice
,
col
,
dilation
s
[
0
],
dilations
[
1
],
dilations
[
2
],
strides
[
0
],
stride
s
[
1
],
strides
[
2
],
paddings
[
0
],
paddings
[
1
],
paddings
[
2
]);
}
// gemm
...
...
@@ -314,7 +314,8 @@ class GemmConvGradKernel : public framework::OpKernel<T> {
}
else
if
(
filter_shape_vec
.
size
()
==
3
)
{
math
::
Col2VolFunctor
<
Place
,
T
>
col2vol
;
col2vol
(
context
.
device_context
(),
in_grad_slice
,
col
,
strides
[
0
],
col2vol
(
context
.
device_context
(),
in_grad_slice
,
col
,
dilations
[
0
],
dilations
[
1
],
dilations
[
2
],
strides
[
0
],
strides
[
1
],
strides
[
2
],
paddings
[
0
],
paddings
[
1
],
paddings
[
2
]);
}
...
...
@@ -371,9 +372,9 @@ class GemmConvGradKernel : public framework::OpKernel<T> {
paddings
[
0
],
paddings
[
1
],
paddings
[
1
]);
}
else
if
(
filter_shape_vec
.
size
()
==
3
)
{
math
::
Vol2ColFunctor
<
Place
,
T
>
vol2col
;
vol2col
(
context
.
device_context
(),
in_slice
,
col
,
stride
s
[
0
],
strides
[
1
],
strides
[
2
],
paddings
[
0
],
padding
s
[
1
],
paddings
[
2
]);
vol2col
(
context
.
device_context
(),
in_slice
,
col
,
dilation
s
[
0
],
dilations
[
1
],
dilations
[
2
],
strides
[
0
],
stride
s
[
1
],
strides
[
2
],
paddings
[
0
],
paddings
[
1
],
paddings
[
2
]);
}
// gemm
...
...
paddle/operators/conv_transpose_op.h
浏览文件 @
271fc9c1
...
...
@@ -69,6 +69,7 @@ class GemmConvTransposeKernel : public framework::OpKernel<T> {
// TODO(Zhuoyuan): Paddings can be added in future.
// groups will alway be disabled in conv2dtranspose.
int
dilaiton_d
=
1
;
int
dilation_h
=
1
;
int
dilation_w
=
1
;
...
...
@@ -149,8 +150,9 @@ class GemmConvTransposeKernel : public framework::OpKernel<T> {
// col2vol: col_matrix -> dy
// from (c * k_d * k_h * k_w, d * h * w) to (c, o_d, o_h, o_w)
math
::
Col2VolFunctor
<
Place
,
T
>
col2vol
;
col2vol
(
context
.
device_context
(),
output_batch
,
col
,
strides
[
0
],
strides
[
1
],
strides
[
2
],
0
,
0
,
0
);
col2vol
(
context
.
device_context
(),
output_batch
,
col
,
dilaiton_d
,
dilation_h
,
dilation_w
,
strides
[
0
],
strides
[
1
],
strides
[
2
],
0
,
0
,
0
);
}
}
}
...
...
@@ -177,6 +179,7 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
// Actually, no paddings and groups allowed in conv transpose.
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
int
dilaiton_d
=
1
;
int
dilation_h
=
1
;
int
dilation_w
=
1
;
...
...
@@ -261,9 +264,9 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
// vol2col: dy -> col_matrix
// from (c, o_d, o_h, o_w) to (c * k_d * k_h * k_w, d * h * w)
math
::
Vol2ColFunctor
<
Place
,
T
>
vol2col
;
vol2col
(
context
.
device_context
(),
output_grad_batch
,
col
,
strides
[
0
]
,
strides
[
1
],
strides
[
2
],
paddings
[
0
],
paddings
[
1
],
paddings
[
2
]);
vol2col
(
context
.
device_context
(),
output_grad_batch
,
col
,
dilaiton_d
,
dilation_h
,
dilation_w
,
strides
[
0
],
strides
[
1
],
strides
[
2
],
paddings
[
0
],
paddings
[
1
],
paddings
[
2
]);
}
if
(
input_grad
)
{
...
...
paddle/operators/math/im2col.cu
浏览文件 @
271fc9c1
...
...
@@ -145,6 +145,7 @@ __global__ void col2im(int n, const T* data_col, int im_height, int im_width,
h_col
)
*
col_width
+
w_col
;
val
+=
data_col
[
data_col_index
];
}
}
...
...
paddle/operators/math/vol2col.cc
浏览文件 @
271fc9c1
...
...
@@ -29,6 +29,7 @@ class Vol2ColFunctor<platform::CPUPlace, T> {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
vol
,
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
{
...
...
@@ -48,6 +49,28 @@ class Vol2ColFunctor<platform::CPUPlace, T> {
int
channels_col
=
input_channels
*
filter_depth
*
filter_height
*
filter_width
;
PADDLE_ENFORCE_EQ
((
input_depth
+
2
*
padding_depth
-
((
dilation_d
*
(
filter_depth
-
1
)
+
1
)))
/
stride_depth
+
1
,
output_depth
,
"input_depth and output_depth are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_height
+
2
*
padding_height
-
((
dilation_h
*
(
filter_height
-
1
)
+
1
)))
/
stride_height
+
1
,
output_height
,
"input_height and output_height are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_width
+
2
*
padding_width
-
((
dilation_w
*
(
filter_width
-
1
)
+
1
)))
/
stride_width
+
1
,
output_width
,
"input_width and output_width are "
"Mismatching."
);
const
T
*
vol_data
=
vol
.
data
<
T
>
();
T
*
col_data
=
col
.
data
<
T
>
();
...
...
@@ -57,24 +80,25 @@ class Vol2ColFunctor<platform::CPUPlace, T> {
int
d_offset
=
(
c
/
filter_width
/
filter_height
)
%
filter_depth
;
int
c_in
=
c
/
filter_width
/
filter_height
/
filter_depth
;
for
(
int
d
=
0
;
d
<
output_depth
;
++
d
)
{
int
d_pad
=
d
*
stride_depth
-
padding_depth
+
d_offset
;
int
d_pad
=
d
*
stride_depth
-
padding_depth
+
d_offset
*
dilation_d
;
for
(
int
h
=
0
;
h
<
output_height
;
++
h
)
{
int
h_pad
=
h
*
stride_height
-
padding_height
+
h_offset
;
int
h_pad
=
h
*
stride_height
-
padding_height
+
h_offset
*
dilation_h
;
for
(
int
w
=
0
;
w
<
output_width
;
++
w
)
{
int
w_pad
=
w
*
stride_width
-
padding_width
+
w_offset
;
int
w_pad
=
w
*
stride_width
-
padding_width
+
w_offset
*
dilation_w
;
int
col_idx
=
((
c
*
output_depth
+
d
)
*
output_height
+
h
)
*
output_width
+
w
;
if
(
h_pad
<
0
||
h_pad
>=
input_height
||
w_pad
<
0
||
w_pad
>=
input_width
||
d_pad
<
0
||
d_pad
>=
input_depth
)
{
col_data
[
col_idx
]
=
static_cast
<
T
>
(
0
);
}
else
{
int
vol_idx
=
((
c_in
*
input_depth
+
d_pad
)
*
input_height
+
h_pad
)
*
input_width
+
w_pad
;
col_data
[
col_idx
]
=
vol_data
[
vol_idx
];
}
int
vol_idx
=
((
c_in
*
input_depth
+
d_pad
)
*
input_height
+
h_pad
)
*
input_width
+
w_pad
;
col_data
[
col_idx
]
=
(
h_pad
<
0
||
h_pad
>=
input_height
||
w_pad
<
0
||
w_pad
>=
input_width
||
d_pad
<
0
||
d_pad
>=
input_depth
)
?
static_cast
<
T
>
(
0
)
:
vol_data
[
vol_idx
];
}
}
}
...
...
@@ -93,6 +117,7 @@ class Col2VolFunctor<platform::CPUPlace, T> {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
framework
::
Tensor
&
vol
,
const
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
{
...
...
@@ -112,6 +137,27 @@ class Col2VolFunctor<platform::CPUPlace, T> {
int
channels_col
=
input_channels
*
filter_depth
*
filter_height
*
filter_width
;
PADDLE_ENFORCE_EQ
((
input_depth
+
2
*
padding_depth
-
((
dilation_d
*
(
filter_depth
-
1
)
+
1
)))
/
stride_depth
+
1
,
output_depth
,
"input_depth and output_depth are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_height
+
2
*
padding_height
-
((
dilation_h
*
(
filter_height
-
1
)
+
1
)))
/
stride_height
+
1
,
output_height
,
"input_height and output_height are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_width
+
2
*
padding_width
-
((
dilation_w
*
(
filter_width
-
1
)
+
1
)))
/
stride_width
+
1
,
output_width
,
"input_width and output_width are "
"Mismatching."
);
T
*
vol_data
=
vol
.
data
<
T
>
();
const
T
*
col_data
=
col
.
data
<
T
>
();
...
...
@@ -121,11 +167,13 @@ class Col2VolFunctor<platform::CPUPlace, T> {
int
d_offset
=
(
c
/
filter_width
/
filter_height
)
%
filter_depth
;
int
cIm
=
c
/
filter_width
/
filter_height
/
filter_depth
;
for
(
int
d
=
0
;
d
<
output_depth
;
++
d
)
{
int
d_pad
=
d
*
stride_depth
-
padding_depth
+
d_offset
;
int
d_pad
=
d
*
stride_depth
-
padding_depth
+
d_offset
*
dilation_d
;
for
(
int
h
=
0
;
h
<
output_height
;
++
h
)
{
int
h_pad
=
h
*
stride_height
-
padding_height
+
h_offset
;
int
h_pad
=
h
*
stride_height
-
padding_height
+
h_offset
*
dilation_h
;
for
(
int
w
=
0
;
w
<
output_width
;
++
w
)
{
int
w_pad
=
w
*
stride_width
-
padding_width
+
w_offset
;
int
w_pad
=
w
*
stride_width
-
padding_width
+
w_offset
*
dilation_w
;
if
(
h_pad
>=
0
&&
h_pad
<
input_height
&&
w_pad
>=
0
&&
w_pad
<
input_width
&&
d_pad
>=
0
&&
d_pad
<
input_depth
)
{
...
...
paddle/operators/math/vol2col.cu
浏览文件 @
271fc9c1
...
...
@@ -21,11 +21,12 @@ namespace math {
template
<
class
T
>
__global__
void
vol2col
(
int
num_kernels
,
const
T
*
data_vol
,
int
depth
,
int
height
,
int
width
,
int
filter_depth
,
int
filter_height
,
int
filter_width
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
,
int
output_detph
,
int
output_height
,
int
output_width
,
T
*
data_col
)
{
int
height
,
int
width
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
filter_depth
,
int
filter_height
,
int
filter_width
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
,
int
output_detph
,
int
output_height
,
int
output_width
,
T
*
data_col
)
{
for
(
int
index
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
index
<
num_kernels
;
index
+=
blockDim
.
x
*
gridDim
.
x
)
{
int
w_out
=
index
%
output_width
;
...
...
@@ -44,12 +45,14 @@ __global__ void vol2col(int num_kernels, const T* data_vol, int depth,
for
(
int
k
=
0
;
k
<
filter_depth
;
++
k
)
{
for
(
int
i
=
0
;
i
<
filter_height
;
++
i
)
{
for
(
int
j
=
0
;
j
<
filter_width
;
++
j
)
{
int
d
=
d_in
+
k
;
int
h
=
h_in
+
i
;
int
w
=
w_in
+
j
;
int
d
=
d_in
+
k
*
dilation_d
;
int
h
=
h_in
+
i
*
dilation_h
;
int
w
=
w_in
+
j
*
dilation_w
;
int
col_idx
=
(
k
*
dilation_d
*
height
+
i
*
dilation_h
)
*
width
+
j
*
dilation_w
;
*
data_col
=
(
d
>=
0
&&
d
<
depth
&&
h
>=
0
&&
h
<
height
&&
w
>=
0
&&
w
<
width
)
?
data_vol
[
(
k
*
height
+
i
)
*
width
+
j
]
?
data_vol
[
col_idx
]
:
0
;
data_col
+=
output_detph
*
output_height
*
output_width
;
}
...
...
@@ -69,6 +72,7 @@ class Vol2ColFunctor<platform::GPUPlace, T> {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
vol
,
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
{
...
...
@@ -86,6 +90,28 @@ class Vol2ColFunctor<platform::GPUPlace, T> {
int
output_height
=
col
.
dims
()[
5
];
int
output_width
=
col
.
dims
()[
6
];
PADDLE_ENFORCE_EQ
((
input_depth
+
2
*
padding_depth
-
((
dilation_d
*
(
filter_depth
-
1
)
+
1
)))
/
stride_depth
+
1
,
output_depth
,
"input_depth and output_depth are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_height
+
2
*
padding_height
-
((
dilation_h
*
(
filter_height
-
1
)
+
1
)))
/
stride_height
+
1
,
output_height
,
"input_height and output_height are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_width
+
2
*
padding_width
-
((
dilation_w
*
(
filter_width
-
1
)
+
1
)))
/
stride_width
+
1
,
output_width
,
"input_width and output_width are "
"Mismatching."
);
int
num_outputs
=
input_channels
*
output_depth
*
output_height
*
output_width
;
...
...
@@ -95,19 +121,25 @@ class Vol2ColFunctor<platform::GPUPlace, T> {
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
context
)
.
stream
()
>>>
(
num_outputs
,
vol
.
data
<
T
>
(),
input_depth
,
input_height
,
input_width
,
filter_depth
,
filter_height
,
filter_width
,
stride_depth
,
stride_height
,
stride_width
,
padding_depth
,
padding_height
,
padding_width
,
output_depth
,
output_height
,
output_width
,
col
.
data
<
T
>
());
dilation_d
,
dilation_h
,
dilation_w
,
filter_depth
,
filter_height
,
filter_width
,
stride_depth
,
stride_height
,
stride_width
,
padding_depth
,
padding_height
,
padding_width
,
output_depth
,
output_height
,
output_width
,
col
.
data
<
T
>
());
}
};
template
<
class
T
>
__global__
void
col2vol
(
int
num_kernels
,
const
T
*
data_col
,
int
depth
,
int
height
,
int
width
,
int
filter_depth
,
int
filter_height
,
int
filter_width
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
,
int
output_detph
,
int
output_height
,
int
output_width
,
T
*
data_vol
)
{
int
height
,
int
width
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
filter_depth
,
int
filter_height
,
int
filter_width
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
,
int
output_detph
,
int
output_height
,
int
output_width
,
T
*
data_vol
)
{
const
int
d_filter_depth
=
dilation_d
*
(
filter_depth
-
1
)
+
1
;
const
int
d_filter_height
=
dilation_h
*
(
filter_height
-
1
)
+
1
;
const
int
d_filter_width
=
dilation_w
*
(
filter_width
-
1
)
+
1
;
for
(
int
index
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
index
<
num_kernels
;
index
+=
blockDim
.
x
*
gridDim
.
x
)
{
T
src_val
=
0
;
...
...
@@ -115,35 +147,42 @@ __global__ void col2vol(int num_kernels, const T* data_col, int depth,
int
h
=
(
index
/
width
)
%
height
+
padding_height
;
int
d
=
(
index
/
width
/
height
)
%
depth
+
padding_depth
;
int
c
=
index
/
width
/
height
/
depth
;
// compute the start and end of the output
int
w_col_start
=
(
w
<
filter_width
)
?
0
:
(
w
-
filter_width
)
/
stride_width
+
1
;
(
w
<
d_filter_width
)
?
0
:
(
w
-
d_
filter_width
)
/
stride_width
+
1
;
int
w_col_end
=
min
(
w
/
stride_width
+
1
,
output_width
);
int
h_col_start
=
(
h
<
filter_height
)
?
0
:
(
h
-
filter_height
)
/
stride_height
+
1
;
(
h
<
d_filter_height
)
?
0
:
(
h
-
d_
filter_height
)
/
stride_height
+
1
;
int
h_col_end
=
min
(
h
/
stride_height
+
1
,
output_height
);
int
d_col_start
=
(
d
<
filter_depth
)
?
0
:
(
d
-
filter_depth
)
/
stride_depth
+
1
;
(
d
<
d_filter_depth
)
?
0
:
(
d
-
d_
filter_depth
)
/
stride_depth
+
1
;
int
d_col_end
=
min
(
d
/
stride_depth
+
1
,
output_detph
);
int
offset
=
(
c
*
filter_depth
*
filter_height
*
filter_width
+
d
*
filter_width
*
filter_height
+
h
*
filter_width
+
w
)
*
output_detph
*
output_height
*
output_width
;
int
coeff_d_col
=
(
1
-
stride_depth
*
filter_width
*
filter_height
*
output_detph
)
*
output_height
*
output_width
;
int
coeff_h_col
=
(
1
-
stride_height
*
filter_width
*
output_detph
*
output_height
)
*
output_width
;
int
coeff_w_col
=
(
1
-
stride_width
*
output_detph
*
output_height
*
output_width
);
for
(
int
d_col
=
d_col_start
;
d_col
<
d_col_end
;
++
d_col
)
{
for
(
int
h_col
=
h_col_start
;
h_col
<
h_col_end
;
++
h_col
)
{
for
(
int
w_col
=
w_col_start
;
w_col
<
w_col_end
;
++
w_col
)
{
src_val
+=
data_col
[
offset
+
d_col
*
coeff_d_col
+
h_col
*
coeff_h_col
+
w_col
*
coeff_w_col
];
int
d_off
=
(
d
-
d_col
*
stride_depth
);
int
h_off
=
(
h
-
h_col
*
stride_height
);
int
w_off
=
(
w
-
w_col
*
stride_width
);
if
(
d_off
%
dilation_d
==
0
&&
h_off
%
dilation_h
==
0
&&
w_off
%
dilation_w
==
0
)
{
d_off
/=
dilation_d
;
h_off
/=
dilation_h
;
w_off
/=
dilation_w
;
int
data_col_index
=
(((((
c
*
filter_depth
+
d_off
)
*
filter_height
+
h_off
)
*
filter_width
+
w_off
)
*
output_detph
+
d_col
)
*
output_height
+
h_col
)
*
output_width
+
w_col
;
src_val
+=
data_col
[
data_col_index
];
}
}
}
}
...
...
@@ -162,6 +201,7 @@ class Col2VolFunctor<platform::GPUPlace, T> {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
framework
::
Tensor
&
vol
,
const
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
{
...
...
@@ -179,6 +219,28 @@ class Col2VolFunctor<platform::GPUPlace, T> {
int
output_height
=
col
.
dims
()[
5
];
int
output_width
=
col
.
dims
()[
6
];
PADDLE_ENFORCE_EQ
((
input_depth
+
2
*
padding_depth
-
((
dilation_d
*
(
filter_depth
-
1
)
+
1
)))
/
stride_depth
+
1
,
output_depth
,
"input_depth and output_depth are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_height
+
2
*
padding_height
-
((
dilation_h
*
(
filter_height
-
1
)
+
1
)))
/
stride_height
+
1
,
output_height
,
"input_height and output_height are "
"Mismatching."
);
PADDLE_ENFORCE_EQ
((
input_width
+
2
*
padding_width
-
((
dilation_w
*
(
filter_width
-
1
)
+
1
)))
/
stride_width
+
1
,
output_width
,
"input_width and output_width are "
"Mismatching."
);
int
num_kernels
=
input_channels
*
input_depth
*
input_height
*
input_width
;
const
int
threads
=
1024
;
...
...
@@ -188,9 +250,10 @@ class Col2VolFunctor<platform::GPUPlace, T> {
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
context
)
.
stream
()
>>>
(
num_kernels
,
col
.
data
<
T
>
(),
input_depth
,
input_height
,
input_width
,
filter_depth
,
filter_height
,
filter_width
,
stride_depth
,
stride_height
,
stride_width
,
padding_depth
,
padding_height
,
padding_width
,
output_depth
,
output_height
,
output_width
,
vol
.
data
<
T
>
());
dilation_d
,
dilation_h
,
dilation_w
,
filter_depth
,
filter_height
,
filter_width
,
stride_depth
,
stride_height
,
stride_width
,
padding_depth
,
padding_height
,
padding_width
,
output_depth
,
output_height
,
output_width
,
vol
.
data
<
T
>
());
}
};
...
...
paddle/operators/math/vol2col.h
浏览文件 @
271fc9c1
...
...
@@ -58,6 +58,7 @@ class Vol2ColFunctor {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
vol
,
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
;
...
...
@@ -68,6 +69,7 @@ class Col2VolFunctor {
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
framework
::
Tensor
&
vol
,
const
framework
::
Tensor
&
col
,
int
dilation_d
,
int
dilation_h
,
int
dilation_w
,
int
stride_depth
,
int
stride_height
,
int
stride_width
,
int
padding_depth
,
int
padding_height
,
int
padding_width
)
const
;
...
...
paddle/operators/math/vol2col_test.cc
浏览文件 @
271fc9c1
...
...
@@ -64,6 +64,7 @@ void testVol2col() {
int
filter_size
=
2
;
int
stride
=
1
;
int
padding
=
0
;
int
dilation
=
1
;
int
output_depth
=
(
input_depth
-
filter_size
+
2
*
padding
)
/
stride
+
1
;
int
output_height
=
(
input_height
-
filter_size
+
2
*
padding
)
/
stride
+
1
;
int
output_width
=
(
input_width
-
filter_size
+
2
*
padding
)
/
stride
+
1
;
...
...
@@ -85,8 +86,8 @@ void testVol2col() {
*
place
);
paddle
::
operators
::
math
::
Vol2ColFunctor
<
Place
,
float
>
vol2col
;
vol2col
(
*
context
,
input
,
output
,
stride
,
stride
,
stride
,
padding
,
padding
,
padding
);
vol2col
(
*
context
,
input
,
output
,
dilation
,
dilation
,
dilation
,
stride
,
stride
,
stride
,
padding
,
padding
,
padding
);
float
vol_2_col
[]
=
{
0
,
1
,
1
,
2
,
3
,
4
,
4
,
5
,
6
,
7
,
7
,
8
,
9
,
10
,
10
,
11
};
float
*
out_cfo_ptr
;
...
...
@@ -111,8 +112,8 @@ void testVol2col() {
}
paddle
::
operators
::
math
::
Col2VolFunctor
<
Place
,
float
>
col2vol
;
col2vol
(
*
context
,
input
,
output
,
stride
,
stride
,
stride
,
padding
,
padding
,
padding
);
col2vol
(
*
context
,
input
,
output
,
dilation
,
dilation
,
dilation
,
stride
,
stride
,
stride
,
padding
,
padding
,
padding
);
float
*
in_ptr
;
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录