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体验新版 GitCode,发现更多精彩内容 >>
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eb070476
编写于
11月 16, 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 padding
上级
9cf60365
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
77 addition
and
37 deletion
+77
-37
paddle/operators/conv_transpose_op.cc
paddle/operators/conv_transpose_op.cc
+1
-6
paddle/operators/conv_transpose_op.h
paddle/operators/conv_transpose_op.h
+2
-4
paddle/operators/math/im2col.cu
paddle/operators/math/im2col.cu
+2
-2
python/paddle/v2/fluid/tests/test_conv2d_op.py
python/paddle/v2/fluid/tests/test_conv2d_op.py
+28
-12
python/paddle/v2/fluid/tests/test_conv2d_transpose_op.py
python/paddle/v2/fluid/tests/test_conv2d_transpose_op.py
+21
-5
python/paddle/v2/fluid/tests/test_conv3d_transpose_op.py
python/paddle/v2/fluid/tests/test_conv3d_transpose_op.py
+23
-8
未找到文件。
paddle/operators/conv_transpose_op.cc
浏览文件 @
eb070476
...
...
@@ -30,11 +30,6 @@ void ConvTransposeOp::InferShape(framework::InferShapeContext* ctx) const {
std
::
vector
<
int
>
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
paddings
[
i
],
0
,
"No Padding allowed in conv transpose op."
);
}
PADDLE_ENFORCE
(
in_dims
.
size
()
==
4
||
in_dims
.
size
()
==
5
,
"ConvTransposeOp intput should be 4-D or 5-D tensor."
);
PADDLE_ENFORCE_EQ
(
in_dims
.
size
(),
filter_dims
.
size
(),
...
...
@@ -52,7 +47,7 @@ void ConvTransposeOp::InferShape(framework::InferShapeContext* ctx) const {
std
::
vector
<
int64_t
>
output_shape
({
in_dims
[
0
],
filter_dims
[
1
]});
for
(
size_t
i
=
0
;
i
<
strides
.
size
();
++
i
)
{
output_shape
.
push_back
((
in_dims
[
i
+
2
]
-
1
)
*
strides
[
i
]
+
output_shape
.
push_back
((
in_dims
[
i
+
2
]
-
1
)
*
strides
[
i
]
-
2
*
paddings
[
i
]
+
filter_dims
[
i
+
2
]);
}
ctx
->
SetOutputDim
(
"Output"
,
framework
::
make_ddim
(
output_shape
));
...
...
paddle/operators/conv_transpose_op.h
浏览文件 @
eb070476
...
...
@@ -62,7 +62,6 @@ class GemmConvTransposeKernel : public framework::OpKernel<T> {
Tensor
*
output
=
context
.
Output
<
Tensor
>
(
"Output"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
// Actually, no paddings and groups allowed in conv transpose.
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
// TODO(Zhuoyuan): Paddings can be added in future.
// groups will alway be disabled in conv2dtranspose.
...
...
@@ -148,8 +147,8 @@ class GemmConvTransposeKernel : public framework::OpKernel<T> {
}
else
if
(
filter_shape_vec
.
size
()
==
3
)
{
// col2vol: col_matrix -> dy
// from (c * k_d * k_h * k_w, d * h * w) to (c, o_d, o_h, o_w)
col2vol
(
context
.
device_context
(),
col
,
dilations
,
strides
,
std
::
vector
<
int
>
{
0
,
0
,
0
},
&
output_batch
);
col2vol
(
context
.
device_context
(),
col
,
dilations
,
strides
,
paddings
,
&
output_batch
);
}
}
}
...
...
@@ -173,7 +172,6 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
if
((
!
input_grad
)
&&
(
!
filter_grad
))
return
;
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
// Actually, no paddings and groups allowed in conv transpose.
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
const
int
batch_size
=
static_cast
<
int
>
(
input
->
dims
()[
0
]);
...
...
paddle/operators/math/im2col.cu
浏览文件 @
eb070476
...
...
@@ -119,8 +119,8 @@ __global__ void col2im(int n, const T* data_col, int im_height, int im_width,
if
(
index
<
n
)
{
T
val
=
0
;
int
w
=
index
%
im_width
;
int
h
=
(
index
/
im_width
)
%
im_height
;
int
w
=
index
%
im_width
+
padding_width
;
int
h
=
(
index
/
im_width
)
%
im_height
+
padding_height
;
int
c
=
index
/
(
im_width
*
im_height
);
// compute the start and end of the output
...
...
python/paddle/v2/fluid/tests/test_conv2d_op.py
浏览文件 @
eb070476
...
...
@@ -110,13 +110,30 @@ class TestConv2dOp(OpTest):
self
.
op_type
=
"conv2d"
class
TestWithPad
(
TestConv2dOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
/
self
.
groups
self
.
filter_size
=
[
6
,
f_c
,
3
,
3
]
class
TestWithStride
(
TestConv2dOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
6
,
6
]
# NCHW
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
/
self
.
groups
self
.
filter_size
=
[
6
,
f_c
,
3
,
3
]
class
TestWithGroup
(
TestConv2dOp
):
def
init_group
(
self
):
self
.
groups
=
3
def
init_op_type
(
self
):
self
.
op_type
=
"conv2d"
class
TestWith1x1
(
TestConv2dOp
):
def
init_test_case
(
self
):
...
...
@@ -127,15 +144,9 @@ class TestWith1x1(TestConv2dOp):
f_c
=
self
.
input_size
[
1
]
/
self
.
groups
self
.
filter_size
=
[
6
,
f_c
,
1
,
1
]
def
init_dilation
(
self
):
self
.
dilations
=
[
1
,
1
]
def
init_group
(
self
):
self
.
groups
=
3
def
init_op_type
(
self
):
self
.
op_type
=
"conv2d"
class
TestWithDilation
(
TestConv2dOp
):
def
init_test_case
(
self
):
...
...
@@ -152,14 +163,19 @@ class TestWithDilation(TestConv2dOp):
def
init_group
(
self
):
self
.
groups
=
3
#----------------Conv2dCudnn----------------
class
TestCudnn
(
TestConv2dOp
):
def
init_op_type
(
self
):
self
.
op_type
=
"conv
2d
"
self
.
op_type
=
"conv
_cudnn
"
#----------------Conv2dCudnn----------------
class
TestCudnnWithPad
(
TestWithPad
):
def
init_op_type
(
self
):
self
.
op_type
=
"conv_cudnn"
class
TestCudnn
(
TestConv2dOp
):
class
TestCudnn
WithStride
(
TestWithStride
):
def
init_op_type
(
self
):
self
.
op_type
=
"conv_cudnn"
...
...
python/paddle/v2/fluid/tests/test_conv2d_transpose_op.py
浏览文件 @
eb070476
...
...
@@ -4,9 +4,7 @@ from op_test import OpTest
def
conv2dtranspose_forward_naive
(
input_
,
filter_
,
conv2dtranspose_param
):
# [2, 3, 5, 5]
in_n
,
in_c
,
in_h
,
in_w
=
input_
.
shape
# [3, 6, 3, 3]
f_c
,
out_c
,
f_h
,
f_w
=
filter_
.
shape
assert
in_c
==
f_c
...
...
@@ -29,6 +27,7 @@ def conv2dtranspose_forward_naive(input_, filter_, conv2dtranspose_param):
j1
,
j2
=
j
*
stride
[
0
],
j
*
stride
[
0
]
+
f_w
out
[
n
,
k
,
i1
:
i2
,
j1
:
j2
]
+=
tmp_out
out
=
out
[:,
:,
pad
[
0
]:
out_h
-
pad
[
0
],
pad
[
1
]:
out_w
-
pad
[
1
]]
return
out
...
...
@@ -36,8 +35,6 @@ class TestConv2dTransposeOp(OpTest):
def
setUp
(
self
):
# init as conv transpose
self
.
init_op_type
()
# [2, 3, 5, 5] -> kernel [3, 6, 3, 3] -> output [2, 6, 7, 7]
self
.
init_test_case
()
conv2dtranspose_param
=
{
'stride'
:
self
.
stride
,
'pad'
:
self
.
pad
}
...
...
@@ -55,7 +52,6 @@ class TestConv2dTransposeOp(OpTest):
self
.
outputs
=
{
'Output'
:
output
}
def
test_check_output
(
self
):
print
'check output here for'
,
self
.
op_type
self
.
check_output
()
def
test_check_grad_no_input
(
self
):
...
...
@@ -88,6 +84,26 @@ class TestConv2dTransposeOp(OpTest):
self
.
op_type
=
"conv2d_transpose"
class
TestWithPad
(
TestConv2dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
dilations
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
]
class
TestWithStride
(
TestConv2dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
dilations
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
]
# ------------ test_cudnn ------------
class
TestCudnn
(
TestConv2dTransposeOp
):
def
init_op_type
(
self
):
...
...
python/paddle/v2/fluid/tests/test_conv3d_transpose_op.py
浏览文件 @
eb070476
...
...
@@ -4,9 +4,7 @@ from op_test import OpTest
def
conv3dtranspose_forward_naive
(
input_
,
filter_
,
conv3dtranspose_param
):
# [2, 3, 5, 5, 5]
in_n
,
in_c
,
in_d
,
in_h
,
in_w
=
input_
.
shape
# [3, 6, 3, 3, 3]
f_c
,
out_c
,
f_d
,
f_h
,
f_w
=
filter_
.
shape
assert
in_c
==
f_c
...
...
@@ -14,7 +12,6 @@ def conv3dtranspose_forward_naive(input_, filter_, conv3dtranspose_param):
out_d
=
(
in_d
-
1
)
*
stride
[
0
]
+
f_d
out_h
=
(
in_h
-
1
)
*
stride
[
1
]
+
f_h
out_w
=
(
in_w
-
1
)
*
stride
[
2
]
+
f_w
out
=
np
.
zeros
((
in_n
,
out_c
,
out_d
,
out_h
,
out_w
))
for
n
in
range
(
in_n
):
...
...
@@ -33,6 +30,8 @@ def conv3dtranspose_forward_naive(input_, filter_, conv3dtranspose_param):
j1
,
j2
=
j
*
stride
[
2
],
j
*
stride
[
2
]
+
f_w
out
[
n
,
k
,
d1
:
d2
,
i1
:
i2
,
j1
:
j2
]
+=
tmp_out
out
=
out
[:,
:,
pad
[
0
]:
out_d
-
pad
[
0
],
pad
[
1
]:
out_h
-
pad
[
1
],
pad
[
2
]:
out_w
-
pad
[
2
]]
return
out
...
...
@@ -40,8 +39,6 @@ class TestConv3dTransposeOp(OpTest):
def
setUp
(
self
):
# init as conv transpose
self
.
init_op_type
()
# [2, 3, 5, 5, 5] -> kernel [3, 6, 3, 3, 3] -> output [2, 6, 7, 7, 7]
self
.
init_test_case
()
conv3dtranspose_param
=
{
'stride'
:
self
.
stride
,
'pad'
:
self
.
pad
}
...
...
@@ -49,7 +46,6 @@ class TestConv3dTransposeOp(OpTest):
filter_
=
np
.
random
.
random
(
self
.
filter_size
).
astype
(
"float32"
)
output
=
conv3dtranspose_forward_naive
(
input_
,
filter_
,
conv3dtranspose_param
).
astype
(
"float32"
)
# print 'deconv output py', output, output.shape
self
.
inputs
=
{
'Input'
:
input_
,
'Filter'
:
filter_
}
self
.
attrs
=
{
...
...
@@ -60,7 +56,6 @@ class TestConv3dTransposeOp(OpTest):
self
.
outputs
=
{
'Output'
:
output
}
def
test_check_output
(
self
):
print
'check output here'
self
.
check_output
()
def
test_check_grad
(
self
):
...
...
@@ -85,7 +80,7 @@ class TestConv3dTransposeOp(OpTest):
self
.
pad
=
[
0
,
0
,
0
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NCHW
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NC
D
HW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
...
...
@@ -93,5 +88,25 @@ class TestConv3dTransposeOp(OpTest):
self
.
op_type
=
"conv3d_transpose"
class
TestWithPad
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NCDHW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
class
TestWithStride
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
2
,
2
,
2
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NCDHW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
if
__name__
==
'__main__'
:
unittest
.
main
()
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