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体验新版 GitCode,发现更多精彩内容 >>
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2321a37b
编写于
9月 18, 2017
作者:
W
wanghaoshuang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix issues
上级
6e964ad5
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
17 addition
and
12 deletion
+17
-12
paddle/operators/clip_op.cu
paddle/operators/clip_op.cu
+8
-2
paddle/operators/clip_op.h
paddle/operators/clip_op.h
+1
-1
python/paddle/v2/framework/tests/gradient_checker.py
python/paddle/v2/framework/tests/gradient_checker.py
+1
-0
python/paddle/v2/framework/tests/op_test_util.py
python/paddle/v2/framework/tests/op_test_util.py
+0
-5
python/paddle/v2/framework/tests/test_clip_op.py
python/paddle/v2/framework/tests/test_clip_op.py
+7
-4
未找到文件。
paddle/operators/clip_op.cu
浏览文件 @
2321a37b
...
...
@@ -27,7 +27,13 @@ using Tensor = framework::Tensor;
template
<
typename
T
>
__global__
void
ClipGradientKernel
(
const
int
N
,
const
T
min
,
const
T
max
,
const
T
*
Y
,
const
T
*
dY
,
T
*
dX
)
{
CUDA_1D_KERNEL_LOOP
(
i
,
N
)
{
dX
[
i
]
=
dY
[
i
]
*
(
Y
[
i
]
>
min
&&
Y
[
i
]
<
max
);
}
CUDA_1D_KERNEL_LOOP
(
i
,
N
)
{
if
(
Y
[
i
]
>
min
&&
Y
[
i
]
<
max
)
{
dX
[
i
]
=
dY
[
i
];
}
else
{
dX
[
i
]
=
0
;
}
}
}
template
<
typename
T
>
...
...
@@ -38,7 +44,7 @@ class ClipGradientOpCUDAKernel : public framework::OpKernel {
auto
min
=
context
.
op
().
Attr
<
float
>
(
"min"
);
auto
*
d_out
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
x
=
context
.
Out
put
<
Tensor
>
(
"X"
);
auto
*
x
=
context
.
In
put
<
Tensor
>
(
"X"
);
auto
dims
=
d_x
->
dims
();
size_t
count
=
1
;
for
(
int
i
=
0
;
i
<
dims
.
size
();
++
i
)
{
...
...
paddle/operators/clip_op.h
浏览文件 @
2321a37b
...
...
@@ -50,7 +50,7 @@ class ClipGradKernel : public framework::OpKernel {
auto
min
=
context
.
op
().
Attr
<
float
>
(
"min"
);
auto
*
d_out
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
x
=
context
.
Out
put
<
Tensor
>
(
"X"
);
auto
*
x
=
context
.
In
put
<
Tensor
>
(
"X"
);
auto
dims
=
d_x
->
dims
();
size_t
count
=
1
;
for
(
int
i
=
0
;
i
<
dims
.
size
();
++
i
)
{
...
...
python/paddle/v2/framework/tests/gradient_checker.py
浏览文件 @
2321a37b
...
...
@@ -238,6 +238,7 @@ class GradientChecker(unittest.TestCase):
:type msf_prefix: string
"""
for
a
,
b
,
name
in
itertools
.
izip
(
numeric_grads
,
analytic_grads
,
names
):
print
"a=%s ; b=%s"
%
(
a
,
b
)
abs_a
=
numpy
.
abs
(
a
)
# if abs_a is nearly zero, then use abs error for a, not relative
# error.
...
...
python/paddle/v2/framework/tests/op_test_util.py
浏览文件 @
2321a37b
...
...
@@ -34,10 +34,8 @@ class OpTestMeta(type):
arr
=
self
.
inputs
[
in_name
]
var
.
set_dims
(
arr
.
shape
)
var
.
set
(
arr
,
place
)
print
"var: %s"
%
in_name
else
:
kwargs
[
in_name
]
=
"@EMPTY@"
print
"var: %s=EMPTY"
%
in_name
for
out_name
in
Operator
.
get_op_output_names
(
self
.
type
):
if
not
hasattr
(
self
,
"outputs"
):
...
...
@@ -48,7 +46,6 @@ class OpTestMeta(type):
(
out_name
))
kwargs
[
out_name
]
=
out_name
scope
.
new_var
(
out_name
).
get_tensor
()
print
"var: %s"
%
out_name
for
attr_name
in
Operator
.
get_op_attr_names
(
self
.
type
):
if
hasattr
(
self
,
"attrs"
)
and
attr_name
in
self
.
attrs
:
...
...
@@ -65,9 +62,7 @@ class OpTestMeta(type):
for
out_name
in
Operator
.
get_op_output_names
(
self
.
type
):
actual
=
numpy
.
array
(
scope
.
find_var
(
out_name
).
get_tensor
())
print
"actual: %s"
%
actual
expect
=
self
.
outputs
[
out_name
]
print
"expect: %s"
%
expect
self
.
assertTrue
(
numpy
.
allclose
(
actual
,
expect
,
atol
=
1e-05
),
...
...
python/paddle/v2/framework/tests/test_clip_op.py
浏览文件 @
2321a37b
...
...
@@ -5,12 +5,13 @@ from gradient_checker import GradientChecker
from
op_test_util
import
OpTestMeta
class
Test
ClipOp
(
unittest
.
TestCase
):
class
ClipOp
(
unittest
.
TestCase
):
__metaclass__
=
OpTestMeta
def
setUp
(
self
):
input
=
np
.
random
.
random
((
16
,
16
)).
astype
(
"float32"
)
print
"input: %s"
%
input
input
[
np
.
abs
(
input
-
0.1
)
<
0.05
]
=
0.5
input
[
np
.
abs
(
input
-
0.9
)
<
0.05
]
=
0.5
self
.
type
=
"clip"
self
.
inputs
=
{
'X'
:
input
,
}
self
.
attrs
=
{}
...
...
@@ -24,14 +25,16 @@ class TestClipOp(unittest.TestCase):
class
TestClipGradOp
(
GradientChecker
):
def
setUp
(
self
):
input
=
np
.
random
.
random
((
8
,
8
)).
astype
(
"float32"
)
print
"input: %s"
%
input
self
.
op
=
Operator
(
type
=
"clip"
,
X
=
"X"
,
Out
=
"Out"
,
min
=
0.1
,
max
=
0.9
)
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
16
,
16
)).
astype
(
"float32"
)
,
}
self
.
inputs
=
{
'X'
:
input
,
}
def
test_normal
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
set
([
"X"
]),
"Out"
,
max_relative_error
=
0.5
)
def
t
est
_cpu_gpu_compare
(
self
):
def
t_cpu_gpu_compare
(
self
):
self
.
compare_grad
(
self
.
op
,
self
.
inputs
)
...
...
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