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体验新版 GitCode,发现更多精彩内容 >>
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cb7bbf42
编写于
4月 10, 2018
作者:
Y
Yancey1989
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
revert uniform_random_op
上级
291aa231
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
7 addition
and
65 deletion
+7
-65
paddle/fluid/operators/uniform_random_op.cc
paddle/fluid/operators/uniform_random_op.cc
+1
-12
paddle/fluid/operators/uniform_random_op.cu
paddle/fluid/operators/uniform_random_op.cu
+1
-12
python/paddle/fluid/tests/unittests/test_uniform_random_op.py
...on/paddle/fluid/tests/unittests/test_uniform_random_op.py
+5
-41
未找到文件。
paddle/fluid/operators/uniform_random_op.cc
浏览文件 @
cb7bbf42
...
...
@@ -24,19 +24,8 @@ template <typename T>
class
CPUUniformRandomKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
framework
::
Tensor
*
tensor
(
nullptr
);
auto
out_var
=
ctx
.
OutputVar
(
"Out"
);
if
(
out_var
->
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
}
else
if
(
out_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
shape
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"shape"
);
tensor
=
ctx
.
Output
<
framework
::
SelectedRows
>
(
"Out"
)
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
shape
));
}
else
{
PADDLE_THROW
(
"Only support LoDTensor and SelectedRows."
);
}
auto
*
tensor
=
ctx
.
Output
<
framework
::
Tensor
>
(
"Out"
);
T
*
data
=
tensor
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
data
[
0
]
=
static_cast
<
T
>
(
1000
);
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
ctx
.
Attr
<
int
>
(
"seed"
));
std
::
minstd_rand
engine
;
if
(
seed
==
0
)
{
...
...
paddle/fluid/operators/uniform_random_op.cu
浏览文件 @
cb7bbf42
...
...
@@ -43,18 +43,7 @@ template <typename T>
class
GPUUniformRandomKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
framework
::
Tensor
*
tensor
(
nullptr
);
auto
out_var
=
ctx
.
OutputVar
(
"Out"
);
if
(
out_var
->
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
}
else
if
(
out_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
shape
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"shape"
);
tensor
=
ctx
.
Output
<
framework
::
SelectedRows
>
(
"Out"
)
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
shape
));
}
else
{
PADDLE_THROW
(
"Only support LoDTensor and SelectedRows."
);
}
auto
*
tensor
=
context
.
Output
<
framework
::
Tensor
>
(
"Out"
);
T
*
data
=
tensor
->
mutable_data
<
T
>
(
context
.
GetPlace
());
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
context
.
Attr
<
int
>
(
"seed"
));
if
(
seed
==
0
)
{
...
...
python/paddle/fluid/tests/unittests/test_uniform_random_op.py
浏览文件 @
cb7bbf42
...
...
@@ -15,16 +15,6 @@
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
import
paddle.fluid.core
as
core
from
paddle.fluid.op
import
Operator
def
output_hist
(
out
):
hist
,
_
=
np
.
histogram
(
out
,
range
=
(
-
5
,
10
))
hist
=
hist
.
astype
(
"float32"
)
hist
/=
float
(
out
.
size
)
prob
=
0.1
*
np
.
ones
((
10
))
return
hist
,
prob
class
TestUniformRandomOp
(
OpTest
):
...
...
@@ -43,37 +33,11 @@ class TestUniformRandomOp(OpTest):
self
.
check_output_customized
(
self
.
verify_output
)
def
verify_output
(
self
,
outs
):
hist
,
prob
=
output_hist
(
outs
[
0
])
self
.
assertTrue
(
np
.
allclose
(
hist
,
prob
,
rtol
=
0
,
atol
=
0.01
),
"hist: "
+
str
(
hist
))
class
TestUniformRandomOpSelectedRows
(
unittest
.
TestCase
):
def
get_places
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
return
places
def
test_check_output
(
self
):
for
place
in
self
.
get_places
():
self
.
check_with_place
(
place
)
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
out
=
scope
.
var
(
"X"
).
get_selected_rows
()
op
=
Operator
(
"uniform_random"
,
Out
=
"X"
,
shape
=
[
1000
,
784
],
min
=-
5.0
,
max
=
10.0
,
seed
=
10
)
op
.
run
(
scope
,
place
)
out_tensor
=
out
.
get_tensor
()
hist
,
prob
=
output_hist
(
np
.
array
(
out_tensor
))
tensor
=
outs
[
0
]
hist
,
_
=
np
.
histogram
(
outs
[
0
],
range
=
(
-
5
,
10
))
hist
=
hist
.
astype
(
"float32"
)
hist
/=
float
(
outs
[
0
].
size
)
prob
=
0.1
*
np
.
ones
((
10
))
self
.
assertTrue
(
np
.
allclose
(
hist
,
prob
,
rtol
=
0
,
atol
=
0.01
),
"hist: "
+
str
(
hist
))
...
...
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