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e54f203c
编写于
4月 15, 2018
作者:
D
dzhwinter
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
"move to a new PR"
上级
494c262a
变更
5
展开全部
显示空白变更内容
内联
并排
Showing
5 changed file
with
246 addition
and
354 deletion
+246
-354
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+186
-330
paddle/fluid/operators/activation_op.h
paddle/fluid/operators/activation_op.h
+48
-10
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+4
-0
python/paddle/fluid/layer_helper.py
python/paddle/fluid/layer_helper.py
+5
-1
python/paddle/fluid/tests/unittests/test_activation_op.py
python/paddle/fluid/tests/unittests/test_activation_op.py
+3
-13
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
e54f203c
此差异已折叠。
点击以展开。
paddle/fluid/operators/activation_op.h
浏览文件 @
e54f203c
...
...
@@ -10,6 +10,9 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <glog/logging.h>
#include <string>
#include <unordered_set>
#include <utility>
#include <vector>
...
...
@@ -25,6 +28,16 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
/* Use ugly global variable, for the using in python layer side
Please refer to the layer_helper.py and get the details.
*/
static
std
::
unordered_set
<
std
::
string
>
InplaceOpSet
=
{
"sigmoid"
,
"exp"
,
"relu"
,
"tanh"
,
"sqrt"
,
"ceil"
,
"floor"
,
"reciprocal"
,
"relu6"
,
"soft_relu"
,
"hard_sigmoid"
,
};
static
bool
IsInplace
(
std
::
string
op
)
{
return
InplaceOpSet
.
count
(
op
);
}
template
<
typename
DeviceContext
,
typename
Functor
>
class
ActivationKernel
:
public
framework
::
OpKernel
<
typename
Functor
::
ELEMENT_TYPE
>
{
...
...
@@ -60,7 +73,6 @@ class ActivationGradKernel
public:
using
T
=
typename
Functor
::
ELEMENT_TYPE
;
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
Out
=
context
.
Input
<
framework
::
Tensor
>
(
"Out"
);
auto
*
dOut
=
context
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
...
...
@@ -68,7 +80,6 @@ class ActivationGradKernel
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dout
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dOut
);
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
auto
out
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
Out
);
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
*
place
=
...
...
@@ -78,7 +89,16 @@ class ActivationGradKernel
for
(
auto
&
attr
:
attrs
)
{
*
attr
.
second
=
context
.
Attr
<
float
>
(
attr
.
first
);
}
bool
inplace
=
functor
.
Inplace
();
if
(
!
inplace
)
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
functor
(
*
place
,
x
,
out
,
dout
,
dx
);
}
else
{
VLOG
(
10
)
<<
" Inplace activation "
;
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
functor
(
*
place
,
x
,
out
,
dout
,
dx
);
}
}
};
...
...
@@ -89,6 +109,14 @@ struct BaseActivationFunctor {
using
AttrPair
=
std
::
vector
<
std
::
pair
<
const
char
*
,
float
*>>
;
AttrPair
GetAttrs
()
{
return
AttrPair
();
}
/* NOTE(*): Output reuse X memory if X is not dependented by its Gradient.
For example, sigmoid op's gradient didn't involve x, so its output can
reuse
input memory. But abs op's gradient use x, it can not be inplaced.
gradient did use x.
*/
bool
Inplace
()
const
{
return
false
;
}
};
// sigmoid(x) = 1 / (1 + exp(-x))
...
...
@@ -102,6 +130,7 @@ struct SigmoidFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
SigmoidGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"sigmoid"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -156,6 +185,7 @@ struct ExpFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ExpGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"exp"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -174,10 +204,11 @@ struct ReluFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ReluGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"relu"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
dout
*
(
x
>
static_cast
<
T
>
(
0
)).
template
cast
<
T
>();
dx
.
device
(
d
)
=
dout
*
(
out
>
static_cast
<
T
>
(
0
)).
template
cast
<
T
>();
}
};
...
...
@@ -192,6 +223,7 @@ struct TanhFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
TanhGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"tanh"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -297,6 +329,7 @@ struct SqrtFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
SqrtGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"sqrt"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -316,10 +349,11 @@ struct CeilFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ZeroGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"ceil"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
static_cast
<
T
>
(
0
)
/
x
;
dx
.
device
(
d
)
=
static_cast
<
T
>
(
0
)
/
out
;
}
};
...
...
@@ -432,6 +466,7 @@ struct ReciprocalFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ReciprocalGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"reciprocal"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -531,11 +566,13 @@ struct Relu6GradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
bool
Inplace
()
const
{
return
IsInplace
(
"relu6"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
dout
*
((
x
>
static_cast
<
T
>
(
0
))
*
(
x
<
static_cast
<
T
>
(
threshold
)))
dx
.
device
(
d
)
=
dout
*
((
out
>
static_cast
<
T
>
(
0
))
*
(
out
<
static_cast
<
T
>
(
threshold
)))
.
template
cast
<
T
>();
}
};
...
...
@@ -611,11 +648,12 @@ struct SoftReluGradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
bool
Inplace
()
const
{
return
IsInplace
(
"softrelu"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
auto
tmp
=
static_cast
<
T
>
(
threshold
);
auto
temp
=
((
x
>
-
tmp
)
*
(
x
<
tmp
)).
template
cast
<
T
>().
eval
();
auto
temp
=
((
out
>
-
tmp
)
*
(
out
<
tmp
)).
template
cast
<
T
>().
eval
();
dx
.
device
(
d
)
=
dout
*
(
static_cast
<
T
>
(
1
)
-
(
-
out
).
exp
())
*
temp
;
}
};
...
...
@@ -791,7 +829,7 @@ struct HardSigmoidGradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"slope"
,
&
slope
},
{
"offset"
,
&
offset
}};
}
bool
Inplace
()
{
return
IsInplace
(
"hard_sigmoid"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
e54f203c
...
...
@@ -33,6 +33,7 @@ limitations under the License. */
#include "paddle/fluid/framework/prune.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/profiler.h"
...
...
@@ -461,6 +462,9 @@ All parameter, weight, gradient are variables in Paddle.
self
.
back
().
set_lod
(
t
.
lod
());
});
m
.
def
(
"IsInplace"
,
[](
std
::
string
op
)
->
bool
{
return
operators
::
IsInplace
(
op
);
});
m
.
def
(
"op_support_gpu"
,
OpSupportGPU
);
#ifdef PADDLE_WITH_CUDA
m
.
def
(
"get_cuda_device_count"
,
platform
::
GetCUDADeviceCount
);
...
...
python/paddle/fluid/layer_helper.py
浏览文件 @
e54f203c
...
...
@@ -19,6 +19,7 @@ from framework import Variable, Parameter, default_main_program, default_startup
import
unique_name
from
paddle.fluid.initializer
import
Constant
,
Xavier
from
param_attr
import
ParamAttr
,
WeightNormParamAttr
import
core
class
LayerHelper
(
object
):
...
...
@@ -398,13 +399,16 @@ class LayerHelper(object):
return
input_var
if
isinstance
(
act
,
basestring
):
act
=
{
'type'
:
act
}
tmp
=
self
.
create_tmp_variable
(
dtype
=
input_var
.
dtype
)
if
'use_mkldnn'
in
self
.
kwargs
:
act
[
'use_mkldnn'
]
=
self
.
kwargs
.
get
(
'use_mkldnn'
)
act_type
=
act
.
pop
(
'type'
)
if
'use_mkldnn'
in
self
.
kwargs
:
act
[
'use_mkldnn'
]
=
self
.
kwargs
.
get
(
'use_mkldnn'
)
tmp
=
input_var
# NOTE(dzhwinter): some activation support inplace compution.
if
not
core
.
IsInplace
(
act_type
):
tmp
=
self
.
create_tmp_variable
(
dtype
=
input_var
.
dtype
)
self
.
append_op
(
type
=
act_type
,
inputs
=
{
"X"
:
[
input_var
]},
...
...
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @
e54f203c
...
...
@@ -361,10 +361,7 @@ class TestCeil(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
# The same reason with TestFloor
def
init_dtype
(
self
):
pass
...
...
@@ -396,10 +393,8 @@ class TestFloor(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
# the gradient on floor, ceil, round is undefined.
# we return zero as gradient, but the numpy return nan
def
init_dtype
(
self
):
pass
...
...
@@ -501,11 +496,6 @@ class TestRound(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
def
init_dtype
(
self
):
pass
...
...
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