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体验新版 GitCode,发现更多精彩内容 >>
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258e000b
编写于
4月 26, 2019
作者:
C
ceci3
提交者:
GitHub
4月 26, 2019
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差异文件
test=develop, double backward leaky_relu (#17067)
backward of backward: leaky_relu
上级
10c487eb
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
161 addition
and
19 deletion
+161
-19
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+65
-0
paddle/fluid/operators/activation_op.cu
paddle/fluid/operators/activation_op.cu
+12
-0
paddle/fluid/operators/activation_op.h
paddle/fluid/operators/activation_op.h
+58
-19
python/paddle/fluid/tests/unittests/test_nn_grad.py
python/paddle/fluid/tests/unittests/test_nn_grad.py
+26
-0
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
258e000b
...
...
@@ -619,6 +619,28 @@ class ActivationOpDoubleGrad : public framework::OperatorWithKernel {
}
};
class
LeakyReluDoubleGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
if
(
ctx
->
HasOutput
(
"DX"
))
{
ctx
->
ShareDim
(
"X"
,
"DX"
);
ctx
->
ShareLoD
(
"X"
,
"DX"
);
}
if
(
ctx
->
HasOutput
(
"DDOut"
))
{
ctx
->
ShareDim
(
"X"
,
"DDOut"
);
ctx
->
ShareLoD
(
"X"
,
"DDOut"
);
}
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
GetKernelType
(
ctx
,
*
this
,
"DDX"
);
}
};
//
// ReluGrad: dx = dy if y >= 0 else 0
// ReluGradGrad: ddy = ddx if y >= 0 else 0
...
...
@@ -643,6 +665,29 @@ class ReluDoubleGradMaker : public ::paddle::framework::SingleGradOpDescMaker {
}
};
// leaky_relu Grad: dx=dy if y>=0 else alpha * dy
// leaky_relu GradGrad: ddy=ddx if y>=0 else alpha * ddx
class
LeakyReluDoubleGradMaker
:
public
::
paddle
::
framework
::
SingleGradOpDescMaker
{
public:
using
::
paddle
::
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<::
paddle
::
framework
::
OpDesc
>
Apply
()
const
override
{
auto
*
op
=
new
::
paddle
::
framework
::
OpDesc
();
op
->
SetType
(
"leaky_relu_grad_grad"
);
// input1: X
op
->
SetInput
(
"X"
,
Input
(
"X"
));
// X@GRAD@GRAD: ddx
op
->
SetInput
(
"DDX"
,
OutputGrad
(
framework
::
GradVarName
(
"X"
)));
op
->
SetAttrMap
(
Attrs
());
// Out@GRAD@GRAD: ddy
op
->
SetOutput
(
"DX"
,
InputGrad
(
"X"
));
op
->
SetOutput
(
"DDOut"
,
InputGrad
(
framework
::
GradVarName
(
"Out"
)));
return
std
::
unique_ptr
<::
paddle
::
framework
::
OpDesc
>
(
op
);
}
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -699,3 +744,23 @@ REGISTER_OP_CPU_KERNEL(
ops
::
ReluGradGradFunctor
<
double
>>
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CPUDeviceContext
,
ops
::
ReluGradGradFunctor
<
plat
::
float16
>>
);
REGISTER_OPERATOR
(
leaky_relu
,
ops
::
ActivationOp
,
ops
::
LeakyReluOpMaker
,
ops
::
ActivationOpInferVarType
,
ops
::
ActivationGradOpDescMaker
<
ops
::
LeakyReluGradFunctor
<
float
>::
FwdDeps
()
>
,
paddle
::
framework
::
SingleOpInplaceInToOut
);
REGISTER_OPERATOR
(
leaky_relu_grad
,
ops
::
ActivationOpGrad
,
paddle
::
framework
::
SingleOpInplaceInToOut
,
ops
::
LeakyReluDoubleGradMaker
);
REGISTER_OPERATOR
(
leaky_relu_grad_grad
,
ops
::
LeakyReluDoubleGrad
);
REGISTER_ACTIVATION_CPU_KERNEL
(
leaky_relu
,
LeakyRelu
,
LeakyReluFunctor
,
LeakyReluGradFunctor
);
REGISTER_OP_CPU_KERNEL
(
leaky_relu_grad_grad
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CPUDeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
float
>>
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CPUDeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
double
>>
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CPUDeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
plat
::
float16
>>
);
paddle/fluid/operators/activation_op.cu
浏览文件 @
258e000b
...
...
@@ -33,6 +33,18 @@ namespace plat = paddle::platform;
FOR_EACH_ACTIVATION_OP
(
REGISTER_ACTIVATION_CUDA_KERNEL
);
REGISTER_ACTIVATION_CUDA_KERNEL
(
leaky_relu
,
LeakyRelu
,
LeakyReluFunctor
,
LeakyReluGradFunctor
);
REGISTER_OP_CUDA_KERNEL
(
leaky_relu_grad_grad
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CUDADeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
float
>>
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CUDADeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
double
>>
,
ops
::
ActivationDoubleGradKernel
<
plat
::
CUDADeviceContext
,
ops
::
LeakyReluGradGradFunctor
<
plat
::
float16
>>
);
REGISTER_ACTIVATION_CUDA_KERNEL
(
relu
,
Relu
,
ReluFunctor
,
ReluGradFunctor
);
REGISTER_OP_CUDA_KERNEL
(
...
...
paddle/fluid/operators/activation_op.h
浏览文件 @
258e000b
...
...
@@ -1208,45 +1208,31 @@ inline void ExtractActivationDoubleGradTensor(
const
framework
::
Tensor
**
Out
,
const
framework
::
Tensor
**
ddX
,
framework
::
Tensor
**
dX
,
framework
::
Tensor
**
dOut
,
framework
::
Tensor
**
ddOut
)
{
auto
out_var
=
ctx
.
InputVar
(
"Out"
);
auto
ddx_var
=
ctx
.
InputVar
(
"DDX"
);
auto
ddo_var
=
ctx
.
OutputVar
(
"DDOut"
);
auto
do_var
=
ctx
.
OutputVar
(
"DOut"
);
PADDLE_ENFORCE
(
out_var
!=
nullptr
,
"Cannot get input Variable Out, variable name = %s"
,
ctx
.
op
().
Input
(
"Out"
));
PADDLE_ENFORCE
(
ddx_var
!=
nullptr
,
"Cannot get input Variable
%s, variable name = %s"
,
"DDX
"
,
"Cannot get input Variable
Out, variable name = %s
"
,
ctx
.
op
().
Input
(
"DDX"
));
if
(
CanBeUsedBySelectedRows
.
count
(
ctx
.
op
().
Type
()))
{
*
Out
=
paddle
::
framework
::
GetLoDTensorOrSelectedRowsValueFromVar
(
*
out_var
);
*
ddX
=
paddle
::
framework
::
GetLoDTensorOrSelectedRowsValueFromVar
(
*
ddx_var
);
if
(
ddo_var
)
{
*
ddOut
=
paddle
::
framework
::
GetMutableLoDTensorOrSelectedRowsValueFromVar
(
ddo_var
);
}
if
(
do_var
)
{
*
dOut
=
paddle
::
framework
::
GetMutableLoDTensorOrSelectedRowsValueFromVar
(
do_var
);
}
}
else
{
*
Out
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Out"
);
*
ddX
=
ctx
.
Input
<
framework
::
Tensor
>
(
"DDX"
);
if
(
ddo_var
)
{
*
ddOut
=
ctx
.
Output
<
framework
::
Tensor
>
(
"DDOut"
);
}
if
(
do_var
)
{
*
dOut
=
ctx
.
Output
<
framework
::
Tensor
>
(
"DOut"
);
}
}
PADDLE_ENFORCE
(
*
ddX
!=
nullptr
,
"Cannot get output tensor
%s, variable name = %s"
,
"DDX
"
,
"Cannot get output tensor
DDX, variable name = %s
"
,
ctx
.
op
().
Output
(
"DDX"
));
if
(
static_cast
<
int
>
(
kDepValue
)
&
static_cast
<
int
>
(
kDepX
))
{
auto
x_var
=
ctx
.
InputVar
(
"X"
);
PADDLE_ENFORCE
(
x_var
!=
nullptr
,
"Cannot get input
tensor X
, variable name = %s"
,
"Cannot get input
Variable Out
, variable name = %s"
,
ctx
.
op
().
Input
(
"X"
));
auto
dx_var
=
ctx
.
OutputVar
(
"DX"
);
if
(
CanBeUsedBySelectedRows
.
count
(
ctx
.
op
().
Type
()))
{
...
...
@@ -1262,9 +1248,33 @@ inline void ExtractActivationDoubleGradTensor(
}
}
}
else
{
VLOG
(
10
)
<<
"
Inplace activation of Op
: "
<<
ctx
.
op
().
Type
();
VLOG
(
10
)
<<
"
Inplace activation of Op
: "
<<
ctx
.
op
().
Type
();
*
X
=
*
ddX
;
}
if
(
static_cast
<
int
>
(
kDepValue
)
&
static_cast
<
int
>
(
kDepOut
))
{
auto
out_var
=
ctx
.
InputVar
(
"Out"
);
PADDLE_ENFORCE
(
out_var
!=
nullptr
,
"Cannot get input tensor Out, variable name = %s"
,
ctx
.
op
().
Input
(
"Out"
));
auto
dout_var
=
ctx
.
OutputVar
(
"DOut"
);
if
(
CanBeUsedBySelectedRows
.
count
(
ctx
.
op
().
Type
()))
{
*
Out
=
paddle
::
framework
::
GetLoDTensorOrSelectedRowsValueFromVar
(
*
out_var
);
if
(
dout_var
)
{
*
dOut
=
paddle
::
framework
::
GetMutableLoDTensorOrSelectedRowsValueFromVar
(
dout_var
);
}
}
else
{
*
Out
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Out"
);
if
(
dout_var
)
{
*
dOut
=
ctx
.
Output
<
framework
::
Tensor
>
(
"DOut"
);
}
}
}
else
{
VLOG
(
10
)
<<
"Inplace activation of Op: "
<<
ctx
.
op
().
Type
();
*
Out
=
*
ddX
;
}
}
template
<
typename
DeviceContext
,
typename
Functor
>
...
...
@@ -1318,6 +1328,36 @@ struct ReluGradGradFunctor : public BaseActivationFunctor<T> {
static
constexpr
ActBwdOpFwdDeps
FwdDeps
()
{
return
kDepOut
;
}
};
template
<
typename
T
>
struct
LeakyReluGradGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
float
alpha
;
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"alpha"
,
&
alpha
}};
}
template
<
typename
Device
>
void
operator
()(
const
Device
&
dev
,
const
framework
::
Tensor
*
X
,
const
framework
::
Tensor
*
Out
,
const
framework
::
Tensor
*
ddX
,
framework
::
Tensor
*
ddOut
,
framework
::
Tensor
*
dOut
,
framework
::
Tensor
*
dX
)
const
{
auto
*
d
=
dev
.
eigen_device
();
auto
ddx
=
framework
::
EigenVector
<
T
>::
Flatten
(
detail
::
Ref
(
ddX
));
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
detail
::
Ref
(
X
));
if
(
ddOut
)
{
auto
ddout
=
framework
::
EigenVector
<
T
>::
Flatten
(
detail
::
Ref
(
ddOut
));
ddout
.
device
(
*
d
)
=
ddx
*
((
x
>=
static_cast
<
T
>
(
0
)).
template
cast
<
T
>().
eval
()
+
static_cast
<
T
>
(
alpha
)
*
(
x
<
static_cast
<
T
>
(
0
)).
template
cast
<
T
>().
eval
())
.
template
cast
<
T
>();
}
if
(
dX
)
{
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
detail
::
Ref
(
dX
));
dx
.
device
(
*
d
)
=
dx
.
constant
(
static_cast
<
T
>
(
0
));
}
}
static
constexpr
ActBwdOpFwdDeps
FwdDeps
()
{
return
kDepX
;
}
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -1349,7 +1389,6 @@ struct ReluGradGradFunctor : public BaseActivationFunctor<T> {
__macro(softplus, Softplus, SoftplusFunctor, SoftplusGradFunctor); \
__macro(softsign, Softsign, SoftsignFunctor, SoftsignGradFunctor); \
__macro(relu6, Relu6, Relu6Functor, Relu6GradFunctor); \
__macro(leaky_relu, LeakyRelu, LeakyReluFunctor, LeakyReluGradFunctor); \
__macro(tanh_shrink, TanhShrink, TanhShrinkFunctor, TanhShrinkGradFunctor); \
__macro(elu, ELU, ELUFunctor, ELUGradFunctor); \
__macro(hard_shrink, HardShrink, HardShrinkFunctor, HardShrinkGradFunctor); \
...
...
python/paddle/fluid/tests/unittests/test_nn_grad.py
浏览文件 @
258e000b
...
...
@@ -68,5 +68,31 @@ class TestReluDoubleGradCheck(unittest.TestCase):
self
.
func
(
p
)
class
TestLeakyReluDoubleGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
# the shape of input variable shoule be clearly specified, not inlcude -1.
shape
=
[
3
,
7
]
eps
=
0.005
alpha
=
0.2
dtype
=
np
.
float64
x
=
layers
.
data
(
'x'
,
shape
,
False
,
dtype
)
x
.
persistable
=
True
y
=
layers
.
leaky_relu
(
x
,
alpha
=
alpha
)
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
shape
).
astype
(
dtype
)
x_arr
[
np
.
abs
(
x_arr
)
<
0.005
]
=
0.02
gradient_checker
.
double_grad_check
(
[
x
],
y
,
x_init
=
x_arr
,
place
=
place
,
eps
=
eps
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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