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体验新版 GitCode,发现更多精彩内容 >>
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560b4323
编写于
12月 08, 2020
作者:
Z
Zhang Ting
提交者:
GitHub
12月 08, 2020
浏览文件
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电子邮件补丁
差异文件
Revert "improve elementwise_add_grad perf (#29277)" (#29464)
This reverts commit
befd6d53
.
上级
57a4f16d
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
37 addition
and
332 deletion
+37
-332
paddle/fluid/operators/elementwise/elementwise_add_op.cu
paddle/fluid/operators/elementwise/elementwise_add_op.cu
+5
-304
paddle/fluid/operators/elementwise/elementwise_add_op.h
paddle/fluid/operators/elementwise/elementwise_add_op.h
+32
-28
未找到文件。
paddle/fluid/operators/elementwise/elementwise_add_op.cu
浏览文件 @
560b4323
...
...
@@ -11,16 +11,12 @@ distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <algorithm>
#include <functional>
#include "paddle/fluid/operators/elementwise/elementwise_add_op.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
#include "paddle/fluid/platform/complex128.h"
#include "paddle/fluid/platform/complex64.h"
#include "paddle/fluid/platform/float16.h"
#define WARPSIZE 32
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
...
...
@@ -78,10 +74,11 @@ static __global__ void SimpleElemwiseAddGradCUDAKernel(const T* dout,
template
<
typename
DeviceContext
,
typename
T
>
typename
std
::
enable_if
<
std
::
is_same
<
DeviceContext
,
plat
::
CUDADeviceContext
>::
value
>::
type
ElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
elementwise_add_grad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
dim3
block_size
=
dim3
(
PADDLE_CUDA_THREAD_SIZE
,
1
);
auto
size
=
x
->
numel
();
dim3
grid_size
=
...
...
@@ -93,302 +90,6 @@ ElementwiseAddGrad(const framework::ExecutionContext& ctx,
dy
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()));
}
inline
static
bool
UseReduceFirstAxisRank1
(
const
framework
::
DDim
&
dout_dims
,
const
framework
::
DDim
&
x_dims
,
const
framework
::
DDim
&
y_dims
,
const
int
axis
)
{
int
start_axis
=
(
axis
==
-
1
?
std
::
abs
(
x_dims
.
size
()
-
y_dims
.
size
())
:
axis
);
if
(
y_dims
[
y_dims
.
size
()
-
1
]
==
1
)
{
return
false
;
}
if
(
y_dims
.
size
()
>
1
)
{
for
(
int
i
=
0
;
i
<
y_dims
.
size
()
-
1
;
++
i
)
{
if
(
y_dims
[
i
]
!=
1
)
{
return
false
;
}
}
return
true
;
}
else
if
(
start_axis
==
x_dims
.
size
()
-
1
)
{
return
true
;
}
return
false
;
}
inline
static
bool
UseReduceFirstAxisRank2
(
const
framework
::
DDim
&
dout_dims
,
const
framework
::
DDim
&
x_dims
,
const
framework
::
DDim
&
y_dims
,
const
int
axis
)
{
int
start_axis
=
(
axis
==
-
1
?
std
::
abs
(
x_dims
.
size
()
-
y_dims
.
size
())
:
axis
);
if
(
y_dims
.
size
()
<
2
||
x_dims
[
x_dims
.
size
()
-
2
]
!=
y_dims
[
y_dims
.
size
()
-
2
]
||
x_dims
[
x_dims
.
size
()
-
1
]
!=
y_dims
[
y_dims
.
size
()
-
1
])
{
return
false
;
}
if
(
start_axis
==
x_dims
.
size
()
-
2
)
{
return
true
;
}
else
if
(
start_axis
==
0
)
{
for
(
int
i
=
0
;
i
<
y_dims
.
size
()
-
2
;
++
i
)
{
if
(
y_dims
[
i
]
!=
1
)
{
return
false
;
}
}
return
true
;
}
return
false
;
}
inline
static
bool
UseReduceSecondAxisRank2
(
const
framework
::
DDim
&
dout_dims
,
const
framework
::
DDim
&
x_dims
,
const
framework
::
DDim
&
y_dims
,
const
int
axis
,
int
*
start
,
int
*
end
)
{
if
(
x_dims
.
size
()
!=
y_dims
.
size
()
||
y_dims
.
size
()
<
3
)
{
return
false
;
}
auto
y_dims_vec
=
framework
::
vectorize
(
y_dims
);
auto
start_iter
=
std
::
find
(
y_dims_vec
.
begin
(),
y_dims_vec
.
end
(),
1
);
auto
end_iter
=
std
::
find
(
y_dims_vec
.
rbegin
(),
y_dims_vec
.
rend
(),
1
);
if
(
start_iter
==
y_dims_vec
.
end
()
||
start_iter
==
y_dims_vec
.
end
()
-
1
)
{
return
false
;
}
else
{
*
start
=
std
::
distance
(
y_dims_vec
.
begin
(),
start_iter
);
*
end
=
y_dims_vec
.
size
()
-
1
-
std
::
distance
(
y_dims_vec
.
rbegin
(),
end_iter
);
for
(
int
i
=
*
start
;
i
<=
*
end
;
++
i
)
{
if
(
y_dims
[
i
]
!=
1
)
{
return
false
;
}
}
return
true
;
}
}
template
<
typename
T
,
typename
OP
>
__global__
__launch_bounds__
(
1024
)
void
ReduceFirstAixsKernel
(
const
T
*
in
,
T
*
out
,
const
int64_t
num_rows
,
const
int64_t
num_cols
,
OP
op
,
T
init
)
{
int
row
=
blockIdx
.
y
*
blockDim
.
y
+
threadIdx
.
y
;
int
col
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
T
sum
=
init
;
if
(
row
<
num_rows
&&
col
<
num_cols
)
sum
=
in
[
row
*
num_cols
+
col
];
__shared__
__align__
(
alignof
(
T
))
char
partial_sums_raw
[
WARPSIZE
*
(
WARPSIZE
+
1
)
*
sizeof
(
T
)];
T
*
partial_sums
=
reinterpret_cast
<
T
*>
(
partial_sums_raw
);
row
+=
gridDim
.
y
*
blockDim
.
y
;
if
(
col
<
num_cols
)
{
for
(;
row
<
num_rows
;
row
+=
gridDim
.
y
*
blockDim
.
y
)
{
sum
=
op
(
sum
,
in
[
row
*
num_cols
+
col
]);
}
}
partial_sums
[
threadIdx
.
x
*
(
WARPSIZE
+
1
)
+
threadIdx
.
y
]
=
sum
;
__syncthreads
();
if
(
threadIdx
.
y
==
0
&&
col
<
num_cols
)
{
T
s
=
partial_sums
[
threadIdx
.
x
*
(
WARPSIZE
+
1
)];
const
int
numRowsThisBlock
=
min
(
static_cast
<
int64_t
>
(
blockDim
.
y
),
num_rows
-
blockIdx
.
y
*
blockDim
.
y
);
for
(
int
row
=
1
;
row
<
numRowsThisBlock
;
++
row
)
{
T
t
=
partial_sums
[
threadIdx
.
x
*
(
WARPSIZE
+
1
)
+
row
];
s
=
op
(
s
,
t
);
}
out
[
col
*
gridDim
.
y
+
blockIdx
.
y
]
=
s
;
}
}
template
<
typename
DeviceContext
,
typename
T
>
static
void
ElemwiseYGradRank1CUDA
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
&
dout
,
const
int
rows
,
const
int
cols
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
dim3
block_dim
(
WARPSIZE
,
std
::
min
(
rows
,
1024
/
WARPSIZE
));
dim3
grid_dim
((
cols
+
(
WARPSIZE
-
1
))
/
WARPSIZE
,
1
,
1
);
if
(
dx
)
{
dx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
framework
::
TensorCopy
(
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
dx
);
}
if
(
dy
)
{
dy
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
const
T
*
dout_data
=
dout
.
data
<
T
>
();
T
*
dy_data
=
dy
->
data
<
T
>
();
auto
stream
=
ctx
.
template
device_context
<
DeviceContext
>().
stream
();
ReduceFirstAixsKernel
<<<
grid_dim
,
block_dim
,
0
,
stream
>>>
(
dout_data
,
dy_data
,
rows
,
cols
,
AddFunctor
<
T
>
(),
static_cast
<
T
>
(
0
));
}
}
template
<
typename
T
,
typename
OP
>
__global__
__launch_bounds__
(
1024
)
void
ReduceFirstOrSecondAxisKernel
(
const
T
*
in
,
T
*
out
,
const
int
num_planes
,
const
int
num_rows
,
const
int
num_cols
,
OP
op
,
T
init
)
{
const
int
gid
=
threadIdx
.
x
+
blockIdx
.
x
*
blockDim
.
x
;
const
int
elems_per_plane
=
num_rows
*
num_cols
;
const
int
plane
=
gid
/
num_cols
;
const
int
col
=
gid
%
num_cols
;
if
(
plane
>=
num_planes
)
return
;
if
(
num_rows
==
1
)
{
out
[
plane
*
elems_per_plane
+
col
]
=
in
[
plane
*
elems_per_plane
+
col
];
return
;
}
T
sum
=
op
(
in
[
plane
*
elems_per_plane
+
col
],
in
[
plane
*
elems_per_plane
+
num_cols
+
col
]);
for
(
int
row
=
2
;
row
<
num_rows
;
++
row
)
{
sum
=
op
(
sum
,
in
[
plane
*
elems_per_plane
+
row
*
num_cols
+
col
]);
}
out
[
plane
*
num_cols
+
col
]
=
sum
;
}
template
<
typename
DeviceContext
,
typename
T
>
static
void
ElemwiseYGradRank2CUDA
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
&
dout
,
const
int
planes
,
const
int
rows
,
const
int
cols
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
int
num_threads
=
128
;
int
num_blocks
=
(
rows
+
num_threads
-
1
)
/
num_threads
;
if
(
planes
!=
1
)
{
num_blocks
=
(
planes
*
cols
+
num_threads
-
1
)
/
num_threads
;
}
if
(
dx
)
{
dx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
framework
::
TensorCopy
(
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
dx
);
}
if
(
dy
)
{
dy
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
const
T
*
dout_data
=
dout
.
data
<
T
>
();
T
*
dy_data
=
dy
->
data
<
T
>
();
auto
stream
=
ctx
.
template
device_context
<
DeviceContext
>().
stream
();
ReduceFirstOrSecondAxisKernel
<<<
num_blocks
,
num_threads
,
0
,
stream
>>>
(
dout_data
,
dy_data
,
planes
,
rows
,
cols
,
AddFunctor
<
T
>
(),
static_cast
<
T
>
(
0
));
}
}
template
<
typename
DeviceContext
,
typename
T
>
static
bool
ElemwiseGradUseReduce
(
const
framework
::
ExecutionContext
&
ctx
,
const
int
axis
,
const
framework
::
DDim
x_dims
,
const
framework
::
DDim
y_dims
,
const
framework
::
Tensor
&
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
int
start
=
0
;
int
end
=
0
;
auto
x_dims_vec
=
framework
::
vectorize
(
x_dims
);
if
(
UseReduceFirstAxisRank1
(
dout
.
dims
(),
x_dims
,
y_dims
,
axis
))
{
int
rows
=
std
::
accumulate
(
x_dims_vec
.
begin
(),
x_dims_vec
.
end
()
-
1
,
1
,
std
::
multiplies
<
int
>
());
int
cols
=
dx
->
dims
()[
dx
->
dims
().
size
()
-
1
];
if
(
cols
>
512
&&
cols
<
4096
)
{
ElemwiseYGradRank1CUDA
<
DeviceContext
,
T
>
(
ctx
,
dout
,
rows
,
cols
,
dx
,
dy
);
return
true
;
}
}
if
(
UseReduceFirstAxisRank2
(
dout
.
dims
(),
x_dims
,
y_dims
,
axis
))
{
int
rows
=
std
::
accumulate
(
x_dims_vec
.
begin
(),
x_dims_vec
.
end
()
-
2
,
1
,
std
::
multiplies
<
int
>
());
int
cols
=
dx
->
dims
()[
dx
->
dims
().
size
()
-
1
]
*
dx
->
dims
()[
dx
->
dims
().
size
()
-
2
];
if
(
cols
>
4096
)
{
ElemwiseYGradRank2CUDA
<
DeviceContext
,
T
>
(
ctx
,
dout
,
1
,
rows
,
cols
,
dx
,
dy
);
return
true
;
}
}
if
(
UseReduceSecondAxisRank2
(
dout
.
dims
(),
x_dims
,
y_dims
,
axis
,
&
start
,
&
end
))
{
int
planes
=
std
::
accumulate
(
x_dims_vec
.
begin
(),
x_dims_vec
.
begin
()
+
start
,
1
,
std
::
multiplies
<
int
>
());
int
rows
=
std
::
accumulate
(
x_dims_vec
.
begin
()
+
start
,
x_dims_vec
.
begin
()
+
end
+
1
,
1
,
std
::
multiplies
<
int
>
());
int
cols
=
std
::
accumulate
(
x_dims_vec
.
begin
()
+
end
+
1
,
x_dims_vec
.
end
(),
1
,
std
::
multiplies
<
int
>
());
if
(
rows
/
(
planes
*
cols
)
<
16
)
{
ElemwiseYGradRank2CUDA
<
DeviceContext
,
T
>
(
ctx
,
dout
,
planes
,
rows
,
cols
,
dx
,
dy
);
return
true
;
}
}
return
false
;
}
template
<
typename
T
>
class
ElementwiseAddGradKernel
<
platform
::
CUDADeviceContext
,
T
>
:
public
ElemwiseGradKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
ElemwiseGradKernel
<
T
>::
Compute
(
ctx
);
using
Tensor
=
framework
::
Tensor
;
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
// skip out
auto
*
out
=
dout
;
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
// Special case when dy is not needed and dx doesn't reduce
if
(
dx
!=
nullptr
&&
dy
==
nullptr
&&
dx
->
dims
()
==
dout
->
dims
())
{
VLOG
(
4
)
<<
"Special case when dy is not needed and dx doesn't "
"reduce"
;
framework
::
TensorCopy
(
*
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
dx
);
}
else
if
(
dx
==
nullptr
&&
dy
!=
nullptr
&&
dy
->
dims
()
==
dout
->
dims
())
{
VLOG
(
4
)
<<
"Special case when dx is not needed and dy doesn't "
"reduce"
;
framework
::
TensorCopy
(
*
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
dy
);
}
else
if
(
dx
&&
dy
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
ElementwiseAddGrad
<
platform
::
CUDADeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
else
if
(
dx
&&
dx
->
dims
()
==
dout
->
dims
()
&&
ElemwiseGradUseReduce
<
platform
::
CUDADeviceContext
,
T
>
(
ctx
,
axis
,
x
->
dims
(),
y
->
dims
(),
*
dout
,
dx
,
dy
))
{
}
else
if
(
dy
&&
dy
->
dims
()
==
dout
->
dims
()
&&
ElemwiseGradUseReduce
<
platform
::
CUDADeviceContext
,
T
>
(
ctx
,
axis
,
x
->
dims
(),
y
->
dims
(),
*
dout
,
dy
,
dx
))
{
}
else
{
DefaultElementwiseAddGrad
<
platform
::
CUDADeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP_CUDA_KERNEL
(
...
...
paddle/fluid/operators/elementwise/elementwise_add_op.h
浏览文件 @
560b4323
...
...
@@ -22,10 +22,9 @@ namespace paddle {
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
void
DefaultElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
void
default_elementwise_add
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
auto
x_dims
=
x
->
dims
();
auto
y_dims
=
y
->
dims
();
...
...
@@ -58,7 +57,7 @@ class ElementwiseAddKernel : public framework::OpKernel<T> {
SameDimsElemwiseAdd
<
DeviceContext
,
T
>
same_dims_add
;
same_dims_add
(
ctx
,
x
,
y
,
z
);
}
else
{
DefaultElementwiseAddGra
d
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
z
);
default_elementwise_ad
d
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
z
);
}
}
};
...
...
@@ -69,12 +68,13 @@ struct IdentityGrad {
};
template
<
typename
DeviceContext
,
typename
T
>
void
DefaultElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
void
default_elementwise_add_grad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
ElemwiseExplicitGradCompute
<
DeviceContext
,
T
,
IdentityGrad
<
T
>
,
...
...
@@ -87,10 +87,11 @@ template <typename DeviceContext, typename T>
typename
std
::
enable_if
<
std
::
is_floating_point
<
T
>::
value
&&
std
::
is_same
<
DeviceContext
,
platform
::
CPUDeviceContext
>::
value
>::
type
ElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
elementwise_add_grad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
auto
blas
=
math
::
GetBlas
<
DeviceContext
,
T
>
(
ctx
);
if
(
dx
)
{
blas
.
VCOPY
(
dout
->
numel
(),
dout
->
data
<
T
>
(),
...
...
@@ -107,11 +108,12 @@ template <typename DeviceContext, typename T>
typename
std
::
enable_if
<
!
std
::
is_floating_point
<
T
>::
value
&&
std
::
is_same
<
DeviceContext
,
platform
::
CPUDeviceContext
>::
value
>::
type
ElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
DefaultElementwiseAddGrad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
elementwise_add_grad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
)
{
default_elementwise_add_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
#ifdef PADDLE_WITH_CUDA
...
...
@@ -119,10 +121,11 @@ ElementwiseAddGrad(const framework::ExecutionContext &ctx,
template
<
typename
DeviceContext
,
typename
T
>
typename
std
::
enable_if
<
std
::
is_same
<
DeviceContext
,
platform
::
CUDADeviceContext
>::
value
>::
type
ElementwiseAddGrad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
);
elementwise_add_grad
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
out
,
const
framework
::
Tensor
*
dout
,
framework
::
Tensor
*
dx
,
framework
::
Tensor
*
dy
);
#endif
template
<
typename
DeviceContext
,
typename
T
>
...
...
@@ -155,9 +158,10 @@ class ElementwiseAddGradKernel : public ElemwiseGradKernel<T> {
*
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
platform
::
DeviceContext
>(),
dy
);
}
else
if
(
dx
!=
nullptr
&&
dy
!=
nullptr
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
ElementwiseAddG
rad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
elementwise_add_g
rad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
else
{
DefaultElementwiseAddGrad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
default_elementwise_add_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
}
};
...
...
@@ -182,8 +186,8 @@ class ElementwiseAddDoubleGradKernel : public framework::OpKernel<T> {
GetDoubleGradSafeTensor
<
DeviceContext
,
T
>
(
ctx
,
y
,
ddy
,
&
ddy_safe
);
ddout
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
DefaultElementwiseAddGra
d
<
DeviceContext
,
T
>
(
ctx
,
&
ddx_safe
,
&
ddy_safe
,
ddout
);
default_elementwise_ad
d
<
DeviceContext
,
T
>
(
ctx
,
&
ddx_safe
,
&
ddy_safe
,
ddout
);
}
}
};
...
...
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