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体验新版 GitCode,发现更多精彩内容 >>
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206a8f6c
编写于
12月 29, 2021
作者:
L
limingshu
提交者:
GitHub
12月 29, 2021
浏览文件
操作
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电子邮件补丁
差异文件
code clean (#38550)
上级
9171aaa0
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
1 addition
and
147 deletion
+1
-147
paddle/fluid/operators/elementwise/elementwise_op_broadcast.cu.h
...fluid/operators/elementwise/elementwise_op_broadcast.cu.h
+0
-140
paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h
paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h
+0
-6
paddle/pten/kernels/hybird/cuda/elementwise/elementwise_broadcast.cu.h
...ernels/hybird/cuda/elementwise/elementwise_broadcast.cu.h
+1
-1
未找到文件。
paddle/fluid/operators/elementwise/elementwise_op_broadcast.cu.h
浏览文件 @
206a8f6c
...
...
@@ -22,146 +22,6 @@ namespace operators {
namespace
kps
=
paddle
::
operators
::
kernel_primitives
;
struct
DimensionsTransform
{
using
DimVector
=
std
::
vector
<
int64_t
>
;
typedef
void
(
*
MergeFunctor
)(
bool
&
,
std
::
vector
<
DimVector
>
&
,
DimVector
&
,
int
,
int
);
int64_t
dim_size
;
DimVector
out_dims
;
std
::
vector
<
DimVector
>
in_dims
;
private:
// To compensate the lackage of input_tensors` dimension with input variable
// 'axis'
void
InputDimensionsExtend
(
int
N
,
int
axis
)
{
for
(
auto
&
in_dim
:
in_dims
)
{
int64_t
in_idx
=
0
;
if
(
in_dim
.
size
()
<
dim_size
)
{
DimVector
tmp_dim
(
dim_size
,
1
);
do
{
if
(
in_dim
[
in_idx
]
==
out_dims
[
axis
]
||
in_dim
[
in_idx
]
==
1
)
{
tmp_dim
[
axis
]
=
in_dim
[
in_idx
];
in_idx
++
;
axis
++
;
}
else
{
PADDLE_THROW
(
platform
::
errors
::
InvalidArgument
(
"The %d-th dimension of input tensor is expected to be equal "
"with the %d-th dimension of output tensor %d or 1, but "
"recieved %d."
,
in_idx
+
1
,
axis
+
1
,
out_dims
[
axis
],
in_dim
[
in_idx
]));
}
}
while
(
in_idx
<
in_dim
.
size
());
in_dim
.
resize
(
dim_size
);
std
::
copy
(
tmp_dim
.
begin
(),
tmp_dim
.
end
(),
in_dim
.
begin
());
}
else
{
do
{
if
(
in_dim
[
in_idx
]
==
out_dims
[
in_idx
]
||
in_dim
[
in_idx
]
==
1
)
{
in_idx
++
;
}
else
{
PADDLE_THROW
(
platform
::
errors
::
InvalidArgument
(
"The %d-th dimension of input tensor is expected to be equal "
"with the %d-th dimension of output tensor %d or 1, but "
"recieved %d."
,
in_idx
+
1
,
in_idx
+
1
,
out_dims
[
in_idx
],
in_dim
[
in_idx
]));
}
}
while
(
in_idx
<
dim_size
);
}
std
::
reverse
(
in_dim
.
begin
(),
in_dim
.
end
());
}
std
::
reverse
(
out_dims
.
begin
(),
out_dims
.
end
());
}
template
<
typename
MergeFunctor
>
__inline__
void
MergeDimensions
(
MergeFunctor
merge_func
,
int
N
)
{
auto
VectorReorganise
=
[](
DimVector
*
vec
,
int
l_idx
,
int
m_idx
)
{
(
*
vec
)[
m_idx
-
1
]
=
std
::
accumulate
(
vec
->
begin
()
+
l_idx
,
vec
->
begin
()
+
m_idx
,
1
,
std
::
multiplies
<
int64_t
>
());
vec
->
erase
(
vec
->
begin
()
+
l_idx
,
vec
->
begin
()
+
m_idx
-
1
);
};
int64_t
i
=
0
;
while
(
i
<
dim_size
)
{
int
cnt
=
0
;
int
low_idx
=
i
;
bool
equal
=
true
;
do
{
merge_func
(
equal
,
in_dims
,
out_dims
,
i
,
N
);
if
(
equal
)
{
i
++
;
cnt
++
;
}
else
{
break
;
}
}
while
(
i
<
dim_size
);
if
(
cnt
>
1
)
{
for
(
auto
&
in_dim
:
in_dims
)
{
VectorReorganise
(
&
in_dim
,
low_idx
,
i
);
}
VectorReorganise
(
&
out_dims
,
low_idx
,
i
);
dim_size
-=
--
cnt
;
i
-=
cnt
;
}
else
if
(
cnt
<
1
)
{
i
++
;
}
}
}
public:
explicit
DimensionsTransform
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
ins
,
const
framework
::
DDim
&
dims
,
int
axis
)
{
const
int
N
=
ins
.
size
();
dim_size
=
dims
.
size
();
out_dims
=
framework
::
vectorize
<
int64_t
>
(
dims
);
in_dims
.
resize
(
N
);
for
(
int
j
=
0
;
j
<
N
;
++
j
)
{
in_dims
[
j
]
=
framework
::
vectorize
<
int64_t
>
(
ins
[
j
]
->
dims
());
}
InputDimensionsExtend
(
N
,
axis
);
auto
merge_sequential_dims
=
[](
bool
&
equal
,
std
::
vector
<
DimVector
>
&
in_dims
,
DimVector
&
out
,
int
i
,
int
num
)
{
for
(
int
j
=
1
;
j
<
num
;
++
j
)
{
equal
&=
(
in_dims
[
0
][
i
]
==
in_dims
[
j
][
i
])
?
true
:
false
;
}
};
auto
merge_sequential_one_dims
=
[](
bool
&
equal
,
std
::
vector
<
DimVector
>
&
in_dims
,
DimVector
&
out
,
int
i
,
int
num
)
{
equal
=
in_dims
[
0
][
i
]
==
1
;
if
(
equal
)
{
for
(
int
j
=
1
;
j
<
num
;
++
j
)
{
equal
&=
in_dims
[
j
][
i
]
==
out
[
i
];
}
}
};
// To Merge the dimensions of input_tensors while the consequtive
// equal-dimensions appears.
MergeFunctor
merge_ptr
=
merge_sequential_dims
;
MergeDimensions
<
MergeFunctor
>
(
merge_ptr
,
N
);
int
min_idx
=
0
;
int
min_val
=
std
::
accumulate
(
in_dims
[
0
].
begin
(),
in_dims
[
0
].
end
(),
1
,
std
::
multiplies
<
int64_t
>
());
for
(
int
j
=
1
;
j
<
N
;
++
j
)
{
int
temp
=
std
::
accumulate
(
in_dims
[
j
].
begin
(),
in_dims
[
j
].
end
(),
1
,
std
::
multiplies
<
int64_t
>
());
min_val
=
min_val
>
temp
?
temp
:
min_val
;
min_idx
=
min_val
==
temp
?
j
:
min_idx
;
}
std
::
swap
(
in_dims
[
0
],
in_dims
[
min_idx
]);
// To Merge the dimension of input_tensors while the consequtive
// 1-value-dimensions appears.
merge_ptr
=
merge_sequential_one_dims
;
MergeDimensions
<
MergeFunctor
>
(
merge_ptr
,
N
);
std
::
swap
(
in_dims
[
min_idx
],
in_dims
[
0
]);
}
};
template
<
ElementwiseType
ET
,
typename
InT
,
typename
OutT
,
typename
Functor
,
int
NumOuts
=
1
>
void
LaunchBroadcastElementwiseCudaKernel
(
...
...
paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h
浏览文件 @
206a8f6c
...
...
@@ -25,12 +25,6 @@ limitations under the License. */
#include "paddle/pten/include/core.h"
#include "paddle/pten/kernels/hybird/cuda/elementwise/elementwise.h"
#ifdef __HIPCC__
#define ELEMENTWISE_BLOCK_SIZE 256
#else
#define ELEMENTWISE_BLOCK_SIZE 512
#endif
namespace
paddle
{
namespace
operators
{
...
...
paddle/pten/kernels/hybird/cuda/elementwise/elementwise_broadcast.cu.h
浏览文件 @
206a8f6c
...
...
@@ -456,7 +456,7 @@ void LaunchBroadcastElementwiseCudaKernel(
ins
.
size
(),
kArity
));
PADDLE_ENFORCE_LE
(
kArity
,
ElementwiseType
::
kTernary
,
3
,
paddle
::
platform
::
errors
::
InvalidArgument
(
"Currently only broadcast of ternary is supported "
"and verified, but received %d."
,
...
...
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