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012d45da
编写于
2月 09, 2022
作者:
Z
zyfncg
提交者:
GitHub
2月 09, 2022
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电子邮件补丁
差异文件
Revert "【Pten】Adjust the Empyt dev_api (#39143)"
This reverts commit
9d4d0c3b
.
上级
9d4d0c3b
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
25 addition
and
16 deletion
+25
-16
paddle/pten/kernels/empty_kernel.h
paddle/pten/kernels/empty_kernel.h
+5
-5
paddle/pten/kernels/funcs/elementwise_base.h
paddle/pten/kernels/funcs/elementwise_base.h
+1
-1
paddle/pten/kernels/sparse/cpu/sparse_utils_kernel.cc
paddle/pten/kernels/sparse/cpu/sparse_utils_kernel.cc
+8
-4
paddle/pten/kernels/sparse/gpu/sparse_utils_kernel.cu
paddle/pten/kernels/sparse/gpu/sparse_utils_kernel.cu
+11
-6
未找到文件。
paddle/pten/kernels/empty_kernel.h
浏览文件 @
012d45da
...
...
@@ -32,7 +32,7 @@ void EmptyLikeKernel(const Context& dev_ctx, DenseTensor* out);
// TODO(chenweihang): the tensor creation method need to be replaced later,
// all kernel api call Empty here instead of making tensor self
template
<
typename
Context
>
template
<
typename
T
,
typename
Context
>
DenseTensor
Empty
(
const
Context
&
dev_ctx
,
DenseTensorMeta
&&
meta
)
{
pten
::
DenseTensor
dense_out
(
pten
::
make_intrusive
<
paddle
::
experimental
::
SharedStorage
>
(
...
...
@@ -43,7 +43,7 @@ DenseTensor Empty(const Context& dev_ctx, DenseTensorMeta&& meta) {
template
<
typename
T
,
typename
Context
>
DenseTensor
Empty
(
const
Context
&
dev_ctx
)
{
return
Empty
(
dev_ctx
,
return
Empty
<
T
,
Context
>
(
dev_ctx
,
{
paddle
::
experimental
::
CppTypeToDataType
<
T
>::
Type
(),
{
-
1
},
DataLayout
::
NCHW
});
...
...
paddle/pten/kernels/funcs/elementwise_base.h
浏览文件 @
012d45da
...
...
@@ -392,7 +392,7 @@ static inline void GetDoubleGradSafeTensor(const DeviceContext &dev_ctx,
*
ddx_safe
=
*
ddx
;
}
else
{
auto
meta
=
pten
::
DenseTensorMeta
(
x
.
dtype
(),
x
.
dims
(),
x
.
layout
());
*
ddx_safe
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
meta
));
*
ddx_safe
=
pten
::
Empty
<
T
,
DeviceContext
>
(
dev_ctx
,
std
::
move
(
meta
));
ddx_safe
->
mutable_data
(
dev_ctx
.
GetPlace
());
paddle
::
operators
::
math
::
SetConstant
<
DeviceContext
,
T
>
set_zero
;
set_zero
(
dev_ctx
,
ddx_safe
,
static_cast
<
T
>
(
0
));
...
...
paddle/pten/kernels/sparse/cpu/sparse_utils_kernel.cc
浏览文件 @
012d45da
...
...
@@ -76,8 +76,10 @@ void DenseToSparseCooKernel(const Context& dev_ctx,
{
sparse_dim
,
static_cast
<
int64_t
>
(
non_zero_num
)},
DataLayout
::
NCHW
);
DenseTensorMeta
values_meta
(
x
.
meta
().
dtype
,
values_dims
,
x
.
meta
().
layout
);
pten
::
DenseTensor
indices
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
indices_meta
));
pten
::
DenseTensor
values
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
values_meta
));
pten
::
DenseTensor
indices
=
pten
::
Empty
<
int64_t
,
Context
>
(
dev_ctx
,
std
::
move
(
indices_meta
));
pten
::
DenseTensor
values
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
values_meta
));
int64_t
*
indices_data
=
indices
.
mutable_data
<
int64_t
>
(
place
);
T
*
values_data
=
values
.
mutable_data
<
T
>
(
place
);
...
...
@@ -121,8 +123,10 @@ void SparseCsrToCooKernel(const Context& dev_ctx,
DenseTensorMeta
indices_meta
(
DataType
::
INT64
,
{
sparse_dim
,
non_zero_num
},
DataLayout
::
NCHW
);
DenseTensorMeta
values_meta
(
x
.
dtype
(),
{
non_zero_num
},
x
.
layout
());
pten
::
DenseTensor
indices
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
indices_meta
));
pten
::
DenseTensor
values
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
values_meta
));
pten
::
DenseTensor
indices
=
pten
::
Empty
<
int64_t
,
Context
>
(
dev_ctx
,
std
::
move
(
indices_meta
));
pten
::
DenseTensor
values
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
values_meta
));
int64_t
*
coo_indices
=
indices
.
mutable_data
<
int64_t
>
(
place
);
int64_t
*
batch_ptr
=
x_dims
.
size
()
==
2
?
nullptr
:
coo_indices
;
int64_t
*
coo_rows_data
=
...
...
paddle/pten/kernels/sparse/gpu/sparse_utils_kernel.cu
浏览文件 @
012d45da
...
...
@@ -111,12 +111,14 @@ void DenseToSparseCooKernel(const Context& dev_ctx,
const
int
cols
=
dims_2d
[
1
];
auto
nums_meta
=
pten
::
DenseTensorMeta
(
DataType
::
INT32
,
{
1
},
pten
::
DataLayout
::
NCHW
);
DenseTensor
nums
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
nums_meta
));
DenseTensor
nums
=
pten
::
Empty
<
int64_t
,
Context
>
(
dev_ctx
,
std
::
move
(
nums_meta
));
auto
x_dims_meta
=
pten
::
DenseTensorMeta
(
DataType
::
INT64
,
{
static_cast
<
int64_t
>
(
x_dims
.
size
())},
pten
::
DataLayout
::
NCHW
);
DenseTensor
d_x_dims
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
x_dims_meta
));
DenseTensor
d_x_dims
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
x_dims_meta
));
const
auto
place
=
dev_ctx
.
GetPlace
();
...
...
@@ -134,7 +136,8 @@ void DenseToSparseCooKernel(const Context& dev_ctx,
auto
temp_indexs_meta
=
pten
::
DenseTensorMeta
(
DataType
::
INT32
,
{
rows
},
pten
::
DataLayout
::
NCHW
);
DenseTensor
temp_indexs
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
temp_indexs_meta
));
DenseTensor
temp_indexs
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
temp_indexs_meta
));
int
*
temp_indexs_ptr
=
temp_indexs
.
mutable_data
<
int
>
(
place
);
GetNonZeroNums
<<<
grid_size
,
block_size
,
0
,
dev_ctx
.
stream
()
>>>
(
x_data
,
rows
,
cols
,
nums_ptr
,
temp_indexs_ptr
);
...
...
@@ -266,9 +269,11 @@ void SparseCsrToCooKernel(const Context& dev_ctx,
DataType
::
INT64
,
{
sparse_dim
,
non_zero_num
},
DataLayout
::
NCHW
);
DenseTensorMeta
values_meta
(
x
.
dtype
(),
{
non_zero_num
},
x
.
layout
());
DenseTensorMeta
offsets_meta
(
DataType
::
INT32
,
{
batchs
},
DataLayout
::
NCHW
);
DenseTensor
indices
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
indices_meta
));
DenseTensor
values
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
values_meta
));
DenseTensor
offsets
=
pten
::
Empty
(
dev_ctx
,
std
::
move
(
offsets_meta
));
DenseTensor
indices
=
pten
::
Empty
<
int64_t
,
Context
>
(
dev_ctx
,
std
::
move
(
indices_meta
));
DenseTensor
values
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
values_meta
));
DenseTensor
offsets
=
pten
::
Empty
<
T
,
Context
>
(
dev_ctx
,
std
::
move
(
offsets_meta
));
int64_t
*
coo_indices
=
indices
.
mutable_data
<
int64_t
>
(
place
);
int64_t
*
batch_ptr
=
x_dims
.
size
()
==
2
?
nullptr
:
coo_indices
;
int64_t
*
coo_rows_data
=
...
...
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