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7d727f36
编写于
3月 14, 2023
作者:
H
Huang Jiyi
提交者:
GitHub
3月 14, 2023
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
[phi decopuling] decouple dependency to device_context in phi (Part 3) (#51559)
* remove device_context include * fix bug * fix bug
上级
e79699fb
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
76 addition
and
78 deletion
+76
-78
paddle/fluid/imperative/reducer.cc
paddle/fluid/imperative/reducer.cc
+2
-1
paddle/fluid/pybind/tensor_py.h
paddle/fluid/pybind/tensor_py.h
+8
-7
paddle/phi/kernels/cpu/concat_kernel.cc
paddle/phi/kernels/cpu/concat_kernel.cc
+8
-7
paddle/phi/kernels/funcs/math_function.cc
paddle/phi/kernels/funcs/math_function.cc
+0
-1
paddle/phi/kernels/funcs/math_function.cu
paddle/phi/kernels/funcs/math_function.cu
+0
-1
paddle/phi/kernels/funcs/strided_memcpy.h
paddle/phi/kernels/funcs/strided_memcpy.h
+47
-52
paddle/phi/kernels/gpu/concat_kernel.cu
paddle/phi/kernels/gpu/concat_kernel.cu
+8
-7
paddle/phi/kernels/impl/concat_grad_kernel_impl.h
paddle/phi/kernels/impl/concat_grad_kernel_impl.h
+1
-1
paddle/phi/kernels/impl/split_kernel_impl.h
paddle/phi/kernels/impl/split_kernel_impl.h
+2
-1
未找到文件。
paddle/fluid/imperative/reducer.cc
浏览文件 @
7d727f36
...
...
@@ -103,7 +103,8 @@ static void SplitTensorsForAllReduce(
}
// Sometimes direct copies will be faster
if
(
p_dense_tensors
->
size
()
<
10
)
{
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
>
(
context
,
*
in
,
shape_refer
,
&
outs
);
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
,
DeviceContext
>
(
context
,
*
in
,
shape_refer
,
&
outs
);
}
else
{
operators
::
math
::
SplitFunctor
<
DeviceContext
,
T
>
split_functor_
;
split_functor_
(
context
,
*
in
,
shape_refer
,
0
,
&
outs
);
...
...
paddle/fluid/pybind/tensor_py.h
浏览文件 @
7d727f36
...
...
@@ -727,13 +727,14 @@ void _concatCompute(const std::vector<phi::DenseTensor> &ins,
for
(
auto
&
in
:
ins
)
{
auto
in_stride
=
phi
::
stride_numel
(
in
.
dims
());
auto
out_stride
=
phi
::
stride_numel
(
out
->
dims
());
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
>
(
ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
.
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
,
phi
::
CPUContext
>
(
ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
.
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
output_offset
+=
in_stride
[
axis
];
}
}
else
{
...
...
paddle/phi/kernels/cpu/concat_kernel.cc
浏览文件 @
7d727f36
...
...
@@ -86,13 +86,14 @@ void ConcatKernel(const Context& dev_ctx,
}
auto
in_stride
=
phi
::
stride_numel
(
in
->
dims
());
auto
out_stride
=
phi
::
stride_numel
(
out
->
dims
());
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
->
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
,
Context
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
->
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
output_offset
+=
in_stride
[
axis
];
}
}
else
{
...
...
paddle/phi/kernels/funcs/math_function.cc
浏览文件 @
7d727f36
...
...
@@ -27,7 +27,6 @@ limitations under the License. */
#include <utility>
#include <vector>
#include "paddle/fluid/platform/device_context.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/common/bfloat16.h"
#include "paddle/phi/common/data_type.h"
...
...
paddle/phi/kernels/funcs/math_function.cu
浏览文件 @
7d727f36
...
...
@@ -14,7 +14,6 @@ limitations under the License. */
#include <algorithm>
#include <vector>
#include "paddle/fluid/platform/device_context.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/bfloat16.h"
#include "paddle/phi/common/data_type.h"
...
...
paddle/phi/kernels/funcs/strided_memcpy.h
浏览文件 @
7d727f36
...
...
@@ -14,9 +14,12 @@ limitations under the License. */
#include "paddle/phi/kernels/funcs/detail/strided_memcpy.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/phi/core/dense_tensor.h"
namespace
phi
{
class
CPUContext
;
}
// namespace phi
namespace
phi
{
namespace
funcs
{
...
...
@@ -46,6 +49,32 @@ inline void StridedMemcpy(const phi::DeviceContext& dev_ctx,
dst_dim
.
apply_visitor
(
func
);
}
template
<
typename
Context
>
inline
void
CopyWithContext
(
const
Context
&
ctx
,
const
Place
&
dst_place
,
void
*
dst
,
const
Place
&
src_place
,
const
void
*
src
,
size_t
num
)
{
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) || \
defined(PADDLE_WITH_ASCEND_CL) || defined(PADDLE_WITH_MLU)
memory_utils
::
Copy
(
dst_place
,
dst
,
src_place
,
src
,
num
,
ctx
.
stream
());
#else
PADDLE_THROW
(
phi
::
errors
::
PreconditionNotMet
(
"Paddle is not compiled with GPU."
));
#endif
}
template
<
>
inline
void
CopyWithContext
<
phi
::
CPUContext
>
(
const
phi
::
CPUContext
&
ctx
,
const
Place
&
dst_place
,
void
*
dst
,
const
Place
&
src_place
,
const
void
*
src
,
size_t
num
)
{
memory_utils
::
Copy
(
dst_place
,
dst
,
src_place
,
src
,
num
);
}
// Strided numel memory copy from src to dst by the specified axis
//
// For example, for a tensor dims [4, 20, 100], the strieded numel is
...
...
@@ -53,8 +82,8 @@ inline void StridedMemcpy(const phi::DeviceContext& dev_ctx,
//
// NOTE: The src and dst tensor should have the same elements
// except the specified axis.
template
<
typename
T
>
inline
void
StridedNumelCopyWithAxis
(
const
phi
::
Device
Context
&
ctx
,
template
<
typename
T
,
typename
Context
>
inline
void
StridedNumelCopyWithAxis
(
const
Context
&
ctx
,
int64_t
axis
,
T
*
dst
,
const
phi
::
DDim
&
dst_stride_numel
,
...
...
@@ -102,52 +131,18 @@ inline void StridedNumelCopyWithAxis(const phi::DeviceContext& ctx,
}
for
(
int64_t
i
=
0
;
i
<
before
;
++
i
)
{
if
(
place
.
GetType
()
==
phi
::
AllocationType
::
CPU
)
{
auto
&
cpu_place
=
place
;
memory_utils
::
Copy
(
cpu_place
,
dst
+
i
*
dst_after
,
cpu_place
,
src
+
i
*
src_after
,
sizeof
(
T
)
*
size
);
}
else
{
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
auto
&
gpu_place
=
place
;
auto
&
cuda_ctx
=
reinterpret_cast
<
const
phi
::
GPUContext
&>
(
ctx
);
memory_utils
::
Copy
(
gpu_place
,
dst
+
i
*
dst_after
,
gpu_place
,
src
+
i
*
src_after
,
sizeof
(
T
)
*
size
,
cuda_ctx
.
stream
());
#elif defined(PADDLE_WITH_ASCEND_CL)
auto
&
npu_place
=
place
;
auto
&
npu_ctx
=
reinterpret_cast
<
const
platform
::
NPUDeviceContext
&>
(
ctx
);
memory_utils
::
Copy
(
npu_place
,
dst
+
i
*
dst_after
,
npu_place
,
src
+
i
*
src_after
,
sizeof
(
T
)
*
size
,
npu_ctx
.
stream
());
#elif defined(PADDLE_WITH_MLU)
auto
&
mlu_place
=
place
;
auto
&
mlu_ctx
=
reinterpret_cast
<
const
platform
::
MLUDeviceContext
&>
(
ctx
);
memory_utils
::
Copy
(
mlu_place
,
dst
+
i
*
dst_after
,
mlu_place
,
src
+
i
*
src_after
,
sizeof
(
T
)
*
size
,
mlu_ctx
.
stream
());
#else
PADDLE_THROW
(
phi
::
errors
::
PreconditionNotMet
(
"Paddle is not compiled with GPU."
));
#endif
}
CopyWithContext
<
Context
>
(
ctx
,
place
,
dst
+
i
*
dst_after
,
place
,
src
+
i
*
src_after
,
sizeof
(
T
)
*
size
);
}
}
template
<
typename
T
>
template
<
typename
T
,
typename
Context
>
inline
void
StridedMemcpyWithAxis0
(
const
phi
::
Device
Context
&
dev_ctx
,
const
Context
&
dev_ctx
,
const
phi
::
DenseTensor
&
input
,
const
std
::
vector
<
const
phi
::
DenseTensor
*>&
shape_refer
,
std
::
vector
<
phi
::
DenseTensor
*>*
outputs
)
{
...
...
@@ -159,13 +154,13 @@ inline void StridedMemcpyWithAxis0(
auto
out_stride
=
stride_numel
(
shape_refer
[
i
]
->
dims
());
auto
out
=
outputs
->
at
(
i
);
if
(
out
!=
nullptr
&&
out
->
initialized
()
&&
out
->
numel
()
>
0
)
{
StridedNumelCopyWithAxis
<
T
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
(),
out_stride
,
input
.
data
<
T
>
()
+
input_offset
,
in_stride
,
out_stride
[
axis
]);
StridedNumelCopyWithAxis
<
T
,
Context
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
(),
out_stride
,
input
.
data
<
T
>
()
+
input_offset
,
in_stride
,
out_stride
[
axis
]);
}
input_offset
+=
out_stride
[
axis
];
}
...
...
paddle/phi/kernels/gpu/concat_kernel.cu
浏览文件 @
7d727f36
...
...
@@ -85,13 +85,14 @@ void ConcatKernel(const Context& dev_ctx,
}
auto
in_stride
=
phi
::
stride_numel
(
in
->
dims
());
auto
out_stride
=
phi
::
stride_numel
(
out
->
dims
());
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
->
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
phi
::
funcs
::
StridedNumelCopyWithAxis
<
T
,
Context
>
(
dev_ctx
,
axis
,
out
->
data
<
T
>
()
+
output_offset
,
out_stride
,
in
->
data
<
T
>
(),
in_stride
,
in_stride
[
axis
]);
output_offset
+=
in_stride
[
axis
];
}
}
else
{
...
...
paddle/phi/kernels/impl/concat_grad_kernel_impl.h
浏览文件 @
7d727f36
...
...
@@ -57,7 +57,7 @@ void ConcatGradKernel(const Context& dev_ctx,
if
(
axis
==
0
&&
outs
.
size
()
<
10
)
{
std
::
vector
<
const
DenseTensor
*>
ref_shape
;
ref_shape
.
insert
(
ref_shape
.
begin
(),
x
.
begin
(),
x
.
end
());
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
>
(
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
,
Context
>
(
dev_ctx
,
out_grad
,
ref_shape
,
&
outputs
);
}
else
{
phi
::
funcs
::
SplitFunctor
<
Context
,
T
>
split_functor
;
...
...
paddle/phi/kernels/impl/split_kernel_impl.h
浏览文件 @
7d727f36
...
...
@@ -37,7 +37,8 @@ void SplitKernel(const Context& dev_ctx,
int
axis
=
axis_scalar
.
to
<
int
>
();
// Sometimes direct copies will be faster, this maybe need deeply analysis.
if
(
axis
==
0
&&
outs
.
size
()
<
10
)
{
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
>
(
dev_ctx
,
x
,
shape_refer
,
&
outs
);
phi
::
funcs
::
StridedMemcpyWithAxis0
<
T
,
Context
>
(
dev_ctx
,
x
,
shape_refer
,
&
outs
);
}
else
{
phi
::
funcs
::
SplitFunctor
<
Context
,
T
>
functor
;
functor
(
dev_ctx
,
x
,
shape_refer
,
axis
,
&
outs
);
...
...
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