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1b9e6790
编写于
2月 14, 2022
作者:
mhhhh1
提交者:
GitHub
2月 14, 2022
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差异文件
[MLU] add mlu kernel for c_broadcast op (#39470)
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db11357c
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paddle/fluid/operators/collective/c_broadcast_op_mlu.cc
paddle/fluid/operators/collective/c_broadcast_op_mlu.cc
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paddle/fluid/operators/collective/c_broadcast_op_mlu.cc
0 → 100644
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1b9e6790
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
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 "paddle/fluid/operators/collective/c_broadcast_op.h"
#if defined(PADDLE_WITH_CNCL)
#include "paddle/fluid/platform/collective_helper.h"
#include "paddle/fluid/platform/device/mlu/cncl_helper.h"
#endif
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
class
CBroadcastOPMLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
#if defined(PADDLE_WITH_CNCL)
auto
x
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
auto
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
int
numel
=
x
->
numel
();
cnclDataType_t
dtype
=
platform
::
ToCNCLDataType
(
x
->
type
());
int
rid
=
ctx
.
Attr
<
int
>
(
"ring_id"
);
auto
place
=
ctx
.
GetPlace
();
auto
comm
=
platform
::
CNCLCommContext
::
Instance
().
Get
(
rid
,
place
);
mluStream
stream
=
nullptr
;
if
(
ctx
.
Attr
<
bool
>
(
"use_calc_stream"
))
{
auto
dev_ctx
=
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
);
stream
=
static_cast
<
platform
::
MLUDeviceContext
*>
(
dev_ctx
)
->
stream
();
}
else
{
stream
=
comm
->
stream
();
}
int
root
=
ctx
.
Attr
<
int
>
(
"root"
);
if
(
root
==
comm
->
rank
())
{
PADDLE_ENFORCE_MLU_SUCCESS
(
cnclBcast
(
reinterpret_cast
<
void
*>
(
const_cast
<
T
*>
(
x
->
data
<
T
>
())),
numel
,
dtype
,
root
,
comm
->
comm
(),
stream
));
VLOG
(
3
)
<<
"rank "
<<
comm
->
rank
()
<<
" invoke Bcast. sent "
<<
x
->
numel
();
if
(
out
!=
x
)
{
framework
::
TensorCopy
(
*
static_cast
<
const
framework
::
Tensor
*>
(
x
),
place
,
*
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
),
static_cast
<
framework
::
Tensor
*>
(
out
));
}
}
else
{
PADDLE_ENFORCE_MLU_SUCCESS
(
cnclBcast
(
out
->
mutable_data
<
T
>
(
place
),
numel
,
dtype
,
root
,
comm
->
comm
(),
stream
));
VLOG
(
3
)
<<
"rank "
<<
comm
->
rank
()
<<
" invoke Bcast. recieved "
<<
framework
::
product
(
out
->
dims
());
}
out
->
Resize
(
x
->
dims
());
out
->
set_lod
(
x
->
lod
());
#else
PADDLE_THROW
(
platform
::
errors
::
PreconditionNotMet
(
"PaddlePaddle should compile with MLU."
));
#endif
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
REGISTER_OP_MLU_KERNEL
(
c_broadcast
,
ops
::
CBroadcastOPMLUKernel
<
float
>
,
ops
::
CBroadcastOPMLUKernel
<
plat
::
float16
>
,
ops
::
CBroadcastOPMLUKernel
<
int
>
,
ops
::
CBroadcastOPMLUKernel
<
int16_t
>
,
ops
::
CBroadcastOPMLUKernel
<
int8_t
>
,
ops
::
CBroadcastOPMLUKernel
<
uint8_t
>
);
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