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体验新版 GitCode,发现更多精彩内容 >>
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42c7bb47
编写于
3月 15, 2022
作者:
Q
qipengh
提交者:
GitHub
3月 15, 2022
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差异文件
[MLU] add check_finite_and_unscale op for amp (#40458)
上级
5cb506b0
变更
2
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2 changed file
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paddle/fluid/operators/amp/check_finite_and_unscale_op_mlu.cc
...le/fluid/operators/amp/check_finite_and_unscale_op_mlu.cc
+88
-0
python/paddle/fluid/tests/unittests/mlu/test_amp_check_finite_and_scale_op_mlu.py
...s/unittests/mlu/test_amp_check_finite_and_scale_op_mlu.py
+145
-0
未找到文件。
paddle/fluid/operators/amp/check_finite_and_unscale_op_mlu.cc
0 → 100644
浏览文件 @
42c7bb47
/* 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/amp/check_finite_and_unscale_op.h"
#include "paddle/fluid/operators/mlu/mlu_baseop.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
>
class
CheckFiniteAndUnscaleMLUKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
&
dev_ctx
=
ctx
.
template
device_context
<
platform
::
MLUDeviceContext
>();
const
auto
xs
=
ctx
.
MultiInput
<
framework
::
Tensor
>
(
"X"
);
const
auto
*
scale
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Scale"
);
auto
outs
=
ctx
.
MultiOutput
<
framework
::
Tensor
>
(
"Out"
);
auto
*
found_inf
=
ctx
.
Output
<
framework
::
Tensor
>
(
"FoundInfinite"
);
found_inf
->
mutable_data
<
bool
>
(
dev_ctx
.
GetPlace
());
MLUCnnlTensorDesc
scale_desc
(
*
scale
);
MLUCnnlTensorDesc
found_inf_desc
(
*
found_inf
,
CNNL_LAYOUT_ARRAY
,
ToCnnlDataType
<
bool
>
());
for
(
size_t
i
=
0
;
i
<
xs
.
size
();
++
i
)
{
const
auto
*
x
=
xs
[
i
];
auto
*
out
=
outs
[
i
];
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// check is_finite or is_nan
Tensor
is_finite
(
found_inf
->
type
());
if
(
i
!=
0
)
{
is_finite
.
Resize
(
phi
::
make_ddim
({
1
}));
is_finite
.
mutable_data
<
bool
>
(
ctx
.
GetPlace
());
}
else
{
is_finite
.
ShareDataWith
(
*
found_inf
);
}
MLUCnnlTensorDesc
x_desc
(
*
x
);
MLUCnnl
::
IsNanInf
(
ctx
,
x_desc
.
get
(),
GetBasePtr
(
x
),
GetBasePtr
(
&
is_finite
));
// save is_finite by logical_and op after checking every input
if
(
i
!=
0
)
{
MLUCnnlTensorDesc
is_finite_desc
(
is_finite
,
CNNL_LAYOUT_ARRAY
,
ToCnnlDataType
<
bool
>
());
MLUCnnl
::
Logic
(
ctx
,
CNNL_LOGIC_OP_OR
,
found_inf_desc
.
get
(),
GetBasePtr
(
found_inf
),
is_finite_desc
.
get
(),
GetBasePtr
(
&
is_finite
),
found_inf_desc
.
get
(),
GetBasePtr
(
found_inf
));
}
// The normal logic is :
// out = in, if found_inf = true
// out = in/scale, if found_inf = false
// But when found_inf is true, the data of Out should not be used.
// So, on MLU, we always compute out with in/scale.
MLUCnnlTensorDesc
out_desc
(
*
out
);
MLUCnnl
::
Div
(
ctx
,
CNNL_COMPUTATION_HIGH_PRECISION
,
x_desc
.
get
(),
GetBasePtr
(
x
),
scale_desc
.
get
(),
GetBasePtr
(
scale
),
out_desc
.
get
(),
GetBasePtr
(
out
));
}
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
REGISTER_OP_MLU_KERNEL
(
check_finite_and_unscale
,
ops
::
CheckFiniteAndUnscaleMLUKernel
<
float
>
,
ops
::
CheckFiniteAndUnscaleMLUKernel
<
plat
::
float16
>
);
python/paddle/fluid/tests/unittests/mlu/test_amp_check_finite_and_scale_op_mlu.py
0 → 100644
浏览文件 @
42c7bb47
# 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.
from
__future__
import
print_function
import
numpy
as
np
import
unittest
import
sys
sys
.
path
.
append
(
".."
)
from
op_test
import
OpTest
import
paddle
paddle
.
enable_static
()
SEED
=
2022
class
TestCheckFiniteAndUnscaleOp
(
OpTest
):
def
setUp
(
self
):
self
.
set_mlu
()
self
.
op_type
=
"check_finite_and_unscale"
self
.
init_dtype
()
self
.
init_test_case
()
def
init_test_case
(
self
):
x
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
0
]),
'Out'
:
[(
'out0'
,
x
/
scale
)],
}
def
set_mlu
(
self
):
self
.
__class__
.
use_mlu
=
True
self
.
place
=
paddle
.
device
.
MLUPlace
(
0
)
def
init_dtype
(
self
):
self
.
dtype
=
np
.
float32
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
)
class
TestCheckFiniteAndUnscaleOpWithNan
(
TestCheckFiniteAndUnscaleOp
):
def
init_test_case
(
self
):
x
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x
[
128
][
128
]
=
np
.
nan
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
1
]),
'Out'
:
[(
'out0'
,
x
)],
}
def
test_check_output
(
self
):
# When input contains nan, do not check the output,
# since the output may be nondeterministic and will be discarded.
self
.
check_output_with_place
(
self
.
place
,
no_check_set
=
[
'Out'
])
class
TestCheckFiniteAndUnscaleOpWithInf
(
TestCheckFiniteAndUnscaleOp
):
def
init_test_case
(
self
):
x
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x
[
128
][
128
]
=
np
.
inf
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
1
]),
'Out'
:
[(
'out0'
,
x
)],
}
def
test_check_output
(
self
):
# When input contains inf, do not check the output,
# since the output may be nondeterministic and will be discarded.
self
.
check_output_with_place
(
self
.
place
,
no_check_set
=
[
'Out'
])
class
TestCheckFiniteAndUnscaleOpMultiInput
(
TestCheckFiniteAndUnscaleOp
):
def
init_test_case
(
self
):
x0
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x1
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x0
),
(
'x1'
,
x1
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
0
]),
'Out'
:
[(
'out0'
,
x0
/
scale
),
(
'out1'
,
x1
/
scale
)],
}
class
TestCheckFiniteAndUnscaleOpMultiInputWithNan
(
TestCheckFiniteAndUnscaleOp
):
def
init_test_case
(
self
):
x0
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x0
[
128
][
128
]
=
np
.
nan
x1
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x0
),
(
'x1'
,
x1
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
1
]),
'Out'
:
[(
'out0'
,
x0
/
scale
),
(
'out1'
,
x1
/
scale
)],
}
def
test_check_output
(
self
):
# When input contains inf, do not check the output,
# since the output may be nondeterministic and will be discarded.
self
.
check_output_with_place
(
self
.
place
,
no_check_set
=
[
'Out'
])
class
TestCheckFiniteAndUnscaleOpMultiInputWithInf
(
TestCheckFiniteAndUnscaleOp
):
def
init_test_case
(
self
):
x0
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x0
[
128
][
128
]
=
np
.
nan
x1
=
np
.
random
.
random
((
129
,
129
)).
astype
(
self
.
dtype
)
x1
[
128
][
128
]
=
np
.
inf
scale
=
np
.
random
.
random
((
1
)).
astype
(
self
.
dtype
)
self
.
inputs
=
{
'X'
:
[(
'x0'
,
x0
),
(
'x1'
,
x1
)],
'Scale'
:
scale
}
self
.
outputs
=
{
'FoundInfinite'
:
np
.
array
([
1
]),
'Out'
:
[(
'out0'
,
x0
/
scale
),
(
'out1'
,
x1
/
scale
)],
}
def
test_check_output
(
self
):
# When input contains inf, do not check the output,
# since the output may be nondeterministic and will be discarded.
self
.
check_output_with_place
(
self
.
place
,
no_check_set
=
[
'Out'
])
if
__name__
==
'__main__'
:
unittest
.
main
()
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