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体验新版 GitCode,发现更多精彩内容 >>
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4a66e7cf
编写于
12月 02, 2022
作者:
Y
Yiqun Liu
提交者:
GitHub
12月 02, 2022
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电子邮件补丁
差异文件
Optimize the python overhead of reshape and layer_norm. (#48635)
上级
5bcf35cd
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
18 addition
and
33 deletion
+18
-33
python/paddle/nn/functional/norm.py
python/paddle/nn/functional/norm.py
+4
-9
python/paddle/tensor/manipulation.py
python/paddle/tensor/manipulation.py
+14
-24
未找到文件。
python/paddle/nn/functional/norm.py
浏览文件 @
4a66e7cf
...
...
@@ -382,16 +382,11 @@ def layer_norm(
)
if
in_dygraph_mode
():
(
pre_act
,
_
,
_
,
)
=
_C_ops
.
layer_norm
(
x
,
weight
,
bias
,
epsilon
,
begin_norm_axis
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
pre_act
,
act
=
None
)
out
,
_
,
_
=
_C_ops
.
layer_norm
(
x
,
weight
,
bias
,
epsilon
,
begin_norm_axis
)
return
out
if
_in_legacy_dygraph
():
pre_ac
t
,
_
,
_
=
_legacy_C_ops
.
layer_norm
(
ou
t
,
_
,
_
=
_legacy_C_ops
.
layer_norm
(
x
,
weight
,
bias
,
...
...
@@ -400,7 +395,7 @@ def layer_norm(
'begin_norm_axis'
,
begin_norm_axis
,
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
pre_act
,
act
=
None
)
return
out
check_variable_and_dtype
(
x
,
'input'
,
[
'float16'
,
'float32'
,
'float64'
],
'LayerNorm'
...
...
python/paddle/tensor/manipulation.py
浏览文件 @
4a66e7cf
...
...
@@ -14,7 +14,6 @@
# TODO: define functions to manipulate a tensor
import
warnings
from
collections
import
Counter
import
numpy
as
np
...
...
@@ -22,7 +21,7 @@ import numpy as np
import
paddle
from
paddle
import
_C_ops
,
_legacy_C_ops
from
..common_ops_import
import
_varbase_creator
,
dygraph_utils
,
fill_constant
from
..common_ops_import
import
_varbase_creator
,
fill_constant
from
..fluid.data_feeder
import
(
check_dtype
,
check_type
,
...
...
@@ -3564,16 +3563,9 @@ def reshape(x, shape, name=None):
"""
actual_shape
=
None
act
=
None
inplace
=
False
if
in_dygraph_mode
():
tmp_tensor_type
=
core
.
eager
.
Tensor
# TODO(zhiqiu): enable inplace in dygraph mode.
if
inplace
:
warnings
.
warn
(
"Inplace on reshape is not allowed and will be discarded in dygraph mode currently."
)
if
isinstance
(
shape
,
(
list
,
tuple
)):
shape
=
[
item
.
numpy
().
item
(
0
)
...
...
@@ -3581,8 +3573,11 @@ def reshape(x, shape, name=None):
else
item
for
item
in
shape
]
out
=
_C_ops
.
reshape
(
x
,
shape
)
elif
isinstance
(
shape
,
tmp_tensor_type
):
if
shape
==
x
.
shape
:
out
=
x
else
:
out
=
_C_ops
.
reshape
(
x
,
shape
)
elif
isinstance
(
shape
,
core
.
eager
.
Tensor
):
shape
.
stop_gradient
=
True
out
=
_C_ops
.
reshape
(
x
,
shape
)
else
:
...
...
@@ -3591,14 +3586,10 @@ def reshape(x, shape, name=None):
" got '{}.'"
.
format
(
type
(
shape
))
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
out
,
act
)
return
out
else
:
if
_in_legacy_dygraph
():
tmp_tensor_type
=
Variable
if
inplace
:
warnings
.
warn
(
"Inplace on reshape is not allowed and will be discarded in dygraph mode currently."
)
if
isinstance
(
shape
,
(
list
,
tuple
)):
shape
=
[
item
.
numpy
().
item
(
0
)
if
isinstance
(
item
,
Variable
)
else
item
...
...
@@ -3614,7 +3605,7 @@ def reshape(x, shape, name=None):
" got '{}.'"
.
format
(
type
(
shape
))
)
return
dygraph_utils
.
_append_activation_in_dygraph
(
out
,
act
)
return
out
check_variable_and_dtype
(
x
,
...
...
@@ -3690,11 +3681,7 @@ def reshape(x, shape, name=None):
actual_shape
.
stop_gradient
=
True
inputs
[
"Shape"
]
=
actual_shape
out
=
(
x
if
inplace
else
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
x_shape
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
"reshape2"
,
...
...
@@ -3703,7 +3690,7 @@ def reshape(x, shape, name=None):
outputs
=
{
"Out"
:
out
,
"XShape"
:
x_shape
},
)
return
helper
.
append_activation
(
out
)
return
out
@
inplace_apis_in_dygraph_only
...
...
@@ -3721,7 +3708,10 @@ def reshape_(x, shape, name=None):
else
item
for
item
in
shape
]
out
=
_C_ops
.
reshape_
(
x
,
shape
)
if
shape
==
x
.
shape
:
out
=
x
else
:
out
=
_C_ops
.
reshape_
(
x
,
shape
)
elif
isinstance
(
shape
,
tmp_tensor_type
):
shape
.
stop_gradient
=
True
out
=
_C_ops
.
reshape_
(
x
,
shape
)
...
...
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