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体验新版 GitCode,发现更多精彩内容 >>
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e33017f2
编写于
7月 18, 2018
作者:
L
Luo Tao
浏览文件
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浏览文件
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电子邮件补丁
差异文件
fix _clone_variable in optimizer.py
上级
9c0fad47
变更
1
隐藏空白更改
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并排
Showing
1 changed file
with
10 addition
and
10 deletion
+10
-10
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+10
-10
未找到文件。
python/paddle/fluid/optimizer.py
浏览文件 @
e33017f2
...
...
@@ -1180,16 +1180,16 @@ class ModelAverage(Optimizer):
self
.
_add_average_restore_op
(
block
,
param_grad
)
def
_add_average_apply_op
(
self
,
block
,
param_grad
):
param
=
block
.
clone_variable
(
param_grad
[
0
])
grad
=
block
.
clone_variable
(
param_grad
[
1
])
sum_1
=
block
.
clone_variable
(
self
.
_get_accumulator
(
'sum_1'
,
param
))
sum_2
=
block
.
clone_variable
(
self
.
_get_accumulator
(
'sum_2'
,
param
))
sum_3
=
block
.
clone_variable
(
self
.
_get_accumulator
(
'sum_3'
,
param
))
num_accumulates
=
block
.
clone_variable
(
param
=
block
.
_
clone_variable
(
param_grad
[
0
])
grad
=
block
.
_
clone_variable
(
param_grad
[
1
])
sum_1
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'sum_1'
,
param
))
sum_2
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'sum_2'
,
param
))
sum_3
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'sum_3'
,
param
))
num_accumulates
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'num_accumulates'
,
param
))
old_num_accumulates
=
block
.
clone_variable
(
old_num_accumulates
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'old_num_accumulates'
,
param
))
num_updates
=
block
.
clone_variable
(
num_updates
=
block
.
_
clone_variable
(
self
.
_get_accumulator
(
'num_updates'
,
param
))
# backup param value to grad
layers
.
assign
(
input
=
param
,
output
=
grad
)
...
...
@@ -1203,8 +1203,8 @@ class ModelAverage(Optimizer):
layers
.
elementwise_div
(
x
=
sum
,
y
=
tmp
,
out
=
param
)
def
_add_average_restore_op
(
self
,
block
,
param_grad
):
param
=
block
.
clone_variable
(
param_grad
[
0
])
grad
=
block
.
clone_variable
(
param_grad
[
1
])
param
=
block
.
_
clone_variable
(
param_grad
[
0
])
grad
=
block
.
_
clone_variable
(
param_grad
[
1
])
layers
.
assign
(
input
=
grad
,
output
=
param
)
def
_append_average_accumulate_op
(
self
,
param
):
...
...
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