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体验新版 GitCode,发现更多精彩内容 >>
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0fe2001a
编写于
4月 02, 2022
作者:
L
Leo Chen
提交者:
GitHub
4月 02, 2022
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差异文件
make variable 'gradient_merge_cond' local (#41262)
上级
acec26a1
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
6 addition
and
21 deletion
+6
-21
python/paddle/distributed/fleet/meta_optimizers/sharding_optimizer.py
...e/distributed/fleet/meta_optimizers/sharding_optimizer.py
+2
-7
python/paddle/distributed/passes/auto_parallel_gradient_merge.py
...paddle/distributed/passes/auto_parallel_gradient_merge.py
+2
-7
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+2
-7
未找到文件。
python/paddle/distributed/fleet/meta_optimizers/sharding_optimizer.py
浏览文件 @
0fe2001a
...
...
@@ -1621,13 +1621,8 @@ class ShardingOptimizer(MetaOptimizerBase):
persistable
=
True
,
force_cpu
=
True
)
cond_var
=
layers
.
create_global_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
value
=
bool
(
0
),
dtype
=
'bool'
,
persistable
=
False
,
force_cpu
=
True
)
cond_var
=
main_block
.
create_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
dtype
=
'bool'
)
with
device_guard
(
"cpu"
):
# step_var = (step_var + 1) % k_step
...
...
python/paddle/distributed/passes/auto_parallel_gradient_merge.py
浏览文件 @
0fe2001a
...
...
@@ -107,13 +107,8 @@ def _get_gm_cond_var(main_program, k_steps, dist_context):
force_cpu
=
True
)
set_var_dist_attr
(
dist_context
,
step_var
,
[
-
1
],
world_process_group
.
ranks
)
cond_var
=
layers
.
create_global_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
value
=
bool
(
0
),
dtype
=
'bool'
,
persistable
=
False
,
force_cpu
=
True
)
cond_var
=
main_block
.
create_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
dtype
=
'bool'
)
set_var_dist_attr
(
dist_context
,
cond_var
,
[
-
1
],
world_process_group
.
ranks
)
with
device_guard
(
"cpu"
):
...
...
python/paddle/fluid/optimizer.py
浏览文件 @
0fe2001a
...
...
@@ -7098,13 +7098,8 @@ class GradientMergeOptimizer(object):
persistable
=
True
,
force_cpu
=
True
)
cond_var
=
layers
.
create_global_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
value
=
bool
(
0
),
dtype
=
'bool'
,
persistable
=
False
,
force_cpu
=
True
)
cond_var
=
main_block
.
create_var
(
name
=
"gradient_merge_cond"
,
shape
=
[
1
],
dtype
=
'bool'
)
with
device_guard
(
"cpu"
):
# step_var = (step_var + 1) % k_step
...
...
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