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8cbc75ca
编写于
4月 12, 2023
作者:
Y
Yiqun Liu
提交者:
GitHub
4月 12, 2023
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电子邮件补丁
差异文件
Cherry-pick the support of bf16 of grad_clip, in #51285. (#52816)
上级
3869a3b4
变更
1
显示空白变更内容
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并排
Showing
1 changed file
with
50 addition
and
14 deletion
+50
-14
python/paddle/fluid/clip.py
python/paddle/fluid/clip.py
+50
-14
未找到文件。
python/paddle/fluid/clip.py
浏览文件 @
8cbc75ca
...
...
@@ -420,6 +420,20 @@ def _allow_pure_fp16_global_norm_clip(*args):
return
old_value
_allow_pure_bf16_global_norm_clip_flag
=
False
def
_allow_pure_bf16_global_norm_clip
(
*
args
):
global
_allow_pure_bf16_global_norm_clip_flag
if
len
(
args
)
==
0
:
return
_allow_pure_bf16_global_norm_clip_flag
else
:
assert
len
(
args
)
==
1
and
isinstance
(
args
[
0
],
bool
)
old_value
=
_allow_pure_bf16_global_norm_clip_flag
_allow_pure_bf16_global_norm_clip_flag
=
args
[
0
]
return
old_value
class
ClipGradByGlobalNorm
(
ClipGradBase
):
r
"""
Given a list of Tensor :math:`t\_list` , calculate the global norm for the elements of all tensors in
...
...
@@ -584,6 +598,7 @@ class ClipGradByGlobalNorm(ClipGradBase):
params_and_grads
=
[]
sum_square_list
=
[]
sum_square_list_fp16
=
[]
sum_square_list_bf16
=
[]
sum_square_list_fp32
=
[]
with
framework
.
name_scope
(
'gradient_clip'
):
for
p
,
g
in
params_grads
:
...
...
@@ -598,18 +613,27 @@ class ClipGradByGlobalNorm(ClipGradBase):
merge_grad
=
layers
.
get_tensor_from_selected_rows
(
merge_grad
)
sum_square
=
_squared_l2_norm
(
merge_grad
)
if
sum_square
.
dtype
==
core
.
VarDesc
.
VarType
.
FP16
:
sum_square_list_fp16
.
append
(
sum_square
)
elif
sum_square
.
dtype
==
core
.
VarDesc
.
VarType
.
BF16
:
sum_square_list_bf16
.
append
(
sum_square
)
elif
sum_square
.
dtype
==
core
.
VarDesc
.
VarType
.
FP32
:
sum_square_list_fp32
.
append
(
sum_square
)
else
:
sum_square_list
.
append
(
sum_square
)
if
len
(
sum_square_list_fp16
)
>
0
and
len
(
sum_square_list_bf16
)
>
0
:
raise
NotSupportedError
(
'FP16 and BF16 are not supported at the same time.'
)
# all parameters have been filterd out
if
(
len
(
sum_square_list
)
+
len
(
sum_square_list_fp16
)
+
len
(
sum_square_list_bf16
)
+
len
(
sum_square_list_fp32
)
==
0
):
...
...
@@ -620,7 +644,7 @@ class ClipGradByGlobalNorm(ClipGradBase):
global_norm_var
=
[]
if
len
(
sum_square_list_fp16
)
>
0
:
global_norm_var_fp16
=
layers
.
sums
(
sum_square_list_fp16
)
global_norm_var_fp16
=
paddle
.
add_n
(
sum_square_list_fp16
)
if
(
sum_square_list_fp32
or
sum_square_list
...
...
@@ -631,8 +655,20 @@ class ClipGradByGlobalNorm(ClipGradBase):
)
else
:
global_norm_var
.
append
(
global_norm_var_fp16
)
if
len
(
sum_square_list_bf16
)
>
0
:
global_norm_var_bf16
=
paddle
.
add_n
(
sum_square_list_bf16
)
if
(
sum_square_list_fp32
or
sum_square_list
or
not
_allow_pure_bf16_global_norm_clip
()
):
global_norm_var
.
append
(
global_norm_var_bf16
.
astype
(
sum_dtype
)
)
else
:
global_norm_var
.
append
(
global_norm_var_bf16
)
if
len
(
sum_square_list_fp32
)
>
0
:
global_norm_var_fp32
=
layers
.
sums
(
sum_square_list_fp32
)
global_norm_var_fp32
=
paddle
.
add_n
(
sum_square_list_fp32
)
if
sum_dtype
==
'float32'
:
global_norm_var
.
append
(
global_norm_var_fp32
)
else
:
...
...
@@ -641,23 +677,24 @@ class ClipGradByGlobalNorm(ClipGradBase):
)
if
len
(
sum_square_list
)
>
0
:
# fp64
global_norm_var_other_dtype
=
layers
.
sums
(
sum_square_list
)
global_norm_var_other_dtype
=
paddle
.
add_n
(
sum_square_list
)
global_norm_var
.
append
(
global_norm_var_other_dtype
)
global_norm_var
=
(
layers
.
sums
(
global_norm_var
)
paddle
.
add_n
(
global_norm_var
)
if
len
(
global_norm_var
)
>
1
else
global_norm_var
[
0
]
)
global_norm_var
=
layers
.
sqrt
(
x
=
global_norm_var
)
max_global_norm
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
global_norm_var
.
dtype
,
value
=
self
.
clip_norm
global_norm_var
=
paddle
.
sqrt
(
x
=
global_norm_var
)
max_global_norm
=
paddle
.
full
(
shape
=
[
1
],
dtype
=
global_norm_var
.
dtype
,
fill_value
=
self
.
clip_norm
,
)
scale_var
=
layers
.
elementwise_div
(
scale_var
=
paddle
.
divide
(
x
=
max_global_norm
,
y
=
layers
.
elementwise_max
(
x
=
max_global_norm
,
y
=
global_norm_var
),
y
=
paddle
.
maximum
(
x
=
max_global_norm
,
y
=
global_norm_var
),
)
param_new_grad_name_dict
=
dict
()
for
p
,
g
in
params_grads
:
...
...
@@ -671,9 +708,8 @@ class ClipGradByGlobalNorm(ClipGradBase):
new_g
=
_cast_to_mp_type_if_enabled
(
g
)
# inplace
scale_input
=
(
scale_var
.
astype
(
'float16'
)
if
new_g
.
dtype
==
core
.
VarDesc
.
VarType
.
FP16
and
scale_var
.
dtype
!=
core
.
VarDesc
.
VarType
.
FP16
scale_var
.
astype
(
new_g
.
dtype
)
if
scale_var
.
dtype
!=
new_g
.
dtype
else
scale_var
)
# NOTE(Yuang Liu): For pure dp with gradient merge, the p and g
...
...
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