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chenpangpang
transformers
Commits
81e1e248
Commit
81e1e248
authored
Dec 10, 2018
by
Li Li
Browse files
Fix optimizer to work with horovod
parent
a2b6918a
Changes
1
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-2
pytorch_pretrained_bert/optimization.py
pytorch_pretrained_bert/optimization.py
+3
-2
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pytorch_pretrained_bert/optimization.py
View file @
81e1e248
...
@@ -17,6 +17,7 @@
...
@@ -17,6 +17,7 @@
import
math
import
math
import
torch
import
torch
from
torch.optim
import
Optimizer
from
torch.optim
import
Optimizer
from
torch.optim.optimizer
import
required
from
torch.nn.utils
import
clip_grad_norm_
from
torch.nn.utils
import
clip_grad_norm_
def
warmup_cosine
(
x
,
warmup
=
0.002
):
def
warmup_cosine
(
x
,
warmup
=
0.002
):
...
@@ -55,10 +56,10 @@ class BertAdam(Optimizer):
...
@@ -55,10 +56,10 @@ class BertAdam(Optimizer):
weight_decay_rate: Weight decay. Default: 0.01
weight_decay_rate: Weight decay. Default: 0.01
max_grad_norm: Maximum norm for the gradients (-1 means no clipping). Default: 1.0
max_grad_norm: Maximum norm for the gradients (-1 means no clipping). Default: 1.0
"""
"""
def
__init__
(
self
,
params
,
lr
,
warmup
=-
1
,
t_total
=-
1
,
schedule
=
'warmup_linear'
,
def
__init__
(
self
,
params
,
lr
=
required
,
warmup
=-
1
,
t_total
=-
1
,
schedule
=
'warmup_linear'
,
b1
=
0.9
,
b2
=
0.999
,
e
=
1e-6
,
weight_decay_rate
=
0.01
,
b1
=
0.9
,
b2
=
0.999
,
e
=
1e-6
,
weight_decay_rate
=
0.01
,
max_grad_norm
=
1.0
):
max_grad_norm
=
1.0
):
if
not
lr
>=
0.0
:
if
lr
is
not
required
and
lr
<
0.0
:
raise
ValueError
(
"Invalid learning rate: {} - should be >= 0.0"
.
format
(
lr
))
raise
ValueError
(
"Invalid learning rate: {} - should be >= 0.0"
.
format
(
lr
))
if
schedule
not
in
SCHEDULES
:
if
schedule
not
in
SCHEDULES
:
raise
ValueError
(
"Invalid schedule parameter: {}"
.
format
(
schedule
))
raise
ValueError
(
"Invalid schedule parameter: {}"
.
format
(
schedule
))
...
...
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