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correct the errors on webpage0817

This commit is contained in:
zhangyi 2022-08-17 16:53:26 +08:00
parent ba031c7277
commit 326173f50a
4 changed files with 4 additions and 4 deletions
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2
docs/api/api_python/nn/mindspore.nn.optim_note_weight_decay.rst
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@ -2,4 +2,4 @@
参数分组情况下，可以分组调整权重衰减策略。
分组时，每组网络参数均可配置 `weight_decay` 。若未配置，则该组网络参数使用优化器中配置的 `weight_decay` 。
分组时，每组网络参数均可配置 `weight_decay` ，若未配置，则该组网络参数使用优化器中配置的 `weight_decay` 。

2
mindspore/python/mindspore/nn/optim/adam.py
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@ -369,7 +369,7 @@ class Adam(Optimizer):
If parameters are not grouped, the `weight_decay` in optimizer will be applied on the network parameters without
'beta' or 'gamma' in their names. Users can group parameters to change the strategy of decaying weight. When
parameters are grouped, each group can set `weight_decay`, if not, the `weight_decay` in optimizer will be
parameters are grouped, each group can set `weight_decay`. If not, the `weight_decay` in optimizer will be
applied.
Args:

2
mindspore/python/mindspore/nn/optim/lamb.py
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@ -138,7 +138,7 @@ class Lamb(Optimizer):
If parameters are not grouped, the `weight_decay` in optimizer will be applied on the network parameters without
'beta' or 'gamma' in their names. Users can group parameters to change the strategy of decaying weight. When
parameters are grouped, each group can set `weight_decay`, if not, the `weight_decay` in optimizer will be
parameters are grouped, each group can set `weight_decay`. If not, the `weight_decay` in optimizer will be
applied.
Args:

2
mindspore/python/mindspore/nn/optim/proximal_ada_grad.py
View File

@ -80,7 +80,7 @@ class ProximalAdagrad(Optimizer):
If parameters are not grouped, the `weight_decay` in optimizer will be applied on the network parameters without
'beta' or 'gamma' in their names. Users can group parameters to change the strategy of decaying weight. When
parameters are grouped, each group can set `weight_decay`, if not, the `weight_decay` in optimizer will be
parameters are grouped, each group can set `weight_decay`. If not, the `weight_decay` in optimizer will be
applied.
Args: