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!525 Add comments explanation about weight_decay and loss_scale supporting int type 

Merge pull request !525 from fanglei/typecheck
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mindspore-ci-bot 2020-04-21 20:44:42 +08:00 committed by Gitee
parent 0ef7983174 9b28d9bd4a
commit d18b366418
1 changed files with 4 additions and 2 deletions
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mindspore/nn/optim/optimizer.py
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@ -45,8 +45,10 @@ class Optimizer(Cell):
learning_rate (float): A floating point value for the learning rate. Should be greater than 0.
parameters (list): A list of parameter, which will be updated. The element in `parameters`
should be class mindspore.Parameter.
weight_decay (float): A floating point value for the weight decay. Default: 0.0.
loss_scale (float): A floating point value for the loss scale. Default: 1.0. Should be greater than 0.
weight_decay (float): A floating point value for the weight decay. If the type of `weight_decay`
input is int, it will be convertd to float. Default: 0.0.
loss_scale (float): A floating point value for the loss scale. It should be greater than 0. If the
type of `loss_scale` input is int, it will be convertd to float. Default: 1.0.
decay_filter (Function): A function to determine whether to apply weight decay on parameters. Default: lambda
x: 'beta' not in x.name and 'gamma' not in x.name.