|
|
@@ -45,8 +45,10 @@ class Optimizer(Cell): |
|
|
learning_rate (float): A floating point value for the learning rate. Should be greater than 0. |
|
|
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` |
|
|
parameters (list): A list of parameter, which will be updated. The element in `parameters` |
|
|
should be class mindspore.Parameter. |
|
|
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 |
|
|
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. |
|
|
x: 'beta' not in x.name and 'gamma' not in x.name. |
|
|
|
|
|
|
|
|
|