Adagrad¶
- class Adagrad(params, lr=0.01, lr_decay=0.0, eps=1e-10, weight_decay=0.0)[源代码]¶
Implements Adagrad algorithm proposed in “Adaptive Subgradient Methods for Online Learning and Stochastic Optimization”.
- 参数
params (Union[Iterable[Parameter], dict]) – 可迭代对象，可以是一组待优化的参数，或定义几组参数的dict类型。
lr (float) – coefficient that scales delta before it is applied to the parameters. Default: 1e-2.
lr_decay (float) – learning rate decay. Default: 0.
eps (float) – term added to the denominator to improve numerical stability. Default: 1e-10.
weight_decay (float) – weight decay (L2 penalty). Default: 0.
- 返回
An instance of the Adagrad optimizer.