mindspore.nn.cosine_decay_lr
- mindspore.nn.cosine_decay_lr(min_lr, max_lr, total_step, step_per_epoch, decay_epoch)[source]
Calculate learning rate base on cosine decay function.
For the i-th step, the formula of computing decayed_learning_rate[i] is:
\[decayed\_learning\_rate[i] = min\_learning\_rate + 0.5 * (max\_learning\_rate - min\_learning\_rate) * (1 + cos(\frac{current\_epoch}{decay\_epoch}\pi))\]Where \(current\_epoch=floor(\frac{i}{step\_per\_epoch})\).
- Parameters
- Returns
list[float]. The size of list is total_step.
Examples
>>> min_lr = 0.01 >>> max_lr = 0.1 >>> total_step = 6 >>> step_per_epoch = 2 >>> decay_epoch = 2 >>> output = cosine_decay_lr(min_lr, max_lr, total_step, step_per_epoch, decay_epoch) >>> print(output) [0.1, 0.1, 0.05500000000000001, 0.05500000000000001, 0.01, 0.01]