mindspore.nn.CosineDecayLR

class mindspore.nn.CosineDecayLR(min_lr, max_lr, decay_steps)

Calculates learning rate base on cosine decay function.

For the i-th step, the formula of computing decayed_learning_rate[i] is:

\[decayed\_learning\_rate[i] = min\_learning\_rate + 0.5 * (max\_learning\_rate - min\_learning\_rate) * (1 + cos(\frac{current\_step}{decay\_steps}\pi))\]

Parameters

• min_lr (float) – The minimum value of learning rate.

• max_lr (float) – The maximum value of learning rate.

• decay_steps (int) – A value used to calculate decayed learning rate.

Inputs:

Tensor. The current step number.

Outputs:

Tensor. The learning rate value for the current step.

Examples

>>> min_lr = 0.01
>>> max_lr = 0.1
>>> decay_steps = 4
>>> global_steps = Tensor(2, mstype.int32)
>>> cosine_decay_lr = nn.CosineDecayLR(min_lr, max_lr, decay_steps)
>>> result = cosine_decay_lr(global_steps)
>>> print(result)
0.055