# PolynomialScheduler#

class composer.optim.PolynomialScheduler(power, t_max='1dur', alpha_f=0.0)[source]#

Sets the learning rate to be proportional to a power of the fraction of training time left.

Specifially, the learning rate multiplier $$\alpha$$ can be expressed as:

$\alpha(t) = \alpha_f + (1 - \alpha_f) \times (1 - \tau) ^ {\kappa}$

Given $$\tau$$, the fraction of time elapsed (clipped to the interval $$[0, 1]$$), as:

$\tau = t / t_{max}$

Where $$\kappa$$ represents the exponent to be used for the proportionality relationship, $$t_{max}$$ represents the duration of this scheduler, and $$\alpha_f$$ represents the learning rate multiplier to decay to.

Parameters
• power (float) – The exponent to be used for the proportionality relationship.

• t_max (str | Time) – The duration of this scheduler. Default = "1dur".

• alpha_f (float) – Learning rate multiplier to decay to. Default = 0.0.