sparse_ho.optimizers.Adam

class sparse_ho.optimizers.Adam(n_outer=100, epsilon=0.001, lr=0.01, beta_1=0.9, beta_2=0.999, verbose=False, tol=1e-05, t_max=10000)

ADAM optimizer for the outer problem.

This Adam code is taken from https://github.com/sagarvegad/Adam-optimizer/blob/master/Adam.py

Parameters
n_outer: int, optional (default=100).

Number of maximum updates of alpha.

epsilon: float, optional (default=1e-3)
lr: float, optional (default=1e-2)

Learning rate

beta_1: float, optional (default=0.9)
beta_2: float, optional (default=0.999)
verbose: bool, optional (default=False)

Indicates whether information about hyperparameter optimization process is printed or not.

tolfloat, optional (default=1e-5)

Tolerance for the inner optimization solver.

t_max: float, optional (default=10_000)

Maximum running time threshold in seconds.

__init__(n_outer=100, epsilon=0.001, lr=0.01, beta_1=0.9, beta_2=0.999, verbose=False, tol=1e-05, t_max=10000)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([n_outer, epsilon, lr, beta_1, …])

Initialize self.