Adamax optimizer

Adamax optimizer from Section 7 of the Adam paper. It is a variant of Adam based on the infinity norm.

optimizer_adamax(lr = 0.002, beta_1 = 0.9, beta_2 = 0.999,
  epsilon = NULL, decay = 0, clipnorm = NULL, clipvalue = NULL)

Arguments

lr

float >= 0. Learning rate.

beta_1

The exponential decay rate for the 1st moment estimates. float, 0 < beta < 1. Generally close to 1.

beta_2

The exponential decay rate for the 2nd moment estimates. float, 0 < beta < 1. Generally close to 1.

epsilon

float >= 0. Fuzz factor. If NULL, defaults to k_epsilon().

decay

float >= 0. Learning rate decay over each update.

clipnorm

Gradients will be clipped when their L2 norm exceeds this value.

clipvalue

Gradients will be clipped when their absolute value exceeds this value.

See also