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)float >= 0. Learning rate.
The exponential decay rate for the 1st moment estimates. float, 0 < beta < 1. Generally close to 1.
The exponential decay rate for the 2nd moment estimates. float, 0 < beta < 1. Generally close to 1.
float >= 0. Fuzz factor. If NULL, defaults to k_epsilon().
float >= 0. Learning rate decay over each update.
Gradients will be clipped when their L2 norm exceeds this value.
Gradients will be clipped when their absolute value exceeds this value.
Other optimizers: optimizer_adadelta,
optimizer_adagrad,
optimizer_adam,
optimizer_nadam,
optimizer_rmsprop,
optimizer_sgd