static adamax(learningRate = 0.002, beta1 = 0.9, beta2 = 0.999, epsilon = null, decay = 0.0) {
        return new (0, _adamaxOptimizer.AdamaxOptimizer)(learningRate, beta1, beta2, epsilon, decay);
    }
Constructs a `tf.AdamaxOptimizer` that uses the Adamax algorithm.
See [https://arxiv.org/abs/1412.6980](https://arxiv.org/abs/1412.6980)

@param learningRate The learning rate to use for the Adamax gradient
descent algorithm.
@param beta1 The exponential decay rate for the 1st moment estimates.
@param beta2 The exponential decay rate for the 2nd moment estimates.
@param epsilon A small constant for numerical stability.
@param decay The learning rate decay over each update.

@doc {heading: 'Training', subheading: 'Optimizers', namespace: 'train'}