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Computes scaled exponential linear: scale * alpha * (exp(features) - 1)

if < 0, scale * features otherwise.

To be used together with initializer = tf.variance_scaling_initializer(factor=1.0, mode='FAN_IN'). For correct dropout, use tf.contrib.nn.alpha_dropout.

See Self-Normalizing Neural Networks

features A Tensor. Must be one of the following types: half, bfloat16, float32, float64.
name A name for the operation (optional).

A Tensor. Has the same type as features.