tf.nn.selu

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

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.nn.selu

tf.nn.selu(
    features: Annotated[Any, TV_Selu_T], name=None
) -> Annotated[Any, TV_Selu_T]

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

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

Returns
A Tensor. Has the same type as features.