TensorFlow 2 version
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Computes scaled exponential linear: scale * alpha * (exp(features) - 1)
tf.nn.selu(
features, name=None
)
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 | |
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features
|
A Tensor. Must be one of the following types: half, bfloat16, float32, float64.
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name
|
A name for the operation (optional). |
Returns | |
|---|---|
A Tensor. Has the same type as features.
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