tf.raw_ops.Selu
Computes scaled exponential linear: scale * alpha * (exp(features) - 1)
tf.raw_ops.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 | |
|---|---|
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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/Selu