tf.keras.activations.hard_sigmoid
Stay organized with collections
Save and categorize content based on your preferences.
Hard sigmoid activation function.
tf.keras.activations.hard_sigmoid(
x
)
A faster approximation of the sigmoid activation.
For example:
a = tf.constant([-3.0,-1.0, 0.0,1.0,3.0], dtype = tf.float32)
b = tf.keras.activations.hard_sigmoid(a)
b.numpy()
array([0. , 0.3, 0.5, 0.7, 1. ], dtype=float32)
Arguments |
|---|
x
|
Input tensor.
|
Returns |
|---|
The hard sigmoid activation, defined as:
if x < -2.5: return 0if x > 2.5: return 1if -2.5 <= x <= 2.5: return 0.2 * x + 0.5
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[]]
TensorFlow 1 version
View source on GitHub