Docs4dev
Docs
tensorflow / 2.4 / keras / activations / hard_sigmoid.html

tf.keras.activations.hard_sigmoid

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 0
  • if x > 2.5: return 1
  • if -2.5 <= x <= 2.5: return 0.2 * x + 0.5

© 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/r2.4/api_docs/python/tf/keras/activations/hard_sigmoid