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 0if x > 2.5: return 1if -2.5 <= x <= 2.5: return 0.2 * x + 0.5
|
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Last updated 2020-10-01 UTC.
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TensorFlow 1 version
View source on GitHub