hard_sigmoid#
- class brainunit.math.hard_sigmoid(x, unit_to_scale=None)#
Hard Sigmoid activation function.
Computes the element-wise function
\[\mathrm{hard\_sigmoid}(x) = \frac{\mathrm{relu6}(x + 3)}{6}\]- Parameters:
x (saiunit.Quantity |
Array|ndarray|number|bool) – Input array. Must be unitless if aQuantity.unit_to_scale (saiunit.Unit |
None) – Unit used to convertxto a dimensionless number before applying the activation.
- Returns:
out – An array with values in the range [0, 1].
- Return type:
Array
Examples
>>> import jax.numpy as jnp >>> import saiunit.math as sumath >>> sumath.hard_sigmoid(jnp.array([-4., 0., 4.])) Array([0. , 0.5, 1. ], dtype=float32)