soft_sign#
- class brainunit.math.soft_sign(x, unit_to_scale=None)#
Soft-sign activation function.
Computes the element-wise function
\[\mathrm{soft\_sign}(x) = \frac{x}{|x| + 1}\]- 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 (-1, 1).
- Return type:
Array
Examples
>>> import jax.numpy as jnp >>> import saiunit.math as sumath >>> sumath.soft_sign(jnp.array([-2., 0., 2.])) Array([-0.6666667, 0. , 0.6666667], dtype=float32)