softplus.py

"""
Softplus Activation Function

Use Case: The Softplus function is a smooth approximation of the ReLU function.
For more detailed information, you can refer to the following link:
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Softplus
"""

import numpy as np


def softplus(vector: np.ndarray) -> np.ndarray:
    """
    Implements the Softplus activation function.

    Parameters:
        vector (np.ndarray): The input array for the Softplus activation.

    Returns:
        np.ndarray: The input array after applying the Softplus activation.

    Formula: f(x) = ln(1 + e^x)

    Examples:
    >>> softplus(np.array([2.3, 0.6, -2, -3.8]))
    array([2.39554546, 1.03748795, 0.12692801, 0.02212422])

    >>> softplus(np.array([-9.2, -0.3, 0.45, -4.56]))
    array([1.01034298e-04, 5.54355244e-01, 9.43248946e-01, 1.04077103e-02])
    """
    return np.log(1 + np.exp(vector))


if __name__ == "__main__":
    import doctest

    doctest.testmod()