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master
neural_network/activation_functions/softplus.py
37 строк
966 B
Kausthub Kannan
Added Softplus activation function (#9944)
06 окт 2023, 23:26
Не верифицирован
06 окт 2023, 23:26
80a2087
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""" 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()