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neural_network/activation_functions/leaky_rectified_linear_unit.py
39 строк
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Kausthub Kannan
Added Leaky ReLU Activation Function (#8962)
17 авг 2023, 04:22
Не верифицирован
17 авг 2023, 04:22
f6b1242
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""" Leaky Rectified Linear Unit (Leaky ReLU) Use Case: Leaky ReLU addresses the problem of the vanishing gradient. For more detailed information, you can refer to the following link: https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Leaky_ReLU """ import numpy as np def leaky_rectified_linear_unit(vector: np.ndarray, alpha: float) -> np.ndarray: """ Implements the LeakyReLU activation function. Parameters: vector (np.ndarray): The input array for LeakyReLU activation. alpha (float): The slope for negative values. Returns: np.ndarray: The input array after applying the LeakyReLU activation. Formula: f(x) = x if x > 0 else f(x) = alpha * x Examples: >>> leaky_rectified_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]), alpha=0.3) array([ 2.3 , 0.6 , -0.6 , -1.14]) >>> leaky_rectified_linear_unit(np.array([-9.2, -0.3, 0.45, -4.56]), alpha=0.067) array([-0.6164 , -0.0201 , 0.45 , -0.30552]) """ return np.where(vector > 0, vector, alpha * vector) if __name__ == "__main__": import doctest doctest.testmod()