Python/neural_network/activation_functions/mish.py

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"""
Mish Activation Function
Use Case: Improved version of the ReLU activation function used in Computer Vision.
For more detailed information, you can refer to the following link:
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Mish
"""
import numpy as np
from softplus import softplus
def mish(vector: np.ndarray) -> np.ndarray:
"""
Implements the Mish activation function.
Parameters:
vector (np.ndarray): The input array for Mish activation.
Returns:
np.ndarray: The input array after applying the Mish activation.
Formula:
f(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + e^x))
Examples:
>>> mish(vector=np.array([2.3,0.6,-2,-3.8]))
array([ 2.26211893, 0.46613649, -0.25250148, -0.08405831])
>>> mish(np.array([-9.2, -0.3, 0.45, -4.56]))
array([-0.00092952, -0.15113318, 0.33152014, -0.04745745])
"""
return vector * np.tanh(softplus(vector))
if __name__ == "__main__":
import doctest
doctest.testmod()