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Added Mish Activation Function #9942

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Oct 6, 2023
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39 changes: 39 additions & 0 deletions neural_network/activation_functions/mish.py
Original file line number Diff line number Diff line change
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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


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(np.log(1 + np.exp(vector)))
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This looks good, but it'd be nice to implement this using the softplus function—once we have an implementation of softplus in this repo.



if __name__ == "__main__":
import doctest

doctest.testmod()