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