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39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
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"""
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Squareplus Activation Function
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Use Case: Squareplus designed to enhance positive values and suppress negative values.
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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)#Squareplus
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"""
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import numpy as np
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def squareplus(vector: np.ndarray, beta: float) -> np.ndarray:
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"""
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Implements the SquarePlus activation function.
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Parameters:
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vector (np.ndarray): The input array for the SquarePlus activation.
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beta (float): size of the curved region
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Returns:
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np.ndarray: The input array after applying the SquarePlus activation.
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Formula: f(x) = ( x + sqrt(x^2 + b) ) / 2
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Examples:
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>>> squareplus(np.array([2.3, 0.6, -2, -3.8]), beta=2)
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array([2.5 , 1.06811457, 0.22474487, 0.12731349])
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>>> squareplus(np.array([-9.2, -0.3, 0.45, -4.56]), beta=3)
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array([0.0808119 , 0.72891979, 1.11977651, 0.15893419])
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"""
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return (vector + np.sqrt(vector**2 + beta)) / 2
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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