mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-10-17 03:01:13 +00:00
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
|
"""
|
||
|
|
Implements the Exponential Linear Unit or ELU function.
|
||
|
|
|
||
|
|
The function takes a vector of K real numbers and a real number alpha as
|
||
|
|
input and then applies the ELU function to each element of the vector.
|
||
|
|
|
||
|
|
Script inspired from its corresponding Wikipedia article
|
||
|
|
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
|
||
|
|
"""
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
|
||
|
|
def exponential_linear_unit(vector: np.ndarray, alpha: float) -> np.ndarray:
|
||
|
|
"""
|
||
|
|
Implements the ELU activation function.
|
||
|
|
Parameters:
|
||
|
|
vector: the array containing input of elu activation
|
||
|
|
alpha: hyper-parameter
|
||
|
|
return:
|
||
|
|
elu (np.array): The input numpy array after applying elu.
|
||
|
|
|
||
|
|
Mathematically, f(x) = x, x>0 else (alpha * (e^x -1)), x<=0, alpha >=0
|
||
|
|
|
||
|
|
Examples:
|
||
|
|
>>> exponential_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]), alpha=0.3)
|
||
|
|
array([ 2.3 , 0.6 , -0.25939942, -0.29328877])
|
||
|
|
|
||
|
|
>>> exponential_linear_unit(vector=np.array([-9.2,-0.3,0.45,-4.56]), alpha=0.067)
|
||
|
|
array([-0.06699323, -0.01736518, 0.45 , -0.06629904])
|
||
|
|
|
||
|
|
|
||
|
|
"""
|
||
|
|
return np.where(vector > 0, vector, (alpha * (np.exp(vector) - 1)))
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
import doctest
|
||
|
|
|
||
|
|
doctest.testmod()
|