Python/neural_network/activation_functions/rectified_linear_unit.py
piyush-poddar 26d650ec28
Moved relu.py from maths/ to neural_network/activation_functions ()
* Moved file relu.py from maths/ to neural_network/activation_functions

* Renamed relu.py to rectified_linear_unit.py

* Renamed relu.py to rectified_linear_unit.py in DIRECTORY.md
2023-10-04 16:28:19 -04:00

41 lines
1.1 KiB
Python

"""
This script demonstrates the implementation of the ReLU function.
It's a kind of activation function defined as the positive part of its argument in the
context of neural network.
The function takes a vector of K real numbers as input and then argmax(x, 0).
After through ReLU, the element of the vector always 0 or real number.
Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
"""
from __future__ import annotations
import numpy as np
def relu(vector: list[float]):
"""
Implements the relu function
Parameters:
vector (np.array,list,tuple): A numpy array of shape (1,n)
consisting of real values or a similar list,tuple
Returns:
relu_vec (np.array): The input numpy array, after applying
relu.
>>> vec = np.array([-1, 0, 5])
>>> relu(vec)
array([0, 0, 5])
"""
# compare two arrays and then return element-wise maxima.
return np.maximum(0, vector)
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]