mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-27 15:01:08 +00:00
26d650ec28
* 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
41 lines
1.1 KiB
Python
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]
|