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neural_network/activation_functions/rectified_linear_unit.py
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[pre-commit.ci] pre-commit autoupdate (#11322)
13 мар 2024, 09:52
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13 мар 2024, 09:52
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""" 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]