mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-10-16 18:51:14 +00:00
490e645ed3
* updating DIRECTORY.md
* types(maths): Fix pylance issues in maths
* reset(vsc): Reset settings changes
* Update maths/jaccard_similarity.py
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
* revert(erosion_operation): Revert erosion_operation
* test(jaccard_similarity): Add doctest to test alternative_union
* types(newton_raphson): Add typehints to func bodies
---------
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
"""
|
|
This script demonstrates an implementation of the Gaussian Error Linear Unit function.
|
|
* https://en.wikipedia.org/wiki/Activation_function#Comparison_of_activation_functions
|
|
|
|
The function takes a vector of K real numbers as input and returns x * sigmoid(1.702*x).
|
|
Gaussian Error Linear Unit (GELU) is a high-performing neural network activation
|
|
function.
|
|
|
|
This script is inspired by a corresponding research paper.
|
|
* https://arxiv.org/abs/1606.08415
|
|
"""
|
|
|
|
import numpy as np
|
|
|
|
|
|
def sigmoid(vector: np.ndarray) -> np.ndarray:
|
|
"""
|
|
Mathematical function sigmoid takes a vector x of K real numbers as input and
|
|
returns 1/ (1 + e^-x).
|
|
https://en.wikipedia.org/wiki/Sigmoid_function
|
|
|
|
>>> sigmoid(np.array([-1.0, 1.0, 2.0]))
|
|
array([0.26894142, 0.73105858, 0.88079708])
|
|
"""
|
|
return 1 / (1 + np.exp(-vector))
|
|
|
|
|
|
def gaussian_error_linear_unit(vector: np.ndarray) -> np.ndarray:
|
|
"""
|
|
Implements the Gaussian Error Linear Unit (GELU) function
|
|
|
|
Parameters:
|
|
vector (np.array): A numpy array of shape (1,n)
|
|
consisting of real values
|
|
|
|
Returns:
|
|
gelu_vec (np.array): The input numpy array, after applying
|
|
gelu.
|
|
|
|
Examples:
|
|
>>> gaussian_error_linear_unit(np.array([-1.0, 1.0, 2.0]))
|
|
array([-0.15420423, 0.84579577, 1.93565862])
|
|
|
|
>>> gaussian_error_linear_unit(np.array([-3]))
|
|
array([-0.01807131])
|
|
"""
|
|
return vector * sigmoid(1.702 * vector)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import doctest
|
|
|
|
doctest.testmod()
|