#### Swish

p
```"""
This script demonstrates the implementation of the Sigmoid Linear Unit (SiLU)
or swish function.
* https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
* https://en.wikipedia.org/wiki/Swish_function

The function takes a vector x of K real numbers as input and returns x * sigmoid(x).
Swish is a smooth, non-monotonic function defined as f(x) = x * sigmoid(x).
Extensive experiments shows that Swish consistently matches or outperforms ReLU
on deep networks applied to a variety of challenging domains such as
image classification and machine translation.

This script is inspired by a corresponding research paper.
* https://arxiv.org/abs/1710.05941
* https://blog.paperspace.com/swish-activation-function/
"""

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 sigmoid_linear_unit(vector: np.ndarray) -> np.ndarray:
"""
Implements the Sigmoid Linear Unit (SiLU) or swish function

Parameters:
vector (np.ndarray): A  numpy array consisting of real values

Returns:
swish_vec (np.ndarray): The input numpy array, after applying swish

Examples:
>>> sigmoid_linear_unit(np.array([-1.0, 1.0, 2.0]))
array([-0.26894142,  0.73105858,  1.76159416])

>>> sigmoid_linear_unit(np.array([-2]))
array([-0.23840584])
"""
return vector * sigmoid(vector)

def swish(vector: np.ndarray, trainable_parameter: int) -> np.ndarray:
"""
Parameters:
vector (np.ndarray): A  numpy array consisting of real values
trainable_parameter: Use to implement various Swish Activation Functions

Returns:
swish_vec (np.ndarray): The input numpy array, after applying swish

Examples:
>>> swish(np.array([-1.0, 1.0, 2.0]), 2)
array([-0.11920292,  0.88079708,  1.96402758])

>>> swish(np.array([-2]), 1)
array([-0.23840584])
"""
return vector * sigmoid(trainable_parameter * vector)

if __name__ == "__main__":
import doctest

doctest.testmod()
```