Added leaky rectified linear algorithm

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()

maths/leaky_relu.py

@@ -0,0 +1,58 @@
+"""
+This algorithm implements the leaky rectified linear algorithm (LReLU).
+
+LReLU is at times used as a substitute to ReLU because it fixes the dying ReLU problem.
+This is done by adding a slight slope to the negative portion of the function.
+The default value for the slope is 0.01.
+The new slope is determined before the network is trained.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+from __future__ import annotations
+
+
+def leaky_relu(
+ vector: float | list[float], negative_slope: float = 0.01
+) -> float | list[float]:
+ """
+ Implements the leaky rectified linear activation function
+
+ :param vector: The float or list of floats to apply the algorithm to
+ :param slope: The multiplier that is applied to every negative value in the list
+ :return: The modified value or list of values after applying LReLU
+
+ >>> leaky_relu([-5])
+ [-0.05]
+ >>> leaky_relu([-2, 0.8, -0.3])
+ [-0.02, 0.8, -0.003]
+ >>> leaky_relu(-3.0)
+ -0.03
+ >>> leaky_relu(2)
+ Traceback (most recent call last):
+ ...
+ ValueError: leaky_relu() only accepts floats or a list of floats for vector
+ """
+ if isinstance(vector, int):
+ raise ValueError(
+ "leaky_relu() only accepts floats or a list of floats for vector"
+ )
+ if not isinstance(negative_slope, float):
+ raise ValueError("leaky_relu() only accepts a float value for negative_slope")
+
+ if isinstance(vector, float):
+ if vector < 0:
+ return vector * negative_slope
+ return vector
+
+ for index, value in enumerate(vector):
+ if value < 0:
+ vector[index] = value * negative_slope
+
+ return vector
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()