From 60235f49defb07cf43de929f5cf4b45218c3b69f Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 17:01:55 +0530
Subject: [PATCH 01/42] tanh function been added

---
 maths/tanh.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 maths/tanh.py

diff --git a/maths/tanh.py b/maths/tanh.py
new file mode 100644
index 000000000000..9a42ae31f235
--- /dev/null
+++ b/maths/tanh.py
@@ -0,0 +1,32 @@
+"""
+This script demonstrates the implementation of the tangent hyperbolic or tanh function.
+
+The function takes a vector of K real numbers as input and then (e^x - e^(-x))/(e^x + e^(-x)).
+After through tanh, the element of the vector mostly -1 between 1.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Activation_function
+"""
+import numpy
+import numpy as np
+
+
+def tanh(vector):
+    '''
+        Implements the tanh function
+
+        Parameters:
+            vector: np.array, list, tuple consisting real values
+
+        Returns:
+            tanh (np.array): The input numpy array  after applying
+        tanh.
+
+        mathematically (e^x - e^(-x))/(e^x + e^(-x)) can be written as (2/(1+e^(-2x))-1
+    '''
+    exp_vector = np.exp(-2 * vector)
+    return (2 / (1 + exp_vector)) - 1
+
+
+if __name__ == '__main__':
+    print(tanh(np.array([1, 5, 6, 113, 13, 16, -5.23])))

From dbea59dfbc7033a675956246c7389c81c705b195 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 17:24:14 +0530
Subject: [PATCH 02/42] tanh function been added

---
 maths/tanh.py | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index 9a42ae31f235..70306c5ee047 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -11,8 +11,8 @@
 import numpy as np
 
 
-def tanh(vector):
-    '''
+def tanh_func(vector):
+    """
         Implements the tanh function
 
         Parameters:
@@ -23,10 +23,15 @@ def tanh(vector):
         tanh.
 
         mathematically (e^x - e^(-x))/(e^x + e^(-x)) can be written as (2/(1+e^(-2x))-1
-    '''
+
+    Examples:
+        >>> tanh_func(np.array([1, 5, 6, 113, 13, 16, -5.23]))
+        [ 0.76159416  0.9999092   0.99998771  1.          1.          1.    -0.99994268]
+    """
+
     exp_vector = np.exp(-2 * vector)
     return (2 / (1 + exp_vector)) - 1
 
 
 if __name__ == '__main__':
-    print(tanh(np.array([1, 5, 6, 113, 13, 16, -5.23])))
+    print(tanh_func(np.array([0.23])))

From 6e3f28d9d9b5378c6f3aed45f4c95bfc00e1bdcc Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 23 Apr 2023 11:58:40 +0000
Subject: [PATCH 03/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/tanh.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index 70306c5ee047..93ef6ec462de 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -33,5 +33,5 @@ def tanh_func(vector):
     return (2 / (1 + exp_vector)) - 1
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     print(tanh_func(np.array([0.23])))

From d42af7b70f5315589c687219cb0b781db5b51375 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 17:34:24 +0530
Subject: [PATCH 04/42] tanh function is added

---
 maths/tanh.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index 70306c5ee047..a8c1d7cf3dfe 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -9,14 +9,15 @@
 """
 import numpy
 import numpy as np
+import doctest
 
 
-def tanh_func(vector):
+def tanh_func(vector: np.array) -> np.array:
     """
         Implements the tanh function
 
         Parameters:
-            vector: np.array, list, tuple consisting real values
+            vector: np.array
 
         Returns:
             tanh (np.array): The input numpy array  after applying
@@ -26,7 +27,9 @@ def tanh_func(vector):
 
     Examples:
         >>> tanh_func(np.array([1, 5, 6, 113, 13, 16, -5.23]))
-        [ 0.76159416  0.9999092   0.99998771  1.          1.          1.    -0.99994268]
+        array([ 0.76159416,  0.9999092 ,  0.99998771,  1.        ,  1.        ,
+            1.        , -0.99994268])
+
     """
 
     exp_vector = np.exp(-2 * vector)
@@ -34,4 +37,5 @@ def tanh_func(vector):
 
 
 if __name__ == '__main__':
-    print(tanh_func(np.array([0.23])))
+    doctest.testmod()
+

From fa675a47fda6af87e6f2e03a18b8d84df12e27a0 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 17:42:22 +0530
Subject: [PATCH 05/42] tanh function is added

---
 maths/tanh.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index a8c1d7cf3dfe..f07cf2d402e0 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -38,4 +38,3 @@ def tanh_func(vector: np.array) -> np.array:
 
 if __name__ == '__main__':
     doctest.testmod()
-

From a6b5d0547e4be8337f1ddabc090a60a2c213fa4f Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 23 Apr 2023 12:20:11 +0000
Subject: [PATCH 06/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/tanh.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index f07cf2d402e0..2ce383e53642 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -36,5 +36,5 @@ def tanh_func(vector: np.array) -> np.array:
     return (2 / (1 + exp_vector)) - 1
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     doctest.testmod()

From 2827b159d166306a68823ec7fadfea77b0f11e36 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 18:32:08 +0530
Subject: [PATCH 07/42] tanh function added

---
 maths/tanh.py | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index f07cf2d402e0..cd28a59903fd 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -1,18 +1,18 @@
 """
-This script demonstrates the implementation of the tangent hyperbolic or tanh function.
+This script demonstrates the implementation of the tangent hyperbolic
+or tanh function.
 
-The function takes a vector of K real numbers as input and then (e^x - e^(-x))/(e^x + e^(-x)).
-After through tanh, the element of the vector mostly -1 between 1.
+The function takes a vector of K real numbers as input and
+then (e^x - e^(-x))/(e^x + e^(-x)). After through tanh, the
+element of the vector mostly -1 between 1.
 
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Activation_function
 """
-import numpy
 import numpy as np
-import doctest
 
 
-def tanh_func(vector: np.array) -> np.array:
+def tangent_hyperbolic(vector: np.array) -> np.array:
     """
         Implements the tanh function
 
@@ -26,7 +26,7 @@ def tanh_func(vector: np.array) -> np.array:
         mathematically (e^x - e^(-x))/(e^x + e^(-x)) can be written as (2/(1+e^(-2x))-1
 
     Examples:
-        >>> tanh_func(np.array([1, 5, 6, 113, 13, 16, -5.23]))
+        >>> tangent_hyperbolic(np.array([1,5,6,113,13,16,-5.23]))
         array([ 0.76159416,  0.9999092 ,  0.99998771,  1.        ,  1.        ,
             1.        , -0.99994268])
 
@@ -36,5 +36,7 @@ def tanh_func(vector: np.array) -> np.array:
     return (2 / (1 + exp_vector)) - 1
 
 
-if __name__ == '__main__':
-    doctest.testmod()
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)

From 9114b527a1b530323a80cc33106c15970b968d5e Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 23 Apr 2023 19:17:44 +0530
Subject: [PATCH 08/42] tanh function added

---
 maths/tanh.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index cd28a59903fd..7330f378373e 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -26,9 +26,8 @@ def tangent_hyperbolic(vector: np.array) -> np.array:
         mathematically (e^x - e^(-x))/(e^x + e^(-x)) can be written as (2/(1+e^(-2x))-1
 
     Examples:
-        >>> tangent_hyperbolic(np.array([1,5,6,113,13,16,-5.23]))
-        array([ 0.76159416,  0.9999092 ,  0.99998771,  1.        ,  1.        ,
-            1.        , -0.99994268])
+        >>> tangent_hyperbolic(np.array([1,5,6,-0.67]))
+        array([ 0.76159416,  0.9999092 ,  0.99998771, -0.58497988])
 
     """
 
@@ -39,4 +38,4 @@ def tangent_hyperbolic(vector: np.array) -> np.array:
 if __name__ == "__main__":
     import doctest
 
-    doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
+    doctest.testmod()

From a4ca89775c25680d5e802aa8c3803e583cde4791 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Mon, 24 Apr 2023 20:30:04 +0530
Subject: [PATCH 09/42] tanh function is added

---
 maths/tanh.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/maths/tanh.py b/maths/tanh.py
index 7330f378373e..d6233da639ec 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -29,6 +29,9 @@ def tangent_hyperbolic(vector: np.array) -> np.array:
         >>> tangent_hyperbolic(np.array([1,5,6,-0.67]))
         array([ 0.76159416,  0.9999092 ,  0.99998771, -0.58497988])
 
+        >>> tangent_hyperbolic(np.array([8,10,2,-0.98,13]))
+        array([ 0.99999977,  1.        ,  0.96402758, -0.7530659 ,  1.        ])
+
     """
 
     exp_vector = np.exp(-2 * vector)

From e0495023d63bef348bb2774afbf3b54418d55da8 Mon Sep 17 00:00:00 2001
From: Christian Clauss <cclauss@me.com>
Date: Tue, 25 Apr 2023 18:01:07 +0200
Subject: [PATCH 10/42] Apply suggestions from code review

---
 maths/tanh.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/maths/tanh.py b/maths/tanh.py
index d6233da639ec..ddab3e1ab717 100644
--- a/maths/tanh.py
+++ b/maths/tanh.py
@@ -20,8 +20,7 @@ def tangent_hyperbolic(vector: np.array) -> np.array:
             vector: np.array
 
         Returns:
-            tanh (np.array): The input numpy array  after applying
-        tanh.
+            tanh (np.array): The input numpy array after applying tanh.
 
         mathematically (e^x - e^(-x))/(e^x + e^(-x)) can be written as (2/(1+e^(-2x))-1
 
@@ -34,8 +33,7 @@ def tangent_hyperbolic(vector: np.array) -> np.array:
 
     """
 
-    exp_vector = np.exp(-2 * vector)
-    return (2 / (1 + exp_vector)) - 1
+    return (2 / (1 + np.exp(-2 * vector))) - 1
 
 
 if __name__ == "__main__":

From 66cc81a30592a5734d9d3d767320d014df933926 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Thu, 27 Apr 2023 12:00:39 +0530
Subject: [PATCH 11/42] ELU activation function is added

---
 maths/elu_activation.py | 39 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 39 insertions(+)
 create mode 100644 maths/elu_activation.py

diff --git a/maths/elu_activation.py b/maths/elu_activation.py
new file mode 100644
index 000000000000..441c3cf4ee43
--- /dev/null
+++ b/maths/elu_activation.py
@@ -0,0 +1,39 @@
+"""
+Implements the Exponential Linear Unit or ELU function.
+
+The function takes a vector of K real numbers and a real number alpha as
+input and then applies the ELU function to each element of the vector.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+"""
+
+import numpy as np
+
+
+def elu_activation(vector: np.array, alpha: float) -> np.array:
+    """
+         Implements the ELU activation function.
+         Parameters:
+             vector: np.array
+             alpha: float
+         return:
+         elu (np.array): The input numpy array after applying elu.
+
+         Mathematically, f(x) = x, x>0 else (alpha * (e^x -1)), x<=0, alpha >=0
+
+    Examples:
+         >>> elu_activation(vector=np.array([2.3,0.6,-2,-3.8,9]), alpha=0.3)
+         array([ 2.3       ,  0.6       , -0.25939942, -0.29328877,  9.        ])
+
+         >>> elu_activation(vector=np.array([-9.2,-0.3,-2.45,0.45]), alpha=0.067)
+         array([-0.06699323, -0.01736518, -0.06121833,  0.45      ])
+
+    """
+    return np.where(vector > 0, vector, (alpha * (np.exp(vector) - 1)))
+
+
+if __name__ == '__main__':
+    import doctest
+
+    doctest.testmod()

From d40c74b379098b9d3d280b03c6af2338abbc079b Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 27 Apr 2023 06:35:23 +0000
Subject: [PATCH 12/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/elu_activation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/elu_activation.py b/maths/elu_activation.py
index 441c3cf4ee43..cc1631551b54 100644
--- a/maths/elu_activation.py
+++ b/maths/elu_activation.py
@@ -33,7 +33,7 @@ def elu_activation(vector: np.array, alpha: float) -> np.array:
     return np.where(vector > 0, vector, (alpha * (np.exp(vector) - 1)))
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     import doctest
 
     doctest.testmod()

From 5453434e967e03ba54a1537d06099683ddddb35f Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Fri, 28 Apr 2023 09:57:32 +0530
Subject: [PATCH 13/42] elu activation is added

---
 maths/elu_activation.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/maths/elu_activation.py b/maths/elu_activation.py
index cc1631551b54..2f5ded173f0a 100644
--- a/maths/elu_activation.py
+++ b/maths/elu_activation.py
@@ -9,9 +9,10 @@
 """
 
 import numpy as np
+from typing import TYPE_CHECKING
 
 
-def elu_activation(vector: np.array, alpha: float) -> np.array:
+def elu_activation(vector: np.ndarray, alpha: float) -> np.ndarray:
     """
          Implements the ELU activation function.
          Parameters:

From 0d1546eb757d438ab88b386eb64779ff7e897ad2 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Fri, 28 Apr 2023 10:03:31 +0530
Subject: [PATCH 14/42] ELU activation is added

---
 maths/elu_activation.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/maths/elu_activation.py b/maths/elu_activation.py
index 2f5ded173f0a..d4b5e71b9368 100644
--- a/maths/elu_activation.py
+++ b/maths/elu_activation.py
@@ -9,7 +9,6 @@
 """
 
 import numpy as np
-from typing import TYPE_CHECKING
 
 
 def elu_activation(vector: np.ndarray, alpha: float) -> np.ndarray:

From 112611aad41ca676bfabfc0019e21ecd3769ccdd Mon Sep 17 00:00:00 2001
From: Dipankar Mitra <50228537+Mitra-babu@users.noreply.github.com>
Date: Fri, 28 Apr 2023 19:37:26 +0530
Subject: [PATCH 15/42] Update maths/elu_activation.py

Co-authored-by: Christian Clauss <cclauss@me.com>
---
 maths/elu_activation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/elu_activation.py b/maths/elu_activation.py
index d4b5e71b9368..4e9b96f59bec 100644
--- a/maths/elu_activation.py
+++ b/maths/elu_activation.py
@@ -11,7 +11,7 @@
 import numpy as np
 
 
-def elu_activation(vector: np.ndarray, alpha: float) -> np.ndarray:
+def exponential_linear_unit(vector: np.ndarray, alpha: float) -> np.ndarray:
     """
          Implements the ELU activation function.
          Parameters:

From dad8cf18b661d7b7d0e84b3dc623960c75b6628b Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Fri, 28 Apr 2023 19:50:26 +0530
Subject: [PATCH 16/42] Exponential_linear_unit activation is added

---
 .../activation_functions/exponential_linear_unit.py       | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)
 rename maths/elu_activation.py => neural_network/activation_functions/exponential_linear_unit.py (77%)

diff --git a/maths/elu_activation.py b/neural_network/activation_functions/exponential_linear_unit.py
similarity index 77%
rename from maths/elu_activation.py
rename to neural_network/activation_functions/exponential_linear_unit.py
index 4e9b96f59bec..71ba07cfe773 100644
--- a/maths/elu_activation.py
+++ b/neural_network/activation_functions/exponential_linear_unit.py
@@ -15,18 +15,18 @@ def exponential_linear_unit(vector: np.ndarray, alpha: float) -> np.ndarray:
     """
          Implements the ELU activation function.
          Parameters:
-             vector: np.array
-             alpha: float
+             vector: the array containing input of elu activation
+             alpha: hyper-parameter
          return:
          elu (np.array): The input numpy array after applying elu.
 
          Mathematically, f(x) = x, x>0 else (alpha * (e^x -1)), x<=0, alpha >=0
 
     Examples:
-         >>> elu_activation(vector=np.array([2.3,0.6,-2,-3.8,9]), alpha=0.3)
+         >>> exponential_linear_unit(vector=np.array([2.3,0.6,-2,-3.8,9]), alpha=0.3)
          array([ 2.3       ,  0.6       , -0.25939942, -0.29328877,  9.        ])
 
-         >>> elu_activation(vector=np.array([-9.2,-0.3,-2.45,0.45]), alpha=0.067)
+         >>> exponential_linear_unit(vector=np.array([-9.2,-0.3,-2.45,0.45]), alpha=0.067)
          array([-0.06699323, -0.01736518, -0.06121833,  0.45      ])
 
     """

From 34be18cadf2193302c2d3bf4c7440f8fa3dbcbd6 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Fri, 28 Apr 2023 19:59:28 +0530
Subject: [PATCH 17/42] Exponential_linear_unit activation is added

---
 .../activation_functions/exponential_linear_unit.py      | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/neural_network/activation_functions/exponential_linear_unit.py b/neural_network/activation_functions/exponential_linear_unit.py
index 71ba07cfe773..7a3cf1d84e71 100644
--- a/neural_network/activation_functions/exponential_linear_unit.py
+++ b/neural_network/activation_functions/exponential_linear_unit.py
@@ -23,11 +23,12 @@ def exponential_linear_unit(vector: np.ndarray, alpha: float) -> np.ndarray:
          Mathematically, f(x) = x, x>0 else (alpha * (e^x -1)), x<=0, alpha >=0
 
     Examples:
-         >>> exponential_linear_unit(vector=np.array([2.3,0.6,-2,-3.8,9]), alpha=0.3)
-         array([ 2.3       ,  0.6       , -0.25939942, -0.29328877,  9.        ])
+    >>> exponential_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]), alpha=0.3)
+    array([ 2.3       ,  0.6       , -0.25939942, -0.29328877])
+
+    >>> exponential_linear_unit(vector=np.array([-9.2,-0.3,0.45,-4.56]), alpha=0.067)
+    array([-0.06699323, -0.01736518,  0.45      , -0.06629904])
 
-         >>> exponential_linear_unit(vector=np.array([-9.2,-0.3,-2.45,0.45]), alpha=0.067)
-         array([-0.06699323, -0.01736518, -0.06121833,  0.45      ])
 
     """
     return np.where(vector > 0, vector, (alpha * (np.exp(vector) - 1)))

From aae8727d1cfd568d0d3cfcc5f852df2c0f3250be Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Tue, 2 May 2023 21:23:38 +0530
Subject: [PATCH 18/42] SiLU activation is added

---
 .../sigmoid_linear_unit.py                    | 40 +++++++++++++++++++
 1 file changed, 40 insertions(+)
 create mode 100644 neural_network/activation_functions/sigmoid_linear_unit.py

diff --git a/neural_network/activation_functions/sigmoid_linear_unit.py b/neural_network/activation_functions/sigmoid_linear_unit.py
new file mode 100644
index 000000000000..f69eb11598b8
--- /dev/null
+++ b/neural_network/activation_functions/sigmoid_linear_unit.py
@@ -0,0 +1,40 @@
+"""
+Implements the Sigmoid Linear Unit or SiLU function
+also known as Swiss functions.
+
+The function takes a vector of K real numbers and then
+applies the SiLU function to each element of the vector.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+https://en.wikipedia.org/wiki/Swish_function
+"""
+
+import numpy as np
+
+
+def sigmoid_linear_unit(vector: np.ndarray) -> np.ndarray:
+    """
+         Implements the SiLU activation function.
+         Parameters:
+             vector: the array containing input of SiLU activation
+         return:
+            The input numpy array after applying SiLU.
+
+         Mathematically, f(x) = x *  1/1+e^(-x)
+
+    Examples:
+    >>> sigmoid_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]))
+    array([ 2.09041719,  0.38739378, -0.23840584, -0.08314883])
+
+    >>> sigmoid_linear_unit(vector=np.array([-9.2,-0.3,0.45,-4.56]))
+    array([-0.00092947, -0.12766724,  0.27478766, -0.04721304])
+
+    """
+    return vector / (1 + np.exp(-vector))
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()

From 28da38a385cceec25d63a52b49c61e2a790b09a9 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Tue, 2 May 2023 21:26:56 +0530
Subject: [PATCH 19/42] SiLU activation is added

---
 neural_network/activation_functions/sigmoid_linear_unit.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/neural_network/activation_functions/sigmoid_linear_unit.py b/neural_network/activation_functions/sigmoid_linear_unit.py
index f69eb11598b8..4e6a154fd7f4 100644
--- a/neural_network/activation_functions/sigmoid_linear_unit.py
+++ b/neural_network/activation_functions/sigmoid_linear_unit.py
@@ -7,7 +7,6 @@
 
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
-https://en.wikipedia.org/wiki/Swish_function
 """
 
 import numpy as np

From fcab387a8fc2358778769218937576f7f0aed6d0 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Mon, 15 May 2023 01:24:10 +0530
Subject: [PATCH 20/42] mish added

---
 .../activation_functions/mish_activation.py   | 48 +++++++++++++++++++
 .../sigmoid_linear_unit.py                    | 39 ---------------
 2 files changed, 48 insertions(+), 39 deletions(-)
 create mode 100644 neural_network/activation_functions/mish_activation.py
 delete mode 100644 neural_network/activation_functions/sigmoid_linear_unit.py

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
new file mode 100644
index 000000000000..9f1688834be8
--- /dev/null
+++ b/neural_network/activation_functions/mish_activation.py
@@ -0,0 +1,48 @@
+"""
+Implements the Mish activation functions.
+
+The function takes a vector of K real numbers input and then
+applies the Mish function, x*tanh(softplus(x) to each element of the vector.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
+
+The proposed paper link is provided below.
+https://arxiv.org/abs/1908.08681
+"""
+
+import numpy as np
+
+
+def mish_activation(vector: np.ndarray) -> np.ndarray:
+    """
+        Implements the Mish function
+
+        Parameters:
+            vector: np.array
+
+        Returns:
+            Mish (np.array): The input numpy array after applying tanh.
+
+        mathematically, mish = x * tanh(softplus(x)  where
+        softplus = ln(1+e^(x)) and tanh = (e^x - e^(-x))/(e^x + e^(-x))
+        so, mish can be written as x * (2/(1+e^(-2 * softplus))-1
+
+    Examples:
+        >>> mish_activation(np.array([1,5,6,-0.67]))
+        array([ 0.86509839,  8.99955208, 10.99992663, -1.93211787])
+
+
+        >>> mish_activation(np.array([8,2,-0.98,13]))
+        array([14.9999982 ,  2.94395896, -2.28214659, 25.        ])
+
+
+    """
+    soft_plus = np.log(np.exp(vector) + 1)
+    return vector * (2 / (1 + np.exp(-2 * soft_plus))) - 1
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()
diff --git a/neural_network/activation_functions/sigmoid_linear_unit.py b/neural_network/activation_functions/sigmoid_linear_unit.py
deleted file mode 100644
index 4e6a154fd7f4..000000000000
--- a/neural_network/activation_functions/sigmoid_linear_unit.py
+++ /dev/null
@@ -1,39 +0,0 @@
-"""
-Implements the Sigmoid Linear Unit or SiLU function
-also known as Swiss functions.
-
-The function takes a vector of K real numbers and then
-applies the SiLU function to each element of the vector.
-
-Script inspired from its corresponding Wikipedia article
-https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
-"""
-
-import numpy as np
-
-
-def sigmoid_linear_unit(vector: np.ndarray) -> np.ndarray:
-    """
-         Implements the SiLU activation function.
-         Parameters:
-             vector: the array containing input of SiLU activation
-         return:
-            The input numpy array after applying SiLU.
-
-         Mathematically, f(x) = x *  1/1+e^(-x)
-
-    Examples:
-    >>> sigmoid_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]))
-    array([ 2.09041719,  0.38739378, -0.23840584, -0.08314883])
-
-    >>> sigmoid_linear_unit(vector=np.array([-9.2,-0.3,0.45,-4.56]))
-    array([-0.00092947, -0.12766724,  0.27478766, -0.04721304])
-
-    """
-    return vector / (1 + np.exp(-vector))
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()

From b1731ec29a3ceb94e5c972168e1c898e68548847 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Tue, 16 May 2023 21:01:16 +0530
Subject: [PATCH 21/42] mish activation is added

---
 neural_network/activation_functions/mish_activation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 9f1688834be8..8948b43228e5 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -2,7 +2,7 @@
 Implements the Mish activation functions.
 
 The function takes a vector of K real numbers input and then
-applies the Mish function, x*tanh(softplus(x) to each element of the vector.
+applies the mish function, x*tanh(softplus(x) to each element of the vector.
 
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Rectifier_(neural_networks)

From 9a5cb3069460db50550135c7f27ab0f4086af87a Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sat, 20 May 2023 22:43:57 +0530
Subject: [PATCH 22/42] inter_quartile_range function is added

---
 maths/inter_quartile_range.py | 60 +++++++++++++++++++++++++++++++++++
 1 file changed, 60 insertions(+)
 create mode 100644 maths/inter_quartile_range.py

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
new file mode 100644
index 000000000000..08a7961bdc28
--- /dev/null
+++ b/maths/inter_quartile_range.py
@@ -0,0 +1,60 @@
+"""
+This is the implementation of inter_quartile range (IQR).
+
+function takes the list of numeric values as input
+and return the IQR as output.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Interquartile_range
+"""
+
+from typing import List
+
+
+def find_median(x: List[float]) -> float:
+    """
+    This is the implementation of median.
+    :param x: The list of numeric values
+    :return: Median of the list
+    >>> find_median([1,2,2,3,4])
+    2
+
+    >>> find_median([1,2,2,3,4,4])
+    2.5
+    """
+    length = len(x)
+    if length % 2:
+        return x[length // 2]
+    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
+
+
+def inter_quartile_range(x: List[float]) -> float:
+    """
+    This is the implementation of inter_quartile
+    range for a list of numeric.
+    :param x: The list of data point
+    :return: Inter_quartile range
+
+    >>> inter_quartile_range([4,1,2,3,2])
+    2.0
+
+    >>> inter_quartile_range([25,32,49,21,37,43,27,45,31])
+    18.0
+    """
+    length = len(x)
+    if length == 0:
+        raise ValueError
+    x.sort()
+    if length % 2:
+        q1 = find_median(x[0: length // 2])
+        q3 = find_median(x[(length // 2) + 1: length])
+    else:
+        q1 = find_median(x[0: length // 2])
+        q3 = find_median(x[length // 2: length])
+    return q3 - q1
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()

From 3296963721fa7199e3696fdc35824e2c778ff290 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 20 May 2023 17:15:56 +0000
Subject: [PATCH 23/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/inter_quartile_range.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index 08a7961bdc28..fb950613ddd1 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -46,11 +46,11 @@ def inter_quartile_range(x: List[float]) -> float:
         raise ValueError
     x.sort()
     if length % 2:
-        q1 = find_median(x[0: length // 2])
-        q3 = find_median(x[(length // 2) + 1: length])
+        q1 = find_median(x[0 : length // 2])
+        q3 = find_median(x[(length // 2) + 1 : length])
     else:
-        q1 = find_median(x[0: length // 2])
-        q3 = find_median(x[length // 2: length])
+        q1 = find_median(x[0 : length // 2])
+        q3 = find_median(x[length // 2 : length])
     return q3 - q1
 
 

From 95caae23e682d7ad9c640a76c578ccb6fbbc6114 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sat, 20 May 2023 22:51:03 +0530
Subject: [PATCH 24/42] Mish activation function is added

---
 neural_network/activation_functions/mish_activation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 8948b43228e5..648232786dd7 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -7,7 +7,7 @@
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
 
-The proposed paper link is provided below.
+The proposed paper link is provided below-
 https://arxiv.org/abs/1908.08681
 """
 

From 784199a862e933cc67565947e77f5e6d0c7ba7af Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sat, 20 May 2023 22:54:24 +0530
Subject: [PATCH 25/42] Mish action is added

---
 maths/inter_quartile_range.py                 | 60 -------------------
 .../activation_functions/mish_activation.py   |  2 +-
 2 files changed, 1 insertion(+), 61 deletions(-)
 delete mode 100644 maths/inter_quartile_range.py

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
deleted file mode 100644
index fb950613ddd1..000000000000
--- a/maths/inter_quartile_range.py
+++ /dev/null
@@ -1,60 +0,0 @@
-"""
-This is the implementation of inter_quartile range (IQR).
-
-function takes the list of numeric values as input
-and return the IQR as output.
-
-Script inspired from its corresponding Wikipedia article
-https://en.wikipedia.org/wiki/Interquartile_range
-"""
-
-from typing import List
-
-
-def find_median(x: List[float]) -> float:
-    """
-    This is the implementation of median.
-    :param x: The list of numeric values
-    :return: Median of the list
-    >>> find_median([1,2,2,3,4])
-    2
-
-    >>> find_median([1,2,2,3,4,4])
-    2.5
-    """
-    length = len(x)
-    if length % 2:
-        return x[length // 2]
-    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
-
-
-def inter_quartile_range(x: List[float]) -> float:
-    """
-    This is the implementation of inter_quartile
-    range for a list of numeric.
-    :param x: The list of data point
-    :return: Inter_quartile range
-
-    >>> inter_quartile_range([4,1,2,3,2])
-    2.0
-
-    >>> inter_quartile_range([25,32,49,21,37,43,27,45,31])
-    18.0
-    """
-    length = len(x)
-    if length == 0:
-        raise ValueError
-    x.sort()
-    if length % 2:
-        q1 = find_median(x[0 : length // 2])
-        q3 = find_median(x[(length // 2) + 1 : length])
-    else:
-        q1 = find_median(x[0 : length // 2])
-        q3 = find_median(x[length // 2 : length])
-    return q3 - q1
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()
diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 648232786dd7..8948b43228e5 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -7,7 +7,7 @@
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
 
-The proposed paper link is provided below-
+The proposed paper link is provided below.
 https://arxiv.org/abs/1908.08681
 """
 

From c91bc2a5281b32ee67526d02b70b58b435ac8b99 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Tue, 20 Jun 2023 19:38:29 +0530
Subject: [PATCH 26/42] mish activation added

---
 neural_network/activation_functions/mish_activation.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 8948b43228e5..8dfd28f01054 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -12,6 +12,7 @@
 """
 
 import numpy as np
+from maths.tanh import tangent_hyperbolic as tanh
 
 
 def mish_activation(vector: np.ndarray) -> np.ndarray:
@@ -39,7 +40,7 @@ def mish_activation(vector: np.ndarray) -> np.ndarray:
 
     """
     soft_plus = np.log(np.exp(vector) + 1)
-    return vector * (2 / (1 + np.exp(-2 * soft_plus))) - 1
+    return vector * tanh(soft_plus)
 
 
 if __name__ == "__main__":

From 44a5ff837a58d95e8ac453f8f5ecd004dcd67b7a Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 20 Jun 2023 14:09:49 +0000
Subject: [PATCH 27/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pyproject.toml | 36 ++++++++++++++++++------------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 48c3fbd4009d..94a773eaa90c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,21 +1,3 @@
-[tool.pytest.ini_options]
-markers = [
-    "mat_ops: mark a test as utilizing matrix operations.",
-]
-addopts = [
-    "--durations=10",
-    "--doctest-modules",
-    "--showlocals",
-]
-
-[tool.coverage.report]
-omit = [".env/*"]
-sort = "Cover"
-
-[tool.codespell]
-ignore-words-list = "3rt,ans,crate,damon,fo,followings,hist,iff,kwanza,mater,secant,som,sur,tim,zar"
-skip = "./.*,*.json,ciphers/prehistoric_men.txt,project_euler/problem_022/p022_names.txt,pyproject.toml,strings/dictionary.txt,strings/words.txt"
-
 [tool.ruff]
 ignore = [      # `ruff rule S101` for a description of that rule
     "B904",     # B904: Within an `except` clause, raise exceptions with `raise ... from err`
@@ -68,3 +50,21 @@ max-args = 10        # default: 5
 max-branches = 20    # default: 12
 max-returns = 8      # default: 6
 max-statements = 88  # default: 50
+
+[tool.pytest.ini_options]
+markers = [
+    "mat_ops: mark a test as utilizing matrix operations.",
+]
+addopts = [
+    "--durations=10",
+    "--doctest-modules",
+    "--showlocals",
+]
+
+[tool.coverage.report]
+omit = [".env/*"]
+sort = "Cover"
+
+[tool.codespell]
+ignore-words-list = "3rt,ans,crate,damon,fo,followings,hist,iff,kwanza,mater,secant,som,sur,tim,zar"
+skip = "./.*,*.json,ciphers/prehistoric_men.txt,project_euler/problem_022/p022_names.txt,pyproject.toml,strings/dictionary.txt,strings/words.txt"

From 88f05ec5a42787a05eac74b2d86fa7e745d995aa Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Tue, 20 Jun 2023 20:05:39 +0530
Subject: [PATCH 28/42] mish activation added

---
 neural_network/activation_functions/mish_activation.py | 9 ---------
 1 file changed, 9 deletions(-)

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 8dfd28f01054..59a3951635bc 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -29,15 +29,6 @@ def mish_activation(vector: np.ndarray) -> np.ndarray:
         softplus = ln(1+e^(x)) and tanh = (e^x - e^(-x))/(e^x + e^(-x))
         so, mish can be written as x * (2/(1+e^(-2 * softplus))-1
 
-    Examples:
-        >>> mish_activation(np.array([1,5,6,-0.67]))
-        array([ 0.86509839,  8.99955208, 10.99992663, -1.93211787])
-
-
-        >>> mish_activation(np.array([8,2,-0.98,13]))
-        array([14.9999982 ,  2.94395896, -2.28214659, 25.        ])
-
-
     """
     soft_plus = np.log(np.exp(vector) + 1)
     return vector * tanh(soft_plus)

From 30bd9c2c61c5b7728a8d88c712f5b1b184f20363 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 20 Jun 2023 14:37:16 +0000
Subject: [PATCH 29/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 .../activation_functions/mish_activation.py      | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
index 59a3951635bc..c292f76f1a8b 100644
--- a/neural_network/activation_functions/mish_activation.py
+++ b/neural_network/activation_functions/mish_activation.py
@@ -17,17 +17,17 @@
 
 def mish_activation(vector: np.ndarray) -> np.ndarray:
     """
-        Implements the Mish function
+    Implements the Mish function
 
-        Parameters:
-            vector: np.array
+    Parameters:
+        vector: np.array
 
-        Returns:
-            Mish (np.array): The input numpy array after applying tanh.
+    Returns:
+        Mish (np.array): The input numpy array after applying tanh.
 
-        mathematically, mish = x * tanh(softplus(x)  where
-        softplus = ln(1+e^(x)) and tanh = (e^x - e^(-x))/(e^x + e^(-x))
-        so, mish can be written as x * (2/(1+e^(-2 * softplus))-1
+    mathematically, mish = x * tanh(softplus(x)  where
+    softplus = ln(1+e^(x)) and tanh = (e^x - e^(-x))/(e^x + e^(-x))
+    so, mish can be written as x * (2/(1+e^(-2 * softplus))-1
 
     """
     soft_plus = np.log(np.exp(vector) + 1)

From 1355f9daa572f64b1f84673fff7dae7a974fe5da Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 2 Jul 2023 20:08:30 +0530
Subject: [PATCH 30/42] inter quartile range (IQR) function is added

---
 maths/inter_quartile_range.py                 | 61 +++++++++++++++++++
 .../activation_functions/mish_activation.py   | 40 ------------
 2 files changed, 61 insertions(+), 40 deletions(-)
 create mode 100644 maths/inter_quartile_range.py
 delete mode 100644 neural_network/activation_functions/mish_activation.py

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
new file mode 100644
index 000000000000..91a5eb330c10
--- /dev/null
+++ b/maths/inter_quartile_range.py
@@ -0,0 +1,61 @@
+"""
+This is the implementation of inter_quartile range (IQR).
+
+function takes the list of numeric values as input
+and return the IQR as output.
+
+Script inspired from its corresponding Wikipedia article
+https://en.wikipedia.org/wiki/Interquartile_range
+"""
+
+from typing import List
+
+
+def find_median(x: List[float]) -> float:
+    """
+    This is the implementation of median.
+    :param x: The list of numeric values
+    :return: Median of the list
+    >>> find_median([1,2,2,3,4])
+    2
+
+    >>> find_median([1,2,2,3,4,4])
+    2.5
+
+
+    """
+    length = len(x)
+    if length % 2:
+        return x[length // 2]
+    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
+
+
+def inter_quartile_range(x: List[float]) -> float:
+    """
+    This is the implementation of inter_quartile
+    range for a list of numeric.
+    :param x: The list of data point
+    :return: Inter_quartile range
+
+    >>> inter_quartile_range([4,1,2,3,2])
+    2.0
+
+    >>> inter_quartile_range([25,32,49,21,37,43,27,45,31])
+    18.0
+    """
+    length = len(x)
+    if length == 0:
+        raise ValueError
+    x.sort()
+    q1 = find_median(x[0: length // 2])
+    if length % 2:
+        q3 = find_median(x[(length // 2) + 1: length])
+    else:
+        q3 = find_median(x[length // 2: length])
+    return q3 - q1
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()
diff --git a/neural_network/activation_functions/mish_activation.py b/neural_network/activation_functions/mish_activation.py
deleted file mode 100644
index c292f76f1a8b..000000000000
--- a/neural_network/activation_functions/mish_activation.py
+++ /dev/null
@@ -1,40 +0,0 @@
-"""
-Implements the Mish activation functions.
-
-The function takes a vector of K real numbers input and then
-applies the mish function, x*tanh(softplus(x) to each element of the vector.
-
-Script inspired from its corresponding Wikipedia article
-https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
-
-The proposed paper link is provided below.
-https://arxiv.org/abs/1908.08681
-"""
-
-import numpy as np
-from maths.tanh import tangent_hyperbolic as tanh
-
-
-def mish_activation(vector: np.ndarray) -> np.ndarray:
-    """
-    Implements the Mish function
-
-    Parameters:
-        vector: np.array
-
-    Returns:
-        Mish (np.array): The input numpy array after applying tanh.
-
-    mathematically, mish = x * tanh(softplus(x)  where
-    softplus = ln(1+e^(x)) and tanh = (e^x - e^(-x))/(e^x + e^(-x))
-    so, mish can be written as x * (2/(1+e^(-2 * softplus))-1
-
-    """
-    soft_plus = np.log(np.exp(vector) + 1)
-    return vector * tanh(soft_plus)
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()

From 483d59adec16477b8e0e6d3f952b3d78edde7e32 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 2 Jul 2023 14:41:28 +0000
Subject: [PATCH 31/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/inter_quartile_range.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index 91a5eb330c10..89bb449ed6eb 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -47,11 +47,11 @@ def inter_quartile_range(x: List[float]) -> float:
     if length == 0:
         raise ValueError
     x.sort()
-    q1 = find_median(x[0: length // 2])
+    q1 = find_median(x[0 : length // 2])
     if length % 2:
-        q3 = find_median(x[(length // 2) + 1: length])
+        q3 = find_median(x[(length // 2) + 1 : length])
     else:
-        q3 = find_median(x[length // 2: length])
+        q3 = find_median(x[length // 2 : length])
     return q3 - q1
 
 

From aa5dccb6b80dc035b9d7ed26271237bafb2cb35a Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 2 Jul 2023 20:23:58 +0530
Subject: [PATCH 32/42] IQR function is added

---
 maths/inter_quartile_range.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index 89bb449ed6eb..c3be9a8674cb 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -8,18 +8,18 @@
 https://en.wikipedia.org/wiki/Interquartile_range
 """
 
-from typing import List
+import numpy as np
 
 
-def find_median(x: List[float]) -> float:
+def find_median(x: np.array) -> float:
     """
     This is the implementation of median.
     :param x: The list of numeric values
     :return: Median of the list
-    >>> find_median([1,2,2,3,4])
+    >>> find_median(x=np.array([1,2,2,3,4]))
     2
 
-    >>> find_median([1,2,2,3,4,4])
+    >>> find_median(np.array([1,2,2,3,4,4]))
     2.5
 
 
@@ -30,28 +30,28 @@ def find_median(x: List[float]) -> float:
     return float((x[length // 2] + x[(length // 2) - 1]) / 2)
 
 
-def inter_quartile_range(x: List[float]) -> float:
+def inter_quartile_range(x: np.array) -> float:
     """
     This is the implementation of inter_quartile
     range for a list of numeric.
     :param x: The list of data point
     :return: Inter_quartile range
 
-    >>> inter_quartile_range([4,1,2,3,2])
+    >>> inter_quartile_range(x=np.array([4,1,2,3,2]))
     2.0
 
-    >>> inter_quartile_range([25,32,49,21,37,43,27,45,31])
+    >>> inter_quartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
     18.0
     """
     length = len(x)
     if length == 0:
         raise ValueError
     x.sort()
-    q1 = find_median(x[0 : length // 2])
+    q1 = find_median(x[0: length // 2])
     if length % 2:
-        q3 = find_median(x[(length // 2) + 1 : length])
+        q3 = find_median(x[(length // 2) + 1: length])
     else:
-        q3 = find_median(x[length // 2 : length])
+        q3 = find_median(x[length // 2: length])
     return q3 - q1
 
 

From 2b5d7c6095408cc11b62eb8836672852d48f19fc Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 2 Jul 2023 14:54:55 +0000
Subject: [PATCH 33/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/inter_quartile_range.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index c3be9a8674cb..421f0d482cc5 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -47,11 +47,11 @@ def inter_quartile_range(x: np.array) -> float:
     if length == 0:
         raise ValueError
     x.sort()
-    q1 = find_median(x[0: length // 2])
+    q1 = find_median(x[0 : length // 2])
     if length % 2:
-        q3 = find_median(x[(length // 2) + 1: length])
+        q3 = find_median(x[(length // 2) + 1 : length])
     else:
-        q3 = find_median(x[length // 2: length])
+        q3 = find_median(x[length // 2 : length])
     return q3 - q1
 
 

From ee3247bd1ca556cbbe3253283dd24415b421de87 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Mon, 3 Jul 2023 20:39:43 +0530
Subject: [PATCH 34/42] code optimized in IQR function

---
 maths/inter_quartile_range.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index 421f0d482cc5..3ef4a2694021 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -47,11 +47,9 @@ def inter_quartile_range(x: np.array) -> float:
     if length == 0:
         raise ValueError
     x.sort()
-    q1 = find_median(x[0 : length // 2])
-    if length % 2:
-        q3 = find_median(x[(length // 2) + 1 : length])
-    else:
-        q3 = find_median(x[length // 2 : length])
+    q1 = find_median(x[0: length // 2])
+    half_length = (length // 2) + 1 if length % 2 else length // 2
+    q3 = find_median(x[half_length:length])
     return q3 - q1
 
 

From 436a48324ec2f96b9216a6e418328a0d0b841e26 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 3 Jul 2023 15:11:41 +0000
Subject: [PATCH 35/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/inter_quartile_range.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/inter_quartile_range.py b/maths/inter_quartile_range.py
index 3ef4a2694021..8dd33879dcde 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/inter_quartile_range.py
@@ -47,7 +47,7 @@ def inter_quartile_range(x: np.array) -> float:
     if length == 0:
         raise ValueError
     x.sort()
-    q1 = find_median(x[0: length // 2])
+    q1 = find_median(x[0 : length // 2])
     half_length = (length // 2) + 1 if length % 2 else length // 2
     q3 = find_median(x[half_length:length])
     return q3 - q1

From ae37fc40be7dbe53901a6c1450d98ce9f2049fdc Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Wed, 2 Aug 2023 00:23:54 +0530
Subject: [PATCH 36/42] interquartile_range function is added

---
 ...inter_quartile_range.py => interquartile_range.py} | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)
 rename maths/{inter_quartile_range.py => interquartile_range.py} (79%)

diff --git a/maths/inter_quartile_range.py b/maths/interquartile_range.py
similarity index 79%
rename from maths/inter_quartile_range.py
rename to maths/interquartile_range.py
index 8dd33879dcde..6f8e0a6ea09a 100644
--- a/maths/inter_quartile_range.py
+++ b/maths/interquartile_range.py
@@ -30,24 +30,25 @@ def find_median(x: np.array) -> float:
     return float((x[length // 2] + x[(length // 2) - 1]) / 2)
 
 
-def inter_quartile_range(x: np.array) -> float:
+def interquartile_range(x: np.array) -> float:
     """
     This is the implementation of inter_quartile
     range for a list of numeric.
     :param x: The list of data point
     :return: Inter_quartile range
 
-    >>> inter_quartile_range(x=np.array([4,1,2,3,2]))
+    >>> interquartile_range(x=np.array([4,1,2,3,2]))
     2.0
 
-    >>> inter_quartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
+
+    >>> interquartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
     18.0
     """
     length = len(x)
     if length == 0:
-        raise ValueError
+        raise ValueError("The list is empty. Provide a non-empty list.")
     x.sort()
-    q1 = find_median(x[0 : length // 2])
+    q1 = find_median(x[0: length // 2])
     half_length = (length // 2) + 1 if length % 2 else length // 2
     q3 = find_median(x[half_length:length])
     return q3 - q1

From 14a3fb419d395a254e3f67e2f1bda7d1dbe480c5 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 1 Aug 2023 18:56:54 +0000
Subject: [PATCH 37/42] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 maths/interquartile_range.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index 6f8e0a6ea09a..03af90849943 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -48,7 +48,7 @@ def interquartile_range(x: np.array) -> float:
     if length == 0:
         raise ValueError("The list is empty. Provide a non-empty list.")
     x.sort()
-    q1 = find_median(x[0: length // 2])
+    q1 = find_median(x[0 : length // 2])
     half_length = (length // 2) + 1 if length % 2 else length // 2
     q3 = find_median(x[half_length:length])
     return q3 - q1

From da1c06313ed2d97f39a803667abe4d59ac5da411 Mon Sep 17 00:00:00 2001
From: Dipankar Mitra <50228537+Mitra-babu@users.noreply.github.com>
Date: Sat, 5 Aug 2023 22:14:40 +0530
Subject: [PATCH 38/42] Update maths/interquartile_range.py

Co-authored-by: Christian Clauss <cclauss@me.com>
---
 maths/interquartile_range.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index 03af90849943..b54ef3704bc5 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -48,8 +48,9 @@ def interquartile_range(x: np.array) -> float:
     if length == 0:
         raise ValueError("The list is empty. Provide a non-empty list.")
     x.sort()
-    q1 = find_median(x[0 : length // 2])
-    half_length = (length // 2) + 1 if length % 2 else length // 2
+    div, mod = divmod(length, 2)
+    q1 = find_median(x[:div])
+    half_length = sum((div, mod))
     q3 = find_median(x[half_length:length])
     return q3 - q1
 

From 05644a075040e62932fe18a72692c2d98379417c Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 6 Aug 2023 23:38:17 +0530
Subject: [PATCH 39/42] Changes on interquartile_range

---
 maths/interquartile_range.py | 44 +++++++++++++++++++++++-------------
 1 file changed, 28 insertions(+), 16 deletions(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index b54ef3704bc5..8ef59b267bf1 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -7,51 +7,63 @@
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Interquartile_range
 """
+from __future__ import annotations
 
 import numpy as np
 
 
-def find_median(x: np.array) -> float:
+def find_median(nums: list[int | float]) -> float:
     """
     This is the implementation of median.
-    :param x: The list of numeric values
+    :param nums: The list of numeric nums
     :return: Median of the list
-    >>> find_median(x=np.array([1,2,2,3,4]))
+    >>> find_median(nums=([1,2,2,3,4]))
     2
 
-    >>> find_median(np.array([1,2,2,3,4,4]))
+    >>> find_median(nums=([1,2,2,3,4,4]))
     2.5
 
 
     """
-    length = len(x)
+    length = len(nums)
     if length % 2:
-        return x[length // 2]
-    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
+        return nums[length // 2]
+    return float((nums[length // 2] + nums[(length // 2) - 1]) / 2)
 
 
-def interquartile_range(x: np.array) -> float:
+def interquartile_range(nums: list[int | float]) -> float:
     """
     This is the implementation of inter_quartile
     range for a list of numeric.
-    :param x: The list of data point
+    :param nums: The list of data point
     :return: Inter_quartile range
 
-    >>> interquartile_range(x=np.array([4,1,2,3,2]))
+    >>> interquartile_range(nums=[4,1,2,3,2])
     2.0
 
 
-    >>> interquartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
-    18.0
+    >>> interquartile_range(nums=[])
+    Traceback (most recent call last):
+    ...
+    ValueError: The list is empty. Provide a non-empty list.
+
+    >>> interquartile_range(nums = [-2,-7,-10,9,8,4, -67, 45])
+    17.0
+
+    >>> interquartile_range(nums = [0,0,0,0,0])
+    0.0
+
+
+
     """
-    length = len(x)
+    length = len(nums)
     if length == 0:
         raise ValueError("The list is empty. Provide a non-empty list.")
-    x.sort()
+    nums.sort()
     div, mod = divmod(length, 2)
-    q1 = find_median(x[:div])
+    q1 = find_median(nums[:div])
     half_length = sum((div, mod))
-    q3 = find_median(x[half_length:length])
+    q3 = find_median(nums[half_length:length])
     return q3 - q1
 
 

From 0e72de66a51b8e629a80c961b29206b317662ef5 Mon Sep 17 00:00:00 2001
From: Mitra-babu <dipankar9612@gmail.com>
Date: Sun, 6 Aug 2023 23:40:35 +0530
Subject: [PATCH 40/42] numpy removed from interquartile_range

---
 maths/interquartile_range.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index 8ef59b267bf1..979a58a8d370 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -9,8 +9,6 @@
 """
 from __future__ import annotations
 
-import numpy as np
-
 
 def find_median(nums: list[int | float]) -> float:
     """

From 9c8c26f467cefc7abcab03f85eb053a52c790442 Mon Sep 17 00:00:00 2001
From: Christian Clauss <cclauss@me.com>
Date: Mon, 7 Aug 2023 06:46:23 -0400
Subject: [PATCH 41/42] Fixes from code review

---
 maths/interquartile_range.py | 59 +++++++++++++++++-------------------
 1 file changed, 27 insertions(+), 32 deletions(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index 979a58a8d370..1d77c75b2420 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -1,10 +1,10 @@
 """
-This is the implementation of inter_quartile range (IQR).
+An implementation of interquartile range (IQR) which is a measure of statistical
+dispersion, which is the spread of the data.
 
-function takes the list of numeric values as input
-and return the IQR as output.
+The function takes the list of numeric values as input and returns the IQR.
 
-Script inspired from its corresponding Wikipedia article
+Script inspired by this Wikipedia article:
 https://en.wikipedia.org/wiki/Interquartile_range
 """
 from __future__ import annotations
@@ -12,52 +12,47 @@
 
 def find_median(nums: list[int | float]) -> float:
     """
-    This is the implementation of median.
+    This is the implementation of the median.
     :param nums: The list of numeric nums
     :return: Median of the list
-    >>> find_median(nums=([1,2,2,3,4]))
+    >>> find_median(nums=([1, 2, 2, 3, 4]))
     2
-
-    >>> find_median(nums=([1,2,2,3,4,4]))
+    >>> find_median(nums=([1, 2, 2, 3, 4, 4]))
     2.5
-
-
+    >>> find_median(nums=([-1, 2, 0, 3, 4, -4]))
+    1.5
+    >>> find_median(nums=([1.1, 2.2, 2, 3.3, 4.4, 4]))
+    2.65
     """
-    length = len(nums)
-    if length % 2:
-        return nums[length // 2]
-    return float((nums[length // 2] + nums[(length // 2) - 1]) / 2)
+    div, mod = divmod(len(nums), 2)
+    if mod:
+        return nums[div]
+    return float((nums[div] + nums[(div) - 1]) / 2)
 
 
 def interquartile_range(nums: list[int | float]) -> float:
     """
-    This is the implementation of inter_quartile
-    range for a list of numeric.
-    :param nums: The list of data point
-    :return: Inter_quartile range
+    Return the interquartile range for a list of numeric values.
+    :param nums: The list of numeric values.
+    :return: interquartile range
 
-    >>> interquartile_range(nums=[4,1,2,3,2])
+    >>> interquartile_range(nums=[4, 1, 2, 3, 2])
     2.0
-
-
+    >>> interquartile_range(nums = [-2, -7, -10, 9, 8, 4, -67, 45])
+    17.0
+    >>> interquartile_range(nums = [-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1])
+    17.2
+    >>> interquartile_range(nums = [0, 0, 0, 0, 0])
+    0.0
     >>> interquartile_range(nums=[])
     Traceback (most recent call last):
     ...
     ValueError: The list is empty. Provide a non-empty list.
-
-    >>> interquartile_range(nums = [-2,-7,-10,9,8,4, -67, 45])
-    17.0
-
-    >>> interquartile_range(nums = [0,0,0,0,0])
-    0.0
-
-
-
     """
-    length = len(nums)
-    if length == 0:
+    if not nums:
         raise ValueError("The list is empty. Provide a non-empty list.")
     nums.sort()
+    length = len(nums)
     div, mod = divmod(length, 2)
     q1 = find_median(nums[:div])
     half_length = sum((div, mod))

From 90748c86aa3dcb9d9292ed5469426fffc0d90ba0 Mon Sep 17 00:00:00 2001
From: Christian Clauss <cclauss@me.com>
Date: Mon, 7 Aug 2023 06:51:30 -0400
Subject: [PATCH 42/42] Update interquartile_range.py

---
 maths/interquartile_range.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index 1d77c75b2420..d4d72e73ef49 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -27,7 +27,7 @@ def find_median(nums: list[int | float]) -> float:
     div, mod = divmod(len(nums), 2)
     if mod:
         return nums[div]
-    return float((nums[div] + nums[(div) - 1]) / 2)
+    return (nums[div] + nums[(div) - 1]) / 2
 
 
 def interquartile_range(nums: list[int | float]) -> float: