OHE doc, Activation functions+doc #102

NandiniGera · 2023-02-11T22:27:32Z

Resolved issue #92 and #102 (Doc added)
Doc added of OneHotEncoder

Ishwarendra · 2023-02-12T06:16:42Z

src/slowmokit/methods/activation_functions.cpp

+#include <math.h>
+//sigmoid
+double sigmoid(double x) {
+    return 1 / (1 + exp(-x));


use std::expl (or std::exp) instead of exp everywhere.

Ishwarendra · 2023-02-12T06:17:08Z

src/slowmokit/methods/activation_functions.cpp

+}
+//tan inverse
+double arctan(double x) {
+    return atan(x);


Use std::atan(...) instead of atan(...)

src/slowmokit/methods/activation_functions.hpp

Ishwarendra · 2023-02-12T06:33:04Z

docs/methods/activation_functions.md

+
+## Example
+
+```


Suggested change

```

```cpp

Ishwarendra · 2023-02-12T06:34:00Z

docs/methods/preprocessing/one_hot_encoder.md

+
+| Name                                   | Definition                                    | Return value  |
+|----------------------------------------|-----------------------------------------------|---------------|
+| `oneHotEncoder(vector<T> data, nClasses)` | To encode the data into numerical values. | `vector<int>` |


type of nClasses?

Ishwarendra · 2023-02-12T06:35:41Z

docs/methods/preprocessing/one_hot_encoder.md

+
+## Example
+
+```


Suggested change

```

```cpp

Ishwarendra · 2023-02-12T06:37:48Z

src/slowmokit/methods/activation_functions.cpp

+
+
+
+


Remove these empty lines.

Ishwarendra · 2023-02-12T07:15:01Z

src/slowmokit/methods/activation_functions.hpp

+template<class T>
+
+double sigmoid(double x);
+double tanh(double x);
+double ReLU(double x);
+double leakyReLU(double x, double alpha);
+std::vector<double> softmax(const std::vector<double> &x);
+double arctan(double x);
+double binaryStep(double x);


Add doc comments above each function..

Example for sigmoid

/** * @brief To calculate sigmoid(x) * @param x: Number whose sigmoid value is to be calculated * @return a double value representing sigmoid(x) */

docs/methods/activation_functions.md

uttammittal02

Only a few changes required and then we're good to go

uttammittal02 · 2023-02-12T10:38:54Z

docs/methods/activation_functions.md

+
+tanh- The Tanh activation function is a hyperbolic tangent sigmoid function that has a range of -1 to 1. It is often used in deep learning models for its ability to model nonlinear boundaries
+
+tan-1h-The inverse of tanh.The ArcTan function is a sigmoid function to model accelerating and decelerating outputs but with useful output ranges.


Arctan is not the inverse of tanh but the normal trignometric tan(x) function

uttammittal02 · 2023-02-12T10:41:19Z

docs/methods/preprocessing/one_hot_encoder.md

+
+| Name         | Definition                                 | Type         |
+|--------------|--------------------------------------------|--------------|
+|   data       | The data that has to be encoded is passed as the data parameter in the oneHotEncoder function. | `vector<int>` |


Data would be vector<string> and not vector<int>

uttammittal02 · 2023-02-12T10:42:11Z

docs/methods/preprocessing/one_hot_encoder.md

+
+| Name                                   | Definition                                    | Return value  |
+|----------------------------------------|-----------------------------------------------|---------------|
+| `oneHotEncoder(vector<T> data, nClasses)` | To encode the data into numerical values. | `vector<int>` |


Return value of this method is vector<vector<int>>

uttammittal02 · 2023-02-12T10:44:23Z

src/slowmokit/methods/activation_functions.cpp

+#include "activation_functions.hpp"
+template<class T>
+// sigmoid
+double sigmoid(double x)


You need to write these functions for a vector and not a single value

You need to write these functions for a vector and not a single value

I'm changing all the functions

You need to write these functions for a vector and not a single value

all changes updated

uttammittal02 · 2023-02-12T10:45:49Z

src/slowmokit/methods/activation_functions.cpp

+}
+<<<<<<< HEAD
+// leaky ReLU
+double leakyReLU(double x, double alpha)


Set default value of alpha to 0.1

uttammittal02 · 2023-02-12T10:46:24Z

src/slowmokit/methods/activation_functions.cpp

+    } else {
+        return alpha * x;
+    }
+}


Add a function to convert binary to bipolar and vice-versa

Ishwarendra · 2023-02-12T10:52:06Z

src/slowmokit/methods/activation_functions.hpp

+<<<<<<< HEAD
+ * @param x {double x} - double value on which the function is applied.
+ *
+ * @param x {vector<double>} - vector containing 'double' values of x for
+ * softmax activation function implementation.
+ *
+ * @return {double value} - double value after putting x in the functions gets
+ * returned.
+=======


Suggested change

<<<<<<< HEAD

* @param x {double x} - double value on which the function is applied.

*

* @param x {vector<double>} - vector containing 'double' values of x for

* softmax activation function implementation.

*

* @return {double value} - double value after putting x in the functions gets

* returned.

=======

@Ishwarendra sir the changes which you've asked to make, these are not visible in my vs code, those unwanted lines of code are already not there.

i formatted all the source files using gitbash, since the clang error was there, but after commiting and pushing those changes, both the checks are coming wrong, how do i fix it?

src/slowmokit/methods/activation_functions.hpp

src/slowmokit/methods/activation_functions.cpp

Ishwarendra · 2023-02-12T10:54:04Z

src/slowmokit/methods/activation_functions.cpp

+=======
+//leaky ReLU
+double leakyReLU(double x, double alpha) {
+    if (x >= 0) {
+        return x;
+    } else {
+        return alpha * x;
+    }
+}
+>>>>>>> 5eebc29054fab6686e728aca29e64e1c53dd7a8c


Suggested change

=======

//leaky ReLU

double leakyReLU(double x, double alpha) {

if (x >= 0) {

return x;

} else {

return alpha * x;

}

}

>>>>>>> 5eebc29054fab6686e728aca29e64e1c53dd7a8c

Co-authored-by: Ishwarendra Jha <75680424+Ishwarendra@users.noreply.github.com>

Ishwarendra · 2023-02-12T12:22:03Z

@NandiniGera Run formatter and commit again.
"How to run formatter?" is already mentioned in README.md point-9

NandiniGera · 2023-02-12T15:26:09Z

@NandiniGera Run formatter and commit again. "How to run formatter?" is already mentioned in README.md point-9

all changes updated

NandiniGera · 2023-02-12T15:27:07Z

really sorry for all the silly mistakes:/
will try to do better next time!

uttammittal02 · 2023-02-12T17:23:47Z

really sorry for all the silly mistakes:/
will try to do better next time!

Arey np with that...you guys are in the learning stage rn so obv you'll commit mistakes in the beginning...just try not to repeat a mistake

ken1000minus7 · 2023-02-13T19:51:09Z

src/slowmokit/methods/activation_functions.cpp

+ * Implementation of activation functions
+ */
+#include "activation_functions.hpp"
+template<class T>


Remove this line, we do not require templates for these functions

Suggested change

template<class T>

ken1000minus7 · 2023-02-13T19:53:33Z

src/slowmokit/methods/activation_functions.cpp

+std::vector<double> leakyReLU(const std::vector<double> &x)
+{
+  std::vector<double> y(x.size());
+  double alpha = 0.1;


Add alpha as a parameter instead with default value 0.1, do the change in hpp file as well

Suggested change

std::vector<double> leakyReLU(const std::vector<double> &x)

{

std::vector<double> y(x.size());

double alpha = 0.1;

std::vector<double> leakyReLU(const std::vector<double> &x, double alpha = 0.1)

{

std::vector<double> y(x.size());

Add alpha as a parameter instead with default value 0.1, do the change in hpp file as well

done

uttammittal02 · 2023-02-14T13:49:48Z

src/slowmokit/methods/activation_functions.cpp

+  std::vector<double> y(x.size());
+  for (int i = 0; i < x.size(); i++)
+  {
+    y[i] = 1 / (1 + exp(-x[i]));


Use std::exp instead of exp

uttammittal02

A few more changes

uttammittal02 · 2023-02-14T13:53:05Z

src/slowmokit/methods/activation_functions.cpp

+#include "activation_functions.hpp"
+template<class T>
+// sigmoid
+std::vector<double> sigmoid(const std::vector<double> &x)


Instead of initialising a new vector and returning it....change the return type to void and do the changes in vector x itself wherever possible

Instead of initialising a new vector and returning it....change the return type to void and do the changes in vector x itself wherever possible

done

uttammittal02 · 2023-02-14T13:53:33Z

src/slowmokit/methods/activation_functions.cpp

+  std::vector<double> y(x.size());
+  for (int i = 0; i < x.size(); i++)
+  {
+    y[i] = atan(x[i]);


Use std::atan instead of atan as told earlier

ken1000minus7 · 2023-02-15T10:03:58Z

You don't need to mention what the function returns in the doc comments if the function returns void, rest lgtm

NandiniGera · 2023-02-15T11:03:07Z

You don't need to mention what the function returns in the doc comments if the function returns void, rest lgtm

okayy done

NandiniGera · 2023-02-15T11:22:33Z

I'm unable to resolve the build issue, how do i fix it?

uttammittal02

Lgtm

docs/methods/activation_functions.md

uttammittal02 · 2023-02-15T13:19:43Z

I'm unable to resolve the build issue, how do i fix it?

We're working on it...will let you know soon

OHE doc, Activation functions+doc

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Update src/slowmokit/methods/activation_functions.hpp

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Co-authored-by: Ishwarendra Jha <75680424+Ishwarendra@users.noreply.github.com>

Update src/slowmokit/methods/activation_functions.hpp

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Co-authored-by: Ishwarendra Jha <75680424+Ishwarendra@users.noreply.github.com>

Update src/slowmokit/methods/activation_functions.cpp

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Co-authored-by: Ishwarendra Jha <75680424+Ishwarendra@users.noreply.github.com>

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		tanh- The Tanh activation function is a hyperbolic tangent sigmoid function that has a range of -1 to 1. It is often used in deep learning models for its ability to model nonlinear boundaries

		tan-1h-The inverse of tanh.The ArcTan function is a sigmoid function to model accelerating and decelerating outputs but with useful output ranges.

OHE doc, Activation functions+doc #102

Are you sure you want to change the base?

OHE doc, Activation functions+doc #102

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NandiniGera commented Feb 11, 2023 • edited by Ishwarendra Loading

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Ishwarendra commented Feb 12, 2023

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ken1000minus7 commented Feb 15, 2023

NandiniGera commented Feb 15, 2023

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uttammittal02 commented Feb 15, 2023

NandiniGera commented Feb 11, 2023 •

edited by Ishwarendra

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