Add new CNN class for handling MNIST dataset and import it into main.py

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Description

This PR adds a new CNN class in a new file called cnn.py to handle the MNIST dataset. The CNN class is designed to train a convolutional neural network on the MNIST dataset and includes methods for defining the architecture, training the model, and saving the trained model. The CNN class is properly documented with docstrings and comments.

The main.py file has been modified to import the CNN class from cnn.py and use it for training the model on the MNIST dataset. The existing code for loading the MNIST dataset and preprocessing it has been reused in the CNN class. After training, the trained model is saved using the save_model method of the CNN class.

Summary of Changes

• Created a new file called cnn.py in the src directory.
• Defined a new class called CNN in cnn.py, which inherits from torch.nn.Module.
• Implemented the init method in the CNN class to define the architecture of the CNN.
• Implemented the forward method in the CNN class to perform the forward pass of the CNN.
• Implemented the train method in the CNN class to train the CNN on the MNIST dataset.
• Implemented the save_model method in the CNN class to save the trained model.
• Added docstrings and comments to the CNN class and its methods.
• Modified main.py to import the CNN class from cnn.py.
• Replaced the existing model definition in main.py with an instance of the CNN class.
• Replaced the existing training code in main.py with a call to the train method of the CNN instance.
• Updated comments and docstrings in main.py to reflect the changes.

Please review and merge this PR. Thank you!

Fixes #9.

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Rollback Files For Sweep

• Rollback changes to src/main.py
• Rollback changes to src/cnn.py
• Rollback changes to src/cnn.py

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