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

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Description

This PR adds a new Convolutional Neural Network (CNN) class in a new file named cnn.py. The CNN class is implemented using PyTorch and is designed to handle the MNIST dataset. The class includes methods for initializing the CNN, defining the forward pass, and training the CNN using the Adam optimizer and CrossEntropyLoss loss function.

In main.py, the CNN class is imported and instantiated after loading and preprocessing the MNIST dataset. The train method of the CNN instance is called to train the CNN using the DataLoader object.

Summary of Changes

• Created a new file src/cnn.py to implement the CNN class.
• Imported necessary PyTorch modules in cnn.py.
• Defined the CNN class with an __init__ method, a forward method, and a train method.
• Added docstrings and comments to the CNN class and its methods.
• Imported the CNN class in main.py.
• Instantiated the CNN class and called the train method in main.py.

Please review and merge this PR. Thank you!

Fixes #9.

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• Rollback changes to src/cnn.py
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