Refactor training loop from script to class

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Description

This PR refactors the training loop from a script to a class for better organization and reusability. The training loop, which was previously located in src/main.py, has been encapsulated within a new class named MNISTTrainer. The class is responsible for loading and preprocessing the MNIST dataset, defining the PyTorch model, and training the model. It also provides a method to save the trained model to a file.

Summary of Changes

• Created a new class named MNISTTrainer in src/main.py to encapsulate the training loop.
• Moved the code for loading and preprocessing the MNIST data into a method named load_data in MNISTTrainer.
• Moved the code for defining the PyTorch model into a method named define_model in MNISTTrainer.
• Implemented a new method named train_model in MNISTTrainer to contain the training loop.
• Created a new method named save_model in MNISTTrainer to save the trained model to a file.
• Updated the import statement in src/api.py to import the MNISTTrainer class instead of the Net class.
• Updated the code in src/api.py to use the MNISTTrainer class for loading the data, defining the model, training the model, and saving the model to a file.

Please review and merge this PR. Thank you!

Fixes #6.

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Rollback Files For Sweep

• [ ] Rollback changes to src/api.py
• [ ] Rollback changes to src/main.py

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