Welcome to the PyTorch Docker Assignment. This assignment is designed to help you understand and work with Docker and PyTorch.
In this assignment, you will:
- Create a Dockerfile for a PyTorch (CPU version) environment.
- Keep the size of your Docker image under 1GB (uncompressed).
- Train any model on the MNIST dataset inside the Docker container.
- Save the trained model checkpoint to the host operating system.
- Add an option to resume model training from a checkpoint.
The provided starter code in train.py provides a basic structure for loading data, defining a model, and running training and testing loops. You will need to complete the code at locations marked by TODO: comments.
When you have completed the assignment, push your code to your Github repository. The Github Actions workflow will automatically build your Docker image, run your training script, and check if the assignment requirements have been met. Check the Github Actions tab for the results of these checks. Make sure that all checks are passing before you submit the assignment.