Containerized GPU Dev Environment for TensorFlow and PyTorch

Note: This is meant for Linux/WSL with GPU available.

Instructions:

1. Run make build from the repo directory to build the image.
2. Run make dev to deploy a container and start a termminal session.
   • You can use make dev PORT=<port> to define which port on the host to access Jupyter Lab/notebook. Default is 8888.
   • /home and /mnt are bound so that the user can dev as normal. The user should also automatically show as themselves in the container.