Allow installation and running of backend locally without CUDA

[skywolf829]

To debug, we may want to run the backend locally even if we dont have CUDA installed. Without CUDA, we cannot install the pip libraries for the rendering and knn packages.

Requirements

• Backend should be installable without the CUDA pip packages via a custom env.yml for conda
• Should be able to run the generic backend.py script with the reduced backend environment
• Necessary scripts should check if the CUDA packages can be imported, and handle the situation when it isn't

[skywolf829]

• Made .env script for conda environment that doesn't include the CUDA packages
• Wrapped the imports for the CUDA packages in a try-catch for the script to recognize when it can/cant call the CUDA libraries
• Replaced all hard-coded "cuda" devices (in torch.zeros(), etc) to settings.device, and updated settings to default device to "cuda" if torch.cuda.is_available() else cpu.

Still need to test that model.render calls (which try to invoke the CUDA backend) will work with the stand-in code I added for when the CUDA backend isn't available. Similar situation with settings.device.

[skywolf829]

Seems to work, have tested frontend with the DEBUG mode in order to get frames (random noise) from backend.