ReadMe for EpochLoss Data Minimization Code

The accompanying code is split into 3 main parts:
1. Running scripts: These are scripts indicating roughly how jobs may be run, to give an idea of how the hyperparameters are passed into the necessary scripts
2. Running scripts: The entrypoints for running the code. Namely these are:
	1. Main-steps.py: The script for training either the baseline on all training data or when removing a portion of the training data
	2. Eval-steps.py: A script for evaluating a given checkpoint on any task, for any attack/corruption setting, with or without substitution of synthetic images.
	3. CorruptDatasets.py: Generates corruptions and saves a given dataset. Used for generating the corrupted test sets, which remain the same between trials/experiments for consistency of comparison.

3. Auxiliary Scripts: Removal method code and any accompanying code needed to run the main scripts, such as dataset and network classes and functions



Note: Since we removed unused parts of the code for simplicity in sharing, there is a potential that some unintended reference to removed imports or functions are missing.
		As such this code is intended to give a reference to what was done, but a more thoroughly polished and coded ready-to-run version will be provided after submission.

