refactor checkpointing#6
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refactor checkpointing to use accelerate.save_state(). no more pickles for noise_scheduler, lr_scheduler, and optimizer.
due to how pytorch saves state dicts, this means we have to "know" the class names before loading, which is why we now write a
ckpt_config.yamlto the checkpoint directory with this info.In principle, we could get this info from the original
config.yamlfile, but the idea here is to maketrain()be able to operate on its own, without needing aconfig.yamlalso fixed a bug that allows the training to be resumed from a checkpoint