The codebase now supports the following additional models

• BartForConditionalGeneration (when positional embedding layers are frozen)
• T5ForConditionalGeneration
• OPTForCausalLM
• ViTForImageClassification (when isolated parameters are frozen; see this example)
• DeiTForImageClassification (when isolated parameters are frozen)
• BeitForImageClassification (when isolated parameters are frozen)

Minor rewrite of the privacy engine, sharing code between ghost and default clipping, thus making future maintaining potentially easier.

Add example file for fine-tuning of vision Transformers on CIFAR-10.

Use callback style implementation for playing with params and gradients after clipping.

Allow forward and backward hooks to use additional args and kwargs (not necessarily torch.Tensors).

Rewrite privacy accounting and remove GDP + CLT, since it under accounts.