Improve TF weight loading, especially PT crossloading
Draft PR for now, this will probably break a bunch of stuff until I get it all working!

- [X] Support `from_pt` and `load_weight_prefix` at the same time
- [x] Replace hacky loading code in models that was written to get around this issue
- [x] ~Test and possibly replace code paths that name submodules based on `cls.load_weight_prefix` - I think this is very risky~
- [x] Support `load_weight_prefix` in the `load_sharded` functions as well
- [x] ~Check the `cls._requires_load_weight_prefix` paths and see if there's a better solution~
- [x] Update any affected tests
- [x] Add test for `load_sharded` with `load_weight_prefix`

Classes using `load_weight_prefix` that may need updating:
- [x] BART
- [x] EncoderDeoder
- [x] VisionEncoderDecoder
- [x] RAG
- [x] Blenderbot
- [x] T5
- [x] LED
- [x] BART
- [x] mBART
- [x] Marian
- [x] OPT
- [x] Pegasus
- [x] The cookiecutter template
_The documentation is not available anymore as the PR was closed or merged._<|||||>This is ready for review now! It's not that big, but it changes a lot of things:

- Loading a PT model in TF with `from_pt=True` now supports `load_weight_prefix`
- Loading a sharded TF checkpoint now supports `load_weight_prefix`
- Sharded TF checkpoints can now be loaded even when not all weights match (this allows model surgery that didn't work with sharded models before!)
- TF `from_pretrained` now supports a `tf_to_pt_weight_rename` kwarg. This should be a callable function which converts TF weight names to PT weight names for that model.
- Composite classes like `TFEncoderDecoder` and `TFVisionEncoderDecoder` have been refactored to use the `tf_to_pt_weight_rename` kwarg, which let me remove all the ingenious workarounds that @ydshieh needed when he added those classes.
- I found a few small issues in other classes when I was testing this PR and fixed them. This is mostly just stuff like removing unused args and disabling TF32 in tests so that the outputs match.
- Add tests for the new features to `test_modeling_tf_common`

cc:
@ArthurZucker because I touched your sharded weight loading code
@ydshieh because I touched your composite model code 
@gante for TF review 
@sgugger as repository overlord