Add `masked_lm_labels` argument to `TFAlbertForMaskedLM`
# 🚀 Feature request

The PyTorch `AlbertForMaskedLM` model has support for the `masked_lm_labels` parameter, while `TFAlbertForMaskedLM` does not. I'd like to bring feature parity.

It looks like a similar feature is also missing for `TFBertForMaskedLM`, `TFRobertaForMaskedLM`, `TFDistilBertForMaskedLM`. I'd be happy to add support for those models as well.

## Motivation

I'm pretraining TF NLP models, and this would simplify the training script by encapsulating the loss function.

## Your contribution

I'm happy to contribute the code. I'll follow CONTRIBUTING.md, any gotchas I should be aware of?

Hi! This feature would be great to have.

I'm curious how `TFBertMaskedLM` (and the like) are supposed to be used with the keras `fit()` functionality?

It seems like one is supposed to loop through the training data and calculate the cross-entropy loss for each batch (#2926). I see there was related discussion also here #1999.

Happy for any input!<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
<|||||>Closing because this feature was added in #4530 