Tf timestamps whisper + update generate support
# What does this PR 
This PR updates the way we generation TF and FLAX to fix the breaking changes that we had. 
It also adds support for the timestamps in `TF`. 
Follows #21965 
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_21334). All of your documentation changes will be reflected on that endpoint.<|||||>Awesome thanks for the review 🤗 <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>lmk when you want to pick this up again :P Meanwhile, shall we add the WIP label, so that the bot doesn't ping us?<|||||>yes! Hahah sorry, maybe next week or 2 weeks from now !<|||||>Okay! Thanks to @gante's recommendations, the xla generation works perfectly! The slow timestamp processing test also passes 🥳 <|||||>Thanks for your review, will adresse all of this <|||||>@ArthurZucker I was testing out if I get the timestamps with TF model with your ```tf-timestamps-whisper``` branch on colab but I see this:
```
[/content/transformers/src/transformers/models/whisper/tokenization_whisper.py](https://localhost:8080/#) in decode(self, token_ids, skip_special_tokens, clean_up_tokenization_spaces, output_offsets, time_precision, decode_with_timestamps, **kwargs)
    593         )
    594         if decode_with_timestamps:
--> 595             text = self._decode_with_timestamps(token_ids, time_precision=time_precision)
    596         # retrieve offsets
    597         if output_offsets:

[/content/transformers/src/transformers/models/whisper/tokenization_whisper.py](https://localhost:8080/#) in _decode_with_timestamps(self, token_ids, time_precision)
    501         for token in token_ids:
    502             if token >= timestamp_begin:
--> 503                 timestamp = f"<|{(token - timestamp_begin) * time_precision:.2f}|>"
    504                 outputs.append(timestamp)
    505                 outputs.append([])

[/usr/local/lib/python3.10/dist-packages/tensorflow/python/util/traceback_utils.py](https://localhost:8080/#) in error_handler(*args, **kwargs)
    151     except Exception as e:
    152       filtered_tb = _process_traceback_frames(e.__traceback__)
--> 153       raise e.with_traceback(filtered_tb) from None
    154     finally:
    155       del filtered_tb

[/usr/local/lib/python3.10/dist-packages/tensorflow/python/ops/gen_math_ops.py](https://localhost:8080/#) in mul(x, y, name)
   6574   if tld.is_eager:
   6575     try:
-> 6576       _result = pywrap_tfe.TFE_Py_FastPathExecute(
   6577         _ctx, "Mul", name, x, y)
   6578       return _result

TypeError: Cannot convert 0.02 to EagerTensor of dtype int32
```


<|||||>Hey! That’s probably because I haven’t pull from main for a while and we changed the whisper tokenizer. As you can see the decoding process is the one failing here <|||||>@ArthurZucker Thanks for the response. I got the issue resolved with 
```
timestamp = f"<|{float(token - timestamp_begin) * time_precision:.2f}|>"
```
i.e. changing ```token - timestamp_begin``` to ```float(token - timestamp_begin)```
<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.