[Whisper] Fix forced decoder ids
# What does this PR do?

The Whisper tokenizer has a property `self.prefix_tokens` that returns the token ids appended to the start of label sequence:
```
<|startoftranscript|> <|lang_id|> <|task|> <|notimestamps|> ...
```

In the PR https://github.com/huggingface/transformers/pull/20589, the method `get_decoder_prompt_ids` was copied from the Whisper processor to the Whisper tokenizer, where it then made use of the tokenizer property `self.prefix_tokens`. The method `get_decoder_prompt_ids` is used to set the tokens that are forced at the beginning of the generation process. 

However, the forced decoder ids **should not** contain the `<|startoftranscript|>` token: this is the `decoder_start_token_id` that we use as token 0 when we start generation. If we include `<|startoftranscript|>` in our forced decoder ids, we'll get a double generation of `<|startoftranscript|>`. Thus, we only want to set the following tokens in the `forced_decoder_ids`:
```
<|lang_id|> <|task|> <|notimestamps|> ...
```

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_The documentation is not available anymore as the PR was closed or merged._<|||||>fyi @sgugger, the final fix we hope 🤞<|||||>Yes! Let me clarify! 

When training, we need to encode a sentence to a sequence of label ids. Here, we need to append the 'special' beginning of sentence tokens to the label ids. This is so that the model learns to predict the correct 'special' tokens for the generation process. For a full list of the tokens added, see this PR: https://github.com/huggingface/transformers/pull/19921

One of these tokens is the `<|startoftranscript|>` token. This is consistent with other tokenisers in the library, such as the BART tokeniser:
```python
from transformers import BartTokenizer

tokenizer = BartTokenizer.from_pretrained("facebook/bart-base")
input_str = "the cat"
tokens = tokenizer(input_str).input_ids
print(tokenizer.decode(tokens))
```
**Print Output:**
```
<s>the cat</s>
```

Now, it doesn't matter for training whether or not we append the decoder start token id to the start of our label sequence, because we cut it in our data collator:

https://github.com/huggingface/transformers/blob/3ac040bca1efbf5cfe9604a5b2a10a5392917c20/examples/pytorch/speech-recognition/run_speech_recognition_seq2seq.py#L249

So, adding the decoder start token id is more for making the tokeniser user friendly and consistent with other tokenisers in the library.
<|||||>@sanchit-gandhi Thanks. Just want to point out: For `bart`, yes, we have  bos `<s>` (id `0`). But it is not the **decoder** start token (which is `</s>` for bart, with id `2`) - it is just the start of the sentence (not ready for generation). The `labels`  has `bos` but not  `decoder_start_token`. The labels will be shifted and prepended with `</s>` to become decoder input ids.

In Whisper, I understand we want to be user-friendly. And as you have cut it in data collator, it is fine. But IMO, this is something a bit different from our NLP models (i.e. Bart here). Hopefully I understand it correctly.

