Misleading warning when using DPRContextEncoderTokenizer
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: `4.9.1`
- Platform: Ubuntu
- Python version: 3.8.10
- PyTorch version (GPU?): 1.9.0
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help

- tokenizers: @LysandreJik

## Information

When running this code

``` python
from transformers import (
    DPRContextEncoder,
    DPRContextEncoderTokenizer,
)

tokenizer = DPRContextEncoderTokenizer.from_pretrained('facebook/dpr-ctx_encoder-single-nq-base')
model = DPRContextEncoder.from_pretrained('facebook/dpr-ctx_encoder-single-nq-base')
```

I receive this warning

```
The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. 
The tokenizer class you load from this checkpoint is 'DPRQuestionEncoderTokenizer'. 
The class this function is called from is 'DPRContextEncoderTokenizer'.
```

## Expected behavior

This warning should not be there - I am not using the Question encoder at all
Yes you are not using it, but it's the tokenizer that was registered with the checkpoint `'facebook/dpr-ctx_encoder-single-nq-base'` so the library is warning you there is a mismatch (which may be okay in this instance).<|||||>Thanks, but `facebook/dpr-ctx_encoder-single-nq-base` encoder should be registered as a context encoder (that's what the `ctx` in its name means) - the corresponding question encoder is `facebook/dpr-question_encoder-single-nq-base`.

I've looked through the source code of the model on the hub ([here](https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/tree/main)), and I do not see any reference to the question encoder. In the source code of the tokenizer ([here](https://github.com/huggingface/transformers/blob/master/src/transformers/models/dpr/tokenization_dpr.py)) all the correspondences seem to be set up correctly too - so this issue is a bit puzzling.

<|||||>It looks like the model does not specify its proper tokenizer then: the default for all DPR models is `DPRQuestionEncoderTokenizer` but since it's not the correct one, there should be a `tokenizer_class` set to `DPRContextEncoderTokenizer` in that repo.

In any case, I just looked at the source code and the two classes are exactly the same, so there is no difference between the tokenizers (why have two different ones then @lhoestq ?)<|||||>If I am not mistaken, the situation is the same for encoders as well - both context and question encoder could have been the same class<|||||>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/master/CONTRIBUTING.md) are likely to be ignored.<|||||>#load pre-trained model and tokenizer
tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-base-960h")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")


The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. 
The tokenizer class you load from this checkpoint is 'Wav2Vec2CTCTokenizer'. 
The class this function is called from is 'Wav2Vec2Tokenizer'.
/Users/sangram/opt/anaconda3/envs/Speech/lib/python3.9/site-packages/transformers/models/wav2vec2/tokenization_wav2vec2.py:421: FutureWarning: The class `Wav2Vec2Tokenizer` is deprecated and will be removed in version 5 of Transformers. Please use `Wav2Vec2Processor` or `Wav2Vec2CTCTokenizer` instead.
  warnings.warn(