LayoutLMv2Processor does not accept the XLMRobertaTokenizerFast
## 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: 4.11.3
- Platform: Linux-4.19.128-microsoft-standard-x86_64-with-glibc2.2.5
- Python version: 3.8.12
- PyTorch version (GPU?): 1.9.1+cu102 (False)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no

### Who can help
@NielsRogge
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- LayoutLMv2 

 -->

## Information

Model I am using: LayoutXLM

The problem arises when using:
* [x] the official example scripts: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/LayoutLMv2/RVL-CDIP/Fine_tuning_LayoutLMv2ForSequenceClassification_on_RVL_CDIP.ipynb

The tasks I am working on is:
* [x] an official task: SequenceClassification

## To reproduce

Steps to reproduce the behavior:

When we replace the layoutlmv2 tokenizer in cell 8 of https://github.com/NielsRogge/Transformers-Tutorials/blob/master/LayoutLMv2/RVL-CDIP/Fine_tuning_LayoutLMv2ForSequenceClassification_on_RVL_CDIP.ipynb
```python
from transformers import LayoutLMv2FeatureExtractor, LayoutLMv2Tokenizer, LayoutLMv2Processor
feature_extractor = LayoutLMv2FeatureExtractor()
tokenizer = LayoutLMv2Tokenizer.from_pretrained("microsoft/layoutlmv2-base-uncased")
processor = LayoutLMv2Processor(feature_extractor, tokenizer)
```
with the layoutxlm tokenizer as described in https://huggingface.co/transformers/model_doc/layoutxlm.html

```python
from transformers import LayoutLMv2FeatureExtractor, LayoutLMv2Tokenizer, LayoutLMv2Processor, AutoTokenizer
feature_extractor = LayoutLMv2FeatureExtractor()
tokenizer = AutoTokenizer.from_pretrained('microsoft/layoutxlm-base')
processor = LayoutLMv2Processor(feature_extractor, tokenizer)
```

the following error occurs
```python
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_3433/3030379235.py in <module>
      5 tokenizer = AutoTokenizer.from_pretrained('microsoft/layoutxlm-base')
      6 #tokenizer = LayoutLMv2Tokenizer.from_pretrained("microsoft/layoutlmv2-base-uncased")
----> 7 processor = LayoutLMv2Processor(feature_extractor, tokenizer)

~/.cache/pypoetry/virtualenvs/stp-experiment0-RgVp7VCN-py3.8/lib/python3.8/site-packages/transformers/models/layoutlmv2/processing_layoutlmv2.py in __init__(self, feature_extractor, tokenizer)
     54             )
     55         if not isinstance(tokenizer, (LayoutLMv2Tokenizer, LayoutLMv2TokenizerFast)):
---> 56             raise ValueError(
     57                 f"`tokenizer` has to be of type {LayoutLMv2Tokenizer.__class__} or {LayoutLMv2TokenizerFast.__class__}, but is {type(tokenizer)}"
     58             )

ValueError: `tokenizer` has to be of type <class 'type'> or <class 'type'>, but is <class 'transformers.models.xlm_roberta.tokenization_xlm_roberta_fast.XLMRobertaTokenizerFast'>
```

It looks like the LayoutLMv2Processor does not accept the XLMRobertaTokenizerFast.

<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
That the LayoutLMv2Processor accepts the XLMRobertaTokenizerFast.
`LayoutLMv2Processor` currently only supports `LayoutLMv2Tokenizer`/`LayoutLMv2TokenizerFast`. It would be a good first issue to add support for a new `LayoutXLMTokenizerFast`, which is based on XLMRoBERTa and takes into account the bounding box and word label inputs.<|||||>Hi @NielsRogge, I'd like to take a shot at this!<|||||>Great! So one would need to add `tokenization_layoutxlm.py` and `tokenization_layoutxlm_fast.py` to the [LayoutLMv2 folder](https://github.com/huggingface/transformers/tree/master/src/transformers/models/layoutlmv2). These should be near identical copies of `tokenization_xlm_roberta.py` and `tokenization_xlm_roberta_fast.py` (found [here](https://github.com/huggingface/transformers/tree/master/src/transformers/models/xlm_roberta)), respectively, but with added support for `boxes` and `word_labels` inputs (you can take a look at `tokenization_layoutlmv2.py` and `tokenization_layoutlmv2_fast.py` respectively how these are implemented).<|||||>> Great! So one would need to add `tokenization_layoutxlm.py` and `tokenization_layoutxlm_fast.py` to the [LayoutLMv2 folder](https://github.com/huggingface/transformers/tree/master/src/transformers/models/layoutlmv2). These should be near identical copies of `tokenization_xlm_roberta.py` and `tokenization_xlm_roberta_fast.py` (found [here](https://github.com/huggingface/transformers/tree/master/src/transformers/models/xlm_roberta)), respectively, but with added support for `boxes` and `word_labels` inputs (you can take a look at `tokenization_layoutlmv2.py` and `tokenization_layoutlmv2_fast.py` respectively how these are implemented).

Thanks. Any advice on how I should go about writing the unit tests?<|||||>For the unit tests, I would define `test_tokenization_layoutxlm`.py and `test_tokenization_layoutxlm_fast.py` based on the corresponding tests of LayoutLMv2.