KeyError 'overflow_to_sample_mapping' when using LayoutXLM with regular Tokenizer + return_overflowing_tokens
### System Info

(Running from Colab)
- `transformers` version: 4.21.1
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.8.1
- PyTorch version (GPU?): 1.12.1+cu113 (True)
- Tensorflow version (GPU?): 2.8.2 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: Yes, but not relevant here
- Using distributed or parallel set-up in script?: No

### Who can help?

- Introduced when adding [LayoutLMv3](https://github.com/huggingface/transformers/pull/17060) @NielsRogge , Tokenizer related @SaulLu

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

View this short notebook on Colab: https://colab.research.google.com/drive/1ETpz8UP42r7HjRg4VUkC7L8ou10qY3bQ?usp=sharing

### Expected behavior

Expected:
Processor extracts features from and tokenizes the input successfully.

Output:
```
---------------------------------------------------------------------------

KeyError                                  Traceback (most recent call last)

[<ipython-input-6-2f428d9c1568>](https://localhost:8080/#) in <module>
----> 1 encoded = processor(image, words, boxes=boxes, word_labels=word_labels, **processor_kwargs)

[/usr/local/lib/python3.7/dist-packages/transformers/models/layoutxlm/processing_layoutxlm.py](https://localhost:8080/#) in __call__(self, images, text, text_pair, boxes, word_labels, add_special_tokens, padding, truncation, max_length, stride, pad_to_multiple_of, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, return_tensors, **kwargs)
    124         images = features.pop("pixel_values")
    125         if return_overflowing_tokens is True:
--> 126             images = self.get_overflowing_images(images, encoded_inputs["overflow_to_sample_mapping"])
    127         encoded_inputs["image"] = images
    128 

[/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_base.py](https://localhost:8080/#) in __getitem__(self, item)
    234         """
    235         if isinstance(item, str):
--> 236             return self.data[item]
    237         elif self._encodings is not None:
    238             return self._encodings[item]

KeyError: 'overflow_to_sample_mapping'
```
Please note that this probably also happens with LMv2 if using this combination of non fast processor + return_overflowing_tokens, not sure about LMv3
<|||||>Hi,

We probably need to update `LayoutXLMProcessor` similar to how it was done for LayoutLMv2 in #17092.

Would you be able to open a PR for this?<|||||>Absolutely!<|||||>Just stumbled over exactly the same bug. Thanks for looking into that! 😁 