Fix somehow incorrect model - tokenizer mapping in tokenization testing
# What does this PR do?

In this method
https://github.com/huggingface/transformers/blob/371337a95b5d82cc9376c2595ed2022a5eb2ee6e/tests/test_tokenization_common.py#L107

we update the mapping whenever we find a tokenizer/model found for a configuration
```
tokenizer[_fast]: (configuration, model)
```

However, **multiple models could share the same tokenizer class**, and, for example, we get `LiLT` (recently added) model for the tokenizer class `LayoutLMv3Tokenizer`. Some tests like the following fails
```bash
tests/models/layoutlmv3/test_tokenization_layoutlmv3.py::LayoutLMv3TokenizationTest::test_torch_encode_plus_sent_to_model
(line 1130)  TypeError: forward() got an unexpected keyword argument 'pixel_values'
```
as the model used for `LayoutLMv3TokenizationTest` is `LiLT` model instead of `LayoutLMv3Model`.

1. This is somehow undesirable, and we would prefer to test the original/canonical mode/tokenizer pair.
2. This PR adds some condition to ensure the desired property in 1.
3. We can probably extend the test to test each possible pair of `(model_1, tokenizer)`, `(model_2, tokenizer)`, ...etc. But I would leave this in another PR.
_The documentation is not available anymore as the PR was closed or merged._