Add canine in documentation_tests_file
Author: oneraghavan
Pull request: yes

# What does this PR do?

modeling_canine has doc test setup by not included in documentation_tests.txt , this PR adds it

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Fixes #16292


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Comments:
_The documentation is not available anymore as the PR was closed or merged._

@ydshieh  Requesting you to review .

Sorry, I missed this PR. Look it now.

@oneraghavan , the doctest would fail for `canine` at this moment. We have to add the expected values (loss or some outputs).

Would you like to follow the changes in PR #16441 for `modeling_longformer.py`, more precisely in `LongformerForSequenceClassification` and `LongformerForTokenClassification`. See those changes [here](https://github.com/huggingface/transformers/pull/16441/files).

Don't hesitate if you have any question. Thank you!

@ydshieh Will add those changes. Request you to reopen this PR.

@oneraghavan Thank you 🤗 . I reopened the PR. Before continue the work, don't forget to update your local `main` branch first, then rebase your working branch on `main` branch.

@ydshieh  I request you to reopen the PR again. I have fixed the checkpoints, the tests should pass now.

@ydshieh  I think this is good to merge. 

Yes, agreed @ydshieh . In general any result that is LABEL_0 or a list of those should really not be included.

@ydshieh  I agree to the part where label_x is not so meaningful. Duplicating the function will make later debugging hard. I will remove the test for token classification. 

@sgugger  Can we make add_code_sample_docstrings decorator use the expected output in optional way ? like if the function does not have the expected output, just don't validate the expected output ?

I don't think we have an easy way to ignore the doctest in this case. The `>>> predicted_tokens_classes` part in `PT_TOKEN_CLASSIFICATION_SAMPLE` in the file `src/transformers/utils/doc.py` requires some expected outputs for `predicted_tokens_classes`. If there is none, the test just fails.


```python
    >>> predicted_tokens_classes
    {expected_output}
```

@ydshieh  @sgugger  Can we do add a paramerter in add_code_sample_docstrings in function and leave the default to None. Then when places we need to use custom sample, we can call it from there .

The function definition will look like this 

def add_code_sample_docstrings(
    *docstr,
    processor_class=None,
    checkpoint=None,
    output_type=None,
    config_class=None,
    mask="[MASK]",
    qa_target_start_index=14,
    qa_target_end_index=15,
    model_cls=None,
    modality=None,
    expected_output="",
    expected_loss="",
    code_sample="",
):

Inside I can use code_sample if it has been passed or look up the code sample from the templates. 

Let me know if this is okay.


I don't see how [the latest change](https://github.com/huggingface/transformers/pull/18225/commits/e1e98b9576c6a331f2b74f730ddd08c6f47421d6) is better than just putting the docstring under `CanineForTokenClassification` directly.

I will leave @sgugger to give his opinion.

We don't need any other tooling here. Either the model falls in the "automatic docstring" category or it does not. If it does not, we just write the docstring (with the replace return decorator).