Add EntityPairClassification Pipeline, AutoClass & LUKE ONNX Support 
Author: kayvane1
Pull request: yes

# What does this PR do?

This PR started out in adding support for Luke in ONNX.

To not break existing AutoPatterns in [FeaturesManager](src/transformers/onnx/features.py), [AutoModelForEntityPairClassification](src/transformers/models/auto/modeling_auto.py) has also been added.

Additionally, a pipeline for [EntityPairClassification](src/transformers/pipelines/entity_pair_classification.py) has been added to make the task more supported overall by the library.

Note: A previous PR (https://github.com/huggingface/transformers/pull/16562) has been closed / not merged for LUKE ONNX support. I believe this PR addresses the remaining comments in that one.

All ONNX tests pass - happy to implement any additional comments for the Pipeline / Autoclass.

I have only implemented one of the additional Tasks `EntityPairClassification` - if this has been done to the appropriate standard, I can also implement it for the other two remaining Luke Heads which are not currently supported `Span Classification` &  `Entity Classification`

@NielsRogge - Worked on the original LUKE implementation
@lewtun & @michaelbenayoun  - Reviewed the previous PR


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<img width="991" alt="Screenshot 2022-08-08 at 13 27 00" src="https://user-images.githubusercontent.com/42403093/183430054-26ee3d97-c9b3-43c8-b844-cde031b263e0.png">



Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_18524). All of your documentation changes will be reflected on that endpoint.

Hi @NielsRogge - what next steps would you suggest?
Happy to make updates to the PR

I don't think it makes sense to create an auto-map just for this model, and the pipeline can be done as a [custom pipeline with code on the Hub](https://huggingface.co/docs/transformers/add_new_pipeline#share-your-pipeline-on-the-hub). If/when there are more models associated to this task, we can revisit this approach of course.

Thanks @NielsRogge , @lewtun & @sgugger !

I'll update the PR by reverting the autoclass creation and bypass the AutoModel Constructors in `test_onnx_v2.py` & use the LukeForXxx classes in `features.py` directly.



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.

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Hi @kayvane1, feel free to revive this PR :)