Supporting Seq2Seq model for question answering task
# What does this PR do?

Add the `run_seq2seq_qa.py` example for supporting seq2seq models to QA tasks.

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Fixes #13029 


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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

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@NielsRogge I do not have the resources to run the trainer on the said device to provide the duration and scores of the model. 
What should I do in this case ?

Also, I looked at the checks that ran on CircleCI and I am afraid that the test I have written is not running i.e. the output says 
```
### MODIFIED FILES ###
- examples/pytorch/question-answering/run_seq2seq_qa.py
- examples/pytorch/test_examples.py

### IMPACTED FILES ###
- examples/pytorch/question-answering/run_seq2seq_qa.py
- examples/pytorch/test_examples.py

### TEST TO RUN ###
```<|||||>For the test, will fix this morning. There is a bug in our module that fetches the proper tests to run. Thanks for flagging there was a problem!<|||||>Fix for the examples tests not being run is in [this PR](https://github.com/huggingface/transformers/pull/13604), you will need to rebase on master when it's merged.<|||||>@sgugger surely.

Also, I had asked about the dataset in the review you had provided earlier. Will SQuAD work as all the QA datasets have context in some format another ?<|||||>Yes, it's fine.<|||||>Thank you :)<|||||>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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>@karthikrangasai - the PR looks very nice already. It would be great if we could try fixing the test so that we can merge it :-)<|||||>Hello @patrickvonplaten , sorry I missed this failing test. I will fix it in some time, sorry for the delay.<|||||>During the evaluation phase, at this [line](https://github.com/huggingface/transformers/blob/c7ccb2e77976931b5738c5d0f89c3de7bb4c5278/src/transformers/trainer.py#L2285) the model return logits as float instead of int which is later causing an error when trying to run a tokenizer decode on the list of floats.

Could someone guide me on how to fix this ?<|||||>I am unsure why you would want logits to be integers. Also you should use the `--predict_with_generate` for evaluation.<|||||>@sgugger Thank you for the help. Addition of the flag `--predict_with_generate` helped here. I didn't want logits to be integers, but the input to decode had to be integers. I didn't that communicate well enough. Sorry for the confusion there.<|||||>Thanks for fixing the test!