[Seq2Seq Trainer] Make sure padding is implemented for models without pad_token
# What does this PR do?

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This PR adds padding for models without padding token as well. The logic is the following:

1) If model predicts `targets` < `max_length` => model has to have at least an `eos_token_id`. If model has no `config.pad_token_id` defined than the model simply uses the `config.eos_token_id` for padding.

2) If the model has no `config.eos_token_id`, => model cannot generate predictions shorter than `max_length`. In this case padding will never happen.

@sshleifer @patil-suraj - you guys were right -> the `Trainer` requires padding in any case (also if model has no padding token).
Could you guys review this PR and see if these fixes in Seq2Seq Trainer are ok for you?


LGTM!<|||||>@patrickvonplaten , @sshleifer 
I am seeing a major slowdown on TPU V3-8,  
last time (9e68d075a4100906509170498480823e7e61874a) `sshleifer/student_marian_en_ro_6_3` finished 1 epoch in ~6 mins,
now on this branch it's showing ~1hr 20 mins<|||||>> @patrickvonplaten , @sshleifer
> I am seeing a major slowdown on TPU V3-8,
> last time ([9e68d07](https://github.com/huggingface/transformers/commit/9e68d075a4100906509170498480823e7e61874a)) `sshleifer/student_marian_en_ro_6_3` finished 1 epoch in ~6 mins,
> now on this branch it's showing ~1hr 20 mins

Ohoh :-/ can you narrow down the commit that caused the slow-down? I took a look again at https://github.com/huggingface/transformers/pull/7809/files and this line I added could be problematic `inputs = copy.deepcopy(inputs)`. <|||||>> > @patrickvonplaten , @sshleifer
> > I am seeing a major slowdown on TPU V3-8,
> > last time ([9e68d07](https://github.com/huggingface/transformers/commit/9e68d075a4100906509170498480823e7e61874a)) `sshleifer/student_marian_en_ro_6_3` finished 1 epoch in ~6 mins,
> > now on this branch it's showing ~1hr 20 mins
> 
> Ohh, can you narrow down the commit that caused the slow-down? I took a look again at https://github.com/huggingface/transformers/pull/7809/files and this line I added could be problematic `inputs = copy.deepcopy(inputs)`.

Yeah this line is actually called at every step -> can you check whether removing the `copy` operation speeds the seq2seq trainer up again? I've been a bit sloppy there I think :-/ <|||||>It's still very slow even after removing that line. I'll try to find the exact commit which is causing this slowdown.