Fix the inconsistency of loss calculation between PT/TF XLNetLMHeadModel
# What does this PR do?

The loss calculation in `XLNetLMHeadModel` doesn't cut the logits/labels (unlike other models say `BertLMHeadModel`).
However, `TFXLNetLMHeadModel` works as other TF Causal LM models, and cut the logits.
This causes the loss difference higher than `4e-2` sometimes.

I believe `XLNet` works somehow differently from the usual causal LM models, and the provided labels and computed logits shouldn't be cut, as  `XLNetLMHeadModel` does.

This PR fixes this inconsistency.
_The documentation is not available anymore as the PR was closed or merged._<|||||>Could @Rocketknight1 or @gante give this a quick look?<|||||>This looks good! Should it be folded into PR #15256 though, or do you think it's better separate?<|||||>> This looks good! Should it be folded into PR #15256 though, or do you think it's better separate?

Hi, @Rocketknight1 

 #15256  we still cut the logits to compute the loss, but we will return the complete logits
But for this PR, we want to **use the complete logits to compute** the loss (and then return the complete one).
(that's my understanding)

They are different, and would be better to be separate PRs. There will be a conflict once one version is merged, but I can take care of resolving it.

<|||||>Nice finding @ydshieh!

I agree with @ydshieh, these are two separate issues -- the other one is general to causal models, this one pertains to the TF/PT mismatch in XLNet. <|||||>> 🚀 (please wait for @Rocketknight1's approval before merging)

Sure, I can't merge anyway 😅<|||||>Sorry for the delay! I looked at this earlier in the week and thought it looked good, and didn't realize you were waiting on me now. I'm happy to merge at this point - @ydshieh is there anything else you want to add, or should I go ahead?<|||||>> Sorry for the delay! I looked at this earlier in the week and thought it looked good, and didn't realize you were waiting on me now. I'm happy to merge at this point - @ydshieh is there anything else you want to add, or should I go ahead?

You can go ahead :-) Thank you!<|||||>Merging then 👍 
Thank you for the PR, @ydshieh!