move preprocess_logits_for_metrics before _nested_gather in trainer.e…
Author: ChenyangLiu
Pull request: yes

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Fixes #22602 


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Comments:
_The documentation is not available anymore as the PR was closed or merged._

Sorry. In my training loop, the `preprocess_logits_for_metrics` do not use `labels`. I ignore the `labels` is gathered before. In the new commit, the code is
```
# Update containers on host
if loss is not None:
    losses = self._nested_gather(loss.repeat(batch_size))
    losses_host = losses if losses_host is None else torch.cat((losses_host, losses), dim=0)
if labels is not None:
    labels = self._pad_across_processes(labels)        
if inputs_decode is not None:
    inputs_decode = self._pad_across_processes(inputs_decode)
    inputs_decode = self._nested_gather(inputs_decode)
    inputs_host = (
        inputs_decode
        if inputs_host is None
        else nested_concat(inputs_host, inputs_decode, padding_index=-100)
    )
if logits is not None:
    logits = self._pad_across_processes(logits)
if self.preprocess_logits_for_metrics is not None and logits is not None:
    logits = self.preprocess_logits_for_metrics(logits, labels)
if labels is not None:
    labels = self._nested_gather(labels)
    labels_host = labels if labels_host is None else nested_concat(labels_host, labels, padding_index=-100)
if logits is not None:
    logits = self._nested_gather(logits)
    preds_host = logits if preds_host is None else nested_concat(preds_host, logits, padding_index=-100)
```
labels and logits should be padded first, then be preprocessed before gathering. In my use case, I trained BLOOM with 32 batch size, the gathered logits size is (32, 1024, 250000+), which takes 15G+ gpu memory and cause to OOM during evaluating. 

@sgugger Done. Rewrite the code with your suggestion. Thanks.