[Trainer] Fix nan-loss condition #13911
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sgugger
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patrickvonplaten
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Fixes a change in the nan loss handling logic introduced by #13896
With
is_torch_tpu_available()==Falseand(torch.isnan(tr_loss_step) or torch.isinf(tr_loss_step))==Falsethe
else:condition was never reached, so the training loss was always0.0.