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autoPyTorch/pipeline/components/training/trainer/__init__.py

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@@ -293,9 +293,9 @@ def _fit(self, X: Dict[str, Any], y: Any = None, **kwargs: Any) -> 'TrainerChoic
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writer=writer,
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)
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# its fine if train_loss is None due to `is_max_time_reached()`
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if train_loss is None:
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if self.budget_tracker.is_max_time_reached():
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# train_loss is None, if epoch could not be started, usually due to `is_max_time_reached()``
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break
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else:
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raise RuntimeError("`train_loss` computed to None.")

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