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on_log event should occur *after* the current log is written (#9872)
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@ -680,7 +680,7 @@ class Trainer:
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self,
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resume_from_checkpoint: Optional[str] = None,
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trial: Union["optuna.Trial", Dict[str, Any]] = None,
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**kwargs
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**kwargs,
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):
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"""
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Main training entry point.
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@ -1248,9 +1248,9 @@ class Trainer:
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if self.state.epoch is not None:
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logs["epoch"] = round(self.state.epoch, 2)
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self.control = self.callback_handler.on_log(self.args, self.state, self.control, logs)
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output = {**logs, **{"step": self.state.global_step}}
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self.state.log_history.append(output)
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self.control = self.callback_handler.on_log(self.args, self.state, self.control, logs)
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def _prepare_inputs(self, inputs: Dict[str, Union[torch.Tensor, Any]]) -> Dict[str, Union[torch.Tensor, Any]]:
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"""
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