TQDMProgressBar bug (?) causes DDP to hang

@deependujha is already working on this.

Since Oct 6, 2025.

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/callbacks/progress/tqdm_progress.py#L285-L286

Is this^ a safe implementation for DDP?

Based on my understanding, this will lead to the following stack trace, ultimately leading to a sync operation on `ResultMetrics` if certain conditions are met. However, `self.train_progress_bar.disable` is only `False` (i.e. enabled) on the rank-zero process, so the metrics computations will only succeed if there happens to be another codepath on non-rank-zero devices that's requesting `self._logger_connector.metrics` at the same time.

Stack trace

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/callbacks/progress/progress_bar.py#L180-L201

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/trainer/trainer.py#L1675-L1683

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/trainer/connectors/logger_connector/logger_connector.py#L253-L258

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/trainer/connectors/logger_connector/logger_connector.py#L232-L237

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/trainer/connectors/logger_connector/result.py#L471-L476

https://github.com/Lightning-AI/pytorch-lightning/blob/918a1a62635e41b72131fc153920594f0f64cc5b/src/lightning/pytorch/trainer/connectors/logger_connector/result.py#L425-L440

I ran into this when debugging an issue in my training script where DDP was hanging at the end of the first epoch. Changing the original code chunk as such resolved the deadlock for me.

```
metrics = self.get_metrics(trainer, pl_module)
if not self.train_progress_bar.disable:
self.train_progress_bar.set_postfix(metrics)
```

To provide a little more detail, I have a `CustomCallback` that calls `trainer.strategy.barrier()` during `on_train_epoch_end`. At the end of the first training epoch, the rank-zero process hangs on `TQDMProgressBar.on_train_epoch_end` and the non-rank-zero processes hang on `CustomCallback.on_train_epoch_end`.

cc @justusschock @lantiga