class_docstr: Custom progress bar for PyTorch Lightning for only update every epoch, not every batch.
class_docstr_tok: ["Custom","progress","bar","for","PyTorch","Lightning","for","only","update","every","epoch",",","not","every","batch","."]
code: def on_train_epoch_start(self, trainer: "pl.Trainer", *_) -> None:
      self.main_progress_bar.reset(self.epochs)
      self.main_progress_bar.set_description(
          f"Epoch {trainer.current_epoch + 1}"
      )
      self._update_n(self.main_progress_bar, trainer.current_epoch + 1)
  
file_path: neural_prophet/neuralprophet/logger.py
imports: import collections
  from typing import Any, Mapping, Optional
  import pytorch_lightning
  from pytorch_lightning.callbacks import TQDMProgressBar
  from pytorch_lightning.loggers import TensorBoardLogger
  from pytorch_lightning.utilities.rank_zero import rank_zero_only
label_desc: Use image node_id 2 for calling the ProgressBar obj's underlying member method code with example usage: obj.on_train_epoch_start(trainer) without return types