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 __init__(self, *args, **kwargs):
      self.epochs = kwargs.pop("epochs")
      super().__init__(*args, **kwargs)
  
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 1 to create a new ProgressBar object from inherited base classes: TQDMProgressBar with example: obj = ProgressBar()