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_batch_end(
      self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", *_
  ) -> None:
      pass
  
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 3 for calling the ProgressBar obj's underlying member method code with example usage: obj.on_train_batch_end(trainer, pl_module) without return types