class_docstr: The base class for progress bars in Lightning. It is a :class:`~lightning.pytorch.callbacks.Callback` that keeps
  track of the batch progress in the :class:`~lightning.pytorch.trainer.trainer.Trainer`. You should implement your
  highly custom progress bars with this as the base class.
  
  Example::
  
      class LitProgressBar(ProgressBar):
  
          def __init__(self):
              super().__init__()  # don't forget this :)
              self.enable = True
  
          def disable(self):
              self.enable = False
  
          def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx):
              super().on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx)  # don't forget this :)
              percent = (batch_idx / self.total_train_batches) * 100
              sys.stdout.flush()
              sys.stdout.write(f'{percent:.01f} percent complete \r')
  
      bar = LitProgressBar()
      trainer = Trainer(callbacks=[bar])
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code: def test_description(self) -> str:
      return "Testing"
  
imports: from typing import Any, Dict, Optional, Union
  from typing_extensions import override
  import lightning.pytorch
  from lightning.pytorch.callbacks import Callback
  from lightning.pytorch.utilities.rank_zero import rank_zero_warn
label_desc: Use image node_id 6 for calling the ProgressBar obj's underlying member method code with example usage: obj.test_description() and returns: str