class_docstr: Tracks batch progress.
  
  These counters are local to a trainer rank. By default, they are not globally synced across all ranks.
  
  Args:
      total: Tracks the total batch progress.
      current: Tracks the current batch progress.
      is_last_batch: Whether the batch is the last one. This is useful for iterable datasets.
class_docstr_tok: ["Tracks","batch","progress",".","These","counters","are","local","to","a","trainer","rank",".","By","default",",","they","are","not","globally","synced","across","all","ranks",".","Args",":","total",":","Tracks","the","total","batch","progress",".","current",":","Tracks","the","current","batch","progress",".","is_last_batch",":","Whether","the","batch","is","the","last","one",".","This","is","useful","for","iterable","datasets","."]
code: def reset(self) -> None:
      super().reset()
      self.is_last_batch = False
  
imports: from dataclasses import asdict, dataclass, field
  from typing import Type
  from typing_extensions import override
label_desc: Use image node_id 1 for calling the _BatchProgress obj's underlying member method code with example usage: obj.reset() without return types