code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.counter = 0
      # self.start_counter = 0
      self.restarting = False
  
file_path: flash-attention/training/src/datamodules/fault_tolerant_sampler.py
imports: from typing import Iterator
  import math
  import torch
  from torch.utils.data import RandomSampler, DistributedSampler
label_desc: Use image node_id 1 to create a new FaultTolerantDistributedSampler object from inherited base classes: DistributedSampler with example: obj = FaultTolerantDistributedSampler()