code: def sample_order(self, epoch: int) -> Sequence[int]:
      if not self.distributed:
          return self.indices
  
      self.sampler.set_epoch(epoch)
  
      return self.indices[np.array(list(self.sampler))]
  
file_path: ffcv/ffcv/traversal_order/sequential.py
imports: from typing import Sequence, TYPE_CHECKING
  import numpy
  from torch.utils.data import DistributedSampler
  from .base import TraversalOrder
label_desc: Use image node_id 2 for calling the Sequential obj's underlying member method code with example usage: obj.sample_order(epoch) and returns: self, self