class_docstr: Adapter that handles torch Dataloaders.
code: def should_recreate_iterator(self):
      # if in eval mode should not recreate iterator
      # but if in train mode and steps not provided, should recreate at end of each epoch
      if not self.training or self.steps is None:
          return self.training
  
      steps_dataset = self.get_size()
      if steps_dataset is None:
          return False
  
      remaining_steps = steps_dataset - self.current_step
      # if remaining steps less than needed steps, should recreate dataloader
      # TODO: This will drop the last steps of data, how to avoid this?
      if remaining_steps < self.steps:
          return True
      else:
          return False
  
file_path: elegy/elegy/data/torch_dataloader_adapter.py
imports: from jax._src.lax.lax import remaining
  from torch.utils.data import DataLoader
  from .data_adapter import DataAdapter
  from .utils import is_none_or_empty, list_to_tuple, map_structure
label_desc: Use image node_id 9 for calling the TorchDataLoaderAdapter obj's underlying member method code with example usage: obj.should_recreate_iterator() and returns: self, False, True, False