class_docstr: Adapter that handles torch Dataloaders.
code: def __init__(
      self,
      x: DataLoader,
      y=None,
      steps=None,
      sample_weights=None,
      training=True,
      **kwargs,
  ):
      if not is_none_or_empty(y):
          raise ValueError(
              "`y` argument is not supported when using "
              "torch Dataloader as input."
          )
      if not is_none_or_empty(sample_weights):
          raise ValueError(
              "`sample_weight` argument is not supported when using "
              "torch Dataloader as input."
          )
  
      super().__init__(x, y, **kwargs)
  
      self.training = training
      self.steps = steps
      self._batch_size = x.batch_size
      self._dataset = x
  
      self.current_step = 0
  
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 2 to create a new TorchDataLoaderAdapter object from inherited base classes: DataAdapter with example: obj = TorchDataLoaderAdapter(x, y, steps, sample_weights, training)