code: def __init__(
      self,
      x: DataLoader,
      y=None,
      sample_weights=None,
      **kwargs,
  ):
      # shuffling is performed in the DataLoader
      kwargs.pop("shuffle", None)
  
      if not is_none_or_empty(y):
          raise ValueError(
              "`y` argument is not supported when using DataLoader as input. The underlying Dataset should return the y values."
          )
      if not is_none_or_empty(sample_weights):
          raise ValueError(
              "`sample_weight` argument is not supported when using DataLoader as input. The underlying Dataset should return the sample weights."
          )
  
      super().__init__(x, y, **kwargs)
      self._dataloader = x
  
imports: import multiprocessing.pool
  import os
  import typing
  import jax
  import jax.numpy
  import numpy
  from .data_adapter import DataAdapter
  from .utils import is_none_or_empty
label_desc: Use image node_id 2 to create a new DataLoaderAdapter object from inherited base classes: DataAdapter with example: obj = DataLoaderAdapter(x, y, sample_weights)