code: def __init__(self, dataset, **kwargs):
      super().__init__(list(dataset) + list(range(5, 10)), **kwargs)
  
imports: import contextlib
  import os
  import random
  from unittest import mock
  from unittest.mock import Mock
  import lightning.fabric
  import numpy
  import pytest
  import torch
  from lightning.fabric.utilities.data import AttributeDict, _get_dataloader_init_args_and_kwargs, _replace_dunder_methods, _replace_value_in_saved_args, _set_sampler_epoch, _update_dataloader, _WrapAttrTag, has_iterable_dataset, has_len, suggested_max_num_workers
  from lightning.fabric.utilities.exceptions import MisconfigurationException
  from lightning_utilities.test.warning import no_warning_call
  from torch import Tensor
  from torch.utils.data import BatchSampler, DataLoader, RandomSampler
  from tests_fabric.helpers.models import RandomDataset, RandomIterableDataset
label_desc: Use image node_id 1 to create a new ChangingDataLoader object from inherited base classes: DataLoader with example: obj = ChangingDataLoader(dataset)