code: def test_basic(self):
      benchmark = get_fast_benchmark()
      ds = [el.dataset for el in benchmark.train_stream]
      data = concat_datasets(ds)
  
      dl = DataLoader(data)
      for el in dl:
          pass
  
      dl = TaskBalancedDataLoader(data)
      for el in dl:
          pass
  
      dl = GroupBalancedDataLoader(ds)
      for el in dl:
          pass
  
      dl = ReplayDataLoader(data, data)
      for el in dl:
          pass
  
      dl = GroupBalancedInfiniteDataLoader(ds)
      max_iters = 10**3
      for i, el in enumerate(dl):
          if i == max_iters:
              break
  
imports: import unittest
  import torch
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from torch.optim import SGD
  from torch.nn import CrossEntropyLoss
  from torch.utils.data import TensorDataset, DataLoader
  from avalanche.benchmarks.utils import _concat_taskaware_classification_datasets
  from avalanche.benchmarks.utils.utils import concat_datasets
  from avalanche.models import SimpleMLP
  from avalanche.training.plugins import ReplayPlugin
  from avalanche.training.supervised import Naive
  from avalanche.benchmarks import nc_benchmark
  from avalanche.benchmarks.utils.data_loader import ReplayDataLoader, TaskBalancedDataLoader, GroupBalancedDataLoader, GroupBalancedInfiniteDataLoader
label_desc: Use image node_id 1 for calling the DataLoaderTests obj's underlying member method code with example usage: obj.test_basic() without return types