code: def test_dataload_reinit(self):
      benchmark = get_fast_benchmark()
      model = SimpleMLP(input_size=6, hidden_size=10)
  
      replayPlugin = ReplayPlugin(mem_size=5)
      cl_strategy = Naive(
          model,
          SGD(
              model.parameters(),
              lr=0.001,
              momentum=0.9,
              weight_decay=0.001,
          ),
          CrossEntropyLoss(),
          train_mb_size=16,
          train_epochs=1,
          eval_mb_size=16,
          plugins=[replayPlugin],
      )
      for step in benchmark.train_stream[:2]:
          cl_strategy.train(step)
  
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 2 for calling the DataLoaderTests obj's underlying member method code with example usage: obj.test_dataload_reinit() without return types