code: def setUp(self):
      scenario = SplitMNIST(2)
      dataset_for_current = scenario.train_stream[1].dataset
      dataset_for_memory = scenario.train_stream[0].dataset
  
      indices_big_set = np.random.choice(
          np.arange(len(dataset_for_current)), size=10000, replace=False
      )
  
      indices_small_set = np.random.choice(
          np.arange(len(dataset_for_current)), size=1000, replace=False
      )
  
      indices_tiny_set = np.random.choice(
          np.arange(len(dataset_for_current)), size=100, replace=False
      )
  
      self.big_task_set = dataset_for_current.subset(indices_big_set)
      self.small_task_set = dataset_for_current.subset(
          indices_small_set
      )
      self.tiny_task_set = dataset_for_current.subset(indices_tiny_set)
  
      indices_memory = np.random.choice(
          np.arange(len(dataset_for_memory)), size=2000, replace=False
      )
  
      indices_memory_small = np.random.choice(
          np.arange(len(dataset_for_memory)), size=100, replace=False
      )
  
      self.memory_set = dataset_for_memory.subset(indices_memory)
      self.small_memory_set = dataset_for_memory.subset(
          indices_memory_small
      )
  
      self._batch_size = None
      self._task_dataset = None
  
file_path: avalanche/tests/benchmarks/utils/test_replay_loader.py
imports: import unittest
  import numpy
  from avalanche.benchmarks.classic import SplitMNIST
  from avalanche.benchmarks.utils.data_loader import ReplayDataLoader
label_desc: Use image node_id 1 for calling the TestReplayDataLoader obj's underlying member method code with example usage: obj.setUp() without return types