code: def test_dictionary_train_replay(self):
      rand_x = torch.randn(100, 10)
      rand_y = torch.randint(0, 2, (100,))
      data = [{"x": x, "y": y} for x, y in zip(rand_x, rand_y)]
  
      train_exps, test_exps = [], []
      for i in range(0, 2):
          tl = ConstantSequence(i, len(data))
          tl = DataAttribute(
              tl, "targets_task_labels", use_in_getitem=True
          )
          av_data = AvalancheDataset(
              [data],
              data_attributes=[tl],
              collate_fn=collate_dictionaries,
          )
          exp = CLExperience(i, None)
          exp.dataset = av_data
          train_exps.append(exp)
          test_exps.append(exp)
  
      train_stream = CLStream("train", train_exps, None)
      test_stream = CLStream("test", test_exps, None)
      benchmark = CLScenario([train_stream, test_stream])
      train_stream.benchmark = benchmark
      test_stream.benchmark = benchmark
  
      eval_plugin = avalanche.training.plugins.EvaluationPlugin(
          avalanche.evaluation.metrics.loss_metrics(
              epoch=True, experience=True, stream=True
          ),
          loggers=[avalanche.logging.InteractiveLogger()],
          strict_checks=False,
      )
  
      plugins = [ReplayPlugin(mem_size=200)]
      model = SimpleMLP(input_size=10, num_classes=2)
      optimizer = torch.optim.Adam(model.parameters(), lr=2)
      strategy = NaiveDictData(
          model,
          optimizer,
          evaluator=eval_plugin,
          train_mb_size=10,
          plugins=plugins,
      )
      for experience in benchmark.train_stream:
          strategy.train(experience)
  
imports: import unittest
  from avalanche.benchmarks.utils import DataAttribute, ConstantSequence
  from avalanche.models import SimpleMLP
  from avalanche.training.plugins import ReplayPlugin
  import torch
  import avalanche
  import torch.nn
  from avalanche.benchmarks import CLScenario, CLStream, CLExperience
  from avalanche.evaluation.metrics import accuracy_metrics
  import avalanche.training.templates.base
  from avalanche.benchmarks.utils import AvalancheDataset
label_desc: Use image node_id 2 for calling the TestDictionaryDatasets obj's underlying member method code with example usage: obj.test_dictionary_train_replay() without return types