code: def assert_balancing(self, policy):
      benchmark = get_fast_benchmark(use_task_labels=True)
      replay = ReplayPlugin(mem_size=100, storage_policy=policy)
      model = SimpleMLP(num_classes=benchmark.n_classes)
  
      # CREATE THE STRATEGY INSTANCE (NAIVE)
      cl_strategy = Naive(
          model,
          SGD(model.parameters(), lr=0.001),
          CrossEntropyLoss(),
          train_mb_size=100,
          train_epochs=0,
          eval_mb_size=100,
          plugins=[replay],
          evaluator=None,
      )
  
      for exp in benchmark.train_stream:
          cl_strategy.train(exp)
  
          ext_mem = policy.buffer_groups
          ext_mem_data = policy.buffer_datasets
          print(list(ext_mem.keys()), [len(el) for el in ext_mem_data])
  
          # buffer size should equal self.mem_size if data is large enough
          len_tot = sum([len(el) for el in ext_mem_data])
          assert len_tot == policy.max_size
  
imports: import unittest
  from typing import List
  from unittest.mock import MagicMock
  import torch
  from torch import tensor, Tensor, zeros
  from torch.nn import CrossEntropyLoss, Module, Identity
  from torch.optim import SGD
  from avalanche.benchmarks.utils import _make_taskaware_classification_dataset, _make_taskaware_tensor_classification_dataset
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.flat_data import _flatdata_depth
  from avalanche.models import SimpleMLP
  from avalanche.training.plugins import ReplayPlugin
  from avalanche.training.storage_policy import ExperienceBalancedBuffer, ClassBalancedBuffer, ExemplarsSelectionStrategy, HerdingSelectionStrategy, ClosestToCenterSelectionStrategy, ParametricBuffer, ReservoirSamplingBuffer
  from avalanche.training.supervised import Naive
  from avalanche.training.templates import SupervisedTemplate
  from tests.unit_tests_utils import get_fast_benchmark
  import time
label_desc: Use image node_id 4 for calling the ReplayTest obj's underlying member method code with example usage: obj.assert_balancing(policy) without return types