code: def test_merging(self):
      x = torch.randn(10)
      fdata = FlatData([x])
  
      dd = fdata
      for i in range(5):
          dd = dd.concat(fdata)
          assert _flatdata_depth(dd) == 2
          assert len(dd._datasets) == 1
  
          idxs = list(range(len(dd)))
          random.shuffle(idxs)
          dd_old = dd
          dd = dd.subset(idxs[:12])
  
          for i in range(12):
              assert dd[i] == dd_old[idxs[i]]
  
          assert _flatdata_depth(dd) == 2
          assert len(dd._indices) == 12
          assert len(dd._datasets) == 1
  
imports: import sys
  import unittest
  import random
  import torch
  from avalanche.benchmarks import FixedSizeExperienceSplitter
  from avalanche.benchmarks.utils import AvalancheDataset, concat_datasets
  from avalanche.benchmarks.utils.classification_dataset import TaskAwareClassificationDataset
  from avalanche.benchmarks.utils.flat_data import FlatData, _flatten_datasets_and_reindex, LazyIndices
  from avalanche.benchmarks.utils.flat_data import _flatdata_depth, _flatdata_print
  from avalanche.training import ReservoirSamplingBuffer
  from tests.unit_tests_utils import get_fast_benchmark
label_desc: Use image node_id 2 for calling the AvalancheDatasetTests obj's underlying member method code with example usage: obj.test_merging() without return types