code: def test_concat_flattens_same_dataset_corner_case(self):
      base_dataset = [1, 2, 3]
      A = FlatData([base_dataset], can_flatten=False, indices=[1, 2])
      B = FlatData([A])
      C = A.concat(B)
      C[3]
      self.assertListEqual([2, 3, 2, 3], list(C))
  
      A = FlatData([base_dataset], can_flatten=False)
      B = FlatData([A], indices=[1, 2])
      C = A.concat(B)
      self.assertListEqual([1, 2, 3, 2, 3], list(C))
  
      A = FlatData([base_dataset], can_flatten=False, indices=[1, 2])
      B = FlatData([A])
      C = B.concat(A)
      self.assertListEqual([2, 3, 2, 3], list(C))
  
      A = FlatData([base_dataset], can_flatten=False)
      B = FlatData([A], indices=[1, 2])
      C = B.concat(A)
      self.assertListEqual([2, 3, 1, 2, 3], list(C))
  
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 3 for calling the FlatteningTests obj's underlying member method code with example usage: obj.test_concat_flattens_same_dataset_corner_case() without return types