class_docstr: More efficient ops for indices.
  
  Avoid wasteful allocations, accept generators. Convert to list only
  when needed.
  
  Do not use for anything outside this file.
docstr: Return the depth of the LazyIndices tree.
  Use it only to eagerify early to avoid RecursionErrors.
docstr_tok: ["Return","the","depth","of","the","LazyIndices","tree",".","Use","it","only","to","eagerify","early","to","avoid","RecursionErrors","."]
code: def _depth(self):
      """Return the depth of the LazyIndices tree.
      Use it only to eagerify early to avoid RecursionErrors.
      """
      if self._eager_list is not None:
          return 0
  
      lens = [0]
      for ll in self._lists:
          if isinstance(ll, LazyIndices):
              lens.append(ll._depth())
      return max(lens) + 1
  
imports: import bisect
  import sys
  import numpy
  from avalanche.benchmarks.utils.dataset_utils import slice_alike_object_to_indices
  from typing import Iterable, List, Optional, Sequence, Tuple, TypeVar, Union, overload
  from torch.utils.data import ConcatDataset
  import itertools
  from avalanche.benchmarks.utils.dataset_definitions import IDataset
label_desc: Use image node_id 2 for calling the LazyIndices obj's underlying member method code with example usage: obj._depth() and returns: unknown, int