class_docstr: A memory-efficient constant sequence.
docstr: Concatenation
  
  :param other: other dataset
  :return:
docstr_tok: ["Concatenation",":","param","other",":","other","dataset",":","return",":"]
code: def concat(self, other: FlatData[DataT]) -> IDataset[DataT]:
      """Concatenation
  
      :param other: other dataset
      :return:
      """
      if (
          isinstance(other, ConstantSequence)
          and self._constant_value == other._constant_value
      ):
          return ConstantSequence(
              self._constant_value, len(self) + len(other)
          )
      else:
          return FlatData([self, other])
  
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 7 for calling the ConstantSequence obj's underlying member method code with example usage: obj.concat(other) and returns: ConstantSequence, FlatData