class_docstr: A utility class used to define a lazily evaluated sub-sequence.
class_docstr_tok: ["A","utility","class","used","to","define","a","lazily","evaluated","sub-sequence","."]
code: def __init__(
      self,
      targets: Sequence[TMappableTargetType],
      *,
      indices: Optional[Sequence[int]] = None,
      converter: Optional[
          Callable[[TMappableTargetType], TTargetType]
      ] = None,
  ):
      self._targets = targets
      self.converter = converter
      super().__init__(
          slice_ids=list(indices) if indices is not None else None
      )
  
imports: from abc import ABC, abstractmethod
  import bisect
  import copy
  from typing import Iterator, overload
  from typing_extensions import final
  import numpy
  from numpy import ndarray
  from torch import Tensor
  from torch.utils.data import Subset
  from .dataset_definitions import IDatasetWithTargets
  from typing import Sequence, List, Iterable, Union, Optional, TypeVar, Callable, Generic
label_desc: Use image node_id 1 to create a new SubSequence object from inherited base classes: SliceSequence, Generic with example: obj = SubSequence(targets)