class_docstr: A dataset from images from a single scene.
class_docstr_tok: ["A","dataset","from","images","from","a","single","scene","."]
code: def sequence_frames_in_order(
      self, seq_name: str, subset_filter: Optional[Sequence[str]] = None
  ) -> Iterator[Tuple[float, int, int]]:
      for i in range(len(self)):
          if (
              subset_filter is None
              or self.frame_types[i] in subset_filter
          ):
              yield 0.0, i, i
  
imports: from dataclasses import field
  from typing import Iterable, Iterator, List, Optional, Sequence, Tuple
  import numpy
  import torch
  from pytorch3d.implicitron.tools.config import Configurable, expand_args_fields, run_auto_creation
  from pytorch3d.renderer import CamerasBase, join_cameras_as_batch, PerspectiveCameras
  from .dataset_base import DatasetBase
  from .dataset_map_provider import DatasetMap, DatasetMapProviderBase, PathManagerFactory
  from .frame_data import FrameData
  from .utils import DATASET_TYPE_KNOWN, DATASET_TYPE_UNKNOWN
label_desc: Use image node_id 3 for calling the SingleSceneDataset obj's underlying member method code with example usage: obj.sequence_frames_in_order(seq_name, subset_filter) without return types