code: def __getitem__(self, index: int) -> Union[T1, T2]:
      img1 = self._read_img(self._image_list[index][0])
      img2 = self._read_img(self._image_list[index][1])
  
      if (
          self._flow_list
      ):  # it will be empty for some dataset when split="test"
          flow = self._read_flow(self._flow_list[index])
          if self._has_builtin_flow_mask:
              flow, valid_flow_mask = flow
          else:
              valid_flow_mask = None
      else:
          flow = valid_flow_mask = None
  
      if self.transforms is not None:
          img1, img2, flow, valid_flow_mask = self.transforms(
              img1, img2, flow, valid_flow_mask
          )
  
      if self._has_builtin_flow_mask or valid_flow_mask is not None:
          # The `or valid_flow_mask is not None` part is here because the mask can be generated within a transform
          return img1, img2, flow, valid_flow_mask
      else:
          return img1, img2, flow
  
imports: import itertools
  import os
  from abc import ABC, abstractmethod
  from glob import glob
  from pathlib import Path
  from typing import Callable, List, Optional, Tuple, Union
  import numpy
  import torch
  from PIL import Image
  from ..io.image import _read_png_16
  from .utils import _read_pfm, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 4 for calling the FlowDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: img1,  img2,  flow,  valid_flow_mask, img1,  img2,  flow