code: def make_disparity_sequence(disparities: List[Tensor]):
      # convert each disparity to [0, 1]
      for idx, disparity_batch in enumerate(disparities):
          disparities[idx] = torch.stack(
              list(map(make_disparity_image, disparity_batch))
          )
      # make the list into a batch
      disparity_sequences = torch.stack(disparities)
      return disparity_sequences
  
file_path: vision/references/depth/stereo/visualization.py
imports: import os
  from typing import List
  import numpy
  import torch
  from torch import Tensor
  from torchvision.utils import make_grid
label_desc: Use image node_id 3 for calling a global function with example usage: make_disparity_sequence(disparities) and returns: disparity_sequences