code: def _get_video_tensor(video_dir, video_file):
      """open a video file, and represent the video data by a PT tensor"""
      full_path = os.path.join(video_dir, video_file)
  
      assert os.path.exists(full_path), "File not found: %s" % full_path
  
      with open(full_path, "rb") as fp:
          video_tensor = torch.frombuffer(fp.read(), dtype=torch.uint8)
  
      return full_path, video_tensor
  
imports: import collections
  import math
  import os
  from fractions import Fraction
  import numpy
  import pytest
  import torch
  import torchvision.io
  from common_utils import assert_equal
  from numpy.random import randint
  from pytest import approx
  from torchvision import set_video_backend
  from torchvision.io import _HAS_VIDEO_OPT
label_desc: Use image node_id 6 for calling a global function with example usage: _get_video_tensor(video_dir, video_file) and returns: full_path,  video_tensor