code: def create_random_bbox(num_boxes: int, height: int, width: int):
      bboxes = torch.rand(num_boxes, 4)
      bboxes[:, 0] *= float(width) / 2.0
      bboxes[:, 2] = (
          bboxes[:, 2] * float(width) / 2.0 + float(width) / 2.0
      )
      bboxes[:, 1] *= float(height) / 2.0
      bboxes[:, 3] = (
          bboxes[:, 3] * float(height) / 2.0 + float(height) / 2.0
      )
      return torch.floor(bboxes)
  
file_path: pytorchvideo/tests/utils.py
imports: import contextlib
  import os
  import pathlib
  import tempfile
  import av
  import numpy
  import torch
  import torchvision.io
  import torchvision.transforms
  from pytorchvideo.data.dataset_manifest_utils import EncodedVideoInfo, VideoFrameInfo, VideoInfo
  from pytorchvideo.data.utils import thwc_to_cthw
label_desc: Use image node_id 2 for calling a global function with example usage: create_random_bbox(num_boxes, height, width) and returns: torch