code: def video_center_crop(
      vid: torch.Tensor, output_size: Tuple[int, int]
  ) -> torch.Tensor:
      h, w = vid.shape[-2:]
      th, tw = output_size
  
      i = int(round((h - th) / 2.0))
      j = int(round((w - tw) / 2.0))
      return video_crop(vid, i, j, th, tw)
  
file_path: mmf/mmf/datasets/processors/functional.py
imports: from typing import List, Tuple, Union
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: video_center_crop(vid, output_size) and returns: video_crop