docstr: Args:
      clip (torch.tensor): Video clip to be cropped. Size is (C, T, H, W)
  Returns:
      torch.tensor: central cropping of video clip. Size is
      (C, T, crop_size, crop_size)
docstr_tok: ["Args",":","clip","(","torch.tensor",")",":","Video","clip","to","be","cropped",".","Size","is","(","C",",","T",",","H",",","W",")","Returns",":","torch.tensor",":","central","cropping","of","video","clip",".","Size","is","(","C",",","T",",","crop_size",",","crop_size",")"]
code: def __call__(self, clip):
      """
      Args:
          clip (torch.tensor): Video clip to be cropped. Size is (C, T, H, W)
      Returns:
          torch.tensor: central cropping of video clip. Size is
          (C, T, crop_size, crop_size)
      """
      return F.resize(clip, self.target_size, self.interpolation_mode)
  
imports: import torch
  from lavis.common.registry import registry
  from lavis.datasets.data_utils import load_video, load_clip
  from lavis.processors import transforms_video
  from lavis.processors.base_processor import BaseProcessor
  from lavis.processors.randaugment import VideoRandomAugment
  from lavis.processors import functional_video
  from omegaconf import OmegaConf
  from torchvision import transforms
label_desc: Use image node_id 2 for calling the ResizeVideo obj's underlying member method code with example usage: obj.__call__(clip) and returns: F