code: def get_dims(module_name, height, width):
      # detection models have curated input sizes
      if module_name == "detection":
          # we can feed a batch of 1 for detection model instead of a list of 1 image
          dims = (3, height, width)
      elif module_name == "video":
          # hard-coding the time dimension to size 16
          dims = (1, 16, 3, height, width)
      else:
          dims = (1, 3, height, width)
  
      return dims
  
imports: import os
  from collections import defaultdict
  from numbers import Number
  from typing import Any, List
  import torch
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils._pytree import tree_map
  from torchvision.models._api import Weights
label_desc: Use image node_id 13 for calling a global function with example usage: get_dims(module_name, height, width) and returns: dims