code: def scale_width(
      num_filters, width_coefficient, width_divisor, min_width
  ):
      """
      Calculates the scaled number of filters based on the width coefficient and
      rounds the result by the width divisor.
      """
      if not width_coefficient:
          return num_filters
  
      num_filters *= width_coefficient
      min_width = min_width or width_divisor
      new_filters = max(
          min_width,
          (int(num_filters + width_divisor / 2) // width_divisor)
          * width_divisor,
      )
      # Do not round down by more than 10%
      if new_filters < 0.9 * num_filters:
          new_filters += width_divisor
      return int(new_filters)
  
imports: import copy
  import math
  from collections import OrderedDict
  from typing import Any, Dict, NamedTuple, Optional
  import torch
  import torch.nn
  from classy_vision.generic.util import get_torch_version
  from classy_vision.models import ClassyModel, register_model
label_desc: Use image node_id 3 for calling a global function with example usage: scale_width(num_filters, width_coefficient, width_divisor, min_width) and returns: int, num_filters