code: def _round_to_multiple_of(
      val: float, divisor: int, round_up_bias: float = 0.9
  ) -> int:
      """Asymmetric rounding to make `val` divisible by `divisor`. With default
      bias, will round up, unless the number is no more than 10% greater than the
      smaller divisible value, i.e. (83, 8) -> 80, but (84, 8) -> 88."""
      if not 0.0 < round_up_bias < 1.0:
          raise ValueError(
              f"round_up_bias should be greater than 0.0 and smaller than 1.0 instead of {round_up_bias}"
          )
      new_val = max(
          divisor, int(val + divisor / 2) // divisor * divisor
      )
      return (
          new_val
          if new_val >= round_up_bias * val
          else new_val + divisor
      )
  
imports: import warnings
  from functools import partial
  from typing import Any, Dict, List, Optional
  import torch
  import torch.nn
  from torch import Tensor
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 2 for calling a global function with example usage: _round_to_multiple_of(val, divisor, round_up_bias) and returns: unknown