code: def safe_div(
      numerator: Tensor,
      denom: Union[Tensor, int, float],
      default_denom: Union[Tensor, int, float] = 1.0,
  ) -> Tensor:
      r"""
      A simple utility function to perform `numerator / denom`
      if the statement is undefined => result will be `numerator / default_denorm`
      """
      if isinstance(denom, (int, float)):
          return numerator / (denom if denom != 0 else default_denom)
  
      # convert default_denom to tensor if it is float
      if not torch.is_tensor(default_denom):
          default_denom = torch.tensor(
              default_denom, dtype=denom.dtype, device=denom.device
          )
  
      return numerator / torch.where(denom != 0, denom, default_denom)
  
imports: import typing
  from enum import Enum
  from functools import reduce
  from inspect import signature
  from typing import Any, Callable, cast, Dict, List, overload, Tuple, Union
  import numpy
  import torch
  from captum._utils.typing import BaselineType, Literal, TargetType, TensorOrTupleOfTensorsGeneric, TupleOrTensorOrBoolGeneric
  from torch import device, Tensor
  from torch.nn import Module
label_desc: Use image node_id 2 for calling a global function with example usage: safe_div(numerator, denom, default_denom) and returns: unknown, unknown