code: def normalize_bcast_dims(*shapes):
      """
      Normalize the lengths of the input shapes to have the same length.
      The shapes are padded at the front by 1 to make the lengths equal.
  
      Examples
      --------
      >>> normalize_bcast_dims([1, 2, 3], [2, 3])
      [[1, 2, 3], [1, 2, 3]]
  
      Parameters
      ----------
      shapes: List[List[int]]
          The shapes to normalize.
  
      Returns
      -------
      List[List[int]]
          The normalized shapes.
  
      """
      maxlens = max([len(shape) for shape in shapes])
      res = [
          [1] * (maxlens - len(shape)) + list(shape) for shape in shapes
      ]
      return res
  
imports: from typing import Tuple
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_bcast_dims() and returns: res