code: def bilinear_upsample_initializer(x):
      cc = x.size(2) // 2
      cr = x.size(3) // 2
  
      for i in range(x.size(2)):
          for j in range(x.size(3)):
              x[..., i, j] = hypot(cc - i, cr - j)
  
      y = 1 - x / x.sum(dim=(2, 3), keepdim=True)
      y = y / y.sum(dim=(2, 3), keepdim=True)
      return y
  
imports: from enum import Enum
  from math import hypot
  from typing import Optional, List, Tuple, Union, Type
  import torch
  from torch import nn, Tensor
label_desc: Use image node_id 1 for calling a global function with example usage: bilinear_upsample_initializer(x) and returns: y