code: def bfloat16_to_float32(ival: int) -> Any:
      if ival == 0x7FC0:
          return np.float32(np.nan)
  
      expo = ival >> 7
      prec = ival - (expo << 7)
      sign = expo & 256
      powe = expo & 255
      fval = float(prec * 2 ** (-7) + 1) * 2.0 ** (powe - 127)
      if sign:
          fval = -fval
      return np.float32(fval)
  
imports: import unittest
  from typing import Any
  import numpy
  import parameterized
  import onnx
  from onnx import helper, numpy_helper
label_desc: Use image node_id 1 for calling a global function with example usage: bfloat16_to_float32(ival) and returns: np, np