code: def quantize_bias_for_hexagon(data):
      np_data = np.array(data).astype(float)
      max_val = max(abs(np_data.min()), abs(np_data.max()))
      in_min = -max_val
      in_max = max_val
      scale = (in_max - in_min) / 2**32
      zero = 0
      output = np.clip(
          (np.round(zero + data / scale).astype(np.int64)),
          -(2**31),
          2**31 - 1,
      )
  
      quantized_data = QuantizedData()
      quantized_data.data = output
      quantized_data.scale = scale
      quantized_data.zero = zero
      quantized_data.minval = in_min
      quantized_data.maxval = in_max
      return quantized_data
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import math
  from transform.base_converter import DeviceType
label_desc: Use image node_id 11 for calling a global function with example usage: quantize_bias_for_hexagon(data) and returns: quantized_data