code: def generate_golden_output(
      x_data, dequantized_x, alpha, o_scale, o_zero_point, i_zero_point
  ):
      prod = np.multiply(dequantized_x, alpha)
      prod = np.around(prod / o_scale + o_zero_point)
  
      q_min = np.iinfo(np.uint8).min
      q_max = np.iinfo(np.uint8).max
      prod = np.clip(prod, q_min, q_max)
  
      requantized = np.clip(
          np.round(dequantized_x / o_scale + o_zero_point), q_min, q_max
      )
  
      output = np.where(x_data < i_zero_point, prod, requantized)
      return output
  
imports: import tvm
  import numpy
  from tvm import relay
label_desc: Use image node_id 2 for calling a global function with example usage: generate_golden_output(x_data, dequantized_x, alpha, o_scale, o_zero_point, i_zero_point) and returns: output