code: def _get_add_scalar_output_quant_param(
      input_scale, input_zero_point, scalar
  ):
      """
      Determine the output scale and zp of quantized::add_scalar op
      This is used for mobilenet v3
      Refer to aten/src/ATen/native/quantized/cpu/qadd.cpp
      The names of variables are the same as torch impl
      """
      q_min = 0
      q_max = 255
      s = input_scale
      z = input_zero_point
      c = scalar
      c_q = round(c / s)
  
      if q_min > z - c_q:
          s_prime = (
              (float(q_max) - (z - c_q)) / (float(q_max) - q_min) * s
          )
          z_prime = q_min
      elif q_max < z - c_q:
          s_prime = (
              (float(z - c_q) - q_min) / (float(q_max) - q_min) * s
          )
          z_prime = q_max
      else:
          s_prime = s
          z_prime = z - c_q
  
      return s_prime, z_prime
  
imports: import numpy
  import tvm
  from tvm import relay
  from tvm.relay import expr
  from tvm.relay import op
  from tvm.relay.frontend.common import infer_shape
  from .common import logger
  from .pytorch_utils import is_version_greater_than
label_desc: Use image node_id 8 for calling a global function with example usage: _get_add_scalar_output_quant_param(input_scale, input_zero_point, scalar) and returns: s_prime,  z_prime