code: def _get_mul_scalar_output_quant_param(
      input_scale, input_zero_point, scalar
  ):
      """
      Determine the output scale and zp of quantized::mul_scalar op
      This is used for mobilenet v3
      Refer to aten/src/ATen/native/quantized/cpu/qmul.cpp
      The names of variables are the same as torch impl
      """
      q_min = 0
      q_max = 255
      self_scale = input_scale
      self_zero_point = input_zero_point
      other_val = scalar
  
      if other_val > 0.0:
          s_prime = other_val * self_scale
          z_prime = self_zero_point
      elif other_val == 0.0:
          s_prime = 1.0
          z_prime = 0
      else:
          s_prime = abs(other_val) * self_scale
          z_prime = q_max - (self_zero_point - q_min)
  
      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 9 for calling a global function with example usage: _get_mul_scalar_output_quant_param(input_scale, input_zero_point, scalar) and returns: s_prime,  z_prime