code: def _calibrate_quantized_sym(qsym, th_dict):
      
      if th_dict is None or len(th_dict) == 0:
          return qsym
      num_layer_outputs = len(th_dict)
      layer_output_names = []
      min_vals = []
      max_vals = []
      for k, v in th_dict.items():
          layer_output_names.append(k)
          min_vals.append(v[0])
          max_vals.append(v[1])
  
      calibrated_sym = SymbolHandle()
      check_call(_LIB.MXSetCalibTableToQuantizedSymbol(qsym.handle,
                                                       mx_uint(num_layer_outputs),
                                                       c_str_array(layer_output_names),
                                                       c_array(ctypes.c_float, min_vals),
                                                       c_array(ctypes.c_float, max_vals),
                                                       ctypes.byref(calibrated_sym)))
      return Symbol(calibrated_sym)
docs: Given a dictionary containing the thresholds for quantizing the layers,
      set the thresholds into the quantized symbol as the params of requantize operators.