"loc": ["body", "grant_type"],
                "msg": "Field required",
                "input": None,
            }
        ]
    }


@pytest.mark.parametrize(
    argnames=["grant_type"],
    argvalues=[
        pytest.param("incorrect", id="incorrect value"),
        pytest.param("passwordblah", id="password with suffix"),
        pytest.param("blahpassword", id="password with prefix"),

		Value:          rm.Current,
		VariableLabels: cloneMSS(rm.Labels),
	})

	if requireAvgMax {
		avgName := MetricName(fmt.Sprintf("%s_avg", name))
		avgHelp := fmt.Sprintf("%s (avg)", help)
		metrics = append(metrics, MetricV2{
			Description:    getResourceMetricDescription(subSys, avgName, avgHelp),
			Value:          math.Round(rm.Avg*100) / 100,
			VariableLabels: cloneMSS(rm.Labels),
		})

}

int TF_OperationOutputListLength(TF_Operation* oper, const char* arg_name,
                                 TF_Status* status) {
  NameRangeMap name_ranges;
  status->status =
      NameRangesForNode(oper->node, oper->node.op_def(), nullptr, &name_ranges);
  if (!status->status.ok()) return -1;
  auto iter = name_ranges.find(arg_name);
  if (iter == name_ranges.end()) {

TF_CAPI_EXPORT extern TF_DataType TF_OperationOutputType(TF_Output oper_out);
TF_CAPI_EXPORT extern int TF_OperationOutputListLength(TF_Operation* oper,
                                                       const char* arg_name,
                                                       TF_Status* status);

TF_CAPI_EXPORT extern int TF_OperationNumInputs(TF_Operation* oper);
TF_CAPI_EXPORT extern TF_DataType TF_OperationInputType(TF_Input oper_in);