code: def _check_het_test(x: np.ndarray, test_name: str) -> None:
      """
      Check validity of the exogenous regressors in a heteroskedasticity test
  
      Parameters
      ----------
      x : ndarray
          The exogenous regressor array
      test_name : str
          The test name for the exception
      """
      x_max = x.max(axis=0)
      if (
          not np.any(((x_max - x.min(axis=0)) == 0) & (x_max != 0))
          or x.shape[1] < 2
      ):
          raise ValueError(
              f"{test_name} test requires exog to have at least "
              "two columns where one is a constant."
          )
  
imports: from statsmodels.compat.pandas import deprecate_kwarg
  from collections.abc import Iterable
  import numpy
  import pandas
  from scipy import stats
  from statsmodels.regression.linear_model import OLS, RegressionResultsWrapper
  from statsmodels.stats._adnorm import anderson_statistic, normal_ad
  from statsmodels.stats._lilliefors import kstest_exponential, kstest_fit, kstest_normal, lilliefors
  from statsmodels.tools.validation import array_like, bool_like, dict_like, float_like, int_like, string_like
  from statsmodels.tsa.tsatools import lagmat
label_desc: Use image node_id 10 for calling a global function with example usage: _check_het_test(x, test_name) without return types