code: def testGEVStd(self):
      loc = np.array([2.0], dtype=self._dtype)
      scale = np.array([1.5], dtype=self._dtype)
      conc = np.array([-0.9, 0.0], dtype=self._dtype)
      gev_dist = stats.genextreme(-conc, loc=loc, scale=scale)
  
      dist = gev.GeneralizedExtremeValue(
          loc=self.make_tensor(loc),
          scale=self.make_tensor(scale),
          concentration=self.make_tensor(conc),
          validate_args=True,
      )
  
      self.assertAllClose(self.evaluate(dist.stddev()), gev_dist.std())
  
      conc_with_inf_std = np.array([1.5], dtype=self._dtype)
      gev_with_inf_std = gev.GeneralizedExtremeValue(
          loc=self.make_tensor(loc),
          scale=self.make_tensor(scale),
          concentration=self.make_tensor(conc_with_inf_std),
          validate_args=True,
      )
      self.assertAllClose(
          self.evaluate(gev_with_inf_std.stddev()), [np.inf]
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gev
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the _GEVTest obj's underlying member method code with example usage: obj.testGEVStd() without return types