code: def testGEVCDF(self):
      batch_size = 6
      loc = np.array([0.0] * batch_size, dtype=self._dtype)
      scale = np.array([3.0] * batch_size, dtype=self._dtype)
      conc = np.array([2.0] * batch_size, dtype=self._dtype)
      gev_dist = stats.genextreme(-conc, loc=loc, scale=scale)
      x = np.array([2.0, 3.0, 4.0, 5.0, 6.0, 7.0], dtype=self._dtype)
  
      dist = gev.GeneralizedExtremeValue(
          loc=self.make_tensor(loc),
          scale=self.make_tensor(scale),
          concentration=self.make_tensor(conc),
          validate_args=True,
      )
  
      log_cdf = dist.log_cdf(self.make_tensor(x))
      self.assertAllClose(self.evaluate(log_cdf), gev_dist.logcdf(x))
  
      cdf = dist.cdf(self.make_tensor(x))
      self.assertAllClose(self.evaluate(cdf), gev_dist.cdf(x))
  
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 6 for calling the _GEVTest obj's underlying member method code with example usage: obj.testGEVCDF() without return types