code: def testGEVMode(self):
      loc = np.array([2.0], dtype=self._dtype)
      scale = np.array([1.5], dtype=self._dtype)
      conc = np.array([-0.9, 0.0, 1.5], dtype=self._dtype)
  
      dist = gev.GeneralizedExtremeValue(
          loc=self.make_tensor(loc),
          scale=self.make_tensor(scale),
          concentration=self.make_tensor(conc),
          validate_args=True,
      )
  
      np_mode_z = np.where(
          conc == 0.0, 0.0, ((conc + 1) ** (-conc) - 1.0) / conc
      )
      np_mode = loc + np_mode_z * scale
      self.assertAllClose(self.evaluate(dist.mode()), np_mode)
  
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 11 for calling the _GEVTest obj's underlying member method code with example usage: obj.testGEVMode() without return types