class_docstr: Tests correctness of the GeneralizedExtremeValue bijector.
code: def testBijector(self):
      loc = 0.3
      scale = 5.0
      concentration = np.array(
          [[[-5.5], [-20], [0.0], [1.0]]], dtype=np.float32
      )
      bijector = gev_cdf.GeneralizedExtremeValueCDF(
          loc=loc,
          scale=scale,
          concentration=concentration,
          validate_args=True,
      )
      self.assertStartsWith(bijector.name, "generalizedextremevalue")
      x = np.array([[[0.0], [-3.0], [0.0], [4.2]]], dtype=np.float32)
      # GeneralizedExtremeValue distribution
      gev_dist = stats.genextreme(-concentration, loc=loc, scale=scale)
      y = gev_dist.cdf(x).astype(np.float32)
      self.assertAllClose(y, self.evaluate(bijector.forward(x)))
      self.assertAllClose(x, self.evaluate(bijector.inverse(y)))
      self.assertAllClose(
          np.squeeze(gev_dist.logpdf(x), axis=-1),
          self.evaluate(
              bijector.forward_log_det_jacobian(x, event_ndims=1)
          ),
      )
      self.assertAllClose(
          self.evaluate(
              -bijector.inverse_log_det_jacobian(y, event_ndims=1)
          ),
          self.evaluate(
              bijector.forward_log_det_jacobian(x, event_ndims=1)
          ),
          rtol=1e-4,
          atol=0.0,
      )
  
file_path: probability/tensorflow_probability/python/bijectors/gev_cdf_test.py
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import gev_cdf
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the GeneralizedExtremeValueCDFTest obj's underlying member method code with example usage: obj.testBijector() without return types