code: def testSupportBijectorOutsideRange(self):
      mean_dir = np.array([[1.0, 2.0, 3.0], [-2.0, -3.0, -1.0]]).astype(
          np.float32
      )
      mean_dir /= np.linalg.norm(mean_dir, axis=-1)[:, np.newaxis]
      concentration = [[0], [0.1], [2], [40], [1000]]
      dist = power_spherical.PowerSpherical(
          mean_direction=mean_dir,
          concentration=concentration,
          validate_args=True,
      )
  
      x = mean_dir
      x[0][0] += 0.01
      with self.assertRaisesOpError("must sum to `1`"):
          self.evaluate(
              dist.experimental_default_event_space_bijector().inverse(
                  x[0]
              )
          )
  
      with self.assertRaisesOpError("must be non-negative"):
          self.evaluate(
              dist.experimental_default_event_space_bijector().inverse(
                  x[1]
              )
          )
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import power_spherical
  from tensorflow_probability.python.distributions import spherical_uniform
  from tensorflow_probability.python.distributions import von_mises_fisher
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 25 for calling the _PowerSphericalTest obj's underlying member method code with example usage: obj.testSupportBijectorOutsideRange() without return types