code: def test_bijector_shapes(self):
      d = sample.Sample(uniform.Uniform(tf.zeros([5]), 1.0), 2)
      b = d.experimental_default_event_space_bijector()
      self.assertEqual((2,), d.event_shape)
      self.assertEqual((2,), b.inverse_event_shape((2,)))
      self.assertEqual((2,), b.forward_event_shape((2,)))
      self.assertEqual((5, 2), b.forward_event_shape((5, 2)))
      self.assertEqual((5, 2), b.inverse_event_shape((5, 2)))
      self.assertEqual((3, 5, 2), b.inverse_event_shape((3, 5, 2)))
      self.assertEqual((3, 5, 2), b.forward_event_shape((3, 5, 2)))
  
      d = sample.Sample(
          cholesky_lkj.CholeskyLKJ(4, concentration=tf.ones([5])), 2
      )
      b = d.experimental_default_event_space_bijector()
      self.assertEqual((2, 4, 4), d.event_shape)
      dim = (4 * 3) // 2
      self.assertEqual((5, 2, dim), b.inverse_event_shape((5, 2, 4, 4)))
      self.assertEqual((5, 2, 4, 4), b.forward_event_shape((5, 2, dim)))
      self.assertEqual(
          (3, 5, 2, dim), b.inverse_event_shape((3, 5, 2, 4, 4))
      )
      self.assertEqual(
          (3, 5, 2, 4, 4), b.forward_event_shape((3, 5, 2, dim))
      )
  
imports: import functools
  import os
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_tril
  from tensorflow_probability.python.distributions import cholesky_lkj
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 15 for calling the SampleDistributionTest obj's underlying member method code with example usage: obj.test_bijector_shapes() without return types