code: def test_zero_sized_event(self):
      tlp_fn = lambda x, y: x[:, 0] + tf.pad(y, [[0, 0], [0, 1]])[:, 0]
      kernel = nuts.NoUTurnSampler(tlp_fn, step_size=0.1)
      xy = [tf.ones([1, 1]), tf.ones([1, 0])]
      results = kernel.bootstrap_results(xy)
      self.evaluate(
          kernel.one_step(xy, results, seed=test_util.test_seed())[0]
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import half_normal
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import sigmoid_beta
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import distribute_test_lib
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.mcmc import diagnostic
  from tensorflow_probability.python.mcmc import dual_averaging_step_size_adaptation
  from tensorflow_probability.python.mcmc import nuts
  from tensorflow_probability.python.mcmc import sample
  from tensorflow_probability.python.mcmc import transformed_kernel
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 15 for calling the NutsTest obj's underlying member method code with example usage: obj.test_zero_sized_event() without return types