code: def testDryRunMode(self):
      if not tf.executing_eagerly():
          return
      _, ev_leapfrogs = self.evaluate(
          run_nuts_chain(
              event_size=3, batch_size=1, num_steps=1, dry_run=True
          )
      )
      ev_leapfrogs = ev_leapfrogs[0]
      self.assertTrue(all(ev_leapfrogs > 1))
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import scale_matvec_tril
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.mcmc import nuts_autobatching
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import sample
label_desc: Use image node_id 8 for calling the NutsTest obj's underlying member method code with example usage: obj.testDryRunMode() without return types