code: def testWarningsDefault(self):
      with warnings.catch_warnings(record=True) as triggered:
          kernel = TestTransitionKernel()
          sample_chain(
              num_results=2,
              current_state=0,
              kernel=kernel,
              seed=test_util.test_seed(),
          )
      self.assertTrue(
          any(
              "Tracing all kernel results by default is deprecated"
              in str(warning.message)
              for warning in triggered
          )
      )
  
imports: import collections
  import warnings
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import pad
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_auto_batched
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import multinomial
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.experimental.mcmc import diagonal_mass_matrix_adaptation
  from tensorflow_probability.python.experimental.mcmc import preconditioned_hmc
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import hmc
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc import nuts
  from tensorflow_probability.python.mcmc import random_walk_metropolis
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
  from tensorflow_probability.python.mcmc import transformed_kernel
  from tensorflow_probability.python.mcmc.sample import sample_chain
  from tensorflow_probability.python.random.random_ops import rayleigh
label_desc: Use image node_id 10 for calling the SampleChainTest obj's underlying member method code with example usage: obj.testWarningsDefault() without return types