code: def test_burn_in(self):
      kernel = test_fixtures.TestTransitionKernel()
      result = sample_chain_with_burnin(
          num_results=2,
          current_state=0.0,
          kernel=kernel,
          num_burnin_steps=1,
          seed=test_util.test_seed(),
      )
      samples = result.trace
      kernel_results = result.final_kernel_results
  
      self.assertAllClose([2], tensorshape_util.as_list(samples.shape))
  
      samples, kernel_results = self.evaluate([samples, kernel_results])
      self.assertAllClose([2, 3], samples)
      self.assertAllClose(3, kernel_results.counter_1)
      self.assertAllClose(6, kernel_results.counter_2)
  
imports: import collections
  import warnings
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.mcmc import covariance_reducer
  from tensorflow_probability.python.experimental.mcmc import expectations_reducer
  from tensorflow_probability.python.experimental.mcmc.internal import test_fixtures
  from tensorflow_probability.python.experimental.mcmc.sample_fold import sample_chain_with_burnin
  from tensorflow_probability.python.experimental.mcmc.sample_fold import sample_fold
  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
label_desc: Use image node_id 3 for calling the SampleChainTest obj's underlying member method code with example usage: obj.test_burn_in() without return types