class_docstr: More careful tests that sampling/preconditioning is actually working.
class_docstr_tok: ["More","careful","tests","that","sampling\/preconditioning","is","actually","working","."]
code: def test_correctness_with_2d_mvn_tril(self, precondition_scheme):
      # Low dimensional test to help people who want to step through and debug.
      target_mvn = mvn_tril.MultivariateNormalTriL(
          loc=tf.constant([0.0, 0.0]),
          scale_tril=[[1.0, 0.0], [0.5, 2.0]],
      )
      self._check_correctness_of_moments_and_preconditioning(
          target_mvn,
          # Lots of results, to test tight tolerance.
          # We're using a small dims here, so this isn't a big deal.
          num_results=5000,
          precondition_scheme=precondition_scheme,
          # We're in such low dimensions that we don't expect asymptotics to work.
          check_step_size_asymptotics=False,
      )
  
imports: import collections
  from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import reshape
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_linear_operator
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.experimental.distributions import mvn_precision_factor_linop
  from tensorflow_probability.python.experimental.mcmc import preconditioned_hmc
  from tensorflow_probability.python.internal import auto_composite_tensor
  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.internal import unnest
  from tensorflow_probability.python.mcmc import diagnostic
  from tensorflow_probability.python.mcmc import dual_averaging_step_size_adaptation
  from tensorflow_probability.python.mcmc import sample
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
  from tensorflow_probability.python.mcmc import transformed_kernel
  from tensorflow_probability.python.mcmc.internal import leapfrog_integrator
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 4 for calling the PreconditionedHMCCorrectnessTest obj's underlying member method code with example usage: obj.test_correctness_with_2d_mvn_tril(precondition_scheme) without return types