docstr: Tests that AIS yields reasonable estimates of normalizers.
docstr_tok: ["Tests","that","AIS","yields","reasonable","estimates","of","normalizers","."]
code: def _ais_gets_correct_log_normalizer_wrapper(
      self, independent_chain_ndims, use_transformed_kernel=False
  ):
      """Tests that AIS yields reasonable estimates of normalizers."""
      initial_draws = np.random.normal(size=[30, 2, 1])
      x_ph = tf1.placeholder_with_default(
          np.float32(initial_draws),
          shape=initial_draws.shape,
          name="x_ph",
      )
      self._ais_gets_correct_log_normalizer(
          x_ph,
          independent_chain_ndims,
          use_transformed_kernel=use_transformed_kernel,
      )
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import hmc
  from tensorflow_probability.python.mcmc import sample_annealed_importance
  from tensorflow_probability.python.mcmc import transformed_kernel
label_desc: Use image node_id 4 for calling the SampleAnnealedImportanceTest obj's underlying member method code with example usage: obj._ais_gets_correct_log_normalizer_wrapper(independent_chain_ndims, use_transformed_kernel) without return types