code: def _test_sample_and_log_prob(self, dist_name, dist):
      seed = test_util.test_seed(sampler_type="stateless")
  
      num_samples = 3
      sample = self.evaluate(
          tf.function(dist.sample, jit_compile=True)(
              num_samples, seed=seed
          )
      )
      hp.note(
          "Trying distribution {}".format(
              self.evaluate_dict(dist.parameters)
          )
      )
      hp.note("Drew samples {}".format(sample))
  
      xla_lp = self.evaluate(
          tf.function(dist.log_prob, jit_compile=True)(
              tf.convert_to_tensor(sample)
          )
      )
      with tfp_hps.no_tf_rank_errors():
          graph_lp = self.evaluate(dist.log_prob(sample))
      self.assertAllClose(
          xla_lp,
          graph_lp,
          atol=XLA_LOGPROB_ATOL[dist_name],
          rtol=XLA_LOGPROB_RTOL[dist_name],
      )
  
imports: import collections
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python import distributions
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the DistributionXLATest obj's underlying member method code with example usage: obj._test_sample_and_log_prob(dist_name, dist) without return types