code: def testSampleConsistentLogProbInterval5(self, dtype):
      # The hardcoded volume boundaries are (5e-7)-confidence intervals
      # of a rejection sampling run.  Ergo, I only have 5e-7 probability
      # mass left for the false fail rate of the test so the aggregate
      # false fail probability is 1e-6.
      concentrations = [
          1.00,
          1.30,
          1.50,
          1.70,
          1.90,
          2.00,
          2.10,
          2.50,
          3.00,
      ]
      det_bounds = [
          0.01,
          0.20,
          0.20,
          0.25,
          0.30,
          0.30,
          0.30,
          0.35,
          0.40,
      ]
  
      for input_output_cholesky in [True, False]:
          self._testSampleConsistentLogProbInterval(
              concentrations,
              det_bounds,
              5,
              dtype=dtype,
              input_output_cholesky=input_output_cholesky,
              false_fail_rate=5e-7,
              target_discrepancy=0.41,
              seed=test_util.test_seed(),
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 8 for calling the LKJTest obj's underlying member method code with example usage: obj.testSampleConsistentLogProbInterval5(dtype) without return types