code: def testOneDimension(self, dtype):
      testee_lkj = cholesky_lkj.CholeskyLKJ(
          dimension=1,
          concentration=dtype([1.0, 4.0]),
          validate_args=True,
      )
      results = testee_lkj.sample(
          sample_shape=[4, 3], seed=test_util.test_seed()
      )
      self.assertEqual(results.shape, [4, 3, 2, 1, 1])
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import cholesky_outer_product
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import square
  from tensorflow_probability.python.distributions import cholesky_lkj
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the CholeskyLKJTest obj's underlying member method code with example usage: obj.testOneDimension(dtype) without return types