code: def testRejection4D(self):
      num_samples = int(
          1e5
      )  # Chosen for a small min detectable discrepancy
      det_bounds = np.array([0.0], dtype=np.float32)
      exact_volumes = [four_by_four_volume()]
      (
          rej_weights,
          rej_proposal_volume,
      ) = corr.correlation_matrix_volume_rejection_samples(
          det_bounds, 4, [num_samples, 1], dtype=np.float32, seed=45
      )
      # shape of rej_weights: [num_samples, 1, 4, 4]
      chk1 = st.assert_true_mean_equal_by_dkwm(
          rej_weights,
          low=0.0,
          high=rej_proposal_volume,
          expected=exact_volumes,
          false_fail_rate=1e-6,
      )
      chk2 = tf.debugging.assert_less(
          st.min_discrepancy_of_true_means_detectable_by_dkwm(
              num_samples,
              low=0.0,
              high=rej_proposal_volume,
              false_fail_rate=1e-6,
              false_pass_rate=1e-6,
          ),
          # Going for about a 10% relative error
          1.1,
      )
      with tf.control_dependencies([chk1, chk2]):
          rej_weights = tf.identity(rej_weights)
      self.evaluate(rej_weights)
  
file_path: probability/tensorflow_probability/python/distributions/internal/correlation_matrix_volumes_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions.internal import correlation_matrix_volumes_lib
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the CorrelationMatrixVolumesTest obj's underlying member method code with example usage: obj.testRejection4D() without return types