code: def test_chol_symmetric_increment_cases(self, increment):
      symmetric_matrix = np.float32(
          [[1.5, -3.75, 2.5], [-3.75, 15.0, -8.75], [2.5, -8.75, 7.5]]
      )
      chol = np.linalg.cholesky(symmetric_matrix)
      expected_result = _naive_symmetric_increment(
          symmetric_matrix, 0, increment
      )
      chol_result = spike_and_slab._symmetric_increment_chol(
          chol, 0, increment
      )
      result = tf.matmul(chol_result, chol_result, adjoint_b=True)
      self.assertAllClose(expected_result, result)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.distributions import normal_conjugate_posteriors
  from tensorflow_probability.python.experimental.sts_gibbs import spike_and_slab
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 2 for calling the SpikeAndSlabTest obj's underlying member method code with example usage: obj.test_chol_symmetric_increment_cases(increment) without return types