code: def testRetryingCholeskyFloat64(self):
      matrix = tf.convert_to_tensor(
          [[2.0, 2.0, 0.0], [2.0, 2.0, 2e-5], [0.0, 2e-5, 0.5]],
          dtype=tf.float64,
      )
  
      expected_shift = tf.eye(3, dtype=tf.float64) * 1e-9
      expected, expected_grad, expected_grad_of_grad = self.evaluate(
          _value_and_grads(
              lambda x: tf.linalg.cholesky(x + expected_shift), matrix
          )
      )
  
      (res, shift), grad, grad_of_grad = self.evaluate(
          _value_and_grads(
              marginal_fns.retrying_cholesky, matrix, has_aux=True
          )
      )
      self.assertAllEqual(expected, res)
      self.assertAllClose(expected_shift[..., 0, 0], shift)
      self.assertAllEqual(expected_grad, grad)
      self.assertAllEqual(expected_grad_of_grad, grad_of_grad)
  
      expected, expected_grad, expected_grad_of_grad = self.evaluate(
          _value_and_grads(
              lambda x: tf.linalg.cholesky(x + expected_shift), matrix
          )
      )
  
file_path: probability/tensorflow_probability/python/experimental/distributions/marginal_fns_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.distributions import marginal_fns
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 4 for calling the MarginalFnsTest obj's underlying member method code with example usage: obj.testRetryingCholeskyFloat64() without return types