code: def testBackoff(self):
      matrix = np.array([[1.0, 2.0], [2.0, 1.0]])
      backoff = marginal_fns.make_backoff_cholesky(tf.convert_to_tensor)
      test = self.evaluate(backoff(matrix))
      self.assertAllClose(test, 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 2 for calling the MarginalFnsTest obj's underlying member method code with example usage: obj.testBackoff() without return types