code: def testOneOfCholeskyAndMarginalFn(self):
      with self.assertRaises(ValueError):
          index_points = np.array([3.0, 4.0, 5.0])[..., np.newaxis]
          gaussian_process.GaussianProcess(
              kernel=psd_kernels.ExponentiatedQuadratic(),
              index_points=index_points,
              marginal_fn=lambda x: x,
              cholesky_fn=lambda x: x,
              validate_args=True,
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gaussian_process
  from tensorflow_probability.python.distributions import gaussian_process_regression_model
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import psd_kernels
  from tensorflow_probability.python.math.psd_kernels.internal import test_util
label_desc: Use image node_id 6 for calling the _GaussianProcessTest obj's underlying member method code with example usage: obj.testOneOfCholeskyAndMarginalFn() without return types