docstr: Tests the Jacobian for random inputs.
docstr_tok: ["Tests","the","Jacobian","for","random","inputs","."]
code: def test_split_jacobian_random(self):
      """Tests the Jacobian for random inputs."""
      split = lambda image: pyramid.split(image, num_levels=_NUM_LEVELS)
      tensor_shape = np.random.randint(1, 5, size=4).tolist()
      image_random_init = np.random.uniform(size=tensor_shape)
  
      for level in range(
          _NUM_LEVELS
      ):  # pylint: disable=unused-variable
          self.assert_jacobian_is_correct_fn(
              lambda x, level=level: split(x)[level],
              [image_random_init],
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  from tensorflow_graphics.image import pyramid
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 14 for calling the PyramidTest obj's underlying member method code with example usage: obj.test_split_jacobian_random() without return types