code: def test_interpolation_gradient():
      """Correctness of gradients is assumed. We compute them
      and check they exist.
      """
      tp = _QuadraticPlusSinProblemND()
      (query_points, _, train_points, train_values) = tp.get_problem(
          optimizable=True
      )
  
      regularization = 0.001
      for interpolation_order in (1, 2, 3, 4):
          with tf.GradientTape() as g:
              interpolator = interpolate_spline(
                  train_points,
                  train_values,
                  query_points,
                  interpolation_order,
                  regularization,
              )
  
          gradients = g.gradient(interpolator, train_points).numpy()
          assert np.sum(np.abs(gradients)) != 0
  
file_path: addons/tensorflow_addons/image/tests/interpolate_spline_test.py
imports: import numpy
  import pytest
  from scipy import interpolate
  import tensorflow
  from tensorflow_addons.image import interpolate_spline
label_desc: Use image node_id 6 for calling a global function with example usage: test_interpolation_gradient() without return types