code: def testValuesAreCorrect(self, feature_ndims, dims):
      amplitude = 5.0
      length_scale = 0.2
  
      np.random.seed(42)
      k = parabolic.Parabolic(amplitude, length_scale, feature_ndims)
      shape = [dims] * feature_ndims
      for _ in range(5):
          x = np.random.uniform(-1, 1, size=shape).astype(np.float32)
          y = np.random.uniform(-1, 1, size=shape).astype(np.float32)
          self.assertAllClose(
              amplitude
              * 0.75
              * np.maximum(
                  0.0, 1 - np.sum((x - y) ** 2) / length_scale**2
              ),
              self.evaluate(k.apply(x, y)),
          )
  
file_path: probability/tensorflow_probability/python/math/psd_kernels/parabolic_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import parabolic
label_desc: Use image node_id 2 for calling the ParabolicTest obj's underlying member method code with example usage: obj.testValuesAreCorrect(feature_ndims, dims) without return types