class_docstr: Mixin test for Matern type kernels.
  
  Subclasses must specify _kernel_type and _numpy_kernel.
code: def testValuesAreCorrectInverseLengthScale(
      self, feature_ndims, dtype, dims
  ):
      amplitude = np.array(5.0, dtype=dtype)
      inverse_length_scale = np.linspace(1.0, 20.0, 20, dtype=dtype)
  
      np.random.seed(42)
      k = self._kernel_type(
          amplitude=amplitude,
          inverse_length_scale=inverse_length_scale,
          feature_ndims=feature_ndims,
      )
      k_ls = self._kernel_type(
          amplitude=amplitude,
          length_scale=1.0 / inverse_length_scale,
          feature_ndims=feature_ndims,
      )
      shape = [dims] * feature_ndims
      x = np.random.uniform(-1, 1, size=shape).astype(dtype)
      y = np.random.uniform(-1, 1, size=shape).astype(dtype)
      self.assertAllClose(
          self.evaluate(k.apply(x, y)), self.evaluate(k_ls.apply(x, y))
      )
  
imports: from absl.testing import parameterized
  import numpy
  import scipy.special
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import matern
label_desc: Use image node_id 6 for calling the _MaternTestCase obj's underlying member method code with example usage: obj.testValuesAreCorrectInverseLengthScale(feature_ndims, dtype, dims) without return types