code: def testDppMarginalKernel(self):
      n_points = 20
      true_kernel, eigvals, eigvecs = kernel_over_unit_square(
          n_points, dtype=self.param_dtype
      )
      dpp = dpp_lib.DeterminantalPointProcess(eigvals, eigvecs)
      marginal_kernel = tf.matmul(
          true_kernel, tf.linalg.inv(true_kernel + np.eye(n_points))
      )
      self.assertAllClose(
          marginal_kernel - dpp.marginal_kernel(),
          tf.zeros([n_points, n_points]),
          atol=1e-5,
      )
  
imports: import contextlib
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import dpp
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import exponentiated_quadratic
label_desc: Use image node_id 10 for calling the _DppTest obj's underlying member method code with example usage: obj.testDppMarginalKernel() without return types