code: def testSampleElementaryDppShape(
      self, eigvals_shape, eigvecs_shape, n_samples, expected
  ):
      eigvals = tf.ones(eigvals_shape, dtype=self.param_dtype)
      eigvecs = tf.eye(
          eigvecs_shape[-1],
          batch_shape=eigvecs_shape[:-2],
          dtype=self.param_dtype,
      )
      dpp = dpp_lib.DeterminantalPointProcess(eigvals, eigvecs)
      with _capture_bernoulli_samples() as sampled_edpp_indices:
          dpp.sample(n_samples, seed=test_util.test_seed())
      self.assertLen(sampled_edpp_indices, 1)
      self.assertAllEqual(sampled_edpp_indices[0].shape, expected)
  
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 4 for calling the _DppTest obj's underlying member method code with example usage: obj.testSampleElementaryDppShape(eigvals_shape, eigvecs_shape, n_samples, expected) without return types