docstr: Tests that for diagonal kernels, we select points w/ eigenvalues > 0.
docstr_tok: ["Tests","that","for","diagonal","kernels",",","we","select","points","w\/","eigenvalues",">","0","."]
code: def testSampleFromEDppDeterministic(self):
      """Tests that for diagonal kernels, we select points w/ eigenvalues > 0."""
      edpp_indices = tf.constant(
          [0, 0, 0, 1, 1, 1, 0, 1, 0, 0], dtype=tf.int32
      )
      eigvecs = tf.eye(10, dtype=self.param_dtype)
      samples = dpp_lib._sample_from_edpp(
          eigvecs, edpp_indices, seed=test_util.test_seed()
      )
      self.assertAllEqual(edpp_indices, samples)
  
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 7 for calling the _DppTest obj's underlying member method code with example usage: obj.testSampleFromEDppDeterministic() without return types