def testFPropEvalMode(self):
    with self.session(), self.SetEval(True):
      tf.random.set_seed(_TF_RANDOM_SEED)
      p = self._testParams()
      mdl = p.Instantiate()
      mdl.FPropDefaultTheta()
      loss = mdl.loss
      logp = mdl.eval_metrics['log_pplx'][0]
      self.evaluate(tf.global_variables_initializer())
      vals = []
      for _ in range(5):
        vals += [self.evaluate((loss, logp))]
      print('actual vals = %s' % np.array_repr(np.array(vals)))
      self.assertAllClose(vals, [[226.91527, 10.373269], [243.76906, 10.373152],
                                 [260.62787, 10.373248], [200.98814, 10.373582],
                                 [272.297, 10.373219]])