code: def testPoissonMultipleMode(self):
      lam_v = np.array(
          [1.0, 3.0, 2.0, 4.0, 5.0, 10.0], dtype=np.float32
      )
      poisson = self._make_poisson(rate=lam_v)
      # For the case where lam is an integer, the modes are: lam and lam - 1.
      # In this case, we get back the larger of the two modes.
      self.assertEqual((6,), poisson.mode().shape)
      self.assertAllClose(lam_v, self.evaluate(poisson.mode()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 19 for calling the PoissonTest obj's underlying member method code with example usage: obj.testPoissonMultipleMode() without return types