code: def testPoissonMean(self):
      lam_v = np.array([1.0, 3.0, 2.5], dtype=np.float32)
      poisson = self._make_poisson(rate=lam_v)
      self.assertEqual(poisson.mean().shape, (3,))
      self.assertAllClose(
          self.evaluate(poisson.mean()), stats.poisson.mean(lam_v)
      )
      self.assertAllClose(self.evaluate(poisson.mean()), lam_v)
  
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 15 for calling the PoissonTest obj's underlying member method code with example usage: obj.testPoissonMean() without return types