code: def testSkellamMean(self):
      rate1 = np.array([1.0, 3.0, 2.5], dtype=self.dtype)
      rate2 = np.array([5.0, 7.13, 2.56, 41.0], dtype=self.dtype)[
          ..., np.newaxis
      ]
      dist = self._make_skellam(rate1=rate1, rate2=rate2)
      self.assertEqual(dist.mean().shape, (4, 3))
      self.assertAllClose(
          self.evaluate(dist.mean()), stats.skellam.mean(rate1, rate2)
      )
      self.assertAllClose(self.evaluate(dist.mean()), rate1 - rate2)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import skellam
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 8 for calling the _SkellamTest obj's underlying member method code with example usage: obj.testSkellamMean() without return types