code: def testSkellamSampleMultidimensionalVariance(self):
      rate1 = self.dtype([2.0, 3.0, 4.0, 5.0, 6.0])
      rate2 = self.dtype([7.1, 3.2, 10.0, 9.0])[..., np.newaxis]
      dist = self._make_skellam(rate1=rate1, rate2=rate2)
      n = int(1e5)
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      self.assertEqual(samples.shape, (n, 4, 5))
      self.assertEqual(sample_values.shape, (n, 4, 5))
  
      self.assertAllClose(
          sample_values.var(axis=0),
          stats.skellam.var(rate1, rate2),
          rtol=0.03,
          atol=0,
      )
  
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 14 for calling the _SkellamTest obj's underlying member method code with example usage: obj.testSkellamSampleMultidimensionalVariance() without return types