code: def testPoissonCdfMultidimensional(self):
      batch_size = 6
      lam = tf.constant([[2.0, 4.0, 5.0]] * batch_size)
      lam_v = np.array([2.0, 4.0, 5.0], dtype=np.float32)
      x = np.array([[2.0, 3.0, 4.0, 5.0, 6.0, 7.0]], dtype=np.float32).T
  
      poisson = self._make_poisson(
          rate=lam, force_probs_to_zero_outside_support=True
      )
      log_cdf = poisson.log_cdf(x)
      self.assertEqual(log_cdf.shape, (6, 3))
      self.assertAllClose(
          self.evaluate(log_cdf), stats.poisson.logcdf(x, lam_v)
      )
  
      cdf = poisson.cdf(x)
      self.assertEqual(cdf.shape, (6, 3))
      self.assertAllClose(
          self.evaluate(cdf), stats.poisson.cdf(x, 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 14 for calling the PoissonTest obj's underlying member method code with example usage: obj.testPoissonCdfMultidimensional() without return types