code: def testZipfLogPmfMultidimensional_IntegerArgs(self):
      batch_size = 6
      power = tf.constant([[2.0, 4.0, 5.0]] * batch_size)
      power_v = [2.0, 4.0, 5.0]
      x = np.array([[2.1, 3.5, 4.9, 5.0, 6.6, 7.0]], dtype=np.int32).T
  
      dist = zipf.Zipf(power=power, validate_args=True)
      log_pmf = dist.log_prob(x)
      self.assertEqual((6, 3), log_pmf.shape)
      self.assertAllClose(
          self.evaluate(log_pmf), stats.zipf.logpmf(x, power_v)
      )
  
      pmf = dist.prob(x)
      self.assertEqual((6, 3), pmf.shape)
      self.assertAllClose(
          self.evaluate(pmf), stats.zipf.pmf(x, power_v)
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import zipf
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 13 for calling the ZipfTest obj's underlying member method code with example usage: obj.testZipfLogPmfMultidimensional_IntegerArgs() without return types