code: def testZipfCdfMultidimensional_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([[2.0, 3.0, 4.0, 5.0, 6.0, 7.0]], dtype=np.float32).T
  
      dist = zipf.Zipf(power=power, validate_args=True)
      log_cdf = dist.log_cdf(x)
      self.assertEqual((6, 3), log_cdf.shape)
      self.assertAllClose(
          self.evaluate(log_cdf), stats.zipf.logcdf(x, power_v)
      )
  
      cdf = dist.cdf(x)
      self.assertEqual((6, 3), cdf.shape)
      self.assertAllClose(
          self.evaluate(cdf), stats.zipf.cdf(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 19 for calling the ZipfTest obj's underlying member method code with example usage: obj.testZipfCdfMultidimensional_IntegerArgs() without return types