code: def testZipfCdfMultidimensional_NonIntegerArgs(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([[2.3, 3.5, 4.1, 5.5, 6.8, 7.9]], dtype=np.float32).T
      floor_x = np.floor(x)
      ceil_x = np.ceil(x)
  
      dist = zipf.Zipf(power=power, validate_args=True)
      log_cdf = dist.log_cdf(x)
      self.assertEqual((6, 3), log_cdf.shape)
      self.assertAllBetween(
          self.evaluate(log_cdf),
          stats.zipf.logcdf(floor_x, power_v),
          stats.zipf.logcdf(ceil_x, power_v),
      )
  
      cdf = dist.cdf(x)
      self.assertEqual((6, 3), cdf.shape)
      self.assertAllBetween(
          self.evaluate(cdf),
          stats.zipf.cdf(floor_x, power_v),
          stats.zipf.cdf(ceil_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 20 for calling the ZipfTest obj's underlying member method code with example usage: obj.testZipfCdfMultidimensional_NonIntegerArgs() without return types