code: def testZipfLogPmf_IntegerArgs(self):
      batch_size = 9
      power = tf.constant([3.0] * batch_size)
      power_v = 3.0
      x = np.array(
          [-3.0, -0.0, 0.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0],
          dtype=np.float32,
      )
      dist = zipf.Zipf(power=power, validate_args=False)
      log_pmf = dist.log_prob(x)
      self.assertEqual((batch_size,), log_pmf.shape)
      self.assertAllClose(
          self.evaluate(log_pmf), stats.zipf.logpmf(x, power_v)
      )
  
      pmf = dist.prob(x)
      self.assertEqual((batch_size,), 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 10 for calling the ZipfTest obj's underlying member method code with example usage: obj.testZipfLogPmf_IntegerArgs() without return types