class_docstr: Computes Kendall's Tau-b Rank Correlation Coefficient.
  
  Usage:
  >>> actuals = tf.constant([12, 2, 1, 12, 2], dtype=tf.int32)
  >>> preds = tf.constant([1, 4, 7, 1, 0], dtype=tf.int32)
  >>> m = tfa.metrics.KendallsTauB(0, 13, 0, 8)
  >>> m.update_state(actuals, preds)
  >>> m.result().numpy()
  -0.47140455
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code: def result(self):
      p, q, t, u = self._compute_variables()
      return (p - q) / tf.math.sqrt((p + q + t) * (p + q + u))
  
imports: from abc import abstractmethod
  import numpy
  import tensorflow
  from tensorflow.keras import backend
  from tensorflow.keras.metrics import Metric
  from tensorflow_addons.utils.types import AcceptableDTypes
  from typeguard import typechecked
label_desc: Use image node_id 1 for calling the KendallsTauB obj's underlying member method code with example usage: obj.result() and returns: unknown