title: tf.keras.metrics.SpecificityAtSensitivity num_thresholds interpretation
body: <p>I'm trying to get my head around <a href="https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/metrics/SensitivityAtSpecificity" rel="nofollow noreferrer">tf.keras.metrics.SensitivityAtSpecificity</a>. I'm fine with the concept of sensity and specificity in isolation, but I'm unsure how the two are related in this single metric.</p>
  
  <p>More specifically, I'm unsure how to interpret the <code>num_thresholds</code> argument. The example in documentation has <code>num_thresholds=1</code>. Setting <code>num_thresholds</code> greater than 1 with the same input data seems to always return a metric value of 1.0.</p>
  
  <pre class="lang-py prettyprint-override"><code>def print_metric_value(num_thresholds):
      # other values based on docs example
      m = tf.keras.metrics.SensitivityAtSpecificity(
          0.4, num_thresholds=num_thresholds)
      m.update_state([0, 0, 1, 1], [0, 0.5, 0.3, 0.9])
      print('Result with num_thresholds = %d: %.1f' %
            (num_thresholds, m.result().numpy()))
  
  print_metric_value(1)    # 0.5 - same as docs
  print_metric_value(2)    # 1.0
  print_metric_value(200)  # 1.0
  </code></pre>