title: PR-curves plugin (pr_curve_raw_data_op) not plotting completely when using metrics in Estimator API
body: <p>TensorBoard version (from pip package, also printed out when running <code>tensorboard</code>): 1.12.0
  TensorFlow version if different from TensorBoard: 1.12.0
  OS Platform and version (e.g., Linux Ubuntu 16.04): Arch Linux
  Python version (e.g. 2.7, 3.5): 3.6.5</p>
  
  <p>Hi there,</p>
  
  <p>I am trying to plot PR curves using <code>pr_curve_raw_data_op</code> function with precisions, recalls and other metrics which I have calculated before hand, but I'm getting wrong results in chart. I am using Estimator API, meaning I create my own dictionary which contains tuple of <code>tf.Tensor</code> and <code>tf.Operation</code> instances which are then forwarded to estimator for dumping summaries. </p>
  
  <p>I evaluate multiple steps during each checkpoint save, which means that I accumulate precision and recall through multiple steps (but I don't use pr_curves plugin to do so, I use custom written metrics), and all I want from the plugin is to dump the PR curve into the tensorboard. Here is the part of the code which serves for storing the <code>pr-curves</code> summary tensor into the metrics dictionary:</p>
  
  <pre><code>metrics_dict['pr_curve/CLASS_{}'.format(cls_index)] = (
      summary.raw_data_op(
          'pr_curve/CLASS_{}'.format(cls_index),
          true_positive_counts=tps,
          false_positive_counts=fps,
          true_negative_counts=tns,
          false_negative_counts=fns,
          precision=precisions,
          recall=recalls,
          num_thresholds=11
      ),
      tf.no_op()
  )
  </code></pre>
  
  <p>I also tried to dump precisions as text summary just to be sure that output printed in terminal is the same that is being stored in summaries, and it was I dumped those summaries using this code:</p>
  
  <pre><code>metrics_dict['precisions_text/CLASS_{}'.format(cls_index)] = (
      tf.summary.text(name="aa",
                      tensor=tf.as_string(precs)),
      tf.no_op()
  )
  </code></pre>
  
  <p>In the end I will attach couple of screenshots. First one shows precisions dumped to text summary and their values ( I only showed first 6 values, as for the remaining 4 values are 0.0):</p>
  
  <p><img src="https://user-images.githubusercontent.com/14930845/48550395-e5254000-e8d2-11e8-97f7-ce0c06c16df3.png" alt="image"></p>
  
  <p>Second screenshot contains those same precisions for same class and step plotted on PR curve:</p>
  
  <p><img src="https://user-images.githubusercontent.com/14930845/48552012-7bf3fb80-e8d7-11e8-9db6-19ff31780fcd.png" alt="image"></p>
  
  <p>You can see that there is only first point on the plot, with precision being 1.0 for 0.0 recall. That occurs in several more cases, along with chart cutting off at last point (for example, I have precision values from recalls 0.0 up to 0.6, but chart plots only up to 0.5).</p>