title: tensorfboard embeddings hangs with "Computing PCA"
body: <p>I'm trying to display my embeddings in tensorboard. When I open embeddings tab of tensorboard I get: "Computing PCA..." and tensorboard hangs infinitely.</p>
  
  <p>Before that it does load my tensor of shape 200x128. It does find the metadata file too.</p>
  
  <p>I tried that on TF versions 0.12 and 1.1 with the same result.</p>
  
  <pre><code>features = np.zeros(shape=(num_batches*batch_size, 128), dtype=float)
  embedding_var = tf.Variable(features, name='feature_embedding')
  config = projector.ProjectorConfig()
  embedding = config.embeddings.add()
  embedding.tensor_name = 'feature_embedding'
  metadata_path = os.path.join(self.log_dir, 'metadata.tsv')
  embedding.metadata_path = metadata_path
  
  with tf.Session(config=self.config) as sess:
    tf.global_variables_initializer().run()
    restorer = tf.train.Saver()
    restorer.restore(sess, self.pretrained_model_path)
  
    with open(metadata_path, 'w') as f:
  
      for step in range(num_batches):
        batch_images, batch_labels = data.next()
  
          for label in batch_labels:
            f.write('%s\n' % label)
  
          feed_dict = {model.images: batch_images}
          features[step*batch_size : (step+1)*batch_size, :] = \ 
                      sess.run(model.features, feed_dict)
  
    sess.run(embedding_var.initializer)
    projector.visualize_embeddings(tf.summary.FileWriter(self.log_dir), config)
  </code></pre>