fix for tf sessions

      top_label = tf.gather(labels_tf, indice)

      # map the indices to labels

      feed_dict = {}

      with tf.Session() as sess:

        for count in range(target_len // 100 + 1):

          feed_dict[similarity_placeholder] = similarity_xs[count * 100:min((

              count + 1) * 100, target_len), :]

          # generating batch of data by slicing similarity matrix 

          # into 100*reference_dataset_length

        with tf.Session() as sess:

          fetched_values = sess.run([value, top_label], feed_dict=feed_dict)

          values.append(fetched_values[0])

          top_labels.append(fetched_values[1])