Summary_statistics_pseoudocode.py

def setup_summary_statistics(self):
  # Create a placeholder for the summary statistics
  with tf.name_scope("accuracy"):
    
  # Compute the edit (Levenshtein) distance of the top path
  distance = tf.edit_distance(tf.cast(self.decoded[0], tf.int32), self.targets)

  # Compute the label error rate (accuracy)
  self.ler = tf.reduce_mean(distance, name='label_error_rate')
  self.ler_placeholder = tf.placeholder(dtype=tf.float32, shape=[])
  self.train_ler_op = tf.summary.scalar("train_label_error_rate", self.ler_placeholder)
  self.dev_ler_op = tf.summary.scalar("validation_label_error_rate", self.ler_placeholder)
  self.test_ler_op = tf.summary.scalar("test_label_error_rate", self.ler_placeholder)