code: def _accuracy(label_file, pred_file):
      """Compute accuracy, each line contains a label."""
  
      with codecs.getreader("utf-8")(
          tf.gfile.GFile(label_file, "rb")
      ) as label_fh:
          with codecs.getreader("utf-8")(
              tf.gfile.GFile(pred_file, "rb")
          ) as pred_fh:
              count = 0.0
              match = 0.0
              for label in label_fh:
                  label = label.strip()
                  pred = pred_fh.readline().strip()
                  if label == pred:
                      match += 1
                  count += 1
      return 100 * match / count
  
file_path: nlp-architect/examples/sparse_gnmt/gnmt/utils/evaluation_utils.py
imports: import codecs
  import os
  import re
  import subprocess
  import tensorflow
  from .None import rouge, bleu
label_desc: Use image node_id 5 for calling a global function with example usage: _accuracy(label_file, pred_file) and returns: unknown