code: def decode_lines(self, lines):
      dec_lines = []
      for line in lines:
          tokens = map(int, line.strip().split())
          dec_lines.append(self.decode(tokens))
      return ["PASS", dec_lines]
  
file_path: fairseq/examples/roberta/multiprocessing_bpe_encoder.py
imports: import argparse
  import contextlib
  import sys
  from collections import Counter
  from multiprocessing import Pool
  from fairseq.data.encoders.gpt2_bpe import get_encoder
label_desc: Use image node_id 6 for calling the MultiprocessingEncoder obj's underlying member method code with example usage: obj.decode_lines(lines) and returns: list