code: def _train_path(lang, trainpref):
      return "{}{}".format(trainpref, ("." + lang) if lang else "")
  
imports: import logging
  import os
  import shutil
  import sys
  import typing
  from argparse import Namespace
  from itertools import zip_longest
  from fairseq import options, tasks, utils
  from fairseq.binarizer import AlignmentDatasetBinarizer, FileBinarizer, VocabularyDatasetBinarizer
  from fairseq.data import Dictionary
label_desc: Use image node_id 1 for calling a global function with example usage: _train_path(lang, trainpref) and returns: str