code: def encode_file(
      self,
      path,
      ordered=False,
      verbose=False,
      add_eos=True,
      add_double_eos=False,
  ):
      if verbose:
          print("encoding file {} ...".format(path))
      assert os.path.exists(path)
      encoded = []
      with open(path, "r", encoding="utf-8") as f:
          for idx, line in enumerate(f):
              if verbose and idx > 0 and idx % 500000 == 0:
                  print("    line {}".format(idx))
              symbols = self.tokenize(
                  line, add_eos=add_eos, add_double_eos=add_double_eos
              )
              encoded.append(self.convert_to_tensor(symbols))
  
      if ordered:
          encoded = torch.cat(encoded)
  
      return encoded
  
imports: import contextlib
  import os
  from collections import Counter
  from collections import OrderedDict
  import torch
  from src.utils.distributed import sync_workers
label_desc: Use image node_id 7 for calling the Vocab obj's underlying member method code with example usage: obj.encode_file(path, ordered, verbose, add_eos, add_double_eos) and returns: encoded