class_docstr: A loader and saver for pretrained embeddings. 
docstr: Write the vocab & values to a text file
docstr_tok: ["Write","the","vocab","&","values","to","a","text","file"]
code: def write_text(self, filename):
      """
      Write the vocab & values to a text file
      """
      with open(filename, "w") as fout:
          for i in range(len(self.vocab)):
              row = self.emb[i]
              fout.write(self.vocab[i])
              fout.write("\t")
              fout.write("\t".join(map(str, row)))
              fout.write("\n")
  
imports: import csv
  import os
  import re
  import lzma
  import logging
  import numpy
  import torch
  from .vocab import BaseVocab, VOCAB_PREFIX, UNK_ID
  from stanza.models.common.utils import open_read_binary, open_read_text
  from stanza.resources.common import DEFAULT_MODEL_DIR
label_desc: Use image node_id 6 for calling the Pretrain obj's underlying member method code with example usage: obj.write_text(filename) without return types