class_docstr: A loader and saver for pretrained embeddings. 
code: def __init__(
      self,
      filename=None,
      vec_filename=None,
      max_vocab=-1,
      save_to_file=True,
      csv_filename=None,
  ):
      self.filename = filename
      self._vec_filename = vec_filename
      self._csv_filename = csv_filename
      self._max_vocab = max_vocab
      self._save_to_file = save_to_file
  
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 1 to create a new Pretrain object  with example: obj = Pretrain(filename, vec_filename, max_vocab, save_to_file, csv_filename)