code: def _get_vector_data(cls, vecs, cache):
      if not isinstance(vecs, list):
          vecs = [vecs]
  
      vec_datas = []
      for vec in vecs:
          if not isinstance(vec, vocab.Vectors):
              vec_name = vec
              vec_data = cls._cached_vec_data.get(vec_name)
              if vec_data is None:
                  parts = vec_name.split(".")
                  if parts[0] == "fasttext":
                      if parts[2] == "bin":
                          vec_data = FastTextBinary(
                              language=parts[1], cache=cache
                          )
                      elif parts[2] == "vec" and parts[1] == "wiki":
                          vec_data = FastText(
                              suffix="wiki-news-300d-1M.vec.zip",
                              cache=cache,
                          )
                      elif parts[2] == "vec" and parts[1] == "crawl":
                          vec_data = FastText(
                              suffix="crawl-300d-2M.vec.zip",
                              cache=cache,
                          )
              if vec_data is None:
                  vec_data = vocab.pretrained_aliases[vec_name](
                      cache=cache
                  )
              cls._cached_vec_data[vec_name] = vec_data
              vec_datas.append(vec_data)
          else:
              vec_datas.append(vec)
  
      return vec_datas
  
imports: import gzip
  import logging
  import os
  import shutil
  import tarfile
  import zipfile
  import nltk
  import six
  import fasttext
  import torch
  from torchtext.legacy import data, vocab
  from torchtext.utils import download_from_url
  from urllib.request import urlretrieve
label_desc: Use image node_id 4 for calling the MatchingField obj's underlying member method code with example usage: obj._get_vector_data(cls, vecs, cache) and returns: vec_datas