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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def load_embeddings(lang="en", task="embeddings", type="cw", normalize=False):
 """Return a word embeddings object for `lang` and of type `type` Args: lang (string):
 language code. task (string):
 parameters that define task. noramlized (boolean):
 returns noramlized word embeddings vectors. """

  src_dir = "_".join((type, task)) if type else task
  p = locate_resource(src_dir, lang)
  e = Embedding.load(p)
  if type == "cw":
    e.apply_expansion(CaseExpander)
    e.apply_expansion(DigitExpander)
  if type == "sgns":
    e.apply_expansion(CaseExpander)
  if type == "ue":
    e.apply_expansion(CaseExpander)
  if normalize:
    e.normalize_words(inplace=True)
  return e