code: def _BOW_FEATURE_EXTRACTOR(sf, target=None):
      
      if isinstance(sf, dict):
          out = _tc.SArray([sf]).unpack('')
      elif isinstance(sf, _tc.SFrame):
          out = sf.__copy__()
      else:
          raise ValueError("Unrecognized input to feature extractor.")
      for f in _get_str_columns(out):
          if target != f:
              out[f] = _tc.text_analytics.count_words(out[f])
      return out
docs: Return an SFrame containing a bag of words representation of each column.