          self.model.attrs["resize_output"](self.model, nO)
  
      def initialize(self, get_examples, nlp=None, labels=None):
          validate_get_examples(get_examples, "Parser.initialize")
          lexeme_norms = self.vocab.lookups.get_table("lexeme_norm", {})
          if len(lexeme_norms) == 0 and self.vocab.lang in util.LEXEME_NORM_LANGS:
              langs = ", ".join(util.LEXEME_NORM_LANGS)
              util.logger.debug(Warnings.W033.format(model="parser or NER", langs=langs))
          if labels is not None:
              actions = dict(labels)
          else:
              actions = self.moves.get_actions(
                  examples=get_examples(),
 
</s> remove     if hasattr(func, "__qualname__") and hasattr(func, "__module__") \
        and func.__module__ in sys.modules:  # method
            cls_func = vars(sys.modules[func.__module__])[func.__qualname__.split(".")[0]]
            return hasattr(cls_func, attr)
 </s> add     if (
        hasattr(func, "__qualname__")
        and hasattr(func, "__module__")
        and func.__module__ in sys.modules
    ):  # method
        cls_func = vars(sys.modules[func.__module__])[func.__qualname__.split(".")[0]]
        return hasattr(cls_func, attr) </s> remove             "package installed. The languages with lexeme normalization tables "
            "are currently: {langs}")
 </s> add             "package installed and load the table in your config. The "
            "languages with lexeme normalization tables are currently: "
            "{langs}\n\nLoad the table in your config with:\n\n"
            "[initialize.lookups]\n"
            "@misc = \"spacy.LookupsDataLoader.v1\"\n"
            "lang = ${{nlp.lang}}\n"
            "tables = [\"lexeme_norm\"]\n")
        util.check_lexeme_norms(self.vocab, "parser or NER")
          self.model.attrs["resize_output"](self.model, nO)
  
      def initialize(self, get_examples, nlp=None, labels=None):
          validate_get_examples(get_examples, "Parser.initialize")
        util.check_lexeme_norms(self.vocab, "parser or NER")
        util.check_lexeme_norms(self.vocab, "parser or NER")
        util.check_lexeme_norms(self.vocab, "parser or NER")
        util.check_lexeme_norms(self.vocab, "parser or NER")
          if labels is not None:
              actions = dict(labels)
          else:
              actions = self.moves.get_actions(
                  examples=get_examples(),
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Update lexeme_norm checks

* Add util method for check
* Add new languages to list with lexeme norm tables
* Add check to all relevant components
* Add config details to warning message

Note that we're not actually inspecting the model config to see if
`NORM` is used as an attribute, so it may warn in cases where it's not
relevant. 
spacy/pipeline/transition_parser.pyx