  
      def begin_training(self, get_gold_tuples, pipeline=None, sgd=None, **cfg):
          if len(self.vocab.lookups.get_table("lexeme_norm", {})) == 0:
              warnings.warn(Warnings.W033.format(model="parser or NER"))
          if 'model' in cfg:
              self.model = cfg['model']
          if not hasattr(get_gold_tuples, '__call__'):
              gold_tuples = get_gold_tuples
 
</s> remove     W033 = ("Training a new {model} using a model with no lexeme normalization "
            "table. This may degrade the performance of the model to some "
            "degree. If this is intentional or the language you're using "
            "doesn't have a normalization table, please ignore this warning. "
            "If this is surprising, make sure you have the spacy-lookups-data "
            "package installed. The languages with lexeme normalization tables "
            "are currently: da, de, el, en, id, lb, pt, ru, sr, ta, th.")
 </s> add     W033 = ("Training a new {model} using a model with an empty lexeme "
            "normalization table. This may degrade the performance to some "
            "degree. If this is intentional or this language doesn't have a "
            "normalization table, please ignore this warning.")
    W034 = ("Please install the package spacy-lookups-data in order to include "
            "the default lexeme normalization table for the language '{lang}'.")
            try:
                import spacy_lookups_data
            except ImportError:
                if self.vocab.lang in ("da", "de", "el", "en", "id", "lb", "pt",
                        "ru", "sr", "ta", "th"):
                    warnings.warn(Warnings.W034.format(lang=self.vocab.lang))
  
      def begin_training(self, get_gold_tuples, pipeline=None, sgd=None, **cfg):
          if len(self.vocab.lookups.get_table("lexeme_norm", {})) == 0:
              warnings.warn(Warnings.W033.format(model="parser or NER"))
            try:
                import spacy_lookups_data
            except ImportError:
                if self.vocab.lang in ("da", "de", "el", "en", "id", "lb", "pt",
                        "ru", "sr", "ta", "th"):
                    warnings.warn(Warnings.W034.format(lang=self.vocab.lang))
          if 'model' in cfg:
              self.model = cfg['model']
          if not hasattr(get_gold_tuples, '__call__'):
              gold_tuples = get_gold_tuples
keep keep keep add keep keep keep keep
 Improve warnings around normalization tables (#5794)

Provide more customized normalization table warnings when training a new
model. Only suggest installing `spacy-lookups-data` if it's not already
installed and it includes a table for this language (currently checked
in a hard-coded list). 
spacy/syntax/nn_parser.pyx