                  component_name,
                  assigns=assigns,
                  requires=requires,
                  retokenizes=retokenizes,
                  scores=scores,
                  default_score_weights=default_score_weights,
                  func=factory_func,
              )
              return component_func
  
          if func is not None:  # Support non-decorator use cases
 
</s> remove             kwargs.setdefault("verbose", verbose)
 </s> add  </s> remove         scores (Iterable[str]): All scores set by the component if it's trainable,
            e.g. ["ents_f", "ents_r", "ents_p"].
        default_score_weights (Dict[str, float]): The scores to report during
            training, and their default weight towards the final score used to
            select the best model. Weights should sum to 1.0 per component and
            will be combined and normalized for the whole pipeline.
 </s> add  </s> remove             if verbose:
                print(doc)
 </s> add             util.logger.debug(doc) </s> remove         getter (Callable[[Doc, str], Any]): Defaults to getattr. If provided,
            getter(doc, attr) should return the spans for the individual doc.
 </s> add         getter (Callable[[Doc, str], Iterable[Span]]): Defaults to getattr. If
            provided, getter(doc, attr) should return the spans for the
            individual doc. </s> remove         verbose (bool): Print debugging information.
 </s> add 
                  component_name,
                  assigns=assigns,
                  requires=requires,
                  retokenizes=retokenizes,


                  func=factory_func,
              )
              return component_func
  
          if func is not None:  # Support non-decorator use cases
keep keep keep keep replace replace keep keep keep keep keep
 Update docs, types and API consistency 
spacy/language.py