      def evaluate(
          self,
          examples: Iterable[Example],
          *,
          verbose: bool = False,
          batch_size: int = 256,
          scorer: Optional[Scorer] = None,
          component_cfg: Optional[Dict[str, Dict[str, Any]]] = None,
          scorer_cfg: Optional[Dict[str, Any]] = None,
      ) -> Dict[str, Union[float, dict]]:
 
</s> remove     docs: Union[Iterable[Doc], Doc],
 </s> add     docs: Union[Iterable[Union[Doc, Span]], Doc, Span], </s> remove         getter: Callable[[Doc, str], Any] = getattr,
 </s> add         getter: Callable[[Doc, str], Iterable[Span]] = getattr, </s> remove         scores: Iterable[str] = tuple(),
        default_score_weights: Dict[str, float] = SimpleFrozenDict(),
 </s> add  </s> remove             if verbose:
                print(doc)
 </s> add             util.logger.debug(doc) </s> remove     scores = nlp.evaluate(dev_dataset, verbose=False)
 </s> add     scores = nlp.evaluate(dev_dataset)
      def evaluate(
          self,
          examples: Iterable[Example],
          *,

          batch_size: int = 256,
          scorer: Optional[Scorer] = None,
          component_cfg: Optional[Dict[str, Dict[str, Any]]] = None,
          scorer_cfg: Optional[Dict[str, Any]] = None,
      ) -> Dict[str, Union[float, dict]]:
keep keep keep keep replace keep keep keep keep keep
 Update docs, types and API consistency 
spacy/language.py