          representation is then simply a matter of summing the component features
          and applying the non-linearity.
      * upper (optional): A feed-forward network that predicts scores from the
          state representation. If not present, the output from the lower model is
          ued as action scores directly.
  
      tok2vec (Model[List[Doc], List[Floats2d]]):
          Subnetwork to map tokens into vector representations.
      nr_feature_tokens (int): The number of tokens in the context to use to
          construct the state vector. Valid choices are 1, 2, 3, 6, 8 and 13. The
 
</s> remove     A IOB tag sequence encodes a sequence of non-overlapping labelled spans
 </s> add     An IOB tag sequence encodes a sequence of non-overlapping labelled spans </s> remove     embed (Model[List[Doc], List[Floats2d]]): Embed tokens into context-indepdent
 </s> add     embed (Model[List[Doc], List[Floats2d]]): Embed tokens into context-independent </s> remove @registry.architectures.register("spacy.BiluoTagger.v1")
 </s> add @registry.architectures.register("spacy.BILUOTagger.v1") </s> remove from ..tokens import Doc
 </s> add from ...tokens import Doc </s> remove dropout = null
 </s> add 
        used as action scores directly.
          representation is then simply a matter of summing the component features
          and applying the non-linearity.
      * upper (optional): A feed-forward network that predicts scores from the
          state representation. If not present, the output from the lower model is
        used as action scores directly.
  
      tok2vec (Model[List[Doc], List[Floats2d]]):
          Subnetwork to map tokens into vector representations.
      nr_feature_tokens (int): The number of tokens in the context to use to
          construct the state vector. Valid choices are 1, 2, 3, 6, 8 and 13. The
keep keep keep keep replace keep keep keep keep keep
 Fix imports, types and default configs 
spacy/ml/models/parser.py