class_docstr: Base class for the neural UD Processors (tokenize,mwt,pos,lemma,depparse,sentiment,constituency) 
class_docstr_tok: ["Base","class","for","the","neural","UD","Processors","(","tokenize",",","mwt",",","pos",",","lemma",",","depparse",",","sentiment",",","constituency",")"]
docstr: Finalize the configurations for this processor, based off of values from a UD model. 
docstr_tok: ["Finalize","the","configurations","for","this","processor",",","based","off","of","values","from","a","UD","model","."]
code: def _set_up_final_config(self, config):
      """Finalize the configurations for this processor, based off of values from a UD model."""
      # set configurations from loaded model
      if self._trainer is not None:
          loaded_args, self._vocab = (
              self._trainer.args,
              self._trainer.vocab,
          )
          # filter out unneeded args from model
          loaded_args = {
              k: v
              for k, v in loaded_args.items()
              if not UDProcessor.filter_out_option(k)
          }
      else:
          loaded_args = {}
      loaded_args.update(config)
      self._config = loaded_args
  
imports: from abc import ABC, abstractmethod
  from stanza.models.common.doc import Document
  from stanza.pipeline.registry import NAME_TO_PROCESSOR_CLASS, PIPELINE_NAMES, PROCESSOR_VARIANTS
label_desc: Use image node_id 3 for calling the UDProcessor obj's underlying member method code with example usage: obj._set_up_final_config(config) without return types