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 len(self.trainers) == 0:
          raise RuntimeError("Somehow there are no models loaded!")
      self._vocab = self.trainers[0].vocab
      self.configs = []
      for trainer in self.trainers:
          loaded_args = trainer.args
          # filter out unneeded args from model
          loaded_args = {
              k: v
              for k, v in loaded_args.items()
              if not UDProcessor.filter_out_option(k)
          }
          loaded_args.update(config)
          self.configs.append(loaded_args)
      self._config = self.configs[0]
  
file_path: stanza/stanza/pipeline/ner_processor.py
imports: import torch
  import logging
  from stanza.models.common import doc
  from stanza.models.common.exceptions import ForwardCharlmNotFoundError, BackwardCharlmNotFoundError
  from stanza.models.common.utils import unsort
  from stanza.models.ner.data import DataLoader
  from stanza.models.ner.trainer import Trainer
  from stanza.models.ner.utils import merge_tags
  from stanza.pipeline._constants import *
  from stanza.pipeline.processor import UDProcessor, register_processor
label_desc: Use image node_id 3 for calling the NERProcessor obj's underlying member method code with example usage: obj._set_up_final_config(config) without return types