code: def _set_up_model(self, config, pipeline, device):
      # set up trainer
      if config.get("pretokenized"):
          self._trainer = None
      else:
          self._trainer = Trainer(
              model_file=config["model_path"], device=device
          )
  
      # get and typecheck the postprocessor
      postprocessor = config.get("postprocessor")
      if postprocessor and callable(postprocessor):
          self._postprocessor = postprocessor
      elif not postprocessor:
          self._postprocessor = None
      else:
          raise ValueError(
              "Tokenizer recieved 'postprocessor' option of unrecognized type; postprocessor must be callable. Got %s"
              % postprocessor
          )
  
imports: import io
  import logging
  import torch
  from stanza.models.tokenization.data import TokenizationDataset
  from stanza.models.tokenization.trainer import Trainer
  from stanza.models.tokenization.utils import output_predictions
  from stanza.pipeline._constants import *
  from stanza.pipeline.processor import UDProcessor, register_processor
  from stanza.pipeline.registry import PROCESSOR_VARIANTS
  from stanza.models.common import doc
  from stanza.pipeline.external.jieba import JiebaTokenizer
  from stanza.pipeline.external.spacy import SpacyTokenizer
  from stanza.pipeline.external.sudachipy import SudachiPyTokenizer
  from stanza.pipeline.external.pythainlp import PyThaiNLPTokenizer
label_desc: Use image node_id 1 for calling the TokenizeProcessor obj's underlying member method code with example usage: obj._set_up_model(config, pipeline, device) without return types