code: def runTest(self) -> None:
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
  
      sentence_detector = (
          SentenceDetector()
          .setInputCols(["document"])
          .setOutputCol("sentence")
      )
  
      pattern = "^(\\s+)|(?=[\\s+\"'\|:;<=>!?~{}*+,$)\(&%\\[\\]])|(?<=[\\s+\"'\|:;<=>!?~{}*+,$)\(&%\\[\\]])|(?=\.$)"
  
      regex_tok = (
          RegexTokenizer()
          .setInputCols(["sentence"])
          .setOutputCol("regex_token")
          .setPattern(pattern)
          .setTrimWhitespace(False)
          .setPreservePosition(True)
      )
  
      pipeline = Pipeline().setStages(
          [document_assembler, sentence_detector, regex_tok]
      )
  
      pipeline_model = pipeline.fit(self.data)
  
      pipe_path = "file:///" + os.getcwd() + "/tmp_regextok_pipeline"
      pipeline_model.write().overwrite().save(pipe_path)
  
      loaded_pipeline: PipelineModel = PipelineModel.read().load(
          pipe_path
      )
      loaded_pipeline.transform(self.data).show()
  
file_path: spark-nlp/python/test/annotator/token/regex_tokenizer_test.py
imports: import os
  import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.util import SparkSessionForTest
label_desc: Use image node_id 2 for calling the RegexTokenizerTestSpec obj's underlying member method code with example usage: obj.runTest() without return types