code: def runTest(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
  
      sentence_embeddings = (
          UniversalSentenceEncoder.pretrained()
          .setInputCols("document")
          .setOutputCol("sentence_embeddings")
      )
  
      classifier = (
          SentimentDLApproach()
          .setInputCols("sentence_embeddings")
          .setOutputCol("category")
          .setLabelColumn("label")
          .setRandomSeed(44)
      )
  
      pipeline = Pipeline(
          stages=[document_assembler, sentence_embeddings, classifier]
      )
  
      model = pipeline.fit(self.data)
      model.stages[-1].write().overwrite().save(
          "./tmp_sentimentDL_model"
      )
  
      sentimentdlModel = (
          SentimentDLModel.load("./tmp_sentimentDL_model")
          .setInputCols(["sentence_embeddings"])
          .setOutputCol("class")
      )
  
file_path: spark-nlp/python/test/annotator/sentiment/sentiment_dl_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 SentimentDLTestSpec obj's underlying member method code with example usage: obj.runTest() without return types