code: def runTest(self):
      test_dataset = self.spark.createDataFrame(
          [["So what happened?"]]
      ).toDF("text")
      train_dataset = CoNLLU(lemmaCol="lemma_train").readDataset(
          self.spark, self.conllu_file
      )
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
      tokenizer = (
          Tokenizer().setInputCols(["document"]).setOutputCol("token")
      )
      lemmatizer = (
          Lemmatizer()
          .setInputCols(["token"])
          .setFormCol("form")
          .setLemmaCol("lemma_train")
          .setOutputCol("lemma")
      )
  
      train_dataset.show()
      pipeline = Pipeline(
          stages=[document_assembler, tokenizer, lemmatizer]
      )
      pipeline.fit(train_dataset).transform(test_dataset).show()
  
file_path: spark-nlp/python/test/annotator/lemmatizer_test.py
imports: import os
  import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from sparknlp.training import CoNLLU
  from test.util import SparkContextForTest
label_desc: Use image node_id 2 for calling the LemmatizerWithTrainingDataSetTestSpec obj's underlying member method code with example usage: obj.runTest() without return types