code: def runTest(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
      tokenizer = (
          Tokenizer().setInputCols("document").setOutputCol("token")
      )
      doc2vec = (
          Word2VecApproach()
          .setInputCols(["token"])
          .setOutputCol("sentence_embeddings")
          .setMaxSentenceLength(512)
          .setStepSize(0.025)
          .setMinCount(5)
          .setVectorSize(300)
          .setNumPartitions(1)
          .setMaxIter(2)
          .setSeed(42)
          .setEnableCaching(True)
          .setStorageRef("doc2vec_aclImdb")
      )
  
      pipeline = Pipeline(
          stages=[document_assembler, tokenizer, doc2vec]
      )
      model = pipeline.fit(self.data)
      model.write().overwrite().save("./tmp_model")
      loaded_model = model.load("./tmp_model")
      loaded_model.transform(self.data).show()
  
file_path: spark-nlp/python/test/annotator/embeddings/word2_vec_test.py
imports: import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.util import SparkContextForTest
label_desc: Use image node_id 2 for calling the Word2VecTestSpec obj's underlying member method code with example usage: obj.runTest() without return types