code: def runTest(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("word")
          .setOutputCol("document")
      )
      tokenizer = (
          Tokenizer().setInputCols("document").setOutputCol("token")
      )
      embeddings = (
          WordEmbeddings()
          .setStoragePath(
              path=os.getcwd()
              + "/../src/test/resources/random_embeddings_dim4.txt",
              read_as=ReadAs.TEXT,
          )
          .setDimension(4)
          .setStorageRef("glove_4d")
          .setInputCols("document", "token")
          .setOutputCol("embeddings")
          .setEnableInMemoryStorage(True)
      )
  
      pipeline = Pipeline(
          stages=[document_assembler, tokenizer, embeddings]
      )
      model = pipeline.fit(self.data)
      model.transform(self.data).show()
  
file_path: spark-nlp/python/test/annotator/embeddings/word_embeddings_test.py
imports: import os
  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 WordEmbeddingsTestSpec obj's underlying member method code with example usage: obj.runTest() without return types