code: def runTest(self):
      data = self.spark.createDataFrame(
          [
              [1, "This is an example sentence"],
              [2, "Each sentence is converted"],
          ]
      ).toDF("id", "text")
  
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("documents")
      )
  
      e5 = self.tested_annotator
  
      pipeline = Pipeline().setStages([document_assembler, e5])
      results = pipeline.fit(data).transform(data)
  
      results.select("mpnet_embeddings.embeddings").show(truncate=False)
  
file_path: spark-nlp/python/test/annotator/embeddings/mpnet_embeddings_test.py
imports: import os
  import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.annotator.common.has_max_sentence_length_test import HasMaxSentenceLengthTests
  from test.util import SparkContextForTest
label_desc: Use image node_id 2 for calling the MPNetEmbeddingsTestSpec obj's underlying member method code with example usage: obj.runTest() without return types