code: def runTest(self):
      multi_document_assembler = (
          MultiDocumentAssembler()
          .setInputCols("input1", "input2")
          .setOutputCols("output1", "output2")
      )
  
      tokenizer = (
          Tokenizer().setInputCols("output2").setOutputCol("token")
      )
  
      pipeline = Pipeline().setStages(
          [multi_document_assembler, tokenizer]
      )
      model = pipeline.fit(self.twoInputDataSet)
      light_pipeline = LightPipeline(model)
  
      actual_result = light_pipeline.annotate(self.input1, self.input2)
      expected_result = {
          "output1": [self.input1],
          "output2": [self.input2],
          "token": ["This", "is", "the", "second", "input"],
      }
  
      self.assertEqual(actual_result, expected_result)
  
      actual_result2 = light_pipeline.annotate(
          [self.input1, self.input1], [self.input2, self.input2]
      )
      expected_result2 = [
          {
              "output1": [self.input1],
              "output2": [self.input2],
              "token": ["This", "is", "the", "second", "input"],
          },
          {
              "output1": [self.input1],
              "output2": [self.input2],
              "token": ["This", "is", "the", "second", "input"],
          },
      ]
  
      self.assertEqual(actual_result2, expected_result2)
  
imports: import unittest
  import pytest
  from sparknlp.base import *
  from sparknlp.annotator import *
  from test.util import SparkSessionForTest
label_desc: Use image node_id 2 for calling the LightAnnotateMultiDocumentAssemblerTest obj's underlying member method code with example usage: obj.runTest() without return types