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.fullAnnotate(
          self.input1, self.input2
      )
      expected_result = [
          {
              "output1": [
                  Annotation(
                      "document",
                      0,
                      len(self.input1) - 1,
                      self.input1,
                      {},
                      [],
                  )
              ],
              "output2": [
                  Annotation(
                      "document",
                      0,
                      len(self.input2) - 1,
                      self.input2,
                      {},
                      [],
                  )
              ],
              "token": [
                  Annotation(
                      "token", 0, 3, "This", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 5, 6, "is", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 8, 10, "the", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 12, 17, "second", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 19, 23, "input", {"sentence": "0"}, []
                  ),
              ],
          }
      ]
  
      self.assertEqual(actual_result, expected_result)
  
      actual_result2 = light_pipeline.fullAnnotate(
          [self.input1, self.input1], [self.input2, self.input2]
      )
      expected_result2 = [
          {
              "output1": [
                  Annotation(
                      "document",
                      0,
                      len(self.input1) - 1,
                      self.input1,
                      {},
                      [],
                  )
              ],
              "output2": [
                  Annotation(
                      "document",
                      0,
                      len(self.input2) - 1,
                      self.input2,
                      {},
                      [],
                  )
              ],
              "token": [
                  Annotation(
                      "token", 0, 3, "This", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 5, 6, "is", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 8, 10, "the", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 12, 17, "second", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 19, 23, "input", {"sentence": "0"}, []
                  ),
              ],
          },
          {
              "output1": [
                  Annotation(
                      "document",
                      0,
                      len(self.input1) - 1,
                      self.input1,
                      {},
                      [],
                  )
              ],
              "output2": [
                  Annotation(
                      "document",
                      0,
                      len(self.input2) - 1,
                      self.input2,
                      {},
                      [],
                  )
              ],
              "token": [
                  Annotation(
                      "token", 0, 3, "This", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 5, 6, "is", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 8, 10, "the", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 12, 17, "second", {"sentence": "0"}, []
                  ),
                  Annotation(
                      "token", 19, 23, "input", {"sentence": "0"}, []
                  ),
              ],
          },
      ]
  
      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 LightFullAnnotateMultiDocumentAssemblerTest obj's underlying member method code with example usage: obj.runTest() without return types