code: def runTest(self):
      document_assembler = (
          MultiDocumentAssembler()
          .setInputCols(["question", "context"])
          .setOutputCols(["document_question", "document_context"])
      )
  
      qa_classifier = (
          DistilBertForQuestionAnswering.pretrained()
          .setInputCols(["document_question", "document_context"])
          .setOutputCol("answer")
      )
  
      pipeline = Pipeline().setStages(
          [document_assembler, qa_classifier]
      )
  
      model = pipeline.fit(self.data)
  
      light_pipeline = LightPipeline(model)
      annotations_result = light_pipeline.fullAnnotate(
          self.question, self.context
      )
  
      self.assertEqual(len(annotations_result), 1)
      self.assertAnnotations(annotations_result)
  
      questions = [self.question, self.question]
      contexts = [self.context, self.context]
      annotations_result = light_pipeline.fullAnnotate(
          questions, contexts
      )
  
      self.assertEqual(len(annotations_result), 2)
      self.assertAnnotations(annotations_result)
  
imports: import os
  import unittest
  import pytest
  from pyspark.sql.functions import col
  from sparknlp.pretrained import PretrainedPipeline
  from test.util import SparkSessionForTest, SparkContextForTest
  from sparknlp.annotator import *
  from sparknlp.base import *
label_desc: Use image node_id 2 for calling the LightPipelineQAInputTest obj's underlying member method code with example usage: obj.runTest() without return types