code: def test_integration_wtq_pt(self):
      table_querier = pipeline("table-question-answering")
  
      data = {
          "Repository": ["Transformers", "Datasets", "Tokenizers"],
          "Stars": ["36542", "4512", "3934"],
          "Contributors": ["651", "77", "34"],
          "Programming language": [
              "Python",
              "Python",
              "Rust, Python and NodeJS",
          ],
      }
      queries = [
          "What repository has the largest number of stars?",
          "Given that the numbers of stars defines if a repository is active, what repository is the most active?",
          "What is the number of repositories?",
          "What is the average number of stars?",
          "What is the total amount of stars?",
      ]
  
      results = table_querier(data, queries)
  
      expected_results = [
          {
              "answer": "Transformers",
              "coordinates": [(0, 0)],
              "cells": ["Transformers"],
              "aggregator": "NONE",
          },
          {
              "answer": "Transformers",
              "coordinates": [(0, 0)],
              "cells": ["Transformers"],
              "aggregator": "NONE",
          },
          {
              "answer": "COUNT > Transformers, Datasets, Tokenizers",
              "coordinates": [(0, 0), (1, 0), (2, 0)],
              "cells": ["Transformers", "Datasets", "Tokenizers"],
              "aggregator": "COUNT",
          },
          {
              "answer": "AVERAGE > 36542, 4512, 3934",
              "coordinates": [(0, 1), (1, 1), (2, 1)],
              "cells": ["36542", "4512", "3934"],
              "aggregator": "AVERAGE",
          },
          {
              "answer": "SUM > 36542, 4512, 3934",
              "coordinates": [(0, 1), (1, 1), (2, 1)],
              "cells": ["36542", "4512", "3934"],
              "aggregator": "SUM",
          },
      ]
      self.assertListEqual(results, expected_results)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_table_question_answering.py
imports: import unittest
  from transformers import MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING, AutoModelForTableQuestionAnswering, AutoTokenizer, TableQuestionAnsweringPipeline, TFAutoModelForTableQuestionAnswering, pipeline
  from transformers.testing_utils import require_pandas, require_tensorflow_probability, require_tf, require_torch, require_torch_scatter, slow
  from .test_pipelines_common import PipelineTestCaseMeta
label_desc: Use image node_id 5 for calling the TQAPipelineTests obj's underlying member method code with example usage: obj.test_integration_wtq_pt() without return types