code: def test_small_model_pt_softmax_trick(self):
      question_answerer = pipeline(
          "question-answering",
          model="sshleifer/tiny-distilbert-base-cased-distilled-squad",
      )
  
      real_postprocess = question_answerer.postprocess
  
      # Tweak start and stop to make sure we encounter the softmax logits
      # bug.
      def ensure_large_logits_postprocess(
          model_outputs,
          top_k=1,
          handle_impossible_answer=False,
          max_answer_len=15,
      ):
          for output in model_outputs:
              output["start"] = output["start"] * 1e6
              output["end"] = output["end"] * 1e6
          return real_postprocess(
              model_outputs,
              top_k=top_k,
              handle_impossible_answer=handle_impossible_answer,
              max_answer_len=max_answer_len,
          )
  
      question_answerer.postprocess = ensure_large_logits_postprocess
  
      outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris.",
      )
  
      self.assertEqual(
          nested_simplify(outputs),
          {
              "score": 0.028,
              "start": 0,
              "end": 11,
              "answer": "HuggingFace",
          },
      )
  
imports: import unittest
  from transformers import MODEL_FOR_QUESTION_ANSWERING_MAPPING, TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING, LxmertConfig, QuestionAnsweringPipeline
  from transformers.data.processors.squad import SquadExample
  from transformers.pipelines import QuestionAnsweringArgumentHandler, pipeline
  from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, require_torch_or_tf, slow
  from .test_pipelines_common import ANY
label_desc: Use image node_id 5 for calling the QAPipelineTests obj's underlying member method code with example usage: obj.test_small_model_pt_softmax_trick() and returns: real_postprocess