Repository: huggingface/transformers
Pull request: clean pipeline question_answering.

# What does this PR do?

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Fixes # (issue)


## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
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      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

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Changed files:
filename: src/transformers/pipelines/question_answering.py
patch: @@ -340,7 +340,6 @@ def _sanitize_parameters(
         if max_answer_len is not None:
             if max_answer_len < 1:
                 raise ValueError(f"max_answer_len parameter should be >= 1 (got {max_answer_len}")
-        if max_answer_len is not None:
             postprocess_params["max_answer_len"] = max_answer_len
         if handle_impossible_answer is not None:
             postprocess_params["handle_impossible_answer"] = handle_impossible_answer
@@ -542,11 +541,9 @@ def postprocess(
         for output in model_outputs:
             if self.framework == "pt" and output["start"].dtype == torch.bfloat16:
                 start_ = output["start"].to(torch.float32)
-            else:
-                start_ = output["start"]
-            if self.framework == "pt" and output["start"].dtype == torch.bfloat16:
                 end_ = output["end"].to(torch.float32)
             else:
+                start_ = output["start"]
                 end_ = output["end"]
             example = output["example"]
             p_mask = output["p_mask"]