Qualcomm AI Engine Direct - [GenAI Pipeline] PR5: Model preparation & quantization strategy implementations - #21899
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… quantization strategy implementations
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21899
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Summary
This PR implements the model preparation and quantization strategy implementations, replacing the
NotImplementedErrorstubs with real logic. Each strategy delegates to injectable adapter interfaces (from PR4) for testability.What's included
Strategy implementations (2 files + 1
__init__fix):ExecuTorchModelPreparationStrategy: 5-step flowload_model→load_tokenizer(viaModelLoaderAdapter)generate_calibration_data(via separately-injectableCalibrationDataAdapter)extra_optionsfallback)model_name,soc_modelrequired)ExecuTorchQuantizationStrategy: Full PT2E single-graph pipeline viaQuantizerAdapterquant_dtype,quant_recipe, and per-channel options viaextra_optionsIterableas calibration data (lists, DataLoaders, generators)training_datais provided (QAT deferred)strategies/model_preparation/__init__.py: adds missingExecuTorchModelPreparationStrategyimport to__all__Unit tests:
test_executorch_model_preparation_strategy.pytest_executorch_quantization_strategy.pytest_default_model_preparation_adapter.pytest_default_model_preparation_adapter.pyPR Review Checklist
Related PRs
Test plan
Run only tests added in this PR:
Run only this PR's tests with coverage:
Result:
Run all
genai_pipelinetests:Run all
genai_pipelinetests with coverage:Result: