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[Feature Branch][LLM Testing] Full Testing Harness for LLMs#1216
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* initial commit * finish creation of helper objects * Update tests/conftest.py * small refactor * [Feature Branch][LLM Testing] LLM Testing Suite (#1227) * Update README.md * Update src/deepsparse/yolov8/README.md * Update text_generation.py * quality * readability * all tests passing * added some full kv cache tests * initial commit * ready for review * Delete tests/deepsparse/transformers/pipelines/proposal_text_generation_tests.md
dsikka
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dsikka
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dsikka
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dsikka
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How confident are we in our test coverage? Possibly add tests when running with deterministic off or multiple input sequences?
…ithub.com/neuralmagic/deepsparse into feature/damian/llm_testing_feature_branch
bfineran
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dsikka
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- Remove ORT ground truth class and use deepsparse pipeline instead
bfineran
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LGTM overall. as discussed offline - will need some refactors to move cleanly to a config based method
dsikka
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LGTM. Support for getting this to run on a nightly basis is still pending?
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The implementation of the test harness for LLMs. By default, the tests are turned off so that we do not choke GHA.
To enable tests: remove
@pytest.mark.skip(reason="Those tests are too heavy to run as a normal part of the CI.")@pytest.mark.skip(reason="Those tests are too heavy to run as a normal part of the CI.")
and run
pytest tests/deepsparse/transformers/pipelines/test_text_generation.pyFuture consideration: adding config and utilizing small toy models to make tests extremely lightweight.
Includes PRs: