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[punet] CI for quantization import/compilation/golden check #76

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stellaraccident opened this issue Jun 26, 2024 · 2 comments
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@stellaraccident
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@ScottTodd
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Could you take a look at #70 and nod-ai/SHARK-TestSuite#272 ? Those are for llama, and it would be nice to have similar testing for punet and llama. For the first, I'm not particularly attached to the bash script but just wanted something running in this repo somehow. The second distills the program down to a common test format we can use from IREE on presubmit.

@stellaraccident
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Oh thanks, will have a look.

stellaraccident added a commit that referenced this issue Jun 29, 2024
* Imports/validates the FP16 model running eagerly.
* Imports/validates the int8 model running eagerly.
* Exports the models.

Progress on #76
ScottTodd added a commit that referenced this issue Jul 1, 2024
Sample run (with failures):
https://github.com/nod-ai/sharktank/actions/runs/9752141473/job/26915109873

Definitely room for improvement, but it's a start.

Progress on #76
ScottTodd added a commit to nod-ai/SHARK-TestSuite that referenced this issue Jul 8, 2024
Related to nod-ai/SHARK-Platform#76

* Model source:
https://github.com/nod-ai/sharktank/tree/main/sharktank/sharktank/models/punet
* Python test:
https://github.com/nod-ai/sharktank/blob/main/sharktank/integration/models/punet/integration_test.py
* Python run script:
https://github.com/nod-ai/sharktank/blob/main/sharktank/sharktank/models/punet/tools/run_punet.py
* Weights are labeled in the sharktank sources. The primarily come from
https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 and
https://huggingface.co/amd-shark/sdxl-quant-models

Only testing compilation and basic execution for now. Result comparisons
will follow once they are enabled upstream. TBD if the quantized outputs
will be different enough across backends to need extra infrastructure
configuration there.
renxida pushed a commit to nod-ai/SHARK-TestSuite that referenced this issue Jul 18, 2024
Related to nod-ai/SHARK-Platform#76

* Model source:
https://github.com/nod-ai/sharktank/tree/main/sharktank/sharktank/models/punet
* Python test:
https://github.com/nod-ai/sharktank/blob/main/sharktank/integration/models/punet/integration_test.py
* Python run script:
https://github.com/nod-ai/sharktank/blob/main/sharktank/sharktank/models/punet/tools/run_punet.py
* Weights are labeled in the sharktank sources. The primarily come from
https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 and
https://huggingface.co/amd-shark/sdxl-quant-models

Only testing compilation and basic execution for now. Result comparisons
will follow once they are enabled upstream. TBD if the quantized outputs
will be different enough across backends to need extra infrastructure
configuration there.
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