Build unit test for AWQ/SmoothQuant wrapper #3000
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Introduce a prototype AWQ/SmoothQuant benchmark within lm_eval (vLLM). Related Issue/PR: pytorch#2815 Test plan: A toy tokenizer model is introduced to validate `TransformerEvalWrapper`. Toy linear models are updated to be compatible with the tokenizer model. Updated unit tests (`test_awq.py` and `test_smoothquant.py`) address the above changes. Future plan: This PR doesn't address latency and consumption. We need to expand metrics for comprehensive benchmarks within AWQ/SmoothQuant.
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3000
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Summary
This is a milestone for building a benchmark for AWQ/SmoothQuant within the vLLM ecosystem (#2815). For vLLM benchmark, AWQ/SmoothQuant needs a wrapper (
TransformerEvalWrapper) to be compatible with vLLM. Therefore, this PR adds unit test to verify ifTransformerEvalWrapperworks with AWQ/SmoothQuant.Test plan
A toy tokenizer model is introduced to validate
TransformerEvalWrapper. Toy linear models are updated to be compatible with the tokenizer model.Future plan
This PR only validates the wrapper for the benchmark within the vLLM ecosystem. We need to expand metrics for comprehensive AWQ/SmoothQuant benchmarks.