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[Benchmark] Benchmark structured output with datasets #10557
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[Benchmark] Benchmark structured output with datasets #10557
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Signed-off-by: Aaron Pham <[email protected]>
Signed-off-by: Aaron Pham <[email protected]>
Signed-off-by: Aaron Pham <[email protected]>
Signed-off-by: Aaron Pham <[email protected]>
Signed-off-by: Aaron Pham <[email protected]>
👋 Hi! Thank you for contributing to the vLLM project. Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging. To run CI, PR reviewers can do one of these:
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tiny comment.
benchmarks/benchmark_guided.py
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from vllm.sampling_params import GuidedDecodingParams | ||
from vllm.utils import FlexibleArgumentParser, merge_async_iterators | ||
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SCHEMA = { |
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hmm, should we move this schema out to a file and we can keep a few json schema to run benchmark against.
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Moved to a separate file, also added 'grammar', 'choice', 'regex' to the benchmark
Signed-off-by: Chendi Xue <[email protected]>
Signed-off-by: Chendi Xue <[email protected]>
Signed-off-by: Chendi Xue <[email protected]>
Add structure output benchmark.
Base PR: #10046
Additional work:
TODO:
How to test:
Expected output
FileName: guided_Llama-3.2-3B-Instruct_xgrammar_bench_10_out512_asyncFalse_warmupFalse_chunkedprefillNone.txt