Add lm-eval benchmark runner for evals#41
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One-entry sweep config used by the manual workflow_dispatch that validates NVIDIA/srt-slurm#41 on GB200. Mirrors the cheapest entry from dsr1-fp8-gb200-dynamo-trt (8k1k stp, eval-conc=63, 1P/3D) so the end-to-end eval path is exercised without running the full gb200 sweep. Not referenced by any automated workflow; picked up only when passed explicitly via --config-files.
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Integrate EleutherAI lm-evaluation-harness as a standalone benchmark runner. The default path runs the lm_eval CLI directly against the OpenAI-compatible endpoint (installing via pip if needed). An external eval harness can optionally take over via LM_EVAL_WORKSPACE mount or LM_EVAL_LIB env var. - New lm-eval runner registered in benchmark registry - _run_post_eval() in do_sweep.py handles EVAL_ONLY and RUN_EVAL modes - LM_EVAL_WORKSPACE env var mounts host workspace at /lm-eval-workspace - Topology/precision env vars passed through for metadata recording - Documentation and comprehensive tests
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Hi, made the changes requested in #12 , more general now and not InferenceX-specific. Tested with InferenceX still https://github.com/SemiAnalysisAI/InferenceX/actions/runs/24812985409 |
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Summary
Add InferenceX multi-node eval support through an
lm-evalbenchmark runner and eval-only orchestration path. Lets InferenceX run accuracy-only jobs against existing srt-slurm multi-node disaggregated recipes without running the throughput benchmark stage.Copied from ishandhanani/srt-slurm#245
How
lm-evalbenchmark runner that sources InferenceX'sbenchmarks/benchmark_lib.shfrom a mounted/infmax-workspace.INFMAX_WORKSPACEinto the container as/infmax-workspacewhen provided.EVAL_ONLY=truehandling indo_sweep.pyso eval-only jobs start infra/workers/frontend, runthe full model health check, skip throughput, and launch
lm-evaldirectly.RUN_EVAL=truebehavior as a post-benchmark eval path for normal throughput jobs.MODEL_NAME, prefill/decode TP/EP/DPA/worker counts, sequence length, precision, runner type, and eval concurrency.PREFILL_DP_ATTN/DECODE_DP_ATTNenv vars to the InferenceXPREFILL_DP_ATTENTION/DECODE_DP_ATTENTIONnames expected byappend_lm_eval_summary.meta_env.json,results*.json,sample*.jsonl) into/logs/eval_results/for launcher-side artifact pickup.code.
docs/accuracy.md.What
For
EVAL_ONLY=true:wait_for_model()verifies the configured prefill/decode or aggregated worker counts.lm-evalruns against the OpenAI-compatible endpoint.For
RUN_EVAL=truewithoutEVAL_ONLY=true:lm-evalruns as a post-step if throughput succeeds.Validation run
https://github.com/SemiAnalysisAI/InferenceX/actions/runs/24059388771
InferenceX PR
SemiAnalysisAI/InferenceX#1000