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cmr "run-mlperf inference _find-performance _all-scenarios" \
--model=bert-99 --implementation=qualcomm --device=qaic --backend=glow \
--category=edge --division=open --quiet
- Use
--division=closed
to run all scenarios for the closed division (compliance tests are skipped for_find-performance
mode) - Use
--category=datacenter
to run datacenter scenarios (only for bert-99.9) - Use
--model=bert-99.9
to run the high-accuracy model (only for datacenter) - Use
--rerun
to force a rerun even when result files (from a previous run) exist
cmr "run-mlperf inference _submission _all-scenarios" --model=bert-99 \
--device=qaic --implementation=qualcomm --backend=qaic \
--execution-mode=valid --category=edge --division=open --quiet
- Use
--power=yes
for measuring power. It is ignored for accuracy and compliance runs - Use
--division=closed
to run all scenarios for the closed division including the compliance tests --offline_target_qps
,--server_target_qps
, and--singlestream_target_latency
can be used to override the determined performance numbers
Follow this guide to generate the submission tree and upload your results.
Check the MLCommons Task Force on Automation and Reproducibility and get in touch via public Discord server.