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This repository contains reusable and cross-platform automation recipes to run DevOps, MLOps, AIOps and MLPerf via a simple and human-readable Collective Mind interface (CM) while adapting to different operating systems, software and hardware.

All СM scripts have a simple Python API, extensible JSON/YAML meta description and unified input/output to make them reusable in different projects either individually or by chaining them together into portable automation workflows, applications and web services adaptable to continuously changing models, data sets, software and hardware.

Please use this BibTeX file.

Online catalog: cKnowledge, MLCommons.

pip install cmind -U

cm pull repo mlcommons@cm4mlops --branch=dev

cmr "python app image-classification onnx" --quiet

pip install cm4mlperf -U

cm run script --tags=run-mlperf,inference,_performance-only,_short  \
   --division=open \
   --category=edge \
   --device=cpu \
   --model=resnet50 \
   --precision=float32 \
   --implementation=mlcommons-python \
   --backend=onnxruntime \
   --scenario=Offline \
   --execution_mode=test \
   --power=no \
   --adr.python.version_min=3.8 \
   --clean \
   --compliance=no \
   --quiet \
   --time

Apache 2.0

We thank cKnowledge.org, cTuning foundation and MLCommons for sponsoring this project!

We also thank all volunteers, collaborators and contributors for their support, fruitful discussions, and useful feedback!