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Merge pull request #18 from ctuning/master
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name: MLPerf inference R-GAT via CMXR
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on:
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pull_request_target:
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branches: [ "master", "main", "dev" ]
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paths:
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- '.github/workflows/test-mlperf-inference-rgat.yml'
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- '**'
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- '!**.md'
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jobs:
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build:
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest]
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python-version: [ "3.12" ]
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backend: [ "pytorch" ]
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implementation: [ "python" ]
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v3
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install CMX
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run: |
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pip install cmind
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- name: Install mlcflow
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run: |
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pip install mlcflow
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pip install tabulate
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- name: Pull MLOps repository
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run: |
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cmx pull repo ${{ github.event.pull_request.head.repo.html_url }} --branch=${{ github.event.pull_request.head.ref }}
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- name: Test MLPerf Inference R-GAT using ${{ matrix.backend }} on ${{ matrix.os }}
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run: |
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cmxr --tags=run,mlperf,inference,generate-run-cmds,_submission,_short --adr.inference-src.tags=_branch.dev --pull_changes=yes --pull_inference_changes=yes --submitter="MLC" --hw_name=gh_${{ matrix.os }}_x86 --model=rgat --implementation=${{ matrix.implementation }} --backend=${{ matrix.backend }} --device=cpu --scenario=Offline --test_query_count=500 --adr.compiler.tags=gcc --category=datacenter --quiet --v --target_qps=1
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- name: Push Test MLPerf Results (only for cTuning dev branches)
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if: github.repository_owner == 'ctuning'
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env:
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USER: "GitHub Action"
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EMAIL: "admin@cTuning.org"
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GITHUB_TOKEN: ${{ secrets.TEST_RESULTS_GITHUB_TOKEN }}
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run: |
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git config --global user.name "mlcommons-bot"
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git config --global user.email "mlcommons-bot@users.noreply.github.com"
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git config --global credential.https://github.com.helper ""
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git config --global credential.https://github.com.helper "!gh auth git-credential"
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git config --global credential.https://gist.github.com.helper ""
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git config --global credential.https://gist.github.com.helper "!gh auth git-credential"
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cmxr --tags=push,github,mlperf,inference,submission --repo_url=https://github.com/mlcommons/mlperf_inference_test_submissions_v5.0 --repo_branch=auto-update --commit_message="Results from R50 GH action on ${{ matrix.os }}" --quiet

README.md

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@@ -18,16 +18,16 @@ in the most efficient and cost-effective way across diverse models, data sets, s
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It includes the following sub-projects.
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### Common Metadata eXchange (CMX)
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### Common Metadata eXchange (CMX, 2025)
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The [CMX framework](https://github.com/mlcommons/ck/tree/master/cmx)
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facilitates the decomposition of complex software systems and benchmarks such as MLPerf
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into portable, reusable, and interconnected automation recipes for MLOps and DevOps.
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These recipes are developed and continuously improved by the community.
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***Starting in 2025, CMX V4.0.0 serves as drop-in, backward-compatible replacement
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for the earlier [Collective Mind framework (CM)](https://github.com/mlcommons/ck/tree/master/cm),
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while providing a simpler and more robust interface.***
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for the earlier [Collective Mind framework (CM)](https://github.com/mlcommons/ck/tree/master/cm)
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and other MLCommons automation prototypes, while providing a simpler and more robust interface.***
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CMX is a lightweight, Python-based toolset that provides a unified
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command-line interface (CLI), a Python API, and minimal dependencies.
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See the [online documentation](https://docs.mlcommons.org/inference)
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at MLCommons to run MLPerf inference benchmarks across diverse systems using CMX.
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Just install `pip install cmind` and substitute the following commands with `cmx`:
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Just install `pip install cmind` and substitute the following commands and flags:
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* `cm` -> `cmx`
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* `mlc` -> `cmx run mlc`
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* `mlcr` -> `cmx run mlcr`
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* `mlc` -> `cmx`
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* `mlcr` -> `cmxr`
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* `-v` -> `--v`
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### MLPerf results visualization
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## Legacy projects
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* [CM](https://github.com/mlcommons/ck/tree/master/cm)
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* [CM-MLOps](https://github.com/mlcommons/ck/tree/master/cm-mlops)
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* [CM4MLOps](https://github.com/mlcommons/cm4mlops)
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* [CM](https://github.com/mlcommons/ck/tree/master/cm) (2022-2024)
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* [CM-MLOps](https://github.com/mlcommons/ck/tree/master/cm-mlops) (2021)
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* [CM4MLOps](https://github.com/mlcommons/cm4mlops) (2022-2024)
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* [CK automation framework v1 and v2](https://github.com/mlcommons/ck/tree/master/ck)
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cm/CHANGES.md

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## CMX V4.0.1
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- provided backward compatibility with various MLCommons tools
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## CMX V4.0.0
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- added CMX interface for new tools
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cm/README.md

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@@ -16,8 +16,8 @@ into portable, reusable, and interconnected automation recipes for MLOps and Dev
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These recipes are developed and continuously improved by the community.
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***Starting in 2025, CMX V4.0.0 serves as drop-in, backward-compatible replacement
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for the earlier [Collective Mind framework (CM)](https://github.com/mlcommons/ck/tree/master/cm),
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while providing a simpler and more robust interface.***
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for the earlier [Collective Mind framework (CM)](https://github.com/mlcommons/ck/tree/master/cm)
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and other MLCommons automation prototypes, while providing a simpler and more robust interface.***
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CMX is a lightweight, Python-based toolset that provides a unified
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command-line interface (CLI), a Python API, and minimal dependencies.
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See the [online documentation](https://docs.mlcommons.org/inference)
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at MLCommons to run MLPerf inference benchmarks across diverse systems using CMX.
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Just install `pip install cmind` and substitute the following commands with `cmx`:
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Just install `pip install cmind` and substitute the following commands and flags:
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* `cm` -> `cmx`
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* `mlc` -> `cmx run mlc`
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* `mlcr` -> `cmx run mlcr`
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* `mlc` -> `cmx`
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* `mlcr` -> `cmxr`
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* `-v` -> `--v`
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### MLPerf results visualization
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* [White paper](https://arxiv.org/abs/2406.16791)
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* [CMX architecture](https://github.com/mlcommons/ck/tree/master/docs/specs/cm-diagram-v3.5.1.png)
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* [CMX installation GUI](https://access.cknowledge.org/playground/?action=install)
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* [CMX Python API](https://cKnowledge.org/docs/cm)
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*TBD*
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cm/cmind/__init__.py

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# White paper: https://arxiv.org/abs/2406.16791
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# Project contributors: https://github.com/mlcommons/ck/blob/master/CONTRIBUTING.md
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__version__ = "4.0.0"
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__version__ = "4.0.1"
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from cmind.core import access
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from cmind.core import x

cm/cmind/cli.py

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# Collective Mind command line wrapper
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# Collective Mind and Common Metadata eXchange command line wrapper
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#
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# Author(s): Grigori Fursin
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# Contributor(s):
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return run(['run', 'script'] + argv)
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############################################################
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def runx_script(argv = None):
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"""
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Shortcut to "cmx run script ..." or "mlcr ..."
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CMX command line format:
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Args:
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argv (list | string): command line arguments
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Returns:
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(CM return dict):
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* return (int): return code == 0 if no error and >0 if error
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* (error) (str): error string if return>0
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* Output from a CM automation action
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"""
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# Access CMX
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if argv is None:
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argv = sys.argv[1:]
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return runx(['run', 'mlcr'] + argv)
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############################################################
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def docker_script(argv = None):
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"""

cm/docs/cmx/README.md

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cm/docs/cmx/install.md

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