Installation

We use MLCommons CM Automation framework to run MLPerf inference benchmarks.

CM needs git, python3-pip and python3-venv installed on your system. If any of these are absent, please follow the official CM installation page to install them. Once the dependencies are installed, do the following

Activate a Virtual ENV for CM

This step is not mandatory as CM can use separate virtual environment for MLPerf inference. But the latest pip install requires this or else will need the --break-system-packages flag while installing cm4mlops.

python3 -m venv cm
source cm/bin/activate

Install CM and pulls any needed repositories

Use the default fork of CM MLOps repositoryUse custom fork/branch of the CM MLOps repository

 pip install cm4mlops

 pip install cmind && cm init --quiet --repo=mlcommons@cm4mlops --branch=mlperf-inference

Here, repo is in the format githubUsername@githubRepo.

Now, you are ready to use the cm commands to run MLPerf inference as given in the benchmarks page