Closed sergey-serebryakov closed 1 year ago
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This PR refers to the old, retired, ssd-v1 benchmark, which was replaced by the Retinanet benchmark.
In an effort to do a better job maintaining this repo, we're closing PRs for retired benchmarks. The old benchmark code still exists, but has been moved to https://github.com/mlcommons/training/tree/master/retired_benchmarks/ssd-v1/.
If you think there is useful cleanup to be done to the retired_benchmarks subtree, please submit a new PR.
Updates
06/05/2021-02
Adding--force-reinstall
switch forpip install
command in the step-by-step guide below.06/05/2021-01
Fixing bug: "docker image exists" check now uses docker command specified in docker platform file. In previous version, thedocker
command was hard coded for this check.05/05/2021-01
Adding missing dependency to MLCube™ docker file (unzip).02/05/2021-01
Fixed errors inCurrent implementation
section related to installing MLCube from GitHub repository.01/05/2021-01
Vision section below now clearly states it's not a working example.22/04/2021-01
All pending MLCube PRs have been merged into master.Known problems
05/05/2021
User environment needssudo
to run docker containers. A quick fix could be to replacecommand: docker
withcommand: sudo docker
in docker.yaml.Introduction
MLCommons™ Best Practices WG is working towards simplifying the process of running ML workloads, including MLCommons reference training and inference benchmarks. We have developed a prototype of a library that we call MLCube™.
The goal of this PR is to show how MLCube can be used to run MLCommons training and inference workloads, and to gather a feedback.
Vision
One possible way of interacting with MLCubes is presented in this section. To simplify the process of running ML models, users need to know the following:
mlcube describe
in a MLCube directory.Install MLCube:
Get the MLCommons SSD reference benchmark:
Explore what tasks SSD MLCube supports:
Run SSD benchmark using local Docker runtime:
Current implementation
We'll be updating this section as we merge MLCube PRs and make new MLCube releases.