mlcommons / mlcommons/storage

Add Object parameters to all the workload yaml files

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enhancement
Dominant language
Python
Stars
203
Forks
67
Avg merge
20m
Merged PRs (30d)
8

Description

After the v3.0 submission round is over, we should add the Object API parameters to the yaml workload config files for the workloads we're no longer supporting in v3.0, such as unet3d. With that, the community can experiment with Object access in support of those workloads even though we're not using them in the benchmark any longer.

Ie: New DLIO with Object support with the older workload definitions like unet3d.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Locate the workload YAML configuration files and compare the older definitions, starting with an example such as unet3d. Determine which Object API parameters are needed for DLIO Object support, add them to the workloads no longer used in the v3.0 benchmark, and verify the updated YAML definitions remain valid.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data, machine-learning
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
55/100

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