metadata

license: apache-2.0

Preparing OpenMLPerf dataset

To process the semi-raw MLPerf data into the OpenMLPerf dataset, run the following command:

# Untar raw files

bzip2 -d semi-raw-mlperf-data.tar.bz2
tar xvf semi-raw-mlperf-data.tar

# Create a virtual environment
python -m venv .venv

# Activate the virtual environment
source .venv/bin/activate

# Install the required packages
pip install -r requirements.txt

# Run the processing script
python process.py

The processed dataset will be saved both as data.json and data.parquet in the OpenMLPerf-dataset directory. The data.json file is a JSON file containing the processed data, while the data.parquet file is a Parquet file containing the same data in a more efficient format for storage and processing.

Preprocessing raw MLPerf results using MLCommons CMX

We preprocess official raw MLPerf data, such as inference v5.0, into semi-raw format compatible with the process.py script, using the MLCommons CM/CMX automation framework. This is done using through the "import mlperf results" automation action, which we plan to document in more detail soon.

License and Copyright

This project is licensed under the Apache License 2.0.

Portions of the data were adapted from the following MLCommons repositories, which are also licensed under the Apache 2.0 license:

Authors and maintaners

Daniel Altunay and Grigori Fursin (FCS Labs)