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A framework for conducting machine learning experiments in python

Project description

What is MLXP?

MLXP (Machine Learning eXperimentalist for Python) package is an open-source Python framework for managing multiple experiments with a flexible option structure from launching, and logging to querying results. A full documentation is available in the MLXP’s project page.

Key functionalities

  1. Launching several jobs automatically using hydra and hierarchical configs by adding a single decorator to the main task function.

  2. Logging outputs (metrics, artifacts, checkpoints) of a job in a uniquely assigned directory along with all metadata and configuration options to reproduce the experiment.

  3. Code version management by automatically generating a deployment version of the code based on the latest git commit.

  4. Submitting jobs to a cluster using a job scheduler.

  5. Exploiting the results of several experiments by easily reading, querying, grouping, and aggregating the output of several jobs.

Installing MLXP

You can install MLXP in a virtualenv/conda environment where pip is installed (check which pip):

Stable release

$ pip install MLXP

Main branch

$ pip install git+https://github.com/inria-thoth/mlxp@master#egg=mlxp

Requirements

Requirements

hydra-core

omegaconf

tinydb

setuptools

PyYAML

pandas

ply

dill

GitPython

Documentation

A full documentation is available in the MLXP’s official documentation website. See the following pages for more detailled information:

Quick start guide: for a simple example of how to use MLXP. Tutorial: to get a better understanding of all functionalities provided by MLXP. Documentation: for detailed documentation.

Acknowledgments

License

MLXP is distributed under MIT license.

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