A modular configuration system for machine learning research
Project description
machinable
machinable is a modular configuration system for machine learning research. Using straight-forward conventions and a powerful configuration engine, it can help structuring your projects in a principled way to move quickly while enabling reuse and collaboration.
Explore key features at a glance →
Ready to start?
$ pip install machinable
Features
Powerful configuration
- YAML-based project-wide configuration files with expressive syntax
- Efficient configuration manipulation
- Modular code organisation to allow for encapsulation and re-use
- Import system to use 3rd party configuration and code without overhead
- 'Mixins' for horizontal inheritance structure
Efficient execution
- Works with existing code
- Support for seamless cloud execution
- Automatic code backups
- Managed randomness and reproducibility
- Advanced hyperparameter tuning using Ray Tune
Effective result collection and analysis
- Logging, tabular record writer and storage API
- File system abstraction (in-memory, AWS S3, and more)
- Flat-file result database with convenient query syntax
Documentation
Read the user guide to get started.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
machinable-2.3.0.tar.gz
(220.7 kB
view details)
File details
Details for the file machinable-2.3.0.tar.gz.
File metadata
- Download URL: machinable-2.3.0.tar.gz
- Upload date:
- Size: 220.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f7b56788b439f47f0590498444ae9cfc18633fa912a4c6b429b72f209b88e7af |
|
| MD5 | b79a87bd628446e87dfcf9f2e3771c0a |
|
| BLAKE2b-256 | 854fe174ff6f5d59292802d1c538579ca78d8eb8e4407462079f0c8562e91c1f |
