An AutoML Library made with Optuna and PyTorch Lightning
Project description
An open-source AutoML Library in PyTorch
Installation
Recommended
pip install -U gradsflow
From source
pip install git+https://github.com/gradsflow/gradsflow@main
Highlights
- 2020-8-25: Released first version 0.0.1 ✨ :tada:
- 2020-8-29: Migrated from Optuna to Ray Tune. Read more...
What is GradsFlow?
!!! attention GradsFlow is changing fast and is not stable yet.
GradsFlow is based on Ray and PyTorch Lightning ⚡️ (support for other torch frameworks will be added soon). It leverages PyTorch Lightning Flash so that you don't have to write any PyTorch or Optuna code for model building or hyperparameter tuning 🚀
Although you might want to train a custom model and search hyperparameters, You can easily integrate any PyTorch/Lightning Flash Model with Gradsflow AutoModel ✨
-
gradsflow.core
: Core defines the building blocks of AutoML tasks. -
gradsflow.autotasks
: AutoTasks defines different ML/DL tasks which is provided by gradsflow AutoML API.
📑 Check out notebooks examples.
💬 Join the Slack group to chat with us.
🤗 Contribute
Contributions of any kind are welcome. Please check the Contributing Guidelines before contributing.
Code Of Conduct
We pledge to act and interact in ways that contribute to an open, welcoming, diverse, inclusive, and healthy community.
Read full Contributor Covenant Code of Conduct
Acknowledgement
GradsFlow is built with help of Ray and PyTorch Lightning 💜
Project details
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