gradsflow 0.0.5

An open-source AutoML Library in PyTorch

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

• 2021-8-25: Released first version 0.0.1 ✨ :tada:
• 2021-8-29: Migrated from Optuna to Ray Tune. Read more...

What is GradsFlow?

!!! attention GradsFlow is changing fast and is not stable yet.

GradsFlow is an open-source AutoML Library for PyTorch that can train Deep Learning Models on your laptop or to a remote cluster directly from your laptop. Our aim is to enable non ML expert to train and build AI Products. GradsFlow leverages the power of PyTorch Lightning ⚡️ and Ray️. It leverages PyTorch Lightning Flash so that you don't have to write any code for model building or hyperparameter tuning 🚀

GradsFlow Model API provides a simple Keras like model training functionality 🔥. You can train any PyTorch model using model.fit(...) and it is easily customizable for more complex tasks.

You might want to train a custom model and search hyperparameters, You can easily integrate any PyTorch 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.

• gradsflow.model: Model defines the model training functionality.

📑 Check out notebooks examples.

💬 Join the Slack group to chat with us.

💙 Sponsor us on ko-fi

📧 Do you need support? Contact us at [e-mail]

🤗 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 awesome open-source projects (including but not limited to) PyTorch Lightning and Ray 💜

It takes inspiration from multiple APIs like Keras, FastAI.