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Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

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Hydra — a Multi-Task Learning Framework

Python 3.6 Using PyTorch License: MIT Contributions welcome

Hydra is a flexible multi-task learning framework written in PyTorch 1.0. The following multi-objective optimization algorithms are implemented:

A comprehensive survey on these algorithms (and more) can be found in this blog article.

Installation

  • The code was written on Python 3.6. Clone this repository:

    git clone https://github.com/hav4ik/Hydra
    
  • It is recommended to use anaconda for installation of core packages (since conda packages comes with low-level libraries that can optimize the runtime):

    conda install pytorch torchvision cudatoolkit=10.0 -c pytorch
    conda install numpy pandas scikit-learn
    
  • Some of the packages are not available from anaconda, so you can install them using pip:

    pip install -r requirements.txt
    

Getting started

Coming soon...

  • Proper framework documentation and examples.

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Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

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