Hydra是用PyTorch编写的灵活的多任务学习框架

Hydra是用PyTorch编写的灵活的多任务学习框架

Hydra — a Multi-Task Learning Framework

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

Naive — a separate optimizer for each taskGradients averaging — average out the gradients to the network's bodyMGDA — described in the paper Multi-Task Learning as Multi-Objective Optimization (NIPS 2018)

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 pytorchconda 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

Examples of configuration files can be found here. A minimal example is available in starter.sh. Execute it as follows (will train with configurations in configs/toy_experiments/naive.yaml): ./starter.sh naive 50

Coming soon...

Proper framework documentation and examples.

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