The main page for SoftAdapt package, a family of methods for adaptive weighting of multi-tasking neural networks. This work was funded by the U.S. Air Force Research Lab, and recently approved for public release. Different parts of the code may be released at different times, accompanied by comprehensive examples. Meanwhile, the algorithm and the test cases can be found in our paper SoftAdapt: Techniques for Adaptive Loss Weighting of Neural Networks with Multi-Part Loss Functions.
Once the repository is cloned, you can use pip to install the package (in the directory):
pip install -e .
After installing the package, you can use any of the three variants during the training of the network. The call to SoftAdapt must be in the training loop (for each epoch), so that the package can get the most recent training statisitics. For example,
An example of SoftAdapt is as follows:
Code and math coming soon