CIFAR 100 Questions about fedjax HOT 5 CLOSED

Just wanted to post an update.
I just merged in #266 that adds the option for matching the preprocessing logic done by TFF.
I also added an example linear model for CIFAR-100 in #265 to show what's needed to check in and contribute a model.

I've also filed a separate issue #268 to add the ResNet-18 model for CIFAR-100 that's actually used in the "Adaptive Federated Optimization" paper. The issue details steps, requirements, etc.
Contributions are very welcomed and encouraged!

from fedjax.

Hi!

Thanks for reaching out to us about this.

1. The model for CIFAR100 was a work in progress but we decided to put it on hold until there was an explicit request for it. Our initial plan was to add a simple linear model that provides a complete example of all the requirements (e.g. baseline accuracy, hyperparameter configs, etc.) needed to add a model so that other collaborators could follow it as a guideline for contributing. If you're interested, we can work on adding this example PR for a simple model so that you can follow it as a guideline for contributing.
2. We actually are downloading the dataset from the same source as TFF. The only difference is that we apply additional preprocessing on top of the source data following pytorch-cifar. If you don't want to apply this preprocessing, you could just manually run fedjax.datasets.cifar100.load_split.

from fedjax.

Got it, thanks for letting me know!

from fedjax.

No problem!

I'm also working on some PRs to add an example model for CIFAR-100 and add an option to match the preprocessing done by TFF according to their baseline task tff.simulation.baselines.cifar100.create_image_classification_task

Hopefully those will help!

from fedjax.

Oh nice, good to hear -- looking forward to it!

from fedjax.