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@fsvehla Yes, that could be an option. Maybe even allowing a name and a decoder, in case, a specific decoder is needed. E.g. there is a `case class Post(id: Long,...

Hi @girba und @chisandrei, 1. Opening the app does not create a crash.dump nor a PharoDebug.log 2. `xattr` includes `com.apple.quarantine` which might be the cause of my problem 3. I...

I would like the clients to store local model parameters which are used during training but are not send to the server. This would be usefull to implement personalisation strategies...

Thank you for adding the example. I'll try to implement the two personalized federating learning algorithms using this as a template. Would these algorithms be of interested as potential contributions...

I am happy to contribute. I have already implemented the algorithms and written test analogous to the ones for Federated Averaging. Unfortunately, writing the experimental scripts will require a few...

I opened a pull request #297 for the Adaptive Personalized Federated Learning Algorithm. I could add the other algorithm in a similar fashion after getting your feedback on this PR.

You have to change line 115 to: ``` zip(track_iter_progress((video_resize, len(video_resize))), video_origin)): ``` `track_iter_progress` expects either a sequence of type `Sequence` or a tuple of an iterable with its length`(Iterable, int)`...

The `.epub` contains the following files: * META-INF * OEBPS * iTunesMetadata-original.plist * iTunesMetadata.plist * mimetype

There also seems to be a bug when serializing and deserializing `AnyUrl`s. ``` from pydantic import AnyUrl, BaseModel class Test(BaseModel): url: AnyUrl expected = Test(url=AnyUrl("http://example.com")) json = expected.model_dump_json() parsed =...