Comments (3)
Good question - we've never defined and documented the style we want to use for Flower, but you're right, we should pick one and declare it as the official style. It should be one that plays well with Sphinx to enable us to link to other parts of the codebase from the docstring itself. We've also started to use docformatter, so it would be good to pick a style that docformatter understands.
Perhaps it's best if we build a very small demo that showcases how a good docstrin in the format we pick looks like, how it can link to / mention other code fragments, and how docformatter itneracts with it. Would you like to take this topic @pedropgusmao ?
from flower.
Are we sticking to a specific docstring style? I found a few here that we could choose from. I particularly like the Numpydoc.
from flower.
Btw, I like the Numpydoc style as well. We sometimes have rather involved type signatures, so it helps to have a dedicated line for that. We should also pick a style that makes it clear which parameters are optional and what their default values are.
from flower.
Related Issues (20)
- Fatal Python error: Aborted HOT 1
- How to Save Client Models and results After Each Round in Flower HOT 4
- How can the client send custom content messages to the server? HOT 3
- Division error in function “divide_dataset” HOT 2
- flwr_datasets with custom/local dataset HOT 1
- No Prometheus nor Grafana Plots - /examples/flower-via-docker-compose HOT 3
- Add Flower Baseline: FedPFT HOT 4
- Dynamic timeout settings
- Running flw baseline fedAVG_MNIST with recommended parameters on README gives accuracy better than the paper "best result" HOT 1
- Facing issue with Flower Simulation with ResNet18 and MNIST dataset HOT 2
- Out of Memory while learning on Cifar with 100 clients HOT 1
- macOS: pip install flwr[simulation] uninstalls flwr 1.8.0 and installs 0.16.0 HOT 6
- RayActorClientProxy.get_parameters() missing 1 required positional argument: 'group_id'
- How to let the client train using the initial model provided by the server?
- How to get consistent order of spawned clients between multiple runs with Flower's simulation?
- flutter support HOT 1
- how to show the full args in task page? HOT 1
- Perform strategy in the sampled clients and its subset at the same time
- Method Doesn't Exist HOT 3
- ConnectionError: Couldn't reach 'cifar10' on the Hub (ConnectionError)
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from flower.