Chaoyang He
Chaoyang He
@rAlexandre00 for production, you still use the same dataset structure by only setting the specific client_index's value in each dictionary. For example, rank 1 loads train_data_dict[1] = rank_1_data_set; rank 2...
> It looks like the aggregator just assumes that every client's data is every client. When I did what you suggested (only setting the specific client_index's value in each dictionary),...
@rAlexandre00 Hi for production, if you want to do training on 10 clients with 10 isolated devices, you can set this two arguments in "fedml_config.yaml" the same as: client_num_in_total: 10...
think about the following example, you will see why. ``` client_indexes = [2, 3, 7, 9] server process id = 0 worker process id = 1, 2, 3, 4 size...
what's the issue you met?
@MichaelLee-ceo you need to tune the hyper-parameters to make it work. Here are some references: https://github.com/FedML-AI/FedML/tree/master/benchmark Could you share the path and the script you run the experiment?
Please change this "single_process" value to "sp".
please check our latest version 0.7.272
check our FedCV project: http://fedml.ai/
@garganubhav Hi we have upgraded object detection supports at: https://github.com/FedML-AI/FedML/tree/master/python/app/fedcv you can also check it at here: https://open.fedml.ai/platform/appStore We've upgraded our library a lot in recent version. Here is a...