You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi,
Recently I've read your paper "Distributionally Robust Federated Averaging" carefully and I'm trying to reproduce the experiments in it.
However, I don't know how to get the plots from the codes, I think modifying main.py and run_mpi.py would help but it seems really complicated. Could you please give me some instructions?
Thanks!
The text was updated successfully, but these errors were encountered:
Thanks for your interest. The logs can be used to plot the results. There are some tools for this under the tools folder that can parse the log files and plot them like this one https://github.com/MLOPTPSU/FedTorch/blob/main/fedtorch/tools/load_console_records.py
In addition, I am working on adding Tensorboard plots, so there might not be a need for manually plotting the results.
Thanks for your interest. The logs can be used to plot the results. There are some tools for this under the tools folder that can parse the log files and plot them like this one https://github.com/MLOPTPSU/FedTorch/blob/main/fedtorch/tools/load_console_records.py In addition, I am working on adding Tensorboard plots, so there might not be a need for manually plotting the results.
Thanks for your answer! One more question that I'm confused with is that in this paper we're interested in the worst distribution accuracy among all the devices, but it seems that no functions in the codes can be utilized to obtain these accuracy. Could you please give me some instructions?
Hi,
Recently I've read your paper "Distributionally Robust Federated Averaging" carefully and I'm trying to reproduce the experiments in it.
However, I don't know how to get the plots from the codes, I think modifying main.py and run_mpi.py would help but it seems really complicated. Could you please give me some instructions?
Thanks!
The text was updated successfully, but these errors were encountered: