Comments (5)
Dear @Jinfeng-Xu ,
Thank you for your kind words!
Oops, I forgot to change that part when deubgging.
It is fixed in this commit.
Please pull the latest version of this repo and try again.
And please let me know if there still exists a problem!
Thank you.
๊ณ ๋ง์์~
Best,
Adam
from federated-learning-in-pytorch.
Many Thanks!
But still, some bugs need to be fixed.
server.update() may raise an error for unexpected type
from federated-learning-in-pytorch.
Thank you for your report, @Jinfeng-Xu !
Could you please provide me corresponding command that causing such an error?
I presume that the error caused when you used BCELoss
.
If in that case (plus if the dataset you want to use has at most 2 classes), however, you should change it into BCEWithLogitsLoss
since any models provided in this repo do not have torch.nn.Sigmoid()
activation in the final layer of the model (i.e., last layer of the model's classifier
submodule).
FYI, it is an intended behavior even if users entered metrics requiring probability ouputs (e.g., AUROC), because it is implicitly transformed in MetricManager
instance.
Hope it helps.
Thank you!
Best,
Adam
from federated-learning-in-pytorch.
Thank you for your guidance, @vaseline555 !
Your guess is right, it works with BCEWithLogitsLoss.
Thanks for your help!
Sincerely,
Jinfeng
from federated-learning-in-pytorch.
Sounds great!
Hope you have a nice Friday. ๐
(๋ถ๊ธ in Korean)
Best,
Adam
from federated-learning-in-pytorch.
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