Running FedMA with large input data shape

[jefersonf]

Hi @hwang595, a few weeks ago I made some questions in another issue thread about I problem that I had when trying to train a model with input image shape greater or equal to 224x224. Since then, I tried to reduce the dimensions of my problem to the default size, i.e. 32x32, and it worked well! But when I run using 224x224, I'm still locked in this training part.

So I'm gonna ask my questions here again:

• Is there such a relationship? Training input size and FedMA communication process? If that's true, what can we do about it?
• By adding a different model, in which part of the code should I take care? Besides changing, for example, the input dimensions to 1x224x224?

Obs.: As I'm working with medical images it is critical resize them.

Thanks for the great work!