library for deep learning and privacy preserving deep learning
Project description
hideandseek
deep learning and privacy preserving deep learning library
import hideandseek as hs
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
cfg = OmegaConf.load('config.yaml') # omegaconf.OmegaConf.DictConfig object
model = DNN() # torch.nn.Module object
train_dataset = dataset # torch.utils.data.Dataset object
kwargs = {
'model': model,
'dataset': train_dataset,
'cfg_train': cfg,
'criterion': criterion,
}
node = hs.Node(**kwargs)
model.to(device)
node.step(local_T=20, horizon='epoch')
model.cpu()
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