Metadata-Version: 2.1
Name: hideandseek
Version: 0.0.7.2
Summary: library for deep learning and privacy preserving deep learning
Home-page: https://github.com/jsyoo61/hideandseek
Author: JaeSung Yoo
Author-email: jsyoo61@korea.ac.kr
License: UNKNOWN
Description: # hideandseek
        deep learning and privacy preserving deep learning library.
        
        Currently integrating from experiment codes. (26.9.2021.)
        
            import torch
            from omegaconf import OmegaConf
            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') # trains for 20 epochs
            # node.step(local_T=1000, horizon='step') # trains for 1000 steps
            model.cpu()
        
            node.save()
        
            test_results = hs.eval.test(node)
            scores = hs.eval.scores(test_results)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
