INNER CODE UNIT · Python

create_model

Tisha-runwal/Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare · pfl_hcare/fl/server.py:25

def create_model(dataset_name: str) -> nn.Module:
    """Return the appropriate model for a given dataset."""
    if dataset_name in ("har", "ucihar"):
        return HARClassifier(accept_flat=True)
    return HealthClassifier()


def load_dataset(dataset_name: str):
    """Load and return (train_dataset, test_dataset)."""
    if dataset_name in ("har", "ucihar"):
        from data.har_loader import HARDataset
        train_ds = HARDataset(split="train", download=False)
        test_ds = HARDataset(split="test", download=False)
    else:
        from data.mimic_loader import MedicalDataset
        train_ds = MedicalDataset(split="train")
        test_ds = MedicalDataset(split="test")
    return train_ds, test_ds

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