from sklearn.model_selection import GroupShuffleSplit

def assign_splits(manifest, val_fraction=0.15, seed=42):
    train_data = manifest[manifest["orig_split"] == "train"]
    groups = train_data["subject_id"].values

    gss = GroupShuffleSplit(n_splits=1, test_size=val_fraction, random_state=seed)
    train_idx, val_idx = next(gss.split(X=train_data, y=None, groups=groups))

    train_subjects = set(train_data.iloc[train_idx]["subject_id"].unique())
    val_subjects = set(train_data.iloc[val_idx]["subject_id"].unique())

    # Crash loudly if leakage ever sneaks in
    assert train_subjects.isdisjoint(val_subjects), "Subject leak detected!"
    return train_subjects, val_subjects