def METHOD_NAME(batch: np.ndarray, device: str):
    global MODEL
    if isinstance(batch, list):
        batch = np.array(batch)
    batch = einops.rearrange(batch.astype(np.float32) / 127.5 - 1.0, 'n h w c -> n c h w')
    batch = torch.from_numpy(batch).to(device)
    with torch.no_grad():
        db, mask = MODEL(batch)
        db = db.sigmoid().cpu().numpy()
        mask = mask.cpu().numpy()
    return db, mask