class MyLoss(nn.Module):
    def __init__(self, ca: float = 1.0, cb: float = 1.0) -> None:
        super().__init__()
        self.ca = ca
        self.cb = cb

    def forward(self, y_pred: Tuple[torch.Tensor, torch.Tensor], y_true: Tuple[torch.Tensor, torch.Tensor]) -> torch.Tensor:
        a_true, b_true = y_true
        a_pred, b_pred = y_pred
        return self.ca * F.mse_loss(a_pred, a_true) + self.cb * F.cross_entropy(b_pred, b_true)

loss = MyLoss(0.5, 1.0)
metrics = {
    "Loss": Loss(loss)
}
train_evaluator = create_supervised_evaluator(model, metrics, device, prepare_batch=prepare_batch)