class AlphaLoss(torch.nn.Module):
    def __init__(self):
        super(AlphaLoss, self).__init__()

    def forward(self, y_value, value, y_policy, policy):
        value_error = (value - y_value) ** 2
        policy_error = torch.sum((-policy*
                                (1e-8 + y_policy.float()).float().log()), 1)
        total_error = (value_error.view(-1).float() + policy_error).mean()
        return total_error