How to use the deepdish.apply_once function in deepdish

def temperature(y, T):
    y = y**(1 / T)
    return y / dd.apply_once(np.sum, y, [1])

M = 2500
        for k in range(int(np.ceil(X.shape[0] / M))):
            y = self.net_.forward_all(data=X[k*M:(k+1)*M]).values()[0].squeeze(axis=(2,3))
            prob[k*M:(k+1)*M] = y

        T = 30.0

        eps = 0.0001

        #prob = prob.clip(eps, 1-eps)

        log_prob = np.log(prob)
        print('log_prob', log_prob.min(), log_prob.max())
        #log_prob = log_prob.clip(min=-4, max=4)
        new_prob = np.exp(log_prob / T)
        new_prob /= dd.apply_once(np.sum, new_prob, [1])

        return new_prob