for ep in range(eps):

            print('Ep {:3d}/{:3d}...'.format(ep+1,eps))

            alpha = alpha * np.exp(-0.2 * ep)

            for j in range(count):#random.permutation(count):
                x = inputs[:, j]
                y = []
                for i in range(self.dim_out):
                    #print(j)
                    #print(y[j])
                    y_i = self.weights[i] @ x + (0 if i == 0 else self.u[i][:i] @ np.array(y).T)

                    self.weights[i] += alpha * y_i * (x - y_i * self.weights[i])
                    norm = np.linalg.norm(self.weights[i])
                    if norm != 0:
                        self.weights[i] /= norm

                    self.u[i] += (- alpha * y_i * (y + y_i * self.u[i]) if i > 0 else 0)
                    norm = np.linalg.norm(self.u[i])
                    if norm != 0:
                        self.u[i] /= norm

                y.append(y_i)