您可以创建一个新轴并进行广播：
dis_mat = np.linalg.norm(feature_mat[:,None] - feature_mat, axis=-1)
定时：
feature_mat = np.random.rand(100,200)def a(): dis_mat = np.zeros([feature_mat.shape[0], feature_mat.shape[0]]) for i in range(feature_mat.shape[0]): for j in range(i, feature_mat.shape[0]): dis_mat[i, j] = np.linalg.norm( feature_mat[i, :] - feature_mat[j, :] ) dis_mat[j, i] = dis_mat[i, j]def b(): dis_mat = np.linalg.norm(feature_mat[:,None] - feature_mat, axis=-1)%timeit a()100 loops, best of 3: 20.5 ms per loop%timeit b()100 loops, best of 3: 11.8 ms per loop
