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
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