python随机打乱代码实现

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train_data 和 train_label保持对应

state = np.random.get_state()
np.random.shuffle(train_data)
np.random.set_state(state)
np.random.shuffle(train_label)

原理

numpy.random.set_state(state)

Set the internal state of the generator from a tuple.

import numpy as np
 
state = np.random.get_state()
chance = np.random.permutation(20)
np.random.set_state(state)
chance2 = np.random.permutation(20)
 
print(chance,chance2)

输出

[13 17  7  1  4 12 15  8  3 16  5  6 11 18  2 14  9 10  0 19] [13 17  7  1  4 12 15  8  3 16  5  6 11 18  2 14  9 10  0 19]