python - 如何 "stash"随机状态生成器状态

Question

我正在播种随机数生成器以获得可重现的结果:

import random

SEED = 32412542
random.seed(SEED)

我想让它只为程序的一部分返回“不可重现”的随机值，如下所示:

import random

SEED = 32412542
random.seed(SEED)

my_list = [1, 2, 3, 4, 5]

res = random.sample(my_list, len(my_list))  # I would like result of this to be the same between runs of the program.

# Do some reproducible calculations, such as training neural network.
print(res)  # E.g. prints [3, 2, 4, 1, 5]

# What to do here?
res = random.sample(my_list, len(my_list))  # I would like result of this to be different between runs.

# Do some non-reproducible calculations, such as picking neural network parameters randomly.
print(res)  # Prints some random order.

res = random.sample(my_list, len(my_list))  # I would like result of this to be the same between runs of the program.

# Do some reproducible calculations, such as training neural network.
print(res)  # E.g. prints [2, 3, 1, 4, 5]

到目前为止，我想到的是在我希望它变得不可重现之前不使用任何参数进行播种，然后使用 SEED 值重新播种:

import random

SEED = 32412542
random.seed(SEED)

my_list = [1, 2, 3, 4, 5]

res = random.sample(my_list, len(my_list))
print(res)  # Prints: [3, 2, 4, 1, 5]

random.seed()
res = random.sample(my_list, len(my_list))
print(res)  # Prints some random order.

random.seed(SEED)
res = random.sample(my_list, len(my_list))
print(res)  # Prints: [3, 2, 4, 1, 5], so exactly what has been printed before.

问题是，重新播种后，会产生完全相同的一组随机值(显然 - 最终这就是使用特定值进行播种的目的)，这是我不希望发生的情况。我想以某种方式恢复随机生成器之前的状态。这可能吗？

Answer 1

您无法使用random 函数来执行此操作，但可以通过创建Random 类的实例来执行此操作。 As the documentation states:

Class Random can also be subclassed if you want to use a different basic generator of your own devising: in that case, override the random(), seed(), getstate(), and setstate() methods. Optionally, a new generator can supply a getrandbits() method — this allows randrange() to produce selections over an arbitrarily large range.

示例:

>>> import random
>>> r = random.Random()
>>> r.randint(1, 1000)
545
>>> r.randint(1, 1000)
349
>>> r.randint(1, 1000)
745
>>> r.randint(1, 1000)
792
>>> state = r.getstate()
>>> r.randint(1, 1000)
52
>>> r.randint(1, 1000)
799
>>> r.randint(1, 1000)
586
>>> r.randint(1, 1000)
581
>>> r.setstate(state)
>>> r.randint(1,1000)
52
>>> r.randint(1,1000)
799
>>> r.randint(1,1000)
586
>>> r.randint(1,1000)
581

<小时/>

实际上you can even using the functions from the random module ，我的错:

random.getstate() Return an object capturing the current internal state of the generator. This object can be passed to setstate() to restore the state.

random.setstate(state) state should have been obtained from a previous call to getstate(), and setstate() restores the internal state of the generator to what it was at the time getstate() was called.