Hello there,
I am try to compare the initialization between torch and another backend which employs numpy for random generator.
I am testing a code as simple as:

import numpy as np
import torch
import random
def random_seeding(seed):
random.seed(seed)
torch.manual_seed(seed)
np.random.seed(seed)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
random_seeding(1)
print(np.random.randn(10))
random_seeding(1)
print(torch.randn(10))

where I tried to set the pytorch output to be equal to numpy. However, the starts values are completely different. and when I tried to copy the seed array (from get_rng_state) into the numpy random state, it breaks, so this option is not possible.
Is there a way to use numpy in pytorch as backend as random generator (ofc, avoiding the use of torch.from_numpy)
Regards