Fixing seeds affects performance?

autograd
1

Hey all,
Referring to topics like How could I fix the random seed absolutely. I couldn’t find any resources talking about the effects of fixing all seeds and goingtorch.backends.cudnn.enabled=False torch.backends.cudnn.deterministic=True. Does this affect performance of training at all ?

import torch
import torch.nn as nn
import numpy as np
import random
import my_model
import my_dataset

torch.manual_seed(123)
torch.cuda.manual_seed(123)
np.ranom.seed(123)
random.seed(123)
torch.backends.cudnn.enabled=False
torch.backends.cudnn.deterministic=True

def train():
...

if __name__ == '__main__':
    train()
2

I assume performance means training speed here. Yes, disabling cuDNN or selecting deterministic algorithms could slow down your code.