Random seeding

pytorch_seed.py

# Source: @kastnerkyle
# https://twitter.com/kastnerkyle/status/1473361479143460872

import os
import random
import numpy as np
import torch

default_seed=4142
print("Setting all possible default seeds based on {}".format(default_seed))

# try to get deterministic runs
def seed_everything(seed=1234)
    random.seed(seed)
    tseed = random.randint(1, 1e6)
    tcseed = random.randint(1, 1e6)
    npseed = random.randint(1, 1e6)
    ospyseed = random.randint(1, 1e6)
    torch.manual_seed(tseed)
    torch.cuda.manual_seed_all(tcseed)
    np.random.seed(npseed)
    os.environ["PYTHONHASHSEED"] = str(ospyseed)
    # torch.backends.cudnn.deterministic = True
    
seed_everything(default_seed)

tf_seed.py

# Source: https://gist.github.com/rish-16/d3566c1940f62df31919763529a01ba4

import os
import random
import numpy as np
import tensorflow as tf
from tfdeterminism import patch

def seed_everything(s=1234):
  random.seed(s)
  np.random.seed(s)
  tf.random.set_seed(s)
  tf.experimental.numpy.random.seed(s)
  tf.set_random_seed(s)
  
  os.environ['TF_CUDNN_DETERMINISTIC'] = '1'
  os.environ['TF_DETERMINISTIC_OPS'] = '1'
  patch()
  
# https://github.com/NVIDIA/framework-determinism