Create seed.py

util/seed.py

@@ -0,0 +1,15 @@
+import os
+import random
+import numpy as np
+import torch
+
+def set_seed(seed=1064):
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed(seed)
+        torch.cuda.manual_seed_all(seed)
+    torch.backends.cudnn.deterministic = True
+    torch.backends.cudnn.benchmark = False
+