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authorAUTOMATIC1111 <16777216c@gmail.com>2023-07-08 12:10:10 +0000
committerGitHub <noreply@github.com>2023-07-08 12:10:10 +0000
commitec9bbda3da846b4aa2f03b1e0f0952ffbc61f4f6 (patch)
tree5ae676b6ac7242ad082ab7421cf8ae9d50d52818 /modules/devices.py
parentc4c63dd5e4760c56405cef2e71abc5c3604c4578 (diff)
parent18256c5f0174126cb103afece2b39b6b831e034a (diff)
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Merge branch 'dev' into img2img-batch-png-info
Diffstat (limited to 'modules/devices.py')
-rw-r--r--modules/devices.py25
1 files changed, 18 insertions, 7 deletions
diff --git a/modules/devices.py b/modules/devices.py
index d8a34a0f..620ed1a6 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -1,5 +1,7 @@
import sys
import contextlib
+from functools import lru_cache
+
import torch
from modules import errors
@@ -13,13 +15,6 @@ def has_mps() -> bool:
else:
return mac_specific.has_mps
-def extract_device_id(args, name):
- for x in range(len(args)):
- if name in args[x]:
- return args[x + 1]
-
- return None
-
def get_cuda_device_string():
from modules import shared
@@ -154,3 +149,19 @@ def test_for_nans(x, where):
message += " Use --disable-nan-check commandline argument to disable this check."
raise NansException(message)
+
+
+@lru_cache
+def first_time_calculation():
+ """
+ just do any calculation with pytorch layers - the first time this is done it allocaltes about 700MB of memory and
+ spends about 2.7 seconds doing that, at least wih NVidia.
+ """
+
+ x = torch.zeros((1, 1)).to(device, dtype)
+ linear = torch.nn.Linear(1, 1).to(device, dtype)
+ linear(x)
+
+ x = torch.zeros((1, 1, 3, 3)).to(device, dtype)
+ conv2d = torch.nn.Conv2d(1, 1, (3, 3)).to(device, dtype)
+ conv2d(x)