Try to check if you have torch installed correctly:
Code:
→ D:\AI\kohya_ss [master ≡ +1 ~0 -0 !]› .\venv\Scripts\Activate.ps1
(venv) → D:\AI\kohya_ss [master ≡ +1 ~0 -0 !]› pip show torch
Name: torch
Version: 1.12.1+cu116
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email: packages@pytorch.org
License: BSD-3
Location: d:\ai\kohya_ss\venv\lib\site-packages
Requires: typing-extensions
Required-by: accelerate, fairscale, lion-pytorch, lycoris-lora, pytorch-lightning, timm, torchmetrics, torchvision, xformers
Make sure to first activate the venv before running pip.
Also, what is your cuda version? You should be able to check it like so:
Code:
(venv) → D:\AI\kohya_ss [master ≡ +1 ~0 -0 !]› nvidia-smi
Thu Mar 16 21:42:29 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 517.40 Driver Version: 517.40 CUDA Version: 11.7 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... WDDM | 00000000:01:00.0 On | N/A |
| 0% 55C P8 32W / 245W | 1386MiB / 24576MiB | 3% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
EDIT: nvidia-smi only shows the highest supported CUDA version actually, to get the actual install version you would need to run nvcc -V but that is not in $PATH by default. Try something like this instead:
Code:
(venv) → D:\AI\kohya_ss [master ≡ +1 ~0 -0 !]› ls "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\"
Directory: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
Mode LastWriteTime Length Name
---- ------------- ------ ----
d---- 10/04/2022 03:26 v11.1
d---- 09/08/2022 22:25 v11.4
d---- 09/08/2022 22:22 v11.6
(venv) → D:\AI\kohya_ss [master ≡ +1 ~0 -0 !]›
That should tell you which CUDA you have installed. 11.6 in my case, my driver supports up to 11.7