How can I find where CUDA 11.x for PyTorch-GPU 1.13 get installed on Windows 10 on my computer?
What I tried:
I installed the NVIDIA CUDA drivers and toolkit for Windows from the NVIDIA website. I can verify this by typing: !nvidia-smi
in Jupyter Lab, which gives me the following output. This indicates that the CUDA tools are installed, but not being used by my PyTorch package. I need to find out what version of CUDA drivers are installed so I can install the correct PyTorch-GPU package.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 513.63 Driver Version: 513.63 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| 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 Quadro P2000 WDDM | 00000000:01:00.0 Off | N/A |
| N/A 46C P8 N/A / N/A | 0MiB / 4096MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
I find many Ubuntu questions and answers for locating CUDA to add it to my PATH, but nothing specific for Windows 10.
For example: Pytorch CUDA installation fails, Pytorch CUDA installation using conda, pytorch-says-that-cuda-is-not-available
What are the equivalent Python commands on Windows 10 to locate the CUDA 11.x toolkits and driver version that my PyTorch-GPU package must use? And then how to fix the problem if PyTorch is out of sync?