Print(torch.cuda.is_available()) False issue

Nothing6_Yin: <p>I’ve been struggling with this issue for 5 days with no luck. What I installed are the below ones:<br>
cuda_11.7.0_windows_network<br>
cudnn-windows-x86_64-8.8.1.3_cuda11-archive</p>
<p>I didn’t install CPU-only version. This is what I typed:<br>
pip3 install torch torchvision torchaudio --index-url <a href="https://download.pytorch.org/whl/cu117" rel="noopener nofollow ugc">https://download.pytorch.org/whl/cu117</a></p>
<p>This one came from Pytorch official website. I also tried this one, but no luck:<br>
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia</p>
<p>Here is the nvcc info:</p>
<pre><code class="lang-auto">nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:59:34_Pacific_Daylight_Time_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0

+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 531.41 Driver Version: 531.41 CUDA Version: 12.1 |
|-----------------------------------------+----------------------+----------------------+
| 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 RTX 3060 L... WDDM | 00000000:01:00.0 On | N/A |
| N/A 32C P8 11W / N/A| 148MiB / 6144MiB | 1% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
+---------------------------------------------------------------------------------------+'

'(base) C:\Users\Mono&gt;python -m torch.utils.collect_env
Collecting environment information...
PyTorch version: 2.0.0
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 10 Pro
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A

Python version: 3.9.12 (main, Apr 4 2022, 05:22:27) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19045-SP0
Is CUDA available: False
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3060 Laptop GPU
Nvidia driver version: 531.41
cuDNN version: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\bin\cudnn_ops_train64_8.dll
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture=9
CurrentClockSpeed=3201
DeviceID=CPU0
Family=107
L2CacheSize=4096
L2CacheSpeed=
Manufacturer=AuthenticAMD
MaxClockSpeed=3201
Name=AMD Ryzen 7 5800H with Radeon Graphics
ProcessorType=3
Revision=20480

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.21.5
[pip3] numpydoc==1.2
[pip3] torch==2.0.0
[pip3] torchaudio==2.0.0
[pip3] torchvision==0.15.0
[conda] blas 1.0 mkl
[conda] cpuonly 2.0 0 pytorch
[conda] mkl 2021.4.0 haa95532_640
[conda] mkl-service 2.4.0 py39h2bbff1b_0
[conda] mkl_fft 1.3.1 py39h277e83a_0
[conda] mkl_random 1.2.2 py39hf11a4ad_0
[conda] numpy 1.21.5 py39h7a0a035_1
[conda] numpy-base 1.21.5 py39hca35cd5_1
[conda] numpydoc 1.2 pyhd3eb1b0_0
[conda] pytorch 2.0.0 py3.9_cpu_0 pytorch
[conda] pytorch-cuda 11.7 h67b0de4_0 pytorch
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torchaudio 2.0.0 py39_cpu pytorch
[conda] torchvision 0.15.0 py39_cpu pytorch

</code></pre>

ptrblck: <p>It seems you are mixing the CPU-only binary with the CUDA one:</p>
<pre><code class="lang-auto">[conda] cpuonly 2.0 0 pytorch
[conda] pytorch 2.0.0 py3.9_cpu_0 pytorch
[conda] pytorch-cuda 11.7 h67b0de4_0 pytorch
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torchaudio 2.0.0 py39_cpu pytorch
[conda] torchvision 0.15.0 py39_cpu pytorch
</code></pre>
<p>so I would recommend uninstalling all PyTorch-related binaries and install the ones with the desired CUDA version or creating a new and empty virtual environment to install them.</p>

Nothing6_Yin: <p>Hi, Ptrblck.<br>
Thanks for the reply. How do I uninstall them completely? As I mentioned, I uninstalled/installed constantly for 5 days with various ways, but no luck.<br>
Could you give me a guide for uninstalling and installing properly, please?</p>