Torch.cuda.is_avaialble() still showing false

username: Luna_MarzouK
cooked: <pre><code class="lang-auto">python -m torch.utils.collect_env
</code></pre>
<p>the output:<br>
Collecting environment information…<br>
PyTorch version: 1.6.0<br>
Is debug build: No<br>
CUDA used to build PyTorch: Could not collect</p>
<p>OS: Microsoft Windows 10 Pro<br>
GCC version: Could not collect<br>
CMake version: Could not collect</p>
<p>Python version: 3.7<br>
Is CUDA available: No<br>
CUDA runtime version: Could not collect<br>
GPU models and configuration: GPU 0: NVIDIA GeForce 930MX<br>
Nvidia driver version: 465.89<br>
cuDNN version: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\bin\cudnn_ops_train64_8.dll</p>
<p>Versions of relevant libraries:<br>
[pip3] numpy==1.18.5<br>
[pip3] numpydoc==0.9.1<br>
[pip3] torch==1.8.1<br>
[pip3] torch-nightly==1.0.0.dev20190325<br>
[pip3] torchaudio==0.6.0<br>
[pip3] torchsummary==1.5.1<br>
[pip3] torchtext==0.9.1<br>
[pip3] torchvision==0.9.1<br>
[conda] _pytorch_select           0.1                       cpu_0<br>
[conda] _tflow_select             2.3.0                       mkl<br>
[conda] blas                      1.0                         mkl<br>
[conda] cudatoolkit               11.1.1               heb2d755_7    conda-forge<br>
[conda] libblas                   3.8.0                    14_mkl    conda-forge<br>
[conda] libcblas                  3.8.0                    14_mkl    conda-forge<br>
[conda] liblapack                 3.8.0                    14_mkl    conda-forge<br>
[conda] libmklml                  2019.0.5             haa95532_0<br>
[conda] mkl                       2019.4                      245<br>
[conda] mkl-service               2.3.0            py37h196d8e1_0<br>
[conda] mkl_fft                   1.3.0            py37h46781fe_0<br>
[conda] mkl_random                1.0.2            py37h343c172_0<br>
[conda] numpy                     1.18.1           py37hc71023c_0    conda-forge<br>
[conda] numpy-base                1.18.5           py37hc3f5095_0<br>
[conda] numpydoc                  0.9.1                      py_0<br>
[conda] pytorch                   1.6.0           cpu_py37h538a6d7_0<br>
[conda] tensorflow                2.1.0           mkl_py37ha977152_0<br>
[conda] tensorflow-base           2.1.0           mkl_py37h230818c_0<br>
[conda] torch                     1.8.1                    pypi_0    pypi<br>
[conda] torch-nightly             1.0.0.dev20190325          pypi_0    pypi<br>
[conda] torchaudio                0.6.0                      py37    pytorch<br>
[conda] torchsummary              1.5.1                    pypi_0    pypi<br>
[conda] torchtext                 0.9.1                    pypi_0    pypi<br>
[conda] torchvision               0.9.1                    pypi_0    pypi</p>
<pre><code class="lang-auto">nvcc -V
</code></pre>
<p>nvcc: NVIDIA (R) Cuda compiler driver<br>
Copyright (c) 2005-2020 NVIDIA Corporation<br>
Built on Tue_Sep_15_19:12:04_Pacific_Daylight_Time_2020<br>
Cuda compilation tools, release 11.1, V11.1.74<br>
Build cuda_11.1.relgpu_drvr455TC455_06.29069683_0</p>
<pre><code class="lang-auto">nvidia-smi.exe 
</code></pre>
<p>Thu Jun  3 14:37:38 2021<br>
±----------------------------------------------------------------------------+<br>
| NVIDIA-SMI 465.89       Driver Version: 465.89       CUDA Version: 11.3     |<br>
|-------------------------------±---------------------±---------------------+<br>
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |<br>
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |<br>
|                               |                      |               MIG M. |<br>
|===============================+======================+======================|<br>
|   0  NVIDIA GeForce … WDDM  | 00000000:01:00.0 Off |                  N/A |<br>
| N/A   44C    P8    N/A /  N/A |     37MiB /  2048MiB |      1%      Default |<br>
|                               |                      |                  N/A |<br>
±------------------------------±---------------------±---------------------+</p>
<p>±----------------------------------------------------------------------------+<br>
| Processes:                                                                  |<br>
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |<br>
|        ID   ID                                                   Usage      |<br>
|=============================================================================|<br>
|  No running processes found                                                 |<br>
±----------------------------------------------------------------------------+</p>