Install nvidia drivers / cuda to support pytorch – needs cuda11.7 / 11.8

I am not sure what your issue is.
I have fedora 37 and fedora 38. Both with nvidia GPUs and both with the latest nvidia (530.41.03) and cuda (12.1) from rpmfusion.

Using the command given on the pytorch site – (pip3 install torch torchvision torchaudio) to do the install as my regular user I did the install of pytorch. Doing so it installed the runtime for cuda 11.7 during the install and properly completed the install. I also already had several of the necessary packages that would have been pulled in previously installed.
Note that wheel is one of the requisites that should be installed, and probably system wide with dnf install python3-wheel, though it can also be installed at the user level with pip install wheel.

Building wheels for collected packages: lit
  Building wheel for lit (setup.py) ... done
  Created wheel for lit: filename=lit-16.0.2-py3-none-any.whl size=88174 sha256=2e73d4a9bde7bc1d9342518fea107594d5ea37c1cb19d82221ce1f81d3add066
  Stored in directory: /home/USER/.cache/pip/wheels/fb/a8/04/72bc6a1756fb8716328752892dc4cc253e2d9a01dbcd3c0543
Successfully built lit
Installing collected packages: mpmath, lit, cmake, typing-extensions, sympy, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, networkx, jinja2, filelock, nvidia-cusolver-cu11, nvidia-cudnn-cu11, triton, torch, torchvision, torchaudio
Successfully installed cmake-3.26.3 filelock-3.12.0 jinja2-3.1.2 lit-16.0.2 mpmath-1.3.0 networkx-3.1 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 sympy-1.11.1 torch-2.0.0 torchaudio-2.0.1 torchvision-0.15.1 triton-2.0.0 typing-extensions-4.5.0

I also did the verification test properly.

$ cat torchtest.py 

import torch
x = torch.rand(5, 3)
print(x)



$ python torchtest.py 
tensor([[0.8762, 0.4845, 0.0485],
        [0.1443, 0.4145, 0.0638],
        [0.0959, 0.4716, 0.5804],
        [0.1758, 0.7861, 0.9566],
        [0.1510, 0.1411, 0.4047]])

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