# Installing PyTorch into a virtual Python environment
**URL:** https://discourse.nixos.org/t/installing-pytorch-into-a-virtual-python-environment/34720
**Category:** Uncategorized
**Created:** [October 28, 2023, 9:34am UTC](https://discourse.nixos.org/t/installing-pytorch-into-a-virtual-python-environment/34720 "2023-10-28T09:34:38Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@dnalor](https://discourse.nixos.org/u/dnalor)
#### Post date: [October 28, 2023, 9:34am UTC](https://discourse.nixos.org/t/installing-pytorch-into-a-virtual-python-environment/34720/1 "2023-10-28T09:34:38Z")
I’m trying to get PyTorch to work in a virtual environment on nixOS, but it doesn’t pick up the GPU:
```auto
$ python3 -m venv .venv
$ .venv/bin/pip install numpy torch
[...]
$ .venv/bin/python -c "import torch; print(torch.cuda.is_available())"
False
```
It does however work when using the globally installed torch (via `pkgs.python3.withPackages (p: p.torch)`:
```auto
$ python -c "import torch; print(torch.cuda.is_available())"
True
```
I tried digging into [https://github.com/NixOS/nixpkgs/blob/2353abf8a5324c41b1646737625c542ab7e82a16/pkgs/development/python-modules/torch/default.nix](https://github.com/NixOS/nixpkgs/blob/2353abf8a5324c41b1646737625c542ab7e82a16/pkgs/development/python-modules/torch/default.nix) to see what the difference is, but didn’t make it very far…
Some more info on both installations:
```auto
# from .venv:
$ .venv/bin/pip show torch
Name: torch
Version: 2.1.0
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: /home/roland/tmp/test/.venv/lib/python3.10/site-packages
Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions
Required-by:
# the global one from `pkgs.python3.withPackages (p: p.torch)`:
$ pip show torch
Name: torch
Version: 2.0.1
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: /nix/store/wzz04sdcldbd61vgrqgdi0h7p31lww6v-python3-3.10.13-env/lib/python3.10/site-packages
Requires: filelock, jinja2, networkx, sympy, typing-extensions
Required-by:
```
Interestingly the global one (the one that does work) doesn’t have any cuda things listed in its `Requires`.
---
### Author:  [@SergeK](https://discourse.nixos.org/u/SergeK)
#### Post date: [October 28, 2023, 10:19am UTC](https://discourse.nixos.org/t/installing-pytorch-into-a-virtual-python-environment/34720/2 "2023-10-28T10:19:35Z")
> `.venv/bin/pip install numpy torch`
> `.venv/bin/python -c "import torch; print(torch.cuda.is_available())"`
> `False`
PyTorch from PyPi doesn’t know where to find the cuda driver, you need to tell tell it explicitly e.g. like so: `LD_LIBRARY_PATH=/run/opengl-driver/lib python -c "import torch; ..."`
_This is because torch from PyPi is built specifically for FHS operating systems, i.e. systems that drop their libraries in the global `/usr/lib` and expose a global `/etc/ld.so.conf` file which tells them extra library search paths, including the location of the cuda driver (`libcuda.so`). If you want a better experience using prebuilt programs built with this assumption, you might also want to look into `programs.nix-ld.enable`._
> Interestingly the global one (the one that does work) doesn’t have any cuda things listed in its `Requires`.
This is because pytorch on pypi only recently started declaring as python dependencies at the dist-info level. They used to just copy cuda native libraries into their own wheels instead. For our source-build this is irrelevant, because we don’t event want to be using the python-packaged cuda, we want to link to our own `cudaPackages`, which has a bunch of patchelf hardening applied and is (or at least should be in the long run, we’re still not doing too great) split into independent outputs to reduce runtime closure sizes
---
### Author:  [@dnalor](https://discourse.nixos.org/u/dnalor)
#### Post date: [October 29, 2023, 6:56pm UTC](https://discourse.nixos.org/t/installing-pytorch-into-a-virtual-python-environment/34720/3 "2023-10-29T18:56:39Z")
Thanks for the helpful answer!