# Torch+cuda installation on CPU-only machine

**URL:** <https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962>\
**Category:** deployment\
**Created:** [January 10, 2023, 3:42pm UTC](https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962 "2023-01-10T15:42:13Z")\
**Posts on this page:** 4\
**Page:** 1

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**Author:** ![dsethz](https://discuss.pytorch.org/letter_avatar_proxy/v4/letter/d/f9ae1b/32.png) [@dsethz](https://discuss.pytorch.org/u/dsethz)\
**Post date:** [January 10, 2023, 3:42pm UTC](https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962/1 "2023-01-10T15:42:13Z")

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Hey,

**Question** : Is it feasible to install a CUDA-compatible version of `torch` (and `torchvision`) on a machine without a GPU (and no CUDA installed) (e.g. `pip install pip install torch==1.10.1+cu111`)?

**Context** : I want to declare `torch` as a dependency in my packaging meta-data. The project is a plug-in for a GUI-based software → intended for users without command line experience. Further, `torch` must be functional irrespective of `OS` and on GPU and CPU machines. However, automatically recognising if the machine has GPUs available at installation time does not seem to be possible (?, currently using [`poetry`](https://python-poetry.org)).

Similar issues have been discussed here:

> <https://stackoverflow.com/questions/74388129/poetry-how-to-deal-with-hardware-dependant-libraries>

> <https://github.com/python-poetry/poetry/issues/6409>
>
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> 
> \- \[x\] I have searched the \[issues\](https://github.com/python-poetry/poetry/issues) of this repo and believe that this is not a duplicate.
> 
> \## Issue
> 
> As mentioned in issue https://github.com/python-poetry/poetry/issues/4231 there is some confusion around installing PyTorch with CUDA but it is now somewhat resolved. It still requires a few steps, and all options have pretty serious flaws. Below are two options that worked for me, on Poetry version \`1.2.0\`.
> 
> \# Option 1 - wheel URLs for a specific platform
> 
> \* You will need to pick the specific wheels you want. These are listed here: https://download.pytorch.org/whl/torch\_stable.html. E.g. if you want CUDA 11.6, Python 3.10 and Windows, search that page for \`cu116-cp310-cp310-win\_amd64.whl\` to see the matches for \`torch\`, \`torchaudio\` and \`torchvision\`
> \* In your \`pyproject.toml\` file add the URLs like:
> 
> \`\`\`toml
> \[tool.poetry.dependencies\]
> python = "^3.10"
> numpy = "^1.23.2"
> torch = { url = "https://download.pytorch.org/whl/cu116/torch-1.12.1%2Bcu116-cp310-cp310-win\_amd64.whl"}
> torchaudio = { url = "https://download.pytorch.org/whl/cu116/torchaudio-0.12.1%2Bcu116-cp310-cp310-win\_amd64.whl"}
> torchvision = { url = "https://download.pytorch.org/whl/cu116/torchvision-0.13.1%2Bcu116-cp310-cp310-win\_amd64.whl"}
> \`\`\`
> \* Run \`poetry update\`. It will download a \_lot\_ of data (many GB) and take quite some time. And this doesn't seem to cache reliably (at least, I've waited 30 minutes+ at 56 Mbps three separate times while troubleshooting this, for the exact same wheels)
> 
> Note that each subsequent \`poetry update\` will do \_another\_ huge download and you'll see this message:
> \`\`\`
> • Updating torch (1.12.1+cu116 -\> 1.12.1+cu116 https://download.pytorch.org/whl/cu116/torch-1.12.1%2Bcu116-cp310-cp310-win\_amd64.whl)
> • Updating torchaudio (0.12.1+cu116 -\> 0.12.1+cu116 https://download.pytorch.org/whl/cu116/torchaudio-0.12.1%2Bcu116-cp310-cp310-win\_amd64.whl)
> • Updating torchvision (0.13.1+cu116 -\> 0.13.1+cu116 https://download.pytorch.org/whl/cu116/torchvision-0.13.1%2Bcu116-cp310-cp310-win\_amd64.whl)
> \`\`\`
> 
> \# Option 2 - alternate source
> 
> \`\`\`toml
> \[tool.poetry.dependencies\]
> python = "^3.10"
> numpy = "^1.23.2"
> torch = { version = "1.12.1", source="torch"}
> torchaudio = { version = "0.12.1", source="torch"}
> torchvision = { version = "0.13.1", source="torch"}
> 
> \[\[tool.poetry.source\]\]
> name = "torch"
> url = "https://download.pytorch.org/whl/cu116"
> secondary = true
> \`\`\`
> 
> This seems to have worked (although I already had the packages installed) but it reports errors like \`Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pillow/\`, but I think they get installed anyway (maybe a better message would be "Can't access pillow at 'https://download.pytorch.org/whl/cu116', falling back to pypi")
> 
> Also, if you later go on to do, say \`poetry add pandas\` (a completely unrelated library) you'll get a wall of messages like:
> \`\`\`
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pandas/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pandas/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pytz/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/python-dateutil/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/numpy/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pillow/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/requests/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/typing-extensions/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/certifi/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/urllib3/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/idna/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/charset-normalizer/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/python-dateutil/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/six/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/pytz/
> Source (torch): Authorization error accessing https://download.pytorch.org/whl/cu116/six/
> \`\`\`
> 
> This happens with or without \`secondary = true\` in the source config.
> 
> Maintainers: please feel free to edit the text of this if I've got something wrong.

Best,  
dsethz

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**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [January 10, 2023, 10:13pm UTC](https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962/2 "2023-01-10T22:13:46Z")

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`pip install torch torchvision` will install the default wheels hosted on PyPI, which ship with the CUDA 11.7 runtime, so it seems this would already solve your issue.

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**Author:** ![dsethz](https://discuss.pytorch.org/letter_avatar_proxy/v4/letter/d/f9ae1b/32.png) [@dsethz](https://discuss.pytorch.org/u/dsethz)\
**Post date:** [January 11, 2023, 10:49am UTC](https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962/3 "2023-01-11T10:49:41Z")

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ok, so do I understand you correctly, that installing a `torch` version that ships with e.g. CUDA 11.7 does not introduce unintended behaviour on a machine that does not have GPUs available?

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<div class="post-metadata">

**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [January 11, 2023, 7:17pm UTC](https://discuss.pytorch.org/t/torch-cuda-installation-on-cpu-only-machine/169962/4 "2023-01-11T19:17:19Z")

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Yes, I don’t think installing the default pip wheels with the CUDA 11.7 runtime has any side effects besides the size increase (since CUDA libs will be downloaded and stored).