CODEWITHSUNDEEP
pythonanacondapytorchconda
questionto42
questionto42

Reputation: 9640

How to run pytorch with NVIDIA "cuda toolkit" version instead of the official conda "cudatoolkit" version

Some questions came up from https://superuser.com/questions/1572640/do-i-need-to-install-cuda-separately-after-installing-the-nvidia-display-driver. One of these questions:

Does conda pytorch need a different version than the official non-conda / non-pip cuda toolkit at https://developer.nvidia.com/cuda-toolkit?

In other words: Can I use the NVIDIA "cuda toolkit" for a pytorch installation?

Context:

If you go through the "command helper" at https://pytorch.org/get-started/locally/, you can choose between cuda versions 9.2, 10.1, 10.2 and None.

Taking 10.2 can result in:

conda install pytorch torchvision cudatoolkit=10.2 -c pytorch

Taking "None" builds the following command, but then you also cannot use cuda in pytorch:

conda install pytorch torchvision cpuonly -c pytorch

Could I then use NVIDIA "cuda toolkit" version 10.2 as the conda cudatoolkit in order to make this command the same as if it was executed with cudatoolkit=10.2 parameter?

The question arose since pytorch installs a different version (10.2 instead of the most recent NVIDIA 11.0), and the conda install takes additional 325 MB. If both versions were 11.0 and the installation size was smaller, you might not even notice the possible difference. But now it is clear that conda carries its own cuda version which is independent from the NVIDIA one.

Upvotes: 4

Views: 18859

Answers (2)

Mikhail Lobanov
Mikhail Lobanov

Reputation: 516

You can try to install PyTorch via Pip:

pip install torch torchvision

It is also official way of installing, available in "command helper" at https://pytorch.org/get-started/locally/.

It uses preinstalled CUDA and doesn't download own CUDA Toolkit. Also you can choose the version of CUDA to install PyTorch for:

pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio===0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

Upvotes: 3

Robert Crovella
Robert Crovella

Reputation: 152249

I imagine it is probably possible to get a conda-installed pytorch to use a non-conda-installed CUDA toolkit. I don't know how to do it, and in my experience, when using conda packages that depend on CUDA, its much easier just to provide a conda-installed CUDA toolkit, and let it use that, rather than anything else. This often means I have one CUDA toolkit installed inside conda, and one installed in the usual location.

However, regardless of how you install pytorch, if you install a binary package (e.g. via conda), that version of pytorch will depend on a specific version of CUDA (that it was compiled against, e.g. 10.2) and you cannot use any other version of CUDA, regardless of how or where it is installed, to satisfy that dependency.

Upvotes: 3

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