[mamba] Installing cpuonly PyTorch and torchvision from conda channel should not require cudatoolkit

🐛 Describe the bug

When installing CPU-only version of PyTorch 1.10 using the official guidelines from the website for using conda as package manager, the package cudatoolkit is also installed. The cudatoolkit package is very large to download (1 GB) and even larger after getting installed. The large size is concern especially in building Docker images.

Basic reproduction steps:

1. Use conda for a dry-run install of cpuonly pytorch=1.10 and torchvision.
2. Check in the output whether cudatooklit would have been installed or not.

The script below saves the dry-run’s output to a file and uses grep to check if cudatoolkit was indeed identified as a dependency.

# assuming conda is installed
conda create -n dry python=3.8
conda install -q -n dry \
    -c pytorch -c defaults -c conda-forge \
    cpuonly pytorch=1.10 torchvision \
    --dry-run > dry-run.txt
grep cudatoolkit dry-run.txt

Versions

PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 10 Enterprise
GCC version: Could not collect
Clang version: 13.0.1
CMake version: version 3.22.2
Libc version: N/A

Python version: 3.8.12 (default, Oct 12 2021, 03:01:40) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19042-SP0
Is CUDA available: N/A
CUDA runtime version: 11.2.67
GPU models and configuration: GPU 0: NVIDIA GeForce 940MX
Nvidia driver version: 472.88
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect

[motjuste]

Yes, with torchvision 0.12.0, it works as expected — no cudatoolkit is installed, and only the cpu versions are installed when asked for cpuonly. Unfortunately, one does have to update to pytorch 1.11.0, but that does not seem to be a breaking change for me at least. Thanks a lot for your work!

[rgommers]

This seems to have been fixed in the 0.12.0 release made 8 days ago. All conda packages now have a dependency on pytorch-mutex 1.0 (click the (i) icon on https://anaconda.org/pytorch/torchvision/files to verify):

@motjuste does it work for you now?