Can't install torch-(scatter|sparse|cluster|spline-conv)
See original GitHub issue📚 Installation
Running python -c "import torch; print(torch.__version__)"
gives 1.6.0
Running python -c "import torch; print(torch.version.cuda)"
gives 10.2
.
Yet, with the following:
pip install torch-scatter==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-${TORCH}.html
pip install torch-sparse==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-${TORCH}.html
pip install torch-cluster==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-${TORCH}.html
pip install torch-spline-conv==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-${TORCH}.html
pip install torch-geometric
I can install only torch-geometric
, while for the first 4 packages I get the following error:
...
File "/data/l989o/miniconda3/envs/spatial_uzh/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py", line 290, in __init__
wheel_version = Version(wheel.version)
File "/data/l989o/miniconda3/envs/spatial_uzh/lib/python3.8/site-packages/pip/_vendor/packaging/version.py", line 298, in __init__
raise InvalidVersion("Invalid version: '{0}'".format(version))
pip._vendor.packaging.version.InvalidVersion: Invalid version: 'latest+cu102'
Environment
- OS: RETTY_NAME=“CentOS Linux 7 (Core)”
- Python version: 3.8.0
- PyTorch version: 1.6.0
- CUDA/cuDNN version: 10.2
- GCC version: 7.2.0
- How did you try to install PyTorch Geometric and its extensions (wheel, source): wheel
- Any other relevant information:
Checklist
- I followed the installation guide.
- I cannot find my error message in the FAQ.
- [/] I set up CUDA correctly and can compile CUDA code via
nvcc
. Cuda works perfectly withtorch
, but I don’t havenvcc
(I am using a machine partly managed by the institute) - [/] I do have multiple CUDA versions on my machine. I think yes:
nvidia-smi
gives10.2
, but I can also usecuda 9.2
with torch, so yes, I guess I have multiple versions installed.
Additional context
Issue Analytics
- State:
- Created 3 years ago
- Comments:9 (6 by maintainers)
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This is now resolved. You can now install the packages via:
For example, for installing for PyTorch 1.7.0 with CUDA 11.0, type:
All “old” links are still intact. You can have a look at all possible combinations here.
Good solution, @rusty1s! Thanks again.