undefined symbol: cusparseScsrgemm #1
Comments
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I will look into this. In the meantime, you can clone torch-sparse locally, remove the spspmm import in torch_sparse/init.py and run python setup.py install. Sparse sparse matrix multiplication currently has no use case in torch_geometric, but this may change in the near future. |
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Thank you for your help. The workaround works fine. Let me know, if you need more information. |
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Does the file |
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Yes it does, also a |
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Same problem here |
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Could you both try out a possible fix to this problem? I guess cusparse is not linked to the nvcc call. Please add -lcusparse as compiler argument to nvcc in setup.py (example can be found here). |
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Just tried it but the same error remains. However the path to the .so library changed: Modified setup.py: |
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I have the same issue. The suggested workaround gets me running though. |
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Which one do you mean? Adding |
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Removing the |
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Please modify if torch.cuda.is_available():
ext_modules += [
CUDAExtension(
'spspmm_cuda',
['cuda/spspmm.cpp', 'cuda/spspmm_kernel.cu'],
extra_link_args=['-l', 'cusparse'],
)
]
cmdclass['build_ext'] = BuildExtensionThis should hopefully work now (borrowed from here). |
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Hi, just tried this. Not sure if it is a fix, as I'm running into another problem but this time with torch_scatter: Reproducible for me using following commands (everything installs fine): #!/bin/bash
pipenv --rm
rm Pipfile Pipfile.lock
pipenv --python 3.6
pipenv lock --clear
export PATH=/opt/cuda/bin:$PATH
export CPATH=/opt/cuda/include
pipenv install http://download.pytorch.org/whl/cu92/torch-0.4.1-cp36-cp36m-linux_x86_64.whl
pipenv install torchvision
pipenv install cffi
pipenv install torch-scatter
pipenv install -e --dev ../pytorch_sparse
pipenv install torch-cluster
pipenv install torch-spline-conv
pipenv install torch-geometric
pipenv run python -c "from torch_sparse import spmm" |
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Ok, cool :) |
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In my case, I still get the same error as before. |
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So I already tried for python 3.7 and there it works fine. pipenv --python 3.7
export path=/opt/cuda/bin:$path
export cpath=/opt/cuda/include
pipenv install http://download.pytorch.org/whl/cu92/torch-0.4.1.post2-cp37-cp37m-linux_x86_64.whl
pipenv install torchvision
pipenv install cffi
pipenv install torch-scatter
pipenv install -e --dev ../pytorch_sparse
pipenv run python -c "from torch_sparse import spmm" |
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Just to confirm, you did uncomment the |
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Oh yeah you are right, I forgot to uncomment the |
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Ok. Sorry to make that mistake. Installing scatter from clone removes my previous error. However the cusparse error remains for me as well. Edit: That is for python 3.6 Edit: and for 3.7 |
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I could reproduce the bug on another machine and hopefully fixed it. Please checkout master and verify, so we can finally close this issue :) |
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Pulled from master and ran: However I still get the same error, it's the same for all the tests: |
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I could get along a bit more but when I execute the example given in the README: I get the error : The complete log is available here |
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Yes, |
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I wonder if this issue has been fixed besides the workaround? I tried the updated master but still got the undefined cusparseScsrgemm error. Thanks!
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It would be best if someone having this error could evaluate differing command options of -lsparse to identify the error and send a pull request. Not much else I can do :( |
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I tried the different options you mentioned so far. They did not work for me yet. If you have a list of other options I could try (or know where I could get the list of possible options), I will try them all and let you know. |
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I had the same problem (python 3.7) and installing from master seems to have fixed it (could run all the examples here, with values as float for @shagunsodhani example). Thank you for a great project with amazing code quality! |
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Hi, |
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The possible solutions seem to be to add: CUDAExtension(
...,
extra_link_args=[x],
)or CUDAExtension(
...,
extra_compile_args={'nvcc': [x]}.
})where Can you test these with |
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I tested this on 5836042. Let me know if I should be testing on any other commit as well. |
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Before I accept the pull request, can you test passing both, CUDAExtension(
...,
extra_link_args=['-lcusparse', '-l', 'cusparse'],
)as using |
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Sure I can do that. I have another request. Could you suggest me a minimal test to ensure that this particular issue is fixed? I did check it with the previous commit's test cases but I am not super confident that those tests are sufficient. |
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If the spspmm test runs for you, the issue is fixed. |
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Fixed 👍 |
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Updated |
Hi,
I'm trying to get the torch-geometry package to work and everything installs just fine.
But I'm getting following error during import from torch_sparse:
For me that can be reproduced with:
More info:
I'm not sure if this is a problem on my side or not. Would appreciate your help.
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