Pytorch_geometric: libcudart.so.10.0 ERROR

[usherbob]

I could install it successfully, but when I tried

from torch_geometric.data import Data,

there would be an error:

ImportError: libcudart.so.10.0: cannot open shared object file: No such file or directory

The complete error message is below:

>>> from torch_geometric.data import Data
 Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_geometric/data/__init__.py", line 1, in <module>
    from .data import Data
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_geometric/data/data.py", line 2, in <module>
    from torch_geometric.utils import (contains_isolated_nodes,
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_geometric/utils/__init__.py", line 2, in <module>
    from .scatter import scatter_
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_geometric/utils/scatter.py", line 1, in <module>
    import torch_scatter
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_scatter/__init__.py", line 3, in <module>
    from .mul import scatter_mul
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_scatter/mul.py", line 3, in <module>
    from torch_scatter.utils.ext import get_func
  File "/home/bob/anaconda3/envs/torch_cu100/lib/python3.7/site-packages/torch_scatter/utils/ext.py", line 5, in <module>
    import torch_scatter.scatter_cuda
ImportError: libcudart.so.10.0: cannot open shared object file: No such file or directory 

I installed CUDA-9.0 and CUDA-10.0 on my PC, and used a symlink pointing cuda package from /usr/local/cuda-10.0/ to /usr/local/cuda/. I wondered if it may cause the error.

[rusty1s]

Did you compile both PyTorch and its extensions with the same CUDA version? You can check this via torch.version.cuda

[usherbob]

Thanks for your reply. It may be the problem you mentioned above. I tested as you mentioned:

>>> torch.version.cuda
'9.0.176'

I guess there is something wrong with CUDA version.
However, I don't know how to compile Pytorch with its corresponding CUDA version. May you give me some help? Thanks.
I tried my way, delete the original symlink and point /usr/local/cuda-9.0 to /usr/local/cuda, but it did not work.

[RobinFrcd]

You're saying that /usr/local/cuda-9.0 points toward /usr/local/cuda, I think it should be the other way around.

[usherbob]

I mean I created a symlink with code,

sudo ln -s /usr/local/cuda-9.0/ /usr/local/cuda

This could be useful for me as I have multiple CUDA on my PC, I could switch CUDA version with this code.
Since I have installed PyTorch through conda install, I knew nothing about compiling PyTorch as @rusty1s said. How could I fix it?

[rusty1s]

PyTorch was compiled with CUDA version 9. As far as I know, you can change that by reinstalling PyTorch from conda and selecting the right CUDA version. For installing PyG, your symlinked version must match the version of PyTorch (in your case 9). However, you need to recompile the extension packages (which get simply cached when you try a reinstall) with the right CUDA version, just changing the symlink is not enough.

[usherbob]

Many thanks. I'll have a try.

[rusty1s]

I created a FAQ for common installation errors. Let me know if this fixes your issues.

[RuihongQiu]

@rusty1s I have the similar problem with PyTorch compiled with CUDA 10. And my environment is using CUDA 10 also.

from torch_geometric.data import Data
4 if torch.cuda.is_available():                                             
----> 5     import torch_scatter.scatter_cuda                                      
6                                                                            
7                                                                                                                                                     
ImportError: libcudart.so.9.0: cannot open shared object file: No such file or directory                                                                              
In [3]: torch.version.cuda                                                         
Out[3]: '10.0.130'

[rusty1s]

Did you modify LD_LIBRARY_PATH to point to CUDA 10?

[RuihongQiu]

I have done it and my PyTorch is working all well.

[rusty1s]

Maybe this helps?

[RuihongQiu]

It doesn't work.

The most strange thing is that I use all packages with CUDA 10.0 but here it still needs to look for libcudart.so.9.0. The version doesn't match. It should not be like this.

@rusty1s

[RuihongQiu]

Fix it.

torch-scatter seems to constantly find *.so files from

/usr/local/cuda/lib64

And there are CUDA 9.0 10.0 and 10.1 on my server. /usr/local/cuda/lib64 is originally set to link CUDA 9.0. Though my ~/.bashrc has set to link /usr/local/cuda-10.0/lib64 for LD_LIBRARY_PATH. The installation still finds /usr/local/cuda/lib64.

So I just remove /usr/local/cuda, copy /usr/local/cuda-10.0 and rename it as /usr/local/cuda, without changing anything in ~/.bashrc. Uninstall and reinstall. Fix it.

And then torch-sparse will cause another libcusparse.so.10.0 problem. So I change lines in ~/.bashrc to point to /usr/local/cuda/. And all things done.

[rusty1s]

Really strange error, but glad that it‘s now working.

[usherbob]

Sorry for my late reply. I still believe these errors

ImportError: libcudart.so.xxx: cannot open shared object file: No such file or directory

arise from multiple Cuda version. When I opened that issue, I have tried to change Cuda from 9.0 to 10.0. However, I might have forgotten to source ~/.bashrc , which could be the reason that changing Cuda version did not work. Anyway, I did not reinstall pytorch or pytorch_geometric package, it just works now.

[silent567]

Really strange error, but glad that it‘s now working.

@rusty1s Hi, I encounted the same problem while installing torch_scatter by pip

libcudart.so.9.0: cannot open shared object file: No such file or directory

And, I believe it's because of the same reason that torch_scatter will always look for *.so from /usr/local/cuda/lib64 when it exists.

All the other requirements are meeted. The output is exactly the same as shown in https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html . And pytorch works very well.

I also have multiple CUDA version installed in a shared server. But I only have privilege to change the .bashrc instead of modifying the links to /usr/loca/cuda.

Have you fixed the problem? Which version should I use to avoid it?

Thanks! And the following are some details:

haotang@descartes:~/.local/cuda-10.0/bin$ python3 --version
Python 3.7.3
haotang@descartes:~/.local/cuda-10.0/bin$ clear
haotang@descartes:~/.local/cuda-10.0/bin$ python --version
Python 3.7.3
haotang@descartes:~/.local/cuda-10.0/bin$ python -c "import torch; print(torch.__version__)"
1.1.0
haotang@descartes:~/.local/cuda-10.0/bin$ python -c "import torch; print(torch.cuda.is_available())"
True
haotang@descartes:~/.local/cuda-10.0/bin$ echo $PATH
/home/haotang/bin:/home/haotang/.local/bin:/home/haotang/.local/cuda-10.0/bin/:/home/haotang/anaconda3/bin:/home/haotang/bin:/home/haotang/.local/bin:/home/haotang/.local/cuda-10.0/bin/:/home/haotang/anaconda3/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
haotang@descartes:~/.local/cuda-10.0/bin$ echo $CPATH
/home/haotang/.local/cuda-10.0/include/:/home/haotang/.local/cuda-10.0/include/:
haotang@descartes:~/.local/cuda-10.0/bin$ echo $LD_LIBRARY_PATH
/home/haotang/.local/cuda-10.0/lib64/:/home/haotang/.local/cuda-10.0/lib64/:
haotang@descartes:~/.local/cuda-10.0/bin$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
haotang@descartes:~/.local/cuda-10.0/bin$ python -c "import torch; print(torch.version.cuda)"
10.0.130
haotang@descartes:~/.local/cuda-10.0/bin$ pip install --verbose --no-cache-dir torch-scatter
Created temporary directory: /tmp/pip-ephem-wheel-cache-nolji8uu
Created temporary directory: /tmp/pip-req-tracker-wu3nanqf
Created requirements tracker '/tmp/pip-req-tracker-wu3nanqf'
Created temporary directory: /tmp/pip-install-mpf2opwn
Collecting torch-scatter
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  https://pypi.org:443 "GET /simple/torch-scatter/ HTTP/1.1" 200 1104
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    Found link https://files.pythonhosted.org/packages/6a/b0/ecffacddf573c147c70c6e43ce05d24f007155ce3fb436959d3d2a24da46/torch_scatter-1.0.2.tar.gz#sha256=ccda794c25265b3450206b7fb0bf74f16a0b45f3f72d9547a42e44648a32faee (from https://pypi.org/simple/torch-scatter/), version: 1.0.2
    Found link https://files.pythonhosted.org/packages/08/09/07b106f3e74246f4ecf6517013a053b6dd7486c4f889d81f39adc662431f/torch_scatter-1.0.3.tar.gz#sha256=e626993194819ba65cdf89a52fbbb7780569d9e157bc63dbef13ead6b7a33930 (from https://pypi.org/simple/torch-scatter/), version: 1.0.3
    Found link https://files.pythonhosted.org/packages/2d/70/df2bc259d9606f00854ca43b6839f9047ec44900563435e0067584c93864/torch_scatter-1.0.4.tar.gz#sha256=ec004d687e47da9d5477407849d815629fc8b571ee87aeeebf6af8ed6f16defc (from https://pypi.org/simple/torch-scatter/), version: 1.0.4
    Found link https://files.pythonhosted.org/packages/2f/97/c50a6aeaedc6924180c6f5810d2a7405ce11aa9b82ba4284badad549d665/torch_scatter-1.1.0.tar.gz#sha256=e534cc2ecb2f9d9b559b1513c
d411737d26ea5585d1d65ff571fec55f42a49de (from https://pypi.org/simple/torch-scatter/), version: 1.1.0
    Found link https://files.pythonhosted.org/packages/91/5f/eb1d3ef3810cb1165859d40db4d9ee6d7f1dfef97d7e5c34010055f43d95/torch_scatter-1.1.1.tar.gz#sha256=9db7f2c0a5cddf6cfde633e33db7c2c94eaab163e9f8edb46460d6414cc97917 (from https://pypi.org/simple/torch-scatter/), version: 1.1.1
    Found link https://files.pythonhosted.org/packages/d4/83/67eeea00c2db1959e2ff95d8680dbd756977bfab254bda8658f09dc3bc11/torch_scatter-1.1.2.tar.gz#sha256=766c2476f5da5ffc25fa8e249ccf50f594031cdce3922abb23559e8e3b14337a (from https://pypi.org/simple/torch-scatter/), version: 1.1.2
    Found link https://files.pythonhosted.org/packages/07/c0/f7ac424496f4a3bcb31aa993fba29077a6d42fc2624c66e90b58a566a98e/torch_scatter-1.2.0.tar.gz#sha256=3a0259105d07d264c740eec8e4267260a5c144cf55472abd26022fff4fd73281 (from https://pypi.org/simple/torch-scatter/), version: 1.2.0
    Found link https://files.pythonhosted.org/packages/24/b7/680c3b392a4b55a0ebfb480aabb0d5c188e94bb21790104175c8cd614947/torch_scatter-1.3.0.tar.gz#sha256=bf7d561b8ef12b39a99f5797c90b989a0ce2c3ee4de74dff3b170f2d8566e1d4 (from https://pypi.org/simple/torch-scatter/), version: 1.3.0
    Found link https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz#sha256=54cbad248350165ddc921ded3fe7a69be5d30c6536273a1a3282e375289f86ec (from https://pypi.org/simple/torch-scatter/), version: 1.3.1
  Using version 1.3.1 (newest of versions: 0.3.0, 1.0.2, 1.0.3, 1.0.4, 1.1.0, 1.1.1, 1.1.2, 1.2.0, 1.3.0, 1.3.1)
  Created temporary directory: /tmp/pip-unpack-o_v8c04y
  Starting new HTTPS connection (1): files.pythonhosted.org:443
  https://files.pythonhosted.org:443 "GET /packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz HTTP/1.1" 200 12787
  Downloading https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz
  Downloading from URL https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz#sha256=54cbad248350165ddc921ded3fe7a69be5d30c6536273a1a3282e375289f86ec (from https://pypi.org/simple/torch-scatter/)
  Added torch-scatter from https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz#sha256=54cbad248350165ddc921ded3fe7a69be5d30c6536273a1a3282e375289f86ec to build tracker '/tmp/pip-req-tracker-wu3nanqf'
    Running setup.py (path:/tmp/pip-install-mpf2opwn/torch-scatter/setup.py) egg_info for package torch-scatter
    Running command python setup.py egg_info
    running egg_info
    creating pip-egg-info/torch_scatter.egg-info
    writing pip-egg-info/torch_scatter.egg-info/PKG-INFO
    writing dependency_links to pip-egg-info/torch_scatter.egg-info/dependency_links.txt
    writing top-level names to pip-egg-info/torch_scatter.egg-info/top_level.txt
    writing manifest file 'pip-egg-info/torch_scatter.egg-info/SOURCES.txt'
    reading manifest file 'pip-egg-info/torch_scatter.egg-info/SOURCES.txt'
    reading manifest template 'MANIFEST.in'
    writing manifest file 'pip-egg-info/torch_scatter.egg-info/SOURCES.txt'
  Source in /tmp/pip-install-mpf2opwn/torch-scatter has version 1.3.1, which satisfies requirement torch-scatter from https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz#sha256=54cbad248350165ddc921ded3fe7a69be5d30c6536273a1a3282e375289f86ec
  Removed torch-scatter from https://files.pythonhosted.org/packages/35/d4/750403a8aa32cdb3d2d05849c6a10e4e0604de5e0cc94b81a0d0d69a75f3/torch_scatter-1.3.1.tar.gz#sha256=54cbad248350165ddc921ded3fe7a69be5d30c6536273a1a3282e375289f86ec from build tracker '/tmp/pip-req-tracker-wu3nanqf'
Installing collected packages: torch-scatter
  Created temporary directory: /tmp/pip-record-chwlm535
  Running setup.py install for torch-scatter ...     Running command /home/haotang/anaconda3/bin/python -u -c "import setuptools, tokenize;__file__='/tmp/pip-install-mpf2opwn/torch-scatter/setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" install --record /tmp/pip-record-chwlm535/install-record.txt --single-version-externally-managed --compile
    running install
    running build
    running build_py
    creating build
    creating build/lib.linux-x86_64-3.7
    creating build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/mul.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/__init__.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/div.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/max.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/mean.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/min.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/std.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/add.py -> build/lib.linux-x86_64-3.7/torch_scatter
    copying torch_scatter/sub.py -> build/lib.linux-x86_64-3.7/torch_scatter
    creating build/lib.linux-x86_64-3.7/test
    copying test/utils.py -> build/lib.linux-x86_64-3.7/test
    copying test/test_backward.py -> build/lib.linux-x86_64-3.7/test
    copying test/__init__.py -> build/lib.linux-x86_64-3.7/test
    copying test/test_std.py -> build/lib.linux-x86_64-3.7/test
    copying test/test_multi_gpu.py -> build/lib.linux-x86_64-3.7/test
    copying test/test_max_min.py -> build/lib.linux-x86_64-3.7/test
    copying test/test_forward.py -> build/lib.linux-x86_64-3.7/test
    creating build/lib.linux-x86_64-3.7/torch_scatter/utils
    copying torch_scatter/utils/__init__.py -> build/lib.linux-x86_64-3.7/torch_scatter/utils
    copying torch_scatter/utils/gen.py -> build/lib.linux-x86_64-3.7/torch_scatter/utils
    copying torch_scatter/utils/ext.py -> build/lib.linux-x86_64-3.7/torch_scatter/utils
    running build_ext
    building 'torch_scatter.scatter_cpu' extension
    creating build/temp.linux-x86_64-3.7
    creating build/temp.linux-x86_64-3.7/cpu
    gcc -pthread -B /home/haotang/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/haotang/anaconda3/include/python3.7m -c cpu/scatter.cpp -o build/temp.linux-x86_64-3.7/cpu/scatter.o -Wno-unused-variable -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=scatter_cpu -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
    cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
    g++ -pthread -shared -B /home/haotang/anaconda3/compiler_compat -L/home/haotang/anaconda3/lib -Wl,-rpath=/home/haotang/anaconda3/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.7/cpu/scatter.o -o build/lib.linux-x86_64-3.7/torch_scatter/scatter_cpu.cpython-37m-x86_64-linux-gnu.so
    building 'torch_scatter.scatter_cuda' extension
    creating build/temp.linux-x86_64-3.7/cuda
    gcc -pthread -B /home/haotang/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/haotang/anaconda3/include/python3.7m -c cuda/scatter.cpp -o build/temp.linux-x86_64-3.7/cuda/scatter.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=scatter_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
    cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
    /usr/local/cuda/bin/nvcc -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/haotang/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/haotang/anaconda3/include/python3.7m -c cuda/scatter_kernel.cu -o build/temp.linux-x86_64-3.7/cuda/scatter_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=scatter_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
    g++ -pthread -shared -B /home/haotang/anaconda3/compiler_compat -L/home/haotang/anaconda3/lib -Wl,-rpath=/home/haotang/anaconda3/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.7/cuda/scatter.o build/temp.linux-x86_64-3.7/cuda/scatter_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/torch_scatter/scatter_cuda.cpython-37m-x86_64-linux-gnu.so
    running install_lib
    creating /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/mul.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/__init__.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    creating /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils
    copying build/lib.linux-x86_64-3.7/torch_scatter/utils/__init__.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils
    copying build/lib.linux-x86_64-3.7/torch_scatter/utils/gen.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils
    copying build/lib.linux-x86_64-3.7/torch_scatter/utils/ext.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils
    copying build/lib.linux-x86_64-3.7/torch_scatter/div.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/max.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/mean.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/min.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/scatter_cuda.cpython-37m-x86_64-linux-gnu.so -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/std.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/add.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/sub.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
    copying build/lib.linux-x86_64-3.7/torch_scatter/scatter_cpu.cpython-37m-x86_64-linux-gnu.so -> /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter
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    copying build/lib.linux-x86_64-3.7/test/__init__.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/test
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    copying build/lib.linux-x86_64-3.7/test/test_multi_gpu.py -> /home/haotang/anaconda3/lib/python3.7/site-packages/test
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    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/mul.py to mul.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/__init__.py to __init__.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils/__init__.py to __init__.cpython-37.pyc
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    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/div.py to div.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/max.py to max.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/mean.py to mean.cpython-37.pyc
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    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/std.py to std.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/add.py to add.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/sub.py to sub.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/utils.py to utils.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/test_backward.py to test_backward.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/__init__.py to __init__.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/test_std.py to test_std.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/test_multi_gpu.py to test_multi_gpu.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/test_max_min.py to test_max_min.cpython-37.pyc
    byte-compiling /home/haotang/anaconda3/lib/python3.7/site-packages/test/test_forward.py to test_forward.cpython-37.pyc
    running install_egg_info
    running egg_info
    writing torch_scatter.egg-info/PKG-INFO
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    writing top-level names to torch_scatter.egg-info/top_level.txt
    reading manifest file 'torch_scatter.egg-info/SOURCES.txt'
    reading manifest template 'MANIFEST.in'
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    running install_scripts
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done
  Removing source in /tmp/pip-install-mpf2opwn/torch-scatter
Successfully installed torch-scatter-1.3.1
Cleaning up...
Removed build tracker '/tmp/pip-req-tracker-wu3nanqf'
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haotang@descartes:~/.local/cuda-10.0/bin$ python3 -c "import torch; import torch_scatter"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/__init__.py", line 3, in <module>
    from .mul import scatter_mul
  File "/home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/mul.py", line 3, in <module>
    from torch_scatter.utils.ext import get_func
  File "/home/haotang/anaconda3/lib/python3.7/site-packages/torch_scatter/utils/ext.py", line 5, in <module>
    import torch_scatter.scatter_cuda
ImportError: libcudart.so.9.0: cannot open shared object file: No such file or directory
haotang@descartes:~/.local/cuda-10.0/bin$

[silent567]

Hi, problem fixed. I have checked the setup.py and found the cuda_path is collected by pytorch.
pytorch checked three paths sequentially: CUDA_HOME, /usr/local/cuda, and at last nvcc's path.

So, a quick work-around is to set the environment variable CUDA_HOME by

export CUDA_HOME=<path>

The related issue: https://github.com/pytorch/pytorch/issues/22844

done

[FreyWang]

Did you modify LD_LIBRARY_PATH to point to CUDA 10?

really thank your solution!! Oh my god I was totally go crazy

[Silva-asilla]

FAQ

File not found :(