diffrent behavior between cpu and cuda #163
Description
when the cuda devices are invisible, my program runs well.
but when the cuda devices are available, it reports the error
Traceback (most recent call last): File "/home/boltzmachine/THG/train.py", line 10, in <module> from models.simple import Simple, Share File "/home/boltzmachine/THG/models/simple.py", line 5, in <module> from .GNN import DenseGatedRGCN File "/home/boltzmachine/THG/models/GNN.py", line 10, in <module> from torch_geometric.nn.inits import glorot, zeros File "/home/boltzmachine/miniconda3/envs/THG/lib/python3.7/site-packages/torch_geometric/__init__.py", line 5, in <module> import torch_geometric.data File "/home/boltzmachine/miniconda3/envs/THG/lib/python3.7/site-packages/torch_geometric/data/__init__.py", line 1, in <module> from .data import Data File "/home/boltzmachine/miniconda3/envs/THG/lib/python3.7/site-packages/torch_geometric/data/data.py", line 8, in <module> from torch_sparse import coalesce, SparseTensor File "/home/boltzmachine/miniconda3/envs/THG/lib/python3.7/site-packages/torch_sparse/__init__.py", line 15, in <module> f'{library}_{suffix}', [osp.dirname(__file__)]).origin) AttributeError: 'NoneType' object has no attribute 'origin'I use torch 1.7.0 and cu101
I uninstalled torch-sparse repeatedly until there's nothing install
and I installed by
pip install torch-sparse -f https://pytorch-geometric.com/whl/torch-1.7.0+cu101.html --no-cache-dir pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.7.0+cu101.html --no-cache-dir pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.7.0+cu101.html --no-cache-dir pip install torch-spline-conv -f https://pytorch-geometric.com/whl/torch-1.7.0+cu101.html --no-cache-dir pip --no-cache-dir install torch-geometricIt seems that there's no *.so of cuda in ~/miniconda3/envs/THG/lib/python3.7/site-packages/torch/cuda/
__init__.py _diag_cpu.so _metis_cpu.so _saint_cpu.so _spspmm_cpu.so bandwidth.py convert.py index_select.py metis.py padding.py rw.py select.py storage.py utils.py __pycache__ _ego_sample_cpu.so _relabel_cpu.so _sample_cpu.so _version_cpu.so cat.py diag.py masked_select.py mul.py permute.py saint.py spmm.py tensor.py _convert_cpu.so _hgt_sample_cpu.so _rw_cpu.so _spmm_cpu.so add.py coalesce.py eye.py matmul.py narrow.py reduce.py sample.py spspmm.py transpose.py One possible reason is that I am using a computer cluster. In my local environment, there is no cuda available until I submit a job by slurm