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Segmentation fault of OptiXContext
Hi
I have encountered segmentation fault while testing your work with this command python train_gshelltet_deepfashion.py --config configs/deepfashion_mc_256.json --index 0 --trainset_path data/deepfashion3d_training_data/ --testset_path data/deepfashion3d_test_data/ --o ./result
DatasetNERF: 72 images with shape [1024, 1024] DatasetNERF: 72 images with shape [1024, 1024] DatasetNERF: 200 images with shape [1024, 1024] /opt/conda/lib/python3.10/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1695392020201/work/aten/src/ATen/native/TensorShape.cpp:3526.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Cuda path /usr/local/cuda Segmentation fault (core dumped)
the exact location of code that yields segmentation fault is at OptiXStateWrapper of render/optixutils/ops.py
class OptiXContext: def init(self): print("Cuda path", torch.utils.cpp_extension.CUDA_HOME) self.cpp_wrapper = _plugin.OptiXStateWrapper(os.path.dirname(file), torch.utils.cpp_extension.CUDA_HOME)
and here is information of my environment
pytorch3d 0.7.5 torch 2.1.0 torchvision 0.16.0 Cuda: 11.8 docker image: pytorch/pytorch:2.1.0-cuda11.8-cudnn8-devel gcc version: 9.4.0
Please let me know how to solve this issue
Without further detailed error messages, I can only tell that there seems to be some compatibility issue -- try check your GPU driver versions.
Related issue: https://github.com/NVlabs/nvdiffrecmc/issues/13
my GPU is RTX 3090 and the driver version is 535.146.02 could relatively higher driver version be a problem? it would be thankful if you can let me know name of your gpu hardware and driver version you used to implement gshell
Hey and sorry for the late response. Hope you have already solved the problem but here is the driver version in one of my working environments: 545.23.08