JonasSchult / Mask3D

Mask3D predicts accurate 3D semantic instances achieving state-of-the-art on ScanNet, ScanNet200, S3DIS and STPLS3D.
MIT License
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CUDAAccelerator error while tranning #164

Open narges-tk opened 4 months ago

narges-tk commented 4 months ago

/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/torch/cuda/init.py:83: UserWarning: CUDA initialization: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 304: OS call failed or operation not supported on this OS (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:109.) return torch._C._cuda_getDeviceCount() > 0 Traceback (most recent call last): File "/home/ntakhtke/DL_models/mask3d_2/Mask3D/main_instance_segmentation.py", line 108, in main train(cfg) File "/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/hydra/main.py", line 27, in decorated_main return task_function(cfg_passthrough) File "/home/ntakhtke/DL_models/mask3d_2/Mask3D/main_instance_segmentation.py", line 77, in train runner = Trainer( File "/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/pytorch_lightning/utilities/argparse.py", line 345, in insert_env_defaults return fn(self, **kwargs) File "/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 433, in init self._accelerator_connector = AcceleratorConnector( File "/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 213, in init self._set_parallel_devices_and_init_accelerator() File "/home/ntakhtke/miniconda3/envs/mask3d_n2/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 530, in _set_parallel_devices_and_init_accelerator raise MisconfigurationException( pytorch_lightning.utilities.exceptions.MisconfigurationException: CUDAAccelerator can not run on your system since the accelerator is not available. The following accelerator(s) is available and can be passed into accelerator argument of Trainer: ['cpu'].