Open zwl8979 opened 1 year ago
Maybe you install the CPU-only spconv. Please install the spconv with CUDA. https://github.com/traveller59/spconv
Ok, thank you, because my cuda version is 10.1.105, the latest spconv2.x supports duda10.2 at least, so I changed the original spconv version to 1.2.1. solved! cuda10.2/11.x refer to: https://github.com/traveller59/spconv pip uninstall spconv git clone -b v1.2.1 https://github.com/traveller59/spconv.git python setup.py bdist_wheel cd dist pip install spconv-1.2.1-cp37-cp37m-linux_x86_64.whl
After I replace it with spconv1.2.1, what effect will spconv display as False, and the result of training with pre-training weights is 0!!! TorchVision: 0.9.0+cu101 OpenCV: 4.6.0 MMCV: 1.6.0 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 10.1 MMDetection: 2.25.3 MMSegmentation: 0.29.1 MMDetection3D: 1.0.0rc5+ spconv2.0: False
2022-11-28 23:59:39,479 - mmdet - INFO - Set random seed to 0, deterministic: False
/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/dense_heads/anchor3d_head.py:85: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
'dir_offset and dir_limit_offset will be depressed and be '
2022-11-28 23:59:39,900 - mmdet - INFO - initialize SECOND with init_cfg {'type': 'Kaiming', 'layer': 'Conv2d'}
2022-11-28 23:59:39,984 - mmdet - INFO - initialize SECONDFPN with init_cfg [{'type': 'Kaiming', 'layer': 'ConvTranspose2d'}, {'type': 'Constant', 'layer': 'NaiveSyncBatchNorm2d', 'val': 1.0}]
2022-11-28 23:59:39,989 - mmdet - INFO - initialize Anchor3DHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01, 'override': {'type': 'Normal', 'name': 'conv_cls', 'std': 0.01, 'bias_prob': 0.01}}
2022-11-28 23:59:39,991 - mmdet - INFO - initialize ResNet with init_cfg [{'type': 'Kaiming', 'layer': 'Conv2d'}, {'type': 'Constant', 'val': 1, 'layer': ['_BatchNorm', 'GroupNorm']}]
2022-11-28 23:59:40,300 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,302 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,303 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,304 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,306 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,307 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,308 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,311 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,312 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,313 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,314 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,316 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,317 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,322 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,327 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,330 - mmdet - INFO - initialize Bottleneck with init_cfg {'type': 'Constant', 'val': 0, 'override': {'name': 'norm3'}}
2022-11-28 23:59:40,343 - mmdet - INFO - initialize FPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
2022-11-28 23:59:40,382 - mmdet - INFO - Model:
DynamicMVXFasterRCNN(
(pts_voxel_layer): Voxelization(voxel_size=[0.05, 0.05, 0.1], point_cloud_range=[0, -40, -3, 70.4, 40, 1], max_num_points=-1, max_voxels=(-1, -1), deterministic=True)
(pts_voxel_encoder): DynamicVFE(
(scatter): DynamicScatter(voxel_size=[0.05, 0.05, 0.1], point_cloud_range=[0, -40, -3, 70.4, 40, 1], average_points=True)
(vfe_layers): ModuleList(
.....
init_cfg={'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
)
2022-11-28 23:59:49,050 - mmdet - INFO - load checkpoint from local path: /home/dell/zhangweili/mmdetection3d-master/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20210831_060805-83442923.pth
2022-11-28 23:59:49,220 - mmdet - INFO - Start running, host: dell@dell-PowerEdge-R740, work_dir: /home/dell/zhangweili/mmdetection3d-master/tools/tools/work_dirs/my_dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class
2022-11-28 23:59:49,220 - mmdet - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH ) CosineAnnealingLrUpdaterHook
(NORMAL ) CheckpointHook
(LOW ) EvalHook
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
before_train_epoch:
(VERY_HIGH ) CosineAnnealingLrUpdaterHook
(LOW ) IterTimerHook
(LOW ) EvalHook
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
before_train_iter:
(VERY_HIGH ) CosineAnnealingLrUpdaterHook
(LOW ) IterTimerHook
(LOW ) EvalHook
after_train_iter:
(ABOVE_NORMAL) OptimizerHook
(NORMAL ) CheckpointHook
(LOW ) IterTimerHook
(LOW ) EvalHook
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
after_train_epoch:
(NORMAL ) CheckpointHook
(LOW ) EvalHook
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
before_val_epoch:
(LOW ) IterTimerHook
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
before_val_iter: (LOW ) IterTimerHook
after_val_iter: (LOW ) IterTimerHook
after_val_epoch:
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
after_run:
(VERY_LOW ) TextLoggerHook
(VERY_LOW ) TensorboardLoggerHook
2022-11-28 23:59:49,220 - mmdet - INFO - workflow: [('train', 1)], max: 20 epochs 2022-11-28 23:59:49,221 - mmdet - INFO - Checkpoints will be saved to /home/dell/zhangweili/mmdetection3d-master/tools/tools/work_dirs/my_dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class by HardDiskBackend. 2022-11-28 23:59:50.060441: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 2022-11-28 23:59:50.060558: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 2022-11-28 23:59:50.060569: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. /home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/fusion_layers/coord_transform.py:35: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requiresgrad(True), rather than torch.tensor(sourceTensor). if 'pcd_rotation' in img_meta else torch.eye( [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 9/9, 5.2 task/s, elapsed: 2s, ETA: 0s Converting prediction to KITTI format [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 9/9, 366.0 task/s, elapsed: 0s, ETA: 0s Result is saved to /tmp/tmpe2hzt4vs/resultspts_bbox.pkl. 2022-11-29 00:00:20,843 - mmdet - INFO - Results of pts_bbox:
----------- AP11 Results ------------
Pedestrian AP11@0.50, 0.50, 0.50: bbox AP11:0.0000, 0.0000, 0.0000 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:0.00, 0.00, 0.00 Pedestrian AP11@0.50, 0.25, 0.25: bbox AP11:0.0000, 0.0000, 0.0000 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:0.00, 0.00, 0.00 Cyclist AP11@0.50, 0.50, 0.50: bbox AP11:0.0000, 0.0000, 0.0000 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:0.00, 0.00, 0.00 Cyclist AP11@0.50, 0.25, 0.25: bbox AP11:0.0000, 0.0000, 0.0000 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:0.00, 0.00, 0.00 Car AP11@0.70, 0.70, 0.70: bbox AP11:3.0303, 3.0303, 3.0303 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:3.03, 3.03, 3.03 Car AP11@0.70, 0.50, 0.50: bbox AP11:3.0303, 3.0303, 3.0303 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:3.03, 3.03, 3.03
Overall AP11@easy, moderate, hard: bbox AP11:1.0101, 1.0101, 1.0101 bev AP11:0.0000, 0.0000, 0.0000 3d AP11:0.0000, 0.0000, 0.0000 aos AP11:1.01, 1.01, 1.01
----------- AP40 Results ------------
Pedestrian AP40@0.50, 0.50, 0.50: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00 Pedestrian AP40@0.50, 0.25, 0.25: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00 Cyclist AP40@0.50, 0.50, 0.50: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00 Cyclist AP40@0.50, 0.25, 0.25: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00 Car AP40@0.70, 0.70, 0.70: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00 Car AP40@0.70, 0.50, 0.50: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00
Overall AP40@easy, moderate, hard: bbox AP40:0.0000, 0.0000, 0.0000 bev AP40:0.0000, 0.0000, 0.0000 3d AP40:0.0000, 0.0000, 0.0000 aos AP40:0.00, 0.00, 0.00
2022-11-29 00:00:20,844 - mmdet - INFO - Exp name: my_dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py 2022-11-29 00:00:20,844 - mmdet - INFO - Epoch(val) [1][9] pts_bbox/KITTI/Pedestrian_3D_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Car_3D_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_easy_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP11_easy_strict: 3.0303, pts_bbox/KITTI/Car_3D_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_moderate_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP11_moderate_strict: 3.0303, pts_bbox/KITTI/Car_3D_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_hard_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP11_hard_strict: 3.0303, pts_bbox/KITTI/Car_3D_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_easy_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP11_easy_loose: 3.0303, pts_bbox/KITTI/Car_3D_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_moderate_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP11_moderate_loose: 3.0303, pts_bbox/KITTI/Car_3D_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP11_hard_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP11_hard_loose: 3.0303, pts_bbox/KITTI/Overall_3D_AP11_easy: 0.0000, pts_bbox/KITTI/Overall_BEV_AP11_easy: 0.0000, pts_bbox/KITTI/Overall_2D_AP11_easy: 1.0101, pts_bbox/KITTI/Overall_3D_AP11_moderate: 0.0000, pts_bbox/KITTI/Overall_BEV_AP11_moderate: 0.0000, pts_bbox/KITTI/Overall_2D_AP11_moderate: 1.0101, pts_bbox/KITTI/Overall_3D_AP11_hard: 0.0000, pts_bbox/KITTI/Overall_BEV_AP11_hard: 0.0000, pts_bbox/KITTI/Overall_2D_AP11_hard: 1.0101, pts_bbox/KITTI/Pedestrian_3D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Pedestrian_3D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Pedestrian_BEV_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Pedestrian_2D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Cyclist_3D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_BEV_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Cyclist_2D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Car_3D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP40_easy_strict: 0.0000, pts_bbox/KITTI/Car_3D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP40_moderate_strict: 0.0000, pts_bbox/KITTI/Car_3D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Car_2D_AP40_hard_strict: 0.0000, pts_bbox/KITTI/Car_3D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP40_easy_loose: 0.0000, pts_bbox/KITTI/Car_3D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP40_moderate_loose: 0.0000, pts_bbox/KITTI/Car_3D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Car_BEV_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Car_2D_AP40_hard_loose: 0.0000, pts_bbox/KITTI/Overall_3D_AP40_easy: 0.0000, pts_bbox/KITTI/Overall_BEV_AP40_easy: 0.0000, pts_bbox/KITTI/Overall_2D_AP40_easy: 0.0000, pts_bbox/KITTI/Overall_3D_AP40_moderate: 0.0000, pts_bbox/KITTI/Overall_BEV_AP40_moderate: 0.0000, pts_bbox/KITTI/Overall_2D_AP40_moderate: 0.0000, pts_bbox/KITTI/Overall_3D_AP40_hard: 0.0000, pts_bbox/KITTI/Overall_BEV_AP40_hard: 0.0000, pts_bbox/KITTI/Overall_2D_AP40_hard: 0.0000 /home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/fusion_layers/coord_transform.py:35: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requiresgrad(True), rather than torch.tensor(sourceTensor). if 'pcd_rotation' in img_meta else torch.eye( [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 9/9, 5.2 task/s, elapsed: 2s, ETA: 0s Converting prediction to KITTI format [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 9/9, 391.3 task/s, elapsed: 0s, ETA: 0s Result is saved to /tmp/tmpu2avay8u/resultspts_bbox.pkl.
Hi, we have support spconv1.x in mmcv, so you don't need to install spconv1.x. And can you use default mmcv's spconv to try again?
And I suggest you check your env by PointPillars model.
@VVsssssk @JingweiZhang12
1. May I use when building a virtual environment:
conda activate -n mmdtection3d python=3.7 cuda=11.1 cudnn=8005 pytorch=0.10.0 torchvision=0.11.0 pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple pip install -r requirements/mminstall.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
2. When we set up the environment for testing, this error still popped up:
(mmdetection3d) ubuntu@ubuntu-ThinkStation-P920:~/zhangweili/mmdetection3d-master$ python demo/pcd_demo.py demo/data/kitti/kitti_000008.bin configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py checkpoints/hv_second_secfpn_6x8_80e_kitti-3d-car_20200620_230238-393f000c.pth --show
/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/dense_heads/anchor3d_head.py:85: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
'dir_offset and dir_limit_offset will be depressed and be '
load checkpoint from local path: checkpoints/hv_second_secfpn_6x8_80e_kitti-3d-car_20200620_230238-393f000c.pth
[Exception|native_pair]indices=torch.Size([13092, 4]),bs=1,ss=[41, 1600, 1408],algo=ConvAlgo.Native,ksize=[3, 3, 3],stride=[1, 1, 1],padding=[1, 1, 1],dilation=[1, 1, 1],subm=True,transpose=False
SPCONV_DEBUG_SAVE_PATH not found, you can specify SPCONV_DEBUG_SAVE_PATH as debug data save path to save debug data which can be attached in a issue.
Traceback (most recent call last):
File "demo/pcd_demo.py", line 44, in
May I ask how to solve this problem? Is the reason for this problem that all dependencies cannot be installed directly? thanks!
_libgcc_mutex 0.1 main
_openmp_mutex 5.1 1_gnu
absl-py 1.3.0 pypi_0 pypi
addict 2.4.0 pypi_0 pypi
anyio 3.6.2 pypi_0 pypi
argon2-cffi 21.3.0 pypi_0 pypi
argon2-cffi-bindings 21.2.0 pypi_0 pypi
astor 0.8.1 pypi_0 pypi
asynctest 0.13.0 pypi_0 pypi
attrs 22.2.0 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
beautifulsoup4 4.11.1 pypi_0 pypi
black 22.12.0 pypi_0 pypi
bleach 5.0.1 pypi_0 pypi
ca-certificates 2022.10.11 h06a4308_0
cachetools 4.2.4 pypi_0 pypi
ccimport 0.4.2 pypi_0 pypi
certifi 2022.12.7 py37h06a4308_0
cffi 1.15.1 pypi_0 pypi
charset-normalizer 2.1.1 pypi_0 pypi
click 8.1.3 pypi_0 pypi
codecov 2.1.12 pypi_0 pypi
colorama 0.4.6 pypi_0 pypi
configargparse 1.5.3 pypi_0 pypi
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cumm 0.3.7 pypi_0 pypi
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dash 2.7.1 pypi_0 pypi
dash-core-components 2.0.0 pypi_0 pypi
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debugpy 1.6.4 pypi_0 pypi
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idna 3.4 pypi_0 pypi
imageio 2.23.0 pypi_0 pypi
importlib-metadata 4.2.0 pypi_0 pypi
importlib-resources 5.10.2 pypi_0 pypi
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ipykernel 6.16.2 pypi_0 pypi
ipython 7.34.0 pypi_0 pypi
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isort 5.11.4 pypi_0 pypi
itsdangerous 2.1.2 pypi_0 pypi
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joblib 1.2.0 pypi_0 pypi
jsonschema 4.17.3 pypi_0 pypi
jupyter 1.0.0 pypi_0 pypi
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kiwisolver 1.4.4 pypi_0 pypi
kwarray 0.6.7 pypi_0 pypi
lark 1.1.5 pypi_0 pypi
ld_impl_linux-64 2.38 h1181459_1
libffi 3.4.2 h6a678d5_6
libgcc-ng 11.2.0 h1234567_1
libgomp 11.2.0 h1234567_1
libstdcxx-ng 11.2.0 h1234567_1
llvmlite 0.36.0 pypi_0 pypi
lyft-dataset-sdk 0.0.8 pypi_0 pypi
markdown 3.3.5 pypi_0 pypi
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mistune 2.0.4 pypi_0 pypi
mmcls 0.25.0 pypi_0 pypi
mmcv-full 1.6.0 pypi_0 pypi
mmdet 2.26.0 pypi_0 pypi
mmdet3d 1.0.0rc6 dev_0
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open3d 0.16.0 pypi_0 pypi
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openssl 1.1.1s h7f8727e_0
opt-einsum 3.3.0 pypi_0 pypi
packaging 22.0 pypi_0 pypi
pandas 1.3.5 pypi_0 pypi
pandocfilters 1.5.0 pypi_0 pypi
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pip 22.3.1 py37h06a4308_0
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py 1.11.0 pypi_0 pypi
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pycparser 2.21 pypi_0 pypi
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pytest 7.2.0 pypi_0 pypi
pytest-cov 4.0.0 pypi_0 pypi
pytest-runner 6.0.0 pypi_0 pypi
python 3.7.15 h7a1cb2a_1
python-dateutil 2.8.2 pypi_0 pypi
pytz 2022.7 pypi_0 pypi
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pyzmq 24.0.1 pypi_0 pypi
qtconsole 5.4.0 pypi_0 pypi
qtpy 2.3.0 pypi_0 pypi
readline 8.2 h5eee18b_0
requests 2.28.1 pypi_0 pypi
requests-oauthlib 1.3.1 pypi_0 pypi
rsa 4.9 pypi_0 pypi
scikit-image 0.19.3 pypi_0 pypi
scikit-learn 1.0.2 pypi_0 pypi
scipy 1.4.1 pypi_0 pypi
send2trash 1.8.0 pypi_0 pypi
setuptools 65.5.0 py37h06a4308_0
shapely 2.0.0 pypi_0 pypi
six 1.16.0 pypi_0 pypi
sniffio 1.3.0 pypi_0 pypi
soupsieve 2.3.2.post1 pypi_0 pypi
spconv 2.2.6 pypi_0 pypi
sqlite 3.40.0 h5082296_0
tabulate 0.9.0 pypi_0 pypi
tenacity 8.1.0 pypi_0 pypi
tensorboard 2.1.1 pypi_0 pypi
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termcolor 2.2.0 pypi_0 pypi
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tifffile 2021.11.2 pypi_0 pypi
tinycss2 1.2.1 pypi_0 pypi
tk 8.6.12 h1ccaba5_0
toml 0.10.2 pypi_0 pypi
tomli 2.0.1 pypi_0 pypi
torch 1.10.0+cu111 pypi_0 pypi
torchaudio 0.10.0+rocm4.1 pypi_0 pypi
torchvision 0.11.0+cu111 pypi_0 pypi
tornado 6.2 pypi_0 pypi
tqdm 4.64.1 pypi_0 pypi
traitlets 5.8.0 pypi_0 pypi
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ubelt 1.2.3 pypi_0 pypi
urllib3 1.26.13 pypi_0 pypi
waymo-open-dataset-tf-2-1-0 1.2.0 pypi_0 pypi
wcwidth 0.2.5 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
websocket-client 1.4.2 pypi_0 pypi
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wheel 0.37.1 pyhd3eb1b0_0
widgetsnbextension 4.0.5 pypi_0 pypi
wrapt 1.14.1 pypi_0 pypi
xdoctest 1.1.0 pypi_0 pypi
xz 5.2.8 h5eee18b_0
yapf 0.32.0 pypi_0 pypi
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@VVsssssk @JingweiZhang12 @ execute statement:pyhton ./mmdet3d/utils/collect_envs.py fatal: not a git repository (or any of the parent directories): .git sys.platform: linux Python: 3.7.15 (default, Nov 24 2022, 21:12:53) [GCC 11.2.0] CUDA available: True GPU 0: NVIDIA RTX A6000 CUDA_HOME: /usr/local/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.10.0+cu111 PyTorch compiling details: PyTorch built with:
TorchVision: 0.11.0+cu111 OpenCV: 4.7.0 MMCV: 1.6.0 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 11.1 MMDetection: 2.26.0 MMSegmentation: 0.29.1 MMDetection3D: 1.0.0rc6+ spconv2.0: True It took almost two weeks to build the light environment, please solve it, thank you!
Is it done? I came across this issue recently.
Prerequisite
Task
I'm using the official example scripts/configs for the officially supported tasks/models/datasets.
Branch
master branch https://github.com/open-mmlab/mmdetection3d
Environment
CUDA_HOME: /usr/local/cuda-10.1/ NVCC: Cuda compilation tools, release 10.1, V10.1.10 GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609 PyTorch: 1.8.0+cu101 PyTorch compiling details: PyTorch built with:
TorchVision: 0.9.0+cu101 OpenCV: 4.6.0 MMCV: 1.6.0 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 10.1 MMDetection: 2.25.3 MMSegmentation: 0.29.1 MMDetection3D: 1.0.0rc5+ spconv2.0: True
<<< conda initialize <<<
export CUDA_HOME=/usr/local/cuda-10.1/ export PATH=$PATH:/usr/local/cuda-10.1/bin export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.1/lib64 export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda-10.1/lib64
cuda
export PATH=$PATH:/usr/local/cuda/bin export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64 export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/lib64
Reproduces the problem - code sample
2022-11-27 23:17:22,114 - mmdet - INFO - workflow: [('train', 1)], max: 40 epochs 2022-11-27 23:17:22,114 - mmdet - INFO - Checkpoints will be saved to /home/dell/zhangweili/mmdetection3d-master/tools/work_dirs/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class by HardDiskBackend. 2022-11-27 23:17:22.798964: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 2022-11-27 23:17:22.799090: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/apis/train.py", line 319, in train_detector runner.run(data_loaders, cfg.workflow) # 启动 File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run epoch_runner(data_loaders[i], kwargs) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train self.run_iter(data_batch, train_mode=True, kwargs) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 32, in run_iter kwargs) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/parallel/data_parallel.py", line 77, in train_step return self.module.train_step(inputs[0], kwargs[0]) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmdet/models/detectors/base.py", line 248, in train_step losses = self(data) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(input, kwargs) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 384, in forward raise e File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 375, in forward self.transposed) File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/ops.py", line 162, in get_indice_pairs stream) RuntimeError: /io/build/temp.linux-x86_64-cpython-37/spconv/build/core_cc/src/csrc/sparse/all/SpconvOps/SpconvOps_get_indice_pairs.cc(65) not implemented for CPU ONLY build.
Reproduces the problem - command or script
run directly train.py
configs/mvxnet/dv_mvx-fp_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
Reproduces the problem - error message
2022-11-27 23:17:22,114 - mmdet - INFO - workflow: [('train', 1)], max: 40 epochs 2022-11-27 23:17:22,114 - mmdet - INFO - Checkpoints will be saved to /home/dell/zhangweili/mmdetection3d-master/tools/work_dirs/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class by HardDiskBackend. 2022-11-27 23:17:22.798964: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 2022-11-27 23:17:22.799090: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/cv2/../../lib64:/usr/local/cuda-9.0/lib64 2022-11-27 23:17:22.799101: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. /home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/fusion_layers/coord_transform.py:35: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requiresgrad(True), rather than torch.tensor(sourceTensor). if 'pcd_rotation' in img_meta else torch.eye( SPCONV_DEBUG_SAVE_PATH not found, you can specify SPCONV_DEBUG_SAVE_PATH as debug data save path to save debug data which can be attached in a issue. [Exception|native_pair]indices=torch.Size([28776, 4]),bs=2,ss=[41, 1600, 1408],algo=ConvAlgo.Native,ksize=[3, 3, 3],stride=[1, 1, 1],padding=[1, 1, 1],dilation=[1, 1, 1],subm=True,transpose=False Traceback (most recent call last): File "/home/dell/zhangweili/mmdetection3d-master/tools/train.py", line 262, in
main()
File "/home/dell/zhangweili/mmdetection3d-master/tools/train.py", line 258, in main
meta=meta)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/apis/train.py", line 351, in train_model
meta=meta)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/apis/train.py", line 319, in train_detector
runner.run(data_loaders, cfg.workflow) # 启动
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train
self.run_iter(data_batch, train_mode=True, kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 32, in run_iter
kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/parallel/data_parallel.py", line 77, in train_step
return self.module.train_step(inputs[0], kwargs[0])
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmdet/models/detectors/base.py", line 248, in train_step
losses = self(data)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(input, kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func
return old_func(args, kwargs)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/base.py", line 60, in forward
return self.forward_train(kwargs)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/mvx_two_stage.py", line 274, in forward_train
points, img=img, img_metas=img_metas)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/mvx_two_stage.py", line 208, in extract_feat
pts_feats = self.extract_pts_feat(points, img_feats, img_metas)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/mvx_faster_rcnn.py", line 57, in extract_pts_feat
x = self.pts_middle_encoder(voxel_features, feature_coors, batch_size)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, inFile "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func
return old_func(args, kwargs)
File "/home/dell/zhangweili/mmdetection3d-master/mmdet3d/models/middle_encoders/sparse_encoder.py", line 123, in forward
x = self.conv_input(input_sp_tensor)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, *kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/modules.py", line 137, in forward
input = module(input)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(input, kwargs)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 384, in forward
raise e
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 375, in forward
self.transposed)
File "/home/dell/anaconda3/envs/mmdet3d/lib/python3.7/site-packages/spconv/pytorch/ops.py", line 162, in get_indice_pairs
stream)
RuntimeError: /io/build/temp.linux-x86_64-cpython-37/spconv/build/core_cc/src/csrc/sparse/all/SpconvOps/SpconvOps_get_indice_pairs.cc(65)
not implemented for CPU ONLY build.
Additional information
Hope it can help us solve or suggest, thank you!