[Bug] 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.

[zwl8979]

Prerequisite

• [X] I have searched Issues and Discussions but cannot get the expected help.
• [X] I have read the FAQ documentation but cannot get the expected help.
• [X] The bug has not been fixed in the latest version (dev) or latest version (1.x).

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:

• GCC 7.3
• C++ Version: 201402
• Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v1.7.0 (Git Hash 7aed236906b1f7a05c0917e5257a1af05e9ff683)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 10.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70
• CuDNN 7.6.3
• Magma 2.5.2
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=10.1, CUDNN_VERSION=7.6.3, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.8.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,

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！

[JingweiZhang12]

Maybe you install the CPU-only spconv. Please install the spconv with CUDA. https://github.com/traveller59/spconv

[zwl8979]

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

[zwl8979]

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.

[VVsssssk]

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?

[VVsssssk]

And I suggest you check your env by PointPillars model.

[zwl8979]

@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 main() File "demo/pcd_demo.py", line 31, in main result, data = inference_detector(model, args.pcd) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/apis/inference.py", line 151, in inference_detector result = model(return_loss=False, rescale=True, data) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, kwargs) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func return old_func(*args, kwargs) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/base.py", line 62, in forward return self.forward_test(kwargs) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/base.py", line 43, in forward_test return self.simple_test(points[0], img_metas[0], img[0], *kwargs) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/voxelnet.py", line 100, in simple_test x = self.extract_feat(points, img_metas) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/detectors/voxelnet.py", line 45, in extract_feat x = self.middle_encoder(voxel_features, coors, batch_size) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(input, kwargs) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/mmcv/runner/fp16_utils.py", line 116, in new_func return old_func(*args, kwargs) File "/home/ubuntu/zhangweili/mmdetection3d-master/mmdet3d/models/middle_encoders/sparse_encoder.py", line 123, in forward x = self.conv_input(input_sp_tensor) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, *kwargs) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/spconv/pytorch/modules.py", line 137, in forward input = module(input) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(input, kwargs) File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 384, in forward raise e File "/home/ubuntu/anaconda3/envs/mmdetection3d/lib/python3.7/site-packages/spconv/pytorch/conv.py", line 375, in forward self.transposed) File "/home/ubuntu/anaconda3/envs/mmdetection3d/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.

May I ask how to solve this problem? Is the reason for this problem that all dependencies cannot be installed directly? thanks！

3. conda list : _# packages in environment at /home/ubuntu/anaconda3/envs/mmdetection3d: #

   Name Version Build Channel

   _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 coverage 7.0.3 pypi_0 pypi cumm 0.3.7 pypi_0 pypi cycler 0.11.0 pypi_0 pypi dash 2.7.1 pypi_0 pypi dash-core-components 2.0.0 pypi_0 pypi dash-html-components 2.0.0 pypi_0 pypi dash-table 5.0.0 pypi_0 pypi debugpy 1.6.4 pypi_0 pypi decorator 5.1.1 pypi_0 pypi defusedxml 0.7.1 pypi_0 pypi descartes 1.1.0 pypi_0 pypi entrypoints 0.4 pypi_0 pypi exceptiongroup 1.1.0 pypi_0 pypi fastjsonschema 2.16.2 pypi_0 pypi fire 0.5.0 pypi_0 pypi flake8 5.0.4 pypi_0 pypi flask 2.2.2 pypi_0 pypi fonttools 4.38.0 pypi_0 pypi gast 0.2.2 pypi_0 pypi google-auth 1.35.0 pypi_0 pypi google-auth-oauthlib 0.4.6 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.51.1 pypi_0 pypi h5py 3.7.0 pypi_0 pypi 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 iniconfig 1.1.1 pypi_0 pypi interrogate 1.5.0 pypi_0 pypi ipykernel 6.16.2 pypi_0 pypi ipython 7.34.0 pypi_0 pypi ipython-genutils 0.2.0 pypi_0 pypi ipywidgets 8.0.4 pypi_0 pypi isort 5.11.4 pypi_0 pypi itsdangerous 2.1.2 pypi_0 pypi jedi 0.18.2 pypi_0 pypi jinja2 3.1.2 pypi_0 pypi joblib 1.2.0 pypi_0 pypi jsonschema 4.17.3 pypi_0 pypi jupyter 1.0.0 pypi_0 pypi jupyter-client 7.4.8 pypi_0 pypi jupyter-console 6.4.4 pypi_0 pypi jupyter-core 4.12.0 pypi_0 pypi jupyter-server 1.23.4 pypi_0 pypi jupyterlab-pygments 0.2.2 pypi_0 pypi jupyterlab-widgets 3.0.5 pypi_0 pypi keras-applications 1.0.8 pypi_0 pypi keras-preprocessing 1.1.2 pypi_0 pypi 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 markupsafe 2.1.1 pypi_0 pypi matplotlib 3.5.3 pypi_0 pypi matplotlib-inline 0.1.6 pypi_0 pypi mccabe 0.7.0 pypi_0 pypi 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 mmsegmentation 0.29.1 pypi_0 pypi mypy-extensions 0.4.3 pypi_0 pypi nbclassic 0.4.8 pypi_0 pypi nbclient 0.7.2 pypi_0 pypi nbconvert 7.2.7 pypi_0 pypi nbformat 5.5.0 pypi_0 pypi ncurses 6.3 h5eee18b_3
   nest-asyncio 1.5.6 pypi_0 pypi networkx 2.2 pypi_0 pypi ninja 1.11.1 pypi_0 pypi notebook 6.5.2 pypi_0 pypi notebook-shim 0.2.2 pypi_0 pypi numba 0.53.0 pypi_0 pypi numpy 1.21.6 pypi_0 pypi nuscenes-devkit 1.1.9 pypi_0 pypi oauthlib 3.2.2 pypi_0 pypi open3d 0.16.0 pypi_0 pypi opencv-python 4.7.0.68 pypi_0 pypi 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 parso 0.8.3 pypi_0 pypi pathspec 0.10.3 pypi_0 pypi pccm 0.4.4 pypi_0 pypi pexpect 4.8.0 pypi_0 pypi pickleshare 0.7.5 pypi_0 pypi pillow 9.4.0 pypi_0 pypi pip 22.3.1 py37h06a4308_0
   pkgutil-resolve-name 1.3.10 pypi_0 pypi platformdirs 2.6.2 pypi_0 pypi plotly 5.11.0 pypi_0 pypi pluggy 1.0.0 pypi_0 pypi plyfile 0.7.4 pypi_0 pypi portalocker 2.6.0 pypi_0 pypi prettytable 3.5.0 pypi_0 pypi prometheus-client 0.15.0 pypi_0 pypi prompt-toolkit 3.0.36 pypi_0 pypi protobuf 4.21.12 pypi_0 pypi psutil 5.9.4 pypi_0 pypi ptyprocess 0.7.0 pypi_0 pypi py 1.11.0 pypi_0 pypi pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi pybind11 2.10.3 pypi_0 pypi pycocotools 2.0.6 pypi_0 pypi pycodestyle 2.9.1 pypi_0 pypi pycparser 2.21 pypi_0 pypi pyflakes 2.5.0 pypi_0 pypi pygments 2.14.0 pypi_0 pypi pyparsing 3.0.9 pypi_0 pypi pyquaternion 0.9.9 pypi_0 pypi pyrsistent 0.19.3 pypi_0 pypi 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 pywavelets 1.3.0 pypi_0 pypi pyyaml 6.0 pypi_0 pypi 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 tensorflow-estimator 2.1.0 pypi_0 pypi tensorflow-gpu 2.1.0 pypi_0 pypi termcolor 2.2.0 pypi_0 pypi terminado 0.17.1 pypi_0 pypi terminaltables 3.1.10 pypi_0 pypi threadpoolctl 3.1.0 pypi_0 pypi 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 trimesh 2.35.39 pypi_0 pypi typed-ast 1.5.4 pypi_0 pypi typing-extensions 4.4.0 pypi_0 pypi 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 werkzeug 2.2.2 pypi_0 pypi 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 zipp 3.11.0 pypi_0 pypi zlib 1.2.13 h5eee18b0

[zwl8979]

@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:

• GCC 7.3
• C++ Version: 201402
• Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• LAPACK is enabled (usually provided by MKL)
• NNPACK is enabled
• CPU capability usage: AVX512
• CUDA Runtime 11.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
• CuDNN 8.0.5
• Magma 2.5.2
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,

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!

[yyxr75]

Is it done? I came across this issue recently.