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open-mmlab / mmdeploy

OpenMMLab Model Deployment Framework
https://mmdeploy.readthedocs.io/en/latest/
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[mmdet3d] PointPillars -> tensorrt fail #434

Open alexandrealmin opened 2 years ago

alexandrealmin commented 2 years ago

First, thanks a lot for your amazing job, it is so helpful!

Describe the bug

I tried to convert a pretrained model of PointPillars (Kitti 3class) to tensorrt but the conversion failed. To be noted that the conversion to ONNX is ok (I didn't check the detection performances yet).

Reproduction

  1. What command or script did you run?
python tools/deploy.py configs/mmdet3d/voxel-detection/voxel-detection_tensorrt_dynamic-kitti.py ../mmdetection3d/configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class.py ../mmdetection3d/demo/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth ../mmdetection3d/demo/data/kitti/kitti_000008.bin --work-dir mmdeploy_workdir/ --show --device cuda:0

The config file for pointpillars config is the one given as an example here https://github.com/open-mmlab/mmdeploy/blob/master/docs/en/codebases/mmdet3d.md. The .pth file was downloaded from https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth

Environment

  1. Please run python tools/check_env.py to collect necessary environment information and paste it here.
2022-05-03 17:47:07,710 - mmdeploy - INFO - 

2022-05-03 17:47:07,711 - mmdeploy - INFO - **********Environmental information**********
2022-05-03 17:47:07,933 - mmdeploy - INFO - sys.platform: linux
2022-05-03 17:47:07,933 - mmdeploy - INFO - Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]
2022-05-03 17:47:07,933 - mmdeploy - INFO - CUDA available: True
2022-05-03 17:47:07,933 - mmdeploy - INFO - GPU 0: Quadro P620
2022-05-03 17:47:07,933 - mmdeploy - INFO - CUDA_HOME: /usr/local/cuda
2022-05-03 17:47:07,933 - mmdeploy - INFO - NVCC: Cuda compilation tools, release 11.3, V11.3.58
2022-05-03 17:47:07,933 - mmdeploy - INFO - GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
2022-05-03 17:47:07,933 - mmdeploy - INFO - PyTorch: 1.11.0
2022-05-03 17:47:07,933 - mmdeploy - INFO - 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 v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.3
  - 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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37
  - CuDNN 8.2
  - Magma 2.5.2
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, 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-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=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, 

2022-05-03 17:47:07,934 - mmdeploy - INFO - TorchVision: 0.12.0
2022-05-03 17:47:07,934 - mmdeploy - INFO - OpenCV: 4.5.5
2022-05-03 17:47:07,934 - mmdeploy - INFO - MMCV: 1.5.0
2022-05-03 17:47:07,934 - mmdeploy - INFO - MMCV Compiler: GCC 7.5
2022-05-03 17:47:07,934 - mmdeploy - INFO - MMCV CUDA Compiler: 11.3
2022-05-03 17:47:07,934 - mmdeploy - INFO - MMDeploy: 0.4.0+16ee9c7
2022-05-03 17:47:07,934 - mmdeploy - INFO - 

2022-05-03 17:47:07,934 - mmdeploy - INFO - **********Backend information**********
2022-05-03 17:47:08,026 - mmdeploy - INFO - onnxruntime: 1.8.1  ops_is_avaliable : True
2022-05-03 17:47:08,026 - mmdeploy - INFO - tensorrt: 8.2.3.0   ops_is_avaliable : True
2022-05-03 17:47:08,027 - mmdeploy - INFO - ncnn: None  ops_is_avaliable : False
2022-05-03 17:47:08,027 - mmdeploy - INFO - pplnn_is_avaliable: False
2022-05-03 17:47:08,028 - mmdeploy - INFO - openvino_is_avaliable: False
2022-05-03 17:47:08,028 - mmdeploy - INFO - 

2022-05-03 17:47:08,028 - mmdeploy - INFO - **********Codebase information**********
2022-05-03 17:47:08,029 - mmdeploy - INFO - mmdet:  2.22.0
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmseg:  0.22.1
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmcls:  0.21.0
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmocr:  None
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmedit: None
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmdet3d:    1.0.0rc2
2022-05-03 17:47:08,030 - mmdeploy - INFO - mmpose: None
  1. You may add addition that may be helpful for locating the problem, such as
    • conda env
    • custom ops of tensorrt are built

Error traceback

If applicable, paste the error trackback here.

2022-05-03 17:26:01,774 - mmdeploy - INFO - torch2onnx success.
2022-05-03 17:26:01,777 - mmdeploy - INFO - onnx2tensorrt of mmdeploy_workdir/end2end.onnx start.
2022-05-03 17:26:03,007 - mmdeploy - INFO - Successfully loaded tensorrt plugins from mmlab/MMDeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-03:17:26:03,mmdeploy INFO     [init_plugins.py:32] Successfully loaded tensorrt plugins from mmlab/MMDeploy/build/lib/libmmdeploy_tensorrt_ops.so
[05/03/2022-17:26:03] [TRT] [I] [MemUsageChange] Init CUDA: CPU +179, GPU +0, now: CPU 251, GPU 1631 (MiB)
[05/03/2022-17:26:03] [TRT] [I] [MemUsageSnapshot] Begin constructing builder kernel library: CPU 251 MiB, GPU 1631 MiB
[05/03/2022-17:26:03] [TRT] [I] [MemUsageSnapshot] End constructing builder kernel library: CPU 312 MiB, GPU 1631 MiB
[05/03/2022-17:26:04] [TRT] [W] onnx2trt_utils.cpp:366: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[05/03/2022-17:26:04] [TRT] [W] onnx2trt_utils.cpp:392: One or more weights outside the range of INT32 was clamped
[05/03/2022-17:26:04] [TRT] [W] onnx2trt_utils.cpp:392: One or more weights outside the range of INT32 was clamped
[05/03/2022-17:26:04] [TRT] [E] [graphShapeAnalyzer.cpp::computeOutputExtents::1026] Error Code 4: Miscellaneous (Concat_97: error while computing output extent)
2022-05-03:17:26:04,root ERROR    [utils.py:43] Failed to parse onnx, In node 97 (parseGraph): INVALID_NODE: Invalid Node - Concat_97
[graphShapeAnalyzer.cpp::computeOutputExtents::1026] Error Code 4: Miscellaneous (Concat_97: error while computing output extent)

Also, when trying to convert a Pointpillars pretrained model like hv_pointpillars_fpn_sbn-all_2x2_2x_nus-3d (same behavior with secfpn), it failed at the ONNX conversion step with another error:

2022-05-03 17:38:10,811 - mmdeploy - WARNING - DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,mmdeploy WARNING  [utils.py:92] DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,root ERROR    [utils.py:43] extract_pts_feat() takes 4 positional arguments but 6 were given
Traceback (most recent call last):
  File "mmlab/MMDeploy/mmdeploy/utils/utils.py", line 38, in target_wrapper
    result = target(*args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 113, in torch2onnx
    output_file=output_file)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 55, in torch2onnx_impl
    verbose=verbose)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/__init__.py", line 309, in export
    export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 122, in export
    custom_opsets=custom_opsets, export_modules_as_functions=export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 724, in _export
    dynamic_axes=dynamic_axes)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 499, in _model_to_graph
    graph, params, torch_out, module = _create_jit_graph(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 440, in _create_jit_graph
    graph, torch_out = _trace_and_get_graph_from_model(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 391, in _trace_and_get_graph_from_model
    torch.jit._get_trace_graph(model, args, strict=False, _force_outplace=False, _return_inputs_states=True)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 1166, in _get_trace_graph
    outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 132, in forward
    self._force_outplace,
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 118, in wrapper
    outs.append(self.inner(*trace_inputs))
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1098, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 23, in base3ddetector__forward
    return self.forward_test(*args)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 16, in base3ddetector__forward_test
    return self.simple_test(voxels, num_points, coors, img_metas, img)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 29, in mvxtwostagedetector__simple_test
    voxels, num_points, coors, img=img, img_metas=img_metas)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 53, in mvxtwostagedetector__extract_feat
    img_metas)
TypeError: extract_pts_feat() takes 4 positional arguments but 6 were given
2022-05-03 17:38:11,339 - mmdeploy - ERROR - torch2onnx failed.

Thanks a lot for your help

RunningLeon commented 2 years ago

@VVsssssk Could take a look at this issue?

VVsssssk commented 2 years ago

Hi, Can you try to use the master branch for mmdet3d? And pointpillars nus version I have supported in #391 and will merge it in next version.

alexandrealmin commented 2 years ago

Hi, I'm already using the master branch on both mmdeploy and mmdet3d (1.0.0rc2). Ok thanks will wait for this PR for nus. For pointpillars kitti, is the command I tried is working for you? Are you using the same version of onnx and tensorrt?

VVsssssk commented 2 years ago

Yes, I have tried to use your command, and it is working. My trt version is 8.0.1.6.

VVsssssk commented 2 years ago

Maybe you can try to use another version trt? We have tested the max version for trt is 8.2.1.8.

chenxyyy commented 2 years ago

@alexandrealmin @VVsssssk Hi I met the save error.

/opt/conda/bin/python /data/pointcloud_alg/mmdeploy/tools/deploy.py
2022-05-12 14:02:05,990 - mmdeploy - INFO - torch2onnx start.
2022-05-12:14:02:07,trimesh WARNING  [collision.py:11] No FCL -- collision checking will not work
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/backbones/mink_resnet.py:9: UserWarning: Please follow `getting_started.md` to install MinkowskiEngine.`
  warnings.warn(
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:84: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
  warnings.warn(
load checkpoint from local path: /data/pointcloud_alg/mmdetection3d/configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth
2022-05-12 14:02:08,889 - mmdeploy - WARNING - DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-12:14:02:08,mmdeploy WARNING  [utils.py:91] DeprecationWarning: get_onnx_config will be deprecated in the future. 
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/pillar_encode.py:41: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
  f_center = features[..., :3] - (coors[..., 1:] * torch.tensor(
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/pillar_encode.py:42: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
  [self.vz, self.vy, self.vx]).to(device) + torch.tensor([
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/voxelnet.py:53: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
  assert batch_size == 1
2022-05-12 14:02:12,641 - mmdeploy - INFO - torch2onnx success.
2022-05-12 14:02:12,642 - mmdeploy - INFO - onnx2tensorrt of /data/pointcloud_alg/mmdeploy/work_dir/end2end.onnx start.
2022-05-12 14:02:13,614 - mmdeploy - INFO - Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-12:14:02:13,mmdeploy INFO     [init_plugins.py:32] Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
[TensorRT] INFO: [MemUsageChange] Init CUDA: CPU +532, GPU +0, now: CPU 606, GPU 821 (MiB)
[TensorRT] WARNING: onnx2trt_utils.cpp:362: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[TensorRT] WARNING: onnx2trt_utils.cpp:390: One or more weights outside the range of INT32 was clamped
[TensorRT] WARNING: onnx2trt_utils.cpp:390: One or more weights outside the range of INT32 was clamped
[TensorRT] WARNING: onnx2trt_utils.cpp:390: One or more weights outside the range of INT32 was clamped
Traceback (most recent call last):
  File "/data/pointcloud_alg/mmdeploy/mmdeploy/utils/utils.py", line 38, in target_wrapper
    result = target(*args, **kwargs)
  File "/data/pointcloud_alg/mmdeploy/mmdeploy/backend/tensorrt/onnx2tensorrt.py", line 75, in onnx2tensorrt
    engine = create_trt_engine(
  File "/data/pointcloud_alg/mmdeploy/mmdeploy/backend/tensorrt/utils.py", line 76, in create_trt_engine
    raise RuntimeError(f'Failed to parse onnx, {error_msgs}')
RuntimeError: Failed to parse onnx, In node 98 (parseGraph): INVALID_NODE: Invalid Node - Concat_98
[graphShapeAnalyzer.cpp::throwIfError::1306] Error Code 2: Internal Error (no further information)

[TensorRT] ERROR: [graphShapeAnalyzer.cpp::throwIfError::1306] Error Code 2: Internal Error (no further information)
2022-05-12:14:02:14,root ERROR    [utils.py:43] Failed to parse onnx, In node 98 (parseGraph): INVALID_NODE: Invalid Node - Concat_98
[graphShapeAnalyzer.cpp::throwIfError::1306] Error Code 2: Internal Error (no further information)

2022-05-12 14:02:14,442 - mmdeploy - ERROR - onnx2tensorrt of /data/pointcloud_alg/mmdeploy/work_dir/end2end.onnx failed.

Process finished with exit code 1

My trt version is 8.0.3.4.

chenxyyy commented 2 years ago

@alexandrealmin @VVsssssk Hi. I have solved this problem. It is caused by environment.

Use this docker images. https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

docker pull nvcr.io/nvidia/pytorch:21.04-py3

The output show below:

/opt/conda/bin/python /data/pointcloud_alg/mmdeploy/tools/deploy.py
2022-05-13 09:34:39,951 - mmdeploy - INFO - torch2onnx start.
2022-05-13:09:34:41,shapely.geos DEBUG    [geos.py:85] Found GEOS DLL: <CDLL '/opt/conda/lib/python3.8/site-packages/Shapely.libs/libgeos_c-fdac42b1.so.1.16.0', handle 55eb413d85b0 at 0x7fe61e47f310>, using it.
2022-05-13:09:34:41,trimesh WARNING  [collision.py:11] No FCL -- collision checking will not work
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:224] matplotlib data path: /opt/conda/lib/python3.8/site-packages/matplotlib/mpl-data
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:224] CONFIGDIR=/root/.config/matplotlib
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:1385] matplotlib version 3.4.1
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:1386] interactive is False
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:1387] platform is linux
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:1388] loaded modules: ['sys', 'builtins', '_frozen_importlib', '_imp', '_warnings', '_frozen_importlib_external', '_io', 'marshal', 'posix', '_thread', '_weakref', 'time', 'zipimport', '_codecs', 'codecs', 'encodings.aliases', 'encodings', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', '_abc', 'abc', 'io', '_stat', 'stat', '_collections_abc', 'genericpath', 'posixpath', 'os.path', 'os', '_sitebuiltins', '_locale', '_bootlocale', 'types', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib', 'importlib.machinery', 'importlib.abc', '_operator', 'operator', 'keyword', '_heapq', 'heapq', 'itertools', 'reprlib', '_collections', 'collections', '_functools', 'functools', 'contextlib', 'importlib.util', 'mpl_toolkits', 'google', 'sphinxcontrib', 'site', '_weakrefset', 'threading', 'enum', 'signal', 'multiprocessing.process', 'copyreg', '_struct', 'struct', '_sre', 'sre_constants', 'sre_parse', 'sre_compile', 're', '_compat_pickle', '_pickle', 'pickle', '_socket', 'collections.abc', 'math', 'select', 'selectors', 'errno', 'socket', 'array', 'multiprocessing.reduction', 'multiprocessing.context', '__mp_main__', 'multiprocessing', 'weakref', 'pkgutil', 'runpy', 'atexit', '_posixsubprocess', 'subprocess', 'multiprocessing.util', 'multiprocessing.spawn', '_multiprocessing', '_posixshmem', 'multiprocessing.resource_tracker', 'fnmatch', 'zlib', '_compression', '_bz2', 'bz2', '_lzma', 'lzma', 'pwd', 'grp', 'shutil', 'locale', 'gettext', 'argparse', 'token', 'tokenize', 'linecache', 'traceback', '_string', 'string', 'logging', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'textwrap', '_datetime', 'datetime', 'numpy.core._multiarray_umath', 'numpy.compat._inspect', 'ntpath', 'urllib', 'urllib.parse', 'pathlib', 'numpy.compat.py3k', 'numpy.compat', 'numpy.core.overrides', 'numpy.core.multiarray', 'numpy.core.umath', 'numbers', 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'networkx.algorithms.coloring.greedy_coloring_with_interchange', 'networkx.algorithms.coloring.greedy_coloring', 'networkx.algorithms.coloring', 'networkx.algorithms.core', 'networkx.algorithms.covering', 'networkx.algorithms.cycles', 'networkx.algorithms.cuts', 'networkx.generators.trees', 'networkx.algorithms.dag', 'networkx.algorithms.distance_measures', 'networkx.algorithms.distance_regular', 'networkx.algorithms.dominance', 'networkx.algorithms.dominating', 'networkx.algorithms.efficiency', 'networkx.algorithms.euler', 'networkx.algorithms.graphical', 'networkx.algorithms.hierarchy', 'networkx.algorithms.hybrid', 'networkx.algorithms.link_analysis.pagerank_alg', 'networkx.algorithms.link_analysis.hits_alg', 'networkx.algorithms.link_analysis', 'networkx.algorithms.link_prediction', 'networkx.algorithms.lowest_common_ancestors', 'networkx.algorithms.isolate', 'networkx.algorithms.matching', 'networkx.algorithms.minors', 'networkx.algorithms.mis', 'networkx.algorithms.operators.all', 'networkx.algorithms.operators.binary', 'networkx.algorithms.operators.product', 'networkx.algorithms.operators.unary', 'networkx.algorithms.operators', 'networkx.algorithms.planarity', 'networkx.algorithms.reciprocity', 'networkx.algorithms.richclub', 'networkx.algorithms.shortest_paths.generic', 'networkx.algorithms.shortest_paths.unweighted', 'networkx.algorithms.shortest_paths.weighted', 'networkx.algorithms.shortest_paths.astar', 'networkx.algorithms.shortest_paths.dense', 'networkx.algorithms.shortest_paths', 'networkx.algorithms.similarity', 'networkx.algorithms.simple_paths', 'networkx.algorithms.smallworld', 'networkx.algorithms.smetric', 'networkx.algorithms.structuralholes', 'networkx.algorithms.sparsifiers', 'networkx.algorithms.swap', 'networkx.algorithms.traversal.breadth_first_search', 'networkx.algorithms.traversal.beamsearch', 'networkx.algorithms.traversal.depth_first_search', 'networkx.algorithms.traversal.edgedfs', 'networkx.algorithms.traversal.edgebfs', 'networkx.algorithms.traversal', 'networkx.algorithms.triads', 'networkx.algorithms.vitality', 'networkx.algorithms.voronoi', 'networkx.algorithms.wiener', 'networkx.algorithms.bipartite.basic', 'networkx.algorithms.bipartite.centrality', 'networkx.algorithms.bipartite.cluster', 'networkx.algorithms.bipartite.matching', 'networkx.algorithms.bipartite.covering', 'networkx.algorithms.bipartite.edgelist', 'networkx.algorithms.bipartite.matrix', 'networkx.algorithms.bipartite.projection', 'networkx.algorithms.bipartite.redundancy', 'networkx.algorithms.bipartite.spectral', 'networkx.algorithms.bipartite.generators', 'networkx.algorithms.bipartite', 'networkx.algorithms.node_classification.utils', 'networkx.algorithms.node_classification.hmn', 'networkx.algorithms.node_classification.lgc', 'networkx.algorithms.node_classification', 'networkx.algorithms.flow.utils', 'networkx.algorithms.flow.boykovkolmogorov', 'networkx.algorithms.flow.dinitz_alg', 'networkx.algorithms.flow.edmondskarp', 'networkx.algorithms.flow.preflowpush', 'networkx.algorithms.flow.shortestaugmentingpath', 'networkx.algorithms.flow.maxflow', 'networkx.algorithms.flow.mincost', 'networkx.algorithms.flow.gomory_hu', 'networkx.algorithms.flow.capacityscaling', 'networkx.algorithms.flow.networksimplex', 'networkx.algorithms.flow', 'networkx.algorithms.connectivity.utils', 'networkx.algorithms.connectivity.connectivity', 'networkx.algorithms.connectivity.cuts', 'networkx.algorithms.connectivity.edge_augmentation', 'networkx.algorithms.connectivity.edge_kcomponents', 'networkx.algorithms.connectivity.disjoint_paths', 'networkx.algorithms.connectivity.kcomponents', 'networkx.algorithms.connectivity.kcutsets', 'networkx.algorithms.connectivity.stoerwagner', 'networkx.algorithms.connectivity', 'networkx.algorithms.community.asyn_fluid', 'networkx.algorithms.community.centrality', 'networkx.algorithms.community.community_generators', 'networkx.algorithms.community.kclique', 'networkx.algorithms.community.community_utils', 'networkx.algorithms.community.kernighan_lin', 'networkx.algorithms.community.label_propagation', 'networkx.algorithms.community.quality', 'networkx.utils.mapped_queue', 'networkx.algorithms.community.modularity_max', 'networkx.algorithms.community', 'networkx.algorithms.isomorphism.isomorph', 'networkx.algorithms.isomorphism.isomorphvf2', 'networkx.algorithms.isomorphism.vf2userfunc', 'networkx.algorithms.isomorphism.matchhelpers', 'networkx.algorithms.isomorphism.temporalisomorphvf2', 'networkx.algorithms.isomorphism', 'networkx.algorithms.tournament', 'networkx.algorithms.tree.recognition', 'networkx.algorithms.tree.branchings', 'networkx.algorithms.tree.coding', 'networkx.algorithms.tree.mst', 'networkx.algorithms.tree.operations', 'networkx.algorithms.tree', 'networkx.algorithms', 'networkx.generators.intersection', 'networkx.generators.joint_degree_seq', 'networkx.generators.lattice', 'networkx.generators.line', 'networkx.generators.mycielski', 'networkx.generators.nonisomorphic_trees', 'networkx.generators.random_clustered', 'networkx.generators.random_graphs', 'networkx.generators.small', 'networkx.generators.social', 'networkx.generators.spectral_graph_forge', 'networkx.generators.stochastic', 'networkx.generators.triads', 'networkx.generators', 'networkx.readwrite.adjlist', 'networkx.readwrite.multiline_adjlist', 'networkx.readwrite.edgelist', 'networkx.readwrite.gpickle', 'networkx.readwrite.pajek', 'networkx.readwrite.leda', 'networkx.readwrite.graph6', 'networkx.readwrite.sparse6', 'networkx.readwrite.nx_yaml', 'networkx.readwrite.gml', 'xml.etree.cElementTree', 'networkx.readwrite.graphml', 'networkx.readwrite.gexf', 'networkx.readwrite.nx_shp', 'networkx.readwrite.json_graph.node_link', 'networkx.readwrite.json_graph.adjacency', 'networkx.readwrite.json_graph.tree', 'networkx.readwrite.json_graph.jit', 'networkx.readwrite.json_graph.cytoscape', 'networkx.readwrite.json_graph', 'networkx.readwrite', 'networkx.linalg.attrmatrix', 'networkx.linalg.spectrum', 'networkx.linalg.graphmatrix', 'networkx.linalg.laplacianmatrix', 'networkx.linalg.algebraicconnectivity', 'networkx.linalg.modularitymatrix', 'networkx.linalg', 'networkx.tests', 'networkx.tests.test', 'networkx.drawing.layout', 'networkx.drawing.nx_pylab', 'networkx.drawing.nx_agraph', 'networkx.drawing.nx_pydot', 'networkx.drawing', 'networkx', 'trimesh.poses', 'trimesh.graph', 'trimesh.remesh', 'trimesh.voxel', 'colorsys', 'trimesh.visual', 'trimesh.sample', 'trimesh.repair', 'trimesh.inertia', 'trimesh.io', 'trimesh.interfaces.generic', 'trimesh.interfaces.scad', 'trimesh.interfaces.blender', 'trimesh.interfaces.vhacd', 'trimesh.interfaces', 'trimesh.boolean', 'trimesh.permutate', 'trimesh.proximity', 'trimesh.collision', 'trimesh.curvature', 'trimesh.comparison', 'trimesh.registration', 'trimesh.decomposition', 'trimesh.io.wavefront', 'trimesh.io.urdf', 'trimesh.io.stl', 'trimesh.io.ply', 'trimesh.io.export', 'trimesh.scene.camera', 'trimesh.rendering', 'trimesh.io.gltf', 'trimesh.scene.transforms', 'trimesh.scene.scene', 'trimesh.scene.viewerJS', 'trimesh.scene', 'trimesh.base', 'trimesh.io.misc', 'trimesh.io.assimp', 'trimesh.io.threemf', 'trimesh.io.openctm', 'trimesh.io.xml_based', 'trimesh.path.util', 'PIL.ImageChops', 'trimesh.path.raster', 'trimesh.path.intersections', 'trimesh.path.arc', 'trimesh.path.curve', 'trimesh.path.entities', 'trimesh.path.simplify', 'shapely.prepared', 'shapely.vectorized._vectorized', 'shapely.vectorized', 'trimesh.io.load', 'shapely.wkb', 'trimesh.creation', 'trimesh.primitives', 'trimesh', 'mmdet3d.core.visualizer.image_vis', 'matplotlib', 'matplotlib._api.deprecation', 'matplotlib._api', 'matplotlib._c_internal_utils', 'matplotlib.cbook', 'matplotlib.docstring', 'matplotlib._animation_data', 'matplotlib.animation', 'PIL.ImageFile', 'PIL.GimpGradientFile', 'PIL.GimpPaletteFile', 'PIL.PaletteFile', 'PIL.ImagePalette', 'PIL.ImageSequence', 'PIL.PngImagePlugin', 'matplotlib._path', 'matplotlib.bezier', 'matplotlib.path', 'matplotlib.transforms', 'matplotlib.ticker', 'matplotlib.scale', 'matplotlib._color_data', 'matplotlib.colors', 'pyparsing', 'matplotlib.fontconfig_pattern', 'matplotlib._enums', 'cycler', 'matplotlib.rcsetup', 'matplotlib._version', 'matplotlib.ft2font', 'dateutil._version', 'dateutil', 'kiwisolver', 'dateutil._common', 'dateutil.rrule', 'dateutil.relativedelta', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.tz.tz', 'dateutil.tz', 'dateutil.parser._parser', 'dateutil.parser.isoparser', 'dateutil.parser', 'matplotlib.units', 'matplotlib.dates']
2022-05-13:09:34:41,matplotlib DEBUG    [__init__.py:224] CACHEDIR=/root/.cache/matplotlib
2022-05-13:09:34:41,matplotlib.font_manager DEBUG    [font_manager.py:1435] Using fontManager instance from /root/.cache/matplotlib/fontlist-v330.json
2022-05-13:09:34:41,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend tkagg version unknown.
2022-05-13:09:34:41,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend TkAgg version unknown.
NOTE! Installing ujson may make loading annotations faster.
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/backbones/mink_resnet.py:9: UserWarning: Please follow `getting_started.md` to install MinkowskiEngine.`
  warnings.warn(
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:84: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
  warnings.warn(
load checkpoint from local path: /data/pointcloud_alg/mmdetection3d/configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth
2022-05-13 09:34:43,432 - mmdeploy - WARNING - DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-13:09:34:43,mmdeploy WARNING  [utils.py:91] DeprecationWarning: get_onnx_config will be deprecated in the future. 
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/pillar_encode.py:41: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
  f_center = features[..., :3] - (coors[..., 1:] * torch.tensor(
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/pillar_encode.py:42: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
  [self.vz, self.vy, self.vx]).to(device) + torch.tensor([
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/voxelnet.py:53: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
  assert batch_size == 1
2022-05-13 09:34:47,130 - mmdeploy - INFO - torch2onnx success.
2022-05-13 09:34:47,132 - mmdeploy - INFO - onnx2tensorrt of /data/pointcloud_alg/mmdeploy/work_dir/end2end.onnx start.
2022-05-13 09:34:47,992 - mmdeploy - INFO - Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-13:09:34:47,mmdeploy INFO     [init_plugins.py:32] Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
[TensorRT] WARNING: /workspace/TensorRT/t/oss-cicd/oss/parsers/onnx/onnx2trt_utils.cpp:227: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[TensorRT] WARNING: /workspace/TensorRT/t/oss-cicd/oss/parsers/onnx/onnx2trt_utils.cpp:255: One or more weights outside the range of INT32 was clamped
[TensorRT] WARNING: /workspace/TensorRT/t/oss-cicd/oss/parsers/onnx/onnx2trt_utils.cpp:255: One or more weights outside the range of INT32 was clamped
[TensorRT] WARNING: /workspace/TensorRT/t/oss-cicd/oss/parsers/onnx/onnx2trt_utils.cpp:255: One or more weights outside the range of INT32 was clamped
[TensorRT] WARNING: /workspace/TensorRT/t/oss-cicd/oss/parsers/onnx/onnx2trt_utils.cpp:255: One or more weights outside the range of INT32 was clamped
[TensorRT] INFO: No importer registered for op: ScatterND. Attempting to import as plugin.
[TensorRT] INFO: Searching for plugin: ScatterND, plugin_version: 1, plugin_namespace: 
[TensorRT] INFO: Successfully created plugin: ScatterND
[TensorRT] WARNING: Output type must be INT32 for shape outputs
[TensorRT] WARNING: Output type must be INT32 for shape outputs
[TensorRT] INFO: Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.
[TensorRT] INFO: Detected 8 inputs and 3 output network tensors.
2022-05-13 09:35:07,622 - mmdeploy - INFO - onnx2tensorrt of /data/pointcloud_alg/mmdeploy/work_dir/end2end.onnx success.
2022-05-13 09:35:07,622 - mmdeploy - INFO - visualize tensorrt model start.
2022-05-13:09:35:08,shapely.geos DEBUG    [geos.py:85] Found GEOS DLL: <CDLL '/opt/conda/lib/python3.8/site-packages/Shapely.libs/libgeos_c-fdac42b1.so.1.16.0', handle 55bee8c3abf0 at 0x7f41064c52b0>, using it.
2022-05-13:09:35:08,trimesh WARNING  [collision.py:11] No FCL -- collision checking will not work
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:224] matplotlib data path: /opt/conda/lib/python3.8/site-packages/matplotlib/mpl-data
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:224] CONFIGDIR=/root/.config/matplotlib
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:1385] matplotlib version 3.4.1
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:1386] interactive is False
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:1387] platform is linux
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:1388] loaded modules: ['sys', 'builtins', '_frozen_importlib', '_imp', '_warnings', '_frozen_importlib_external', '_io', 'marshal', 'posix', '_thread', '_weakref', 'time', 'zipimport', '_codecs', 'codecs', 'encodings.aliases', 'encodings', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', '_abc', 'abc', 'io', '_stat', 'stat', '_collections_abc', 'genericpath', 'posixpath', 'os.path', 'os', '_sitebuiltins', '_locale', '_bootlocale', 'types', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib', 'importlib.machinery', 'importlib.abc', '_operator', 'operator', 'keyword', '_heapq', 'heapq', 'itertools', 'reprlib', '_collections', 'collections', '_functools', 'functools', 'contextlib', 'importlib.util', 'mpl_toolkits', 'google', 'sphinxcontrib', 'site', '_weakrefset', 'threading', 'enum', 'signal', 'multiprocessing.process', 'copyreg', '_struct', 'struct', '_sre', 'sre_constants', 'sre_parse', 'sre_compile', 're', '_compat_pickle', '_pickle', 'pickle', '_socket', 'collections.abc', 'math', 'select', 'selectors', 'errno', 'socket', 'array', 'multiprocessing.reduction', 'multiprocessing.context', '__mp_main__', 'multiprocessing', 'weakref', 'pkgutil', 'runpy', 'atexit', '_posixsubprocess', 'subprocess', 'multiprocessing.util', 'multiprocessing.spawn', '_multiprocessing', '_posixshmem', 'multiprocessing.resource_tracker', 'fnmatch', 'zlib', '_compression', '_bz2', 'bz2', '_lzma', 'lzma', 'pwd', 'grp', 'shutil', 'locale', 'gettext', 'argparse', 'token', 'tokenize', 'linecache', 'traceback', '_string', 'string', 'logging', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'textwrap', '_datetime', 'datetime', 'numpy.core._multiarray_umath', 'numpy.compat._inspect', 'ntpath', 'urllib', 'urllib.parse', 'pathlib', 'numpy.compat.py3k', 'numpy.compat', 'numpy.core.overrides', 'numpy.core.multiarray', 'numpy.core.umath', 'numbers', 'numpy.core._string_helpers', 'numpy.core._dtype', 'numpy.core._type_aliases', 'numpy.core.numerictypes', 'numpy.core._asarray', 'numpy.core._exceptions', 'numpy.core._methods', 'numpy.core.fromnumeric', 'numpy.core.shape_base', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.numeric', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._multiarray_tests', 'numpy.core._add_newdocs', 'numpy.core._add_newdocs_scalars', 'numpy.core._dtype_ctypes', '_ast', 'ast', 'platform', '_ctypes', 'ctypes._endian', 'ctypes', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.core', 'numpy.lib.mixins', 'numpy.lib.ufunclike', 'numpy.lib.type_check', 'numpy.lib.scimath', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.linalg.linalg', 'numpy.linalg', 'numpy.matrixlib.defmatrix', 'numpy.matrixlib', 'numpy.lib.histograms', 'numpy.lib.function_base', 'numpy.lib.stride_tricks', 'numpy.lib.index_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.npyio', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.lib', 'numpy.fft._pocketfft_internal', 'numpy.fft._pocketfft', 'numpy.fft.helper', 'numpy.fft', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.polynomial', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.polynomial', 'cython_runtime', '_cython_0_29_23', 'numpy.random._common', 'binascii', 'base64', '_hashlib', '_blake2', '_sha3', 'hashlib', 'hmac', '_bisect', 'bisect', '_sha512', '_random', 'random', 'secrets', 'numpy.random.bit_generator', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random.mtrand', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.random._pickle', 'numpy.random', 'numpy.ctypeslib', '_opcode', 'opcode', 'dis', 'inspect', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.ma', 'numpy', 'mmcv.arraymisc.quantization', 'mmcv.arraymisc', 'tempfile', 'typing.io', 'typing.re', 'typing', 'email', 'http', 'email.errors', 'email.quoprimime', 'email.base64mime', 'quopri', 'email.encoders', 'email.charset', 'email.header', 'calendar', 'email._parseaddr', 'email.utils', 'email._policybase', 'email.feedparser', 'email.parser', 'uu', 'email._encoded_words', 'email.iterators', 'email.message', '_ssl', 'ssl', 'http.client', 'urllib.response', 'urllib.error', 'urllib.request', 'copy', 'uuid', 'addict.addict', 'addict', '__future__', 'yapf.yapflib', 'lib2to3', 'lib2to3.pgen2', 'lib2to3.pgen2.token', 'lib2to3.pgen2.tokenize', 'yapf.yapflib.errors', 'configparser', 'yapf.yapflib.py3compat', 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'trimesh.io.stl', 'trimesh.io.ply', 'trimesh.io.export', 'trimesh.scene.camera', 'trimesh.rendering', 'trimesh.io.gltf', 'trimesh.scene.transforms', 'trimesh.scene.scene', 'trimesh.scene.viewerJS', 'trimesh.scene', 'trimesh.base', 'trimesh.io.misc', 'trimesh.io.assimp', 'trimesh.io.threemf', 'trimesh.io.openctm', 'trimesh.io.xml_based', 'trimesh.path.util', 'PIL.ImageChops', 'trimesh.path.raster', 'trimesh.path.intersections', 'trimesh.path.arc', 'trimesh.path.curve', 'trimesh.path.entities', 'trimesh.path.simplify', 'shapely.prepared', 'shapely.vectorized._vectorized', 'shapely.vectorized', 'trimesh.io.load', 'shapely.wkb', 'trimesh.creation', 'trimesh.primitives', 'trimesh', 'mmdet3d.core.visualizer.image_vis', 'matplotlib', 'matplotlib._api.deprecation', 'matplotlib._api', 'matplotlib._c_internal_utils', 'matplotlib.cbook', 'matplotlib.docstring', 'matplotlib._animation_data', 'matplotlib.animation', 'PIL.ImageFile', 'PIL.GimpGradientFile', 'PIL.GimpPaletteFile', 'PIL.PaletteFile', 'PIL.ImagePalette', 'PIL.ImageSequence', 'PIL.PngImagePlugin', 'matplotlib._path', 'matplotlib.bezier', 'matplotlib.path', 'matplotlib.transforms', 'matplotlib.ticker', 'matplotlib.scale', 'matplotlib._color_data', 'matplotlib.colors', 'pyparsing', 'matplotlib.fontconfig_pattern', 'matplotlib._enums', 'cycler', 'matplotlib.rcsetup', 'matplotlib._version', 'matplotlib.ft2font', 'dateutil._version', 'dateutil', 'kiwisolver', 'dateutil._common', 'dateutil.rrule', 'dateutil.relativedelta', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.tz.tz', 'dateutil.tz', 'dateutil.parser._parser', 'dateutil.parser.isoparser', 'dateutil.parser', 'matplotlib.units', 'matplotlib.dates']
2022-05-13:09:35:09,matplotlib DEBUG    [__init__.py:224] CACHEDIR=/root/.cache/matplotlib
2022-05-13:09:35:09,matplotlib.font_manager DEBUG    [font_manager.py:1435] Using fontManager instance from /root/.cache/matplotlib/fontlist-v330.json
2022-05-13:09:35:09,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend tkagg version unknown.
2022-05-13:09:35:09,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend TkAgg version unknown.
NOTE! Installing ujson may make loading annotations faster.
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/backbones/mink_resnet.py:9: UserWarning: Please follow `getting_started.md` to install MinkowskiEngine.`
  warnings.warn(
2022-05-13 09:35:09,621 - mmdeploy - INFO - Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-13:09:35:09,mmdeploy INFO     [init_plugins.py:32] Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-13 09:35:09,621 - mmdeploy - INFO - Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
2022-05-13:09:35:09,mmdeploy INFO     [init_plugins.py:32] Successfully loaded tensorrt plugins from /data/pointcloud_alg/mmdeploy/build/lib/libmmdeploy_tensorrt_ops.so
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:84: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
  warnings.warn(
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
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2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] nodes_geometry was not in cache, executed in 0.000015
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000002
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:17,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:17,trimesh DEBUG    [export.py:43] Exporting 120 faces as OBJ
2022-05-13 09:35:18,003 - mmdeploy - INFO - visualize tensorrt model success.
2022-05-13 09:35:18,003 - mmdeploy - INFO - visualize pytorch model start.
2022-05-13:09:35:19,shapely.geos DEBUG    [geos.py:85] Found GEOS DLL: <CDLL '/opt/conda/lib/python3.8/site-packages/Shapely.libs/libgeos_c-fdac42b1.so.1.16.0', handle 55d69cc5c2f0 at 0x7f8f43fbb2b0>, using it.
2022-05-13:09:35:19,trimesh WARNING  [collision.py:11] No FCL -- collision checking will not work
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:224] matplotlib data path: /opt/conda/lib/python3.8/site-packages/matplotlib/mpl-data
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:224] CONFIGDIR=/root/.config/matplotlib
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:1385] matplotlib version 3.4.1
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:1386] interactive is False
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:1387] platform is linux
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:1388] loaded modules: ['sys', 'builtins', '_frozen_importlib', '_imp', '_warnings', '_frozen_importlib_external', '_io', 'marshal', 'posix', '_thread', '_weakref', 'time', 'zipimport', '_codecs', 'codecs', 'encodings.aliases', 'encodings', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', '_abc', 'abc', 'io', '_stat', 'stat', '_collections_abc', 'genericpath', 'posixpath', 'os.path', 'os', '_sitebuiltins', '_locale', '_bootlocale', 'types', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib', 'importlib.machinery', 'importlib.abc', '_operator', 'operator', 'keyword', '_heapq', 'heapq', 'itertools', 'reprlib', '_collections', 'collections', '_functools', 'functools', 'contextlib', 'importlib.util', 'mpl_toolkits', 'google', 'sphinxcontrib', 'site', '_weakrefset', 'threading', 'enum', 'signal', 'multiprocessing.process', 'copyreg', '_struct', 'struct', '_sre', 'sre_constants', 'sre_parse', 'sre_compile', 're', '_compat_pickle', '_pickle', 'pickle', '_socket', 'collections.abc', 'math', 'select', 'selectors', 'errno', 'socket', 'array', 'multiprocessing.reduction', 'multiprocessing.context', '__mp_main__', 'multiprocessing', 'weakref', 'pkgutil', 'runpy', 'atexit', '_posixsubprocess', 'subprocess', 'multiprocessing.util', 'multiprocessing.spawn', '_multiprocessing', '_posixshmem', 'multiprocessing.resource_tracker', 'fnmatch', 'zlib', '_compression', '_bz2', 'bz2', '_lzma', 'lzma', 'pwd', 'grp', 'shutil', 'locale', 'gettext', 'argparse', 'token', 'tokenize', 'linecache', 'traceback', '_string', 'string', 'logging', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'textwrap', '_datetime', 'datetime', 'numpy.core._multiarray_umath', 'numpy.compat._inspect', 'ntpath', 'urllib', 'urllib.parse', 'pathlib', 'numpy.compat.py3k', 'numpy.compat', 'numpy.core.overrides', 'numpy.core.multiarray', 'numpy.core.umath', 'numbers', 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'ctypes.util', 'shapely.ctypes_declarations', 'shapely.geos', 'shapely.topology', 'shapely.coords', 'shapely.algorithms', 'shapely.algorithms.cga', 'shapely.linref', 'shapely.predicates', 'shapely.impl', 'shapely.geometry.base', 'shapely.geometry.proxy', 'shapely.geometry.point', 'shapely.geometry.linestring', 'shapely.geometry.polygon', 'shapely.geometry.multipoint', 'shapely.geometry.multilinestring', 'shapely.geometry.multipolygon', 'shapely.geometry.collection', 'shapely.geometry.geo', '_cython_0_29_28', 'shapely.speedups._speedups', 'shapely.speedups', 'shapely.geometry', 'lyft_dataset_sdk.eval.detection.mAP_evaluation', 'mmdet3d.core.evaluation.lyft_eval', 'mmdet3d.core.evaluation.seg_eval', 'mmdet3d.core.evaluation', 'mmdet3d.core.post_processing.box3d_nms', 'mmdet3d.core.post_processing.merge_augs', 'mmdet3d.core.post_processing', 'mmdet3d.core.visualizer', 'mmdet3d.core.visualizer.show_result', 'trimesh.version', 'trimesh.util', 'trimesh.constants', 'trimesh.transformations', 'trimesh.geometry', 'trimesh.caching', 'trimesh.parent', 'trimesh.grouping', 'trimesh.points', 'trimesh.triangles', 'trimesh.convex', 'trimesh.nsphere', 'trimesh.bounds', 'trimesh.ray.ray_util', 'trimesh.intersections', 'trimesh.ray.ray_triangle', 'trimesh.ray', 'trimesh.resources', 'trimesh.units', 'networkx.release', 'networkx.exception', 'networkx.utils.misc', 'decorator', 'networkx.utils.decorators', 'networkx.utils.random_sequence', 'networkx.utils.union_find', 'networkx.utils.rcm', 'networkx.utils.heaps', 'networkx.utils.contextmanagers', 'networkx.utils', 'networkx.classes.coreviews', 'networkx.classes.reportviews', 'networkx.convert', 'networkx.classes.graph', 'networkx.classes.digraph', 'networkx.classes.multigraph', 'networkx.classes.multidigraph', 'networkx.classes.ordered', 'networkx.classes.function', 'networkx.classes.filters', 'networkx.classes.graphviews', 'networkx.classes', 'networkx.convert_matrix', 'networkx.relabel', 'networkx.generators.atlas', 'networkx.generators.classic', 'networkx.generators.community', 'networkx.generators.degree_seq', 'networkx.generators.directed', 'networkx.generators.duplication', 'networkx.generators.ego', 'networkx.generators.expanders', 'networkx.generators.geometric', 'networkx.algorithms.assortativity.connectivity', 'networkx.algorithms.assortativity.pairs', 'networkx.algorithms.assortativity.mixing', 'networkx.algorithms.assortativity.correlation', 'networkx.algorithms.assortativity.neighbor_degree', 'networkx.algorithms.assortativity', 'networkx.algorithms.boundary', 'networkx.algorithms.bridges', 'networkx.algorithms.chains', 'networkx.algorithms.centrality.betweenness', 'networkx.algorithms.centrality.betweenness_subset', 'networkx.algorithms.centrality.closeness', 'networkx.algorithms.centrality.subgraph_alg', 'networkx.algorithms.centrality.flow_matrix', 'networkx.algorithms.centrality.current_flow_closeness', 'networkx.algorithms.centrality.current_flow_betweenness', 'networkx.algorithms.centrality.current_flow_betweenness_subset', 'networkx.algorithms.centrality.degree_alg', 'networkx.algorithms.centrality.dispersion', 'networkx.algorithms.centrality.eigenvector', 'networkx.algorithms.centrality.harmonic', 'networkx.algorithms.centrality.katz', 'networkx.algorithms.centrality.load', 'networkx.algorithms.centrality.reaching', 'networkx.algorithms.centrality.percolation', 'networkx.algorithms.centrality.second_order', 'networkx.algorithms.centrality', 'networkx.algorithms.chordal', 'networkx.algorithms.cluster', 'networkx.algorithms.clique', 'networkx.algorithms.communicability_alg', 'networkx.algorithms.components.connected', 'networkx.algorithms.components.strongly_connected', 'networkx.algorithms.components.weakly_connected', 'networkx.algorithms.components.attracting', 'networkx.algorithms.components.biconnected', 'networkx.algorithms.components.semiconnected', 'networkx.algorithms.components', 'networkx.algorithms.coloring.greedy_coloring_with_interchange', 'networkx.algorithms.coloring.greedy_coloring', 'networkx.algorithms.coloring', 'networkx.algorithms.core', 'networkx.algorithms.covering', 'networkx.algorithms.cycles', 'networkx.algorithms.cuts', 'networkx.generators.trees', 'networkx.algorithms.dag', 'networkx.algorithms.distance_measures', 'networkx.algorithms.distance_regular', 'networkx.algorithms.dominance', 'networkx.algorithms.dominating', 'networkx.algorithms.efficiency', 'networkx.algorithms.euler', 'networkx.algorithms.graphical', 'networkx.algorithms.hierarchy', 'networkx.algorithms.hybrid', 'networkx.algorithms.link_analysis.pagerank_alg', 'networkx.algorithms.link_analysis.hits_alg', 'networkx.algorithms.link_analysis', 'networkx.algorithms.link_prediction', 'networkx.algorithms.lowest_common_ancestors', 'networkx.algorithms.isolate', 'networkx.algorithms.matching', 'networkx.algorithms.minors', 'networkx.algorithms.mis', 'networkx.algorithms.operators.all', 'networkx.algorithms.operators.binary', 'networkx.algorithms.operators.product', 'networkx.algorithms.operators.unary', 'networkx.algorithms.operators', 'networkx.algorithms.planarity', 'networkx.algorithms.reciprocity', 'networkx.algorithms.richclub', 'networkx.algorithms.shortest_paths.generic', 'networkx.algorithms.shortest_paths.unweighted', 'networkx.algorithms.shortest_paths.weighted', 'networkx.algorithms.shortest_paths.astar', 'networkx.algorithms.shortest_paths.dense', 'networkx.algorithms.shortest_paths', 'networkx.algorithms.similarity', 'networkx.algorithms.simple_paths', 'networkx.algorithms.smallworld', 'networkx.algorithms.smetric', 'networkx.algorithms.structuralholes', 'networkx.algorithms.sparsifiers', 'networkx.algorithms.swap', 'networkx.algorithms.traversal.breadth_first_search', 'networkx.algorithms.traversal.beamsearch', 'networkx.algorithms.traversal.depth_first_search', 'networkx.algorithms.traversal.edgedfs', 'networkx.algorithms.traversal.edgebfs', 'networkx.algorithms.traversal', 'networkx.algorithms.triads', 'networkx.algorithms.vitality', 'networkx.algorithms.voronoi', 'networkx.algorithms.wiener', 'networkx.algorithms.bipartite.basic', 'networkx.algorithms.bipartite.centrality', 'networkx.algorithms.bipartite.cluster', 'networkx.algorithms.bipartite.matching', 'networkx.algorithms.bipartite.covering', 'networkx.algorithms.bipartite.edgelist', 'networkx.algorithms.bipartite.matrix', 'networkx.algorithms.bipartite.projection', 'networkx.algorithms.bipartite.redundancy', 'networkx.algorithms.bipartite.spectral', 'networkx.algorithms.bipartite.generators', 'networkx.algorithms.bipartite', 'networkx.algorithms.node_classification.utils', 'networkx.algorithms.node_classification.hmn', 'networkx.algorithms.node_classification.lgc', 'networkx.algorithms.node_classification', 'networkx.algorithms.flow.utils', 'networkx.algorithms.flow.boykovkolmogorov', 'networkx.algorithms.flow.dinitz_alg', 'networkx.algorithms.flow.edmondskarp', 'networkx.algorithms.flow.preflowpush', 'networkx.algorithms.flow.shortestaugmentingpath', 'networkx.algorithms.flow.maxflow', 'networkx.algorithms.flow.mincost', 'networkx.algorithms.flow.gomory_hu', 'networkx.algorithms.flow.capacityscaling', 'networkx.algorithms.flow.networksimplex', 'networkx.algorithms.flow', 'networkx.algorithms.connectivity.utils', 'networkx.algorithms.connectivity.connectivity', 'networkx.algorithms.connectivity.cuts', 'networkx.algorithms.connectivity.edge_augmentation', 'networkx.algorithms.connectivity.edge_kcomponents', 'networkx.algorithms.connectivity.disjoint_paths', 'networkx.algorithms.connectivity.kcomponents', 'networkx.algorithms.connectivity.kcutsets', 'networkx.algorithms.connectivity.stoerwagner', 'networkx.algorithms.connectivity', 'networkx.algorithms.community.asyn_fluid', 'networkx.algorithms.community.centrality', 'networkx.algorithms.community.community_generators', 'networkx.algorithms.community.kclique', 'networkx.algorithms.community.community_utils', 'networkx.algorithms.community.kernighan_lin', 'networkx.algorithms.community.label_propagation', 'networkx.algorithms.community.quality', 'networkx.utils.mapped_queue', 'networkx.algorithms.community.modularity_max', 'networkx.algorithms.community', 'networkx.algorithms.isomorphism.isomorph', 'networkx.algorithms.isomorphism.isomorphvf2', 'networkx.algorithms.isomorphism.vf2userfunc', 'networkx.algorithms.isomorphism.matchhelpers', 'networkx.algorithms.isomorphism.temporalisomorphvf2', 'networkx.algorithms.isomorphism', 'networkx.algorithms.tournament', 'networkx.algorithms.tree.recognition', 'networkx.algorithms.tree.branchings', 'networkx.algorithms.tree.coding', 'networkx.algorithms.tree.mst', 'networkx.algorithms.tree.operations', 'networkx.algorithms.tree', 'networkx.algorithms', 'networkx.generators.intersection', 'networkx.generators.joint_degree_seq', 'networkx.generators.lattice', 'networkx.generators.line', 'networkx.generators.mycielski', 'networkx.generators.nonisomorphic_trees', 'networkx.generators.random_clustered', 'networkx.generators.random_graphs', 'networkx.generators.small', 'networkx.generators.social', 'networkx.generators.spectral_graph_forge', 'networkx.generators.stochastic', 'networkx.generators.triads', 'networkx.generators', 'networkx.readwrite.adjlist', 'networkx.readwrite.multiline_adjlist', 'networkx.readwrite.edgelist', 'networkx.readwrite.gpickle', 'networkx.readwrite.pajek', 'networkx.readwrite.leda', 'networkx.readwrite.graph6', 'networkx.readwrite.sparse6', 'networkx.readwrite.nx_yaml', 'networkx.readwrite.gml', 'xml.etree.cElementTree', 'networkx.readwrite.graphml', 'networkx.readwrite.gexf', 'networkx.readwrite.nx_shp', 'networkx.readwrite.json_graph.node_link', 'networkx.readwrite.json_graph.adjacency', 'networkx.readwrite.json_graph.tree', 'networkx.readwrite.json_graph.jit', 'networkx.readwrite.json_graph.cytoscape', 'networkx.readwrite.json_graph', 'networkx.readwrite', 'networkx.linalg.attrmatrix', 'networkx.linalg.spectrum', 'networkx.linalg.graphmatrix', 'networkx.linalg.laplacianmatrix', 'networkx.linalg.algebraicconnectivity', 'networkx.linalg.modularitymatrix', 'networkx.linalg', 'networkx.tests', 'networkx.tests.test', 'networkx.drawing.layout', 'networkx.drawing.nx_pylab', 'networkx.drawing.nx_agraph', 'networkx.drawing.nx_pydot', 'networkx.drawing', 'networkx', 'trimesh.poses', 'trimesh.graph', 'trimesh.remesh', 'trimesh.voxel', 'colorsys', 'trimesh.visual', 'trimesh.sample', 'trimesh.repair', 'trimesh.inertia', 'trimesh.io', 'trimesh.interfaces.generic', 'trimesh.interfaces.scad', 'trimesh.interfaces.blender', 'trimesh.interfaces.vhacd', 'trimesh.interfaces', 'trimesh.boolean', 'trimesh.permutate', 'trimesh.proximity', 'trimesh.collision', 'trimesh.curvature', 'trimesh.comparison', 'trimesh.registration', 'trimesh.decomposition', 'trimesh.io.wavefront', 'trimesh.io.urdf', 'trimesh.io.stl', 'trimesh.io.ply', 'trimesh.io.export', 'trimesh.scene.camera', 'trimesh.rendering', 'trimesh.io.gltf', 'trimesh.scene.transforms', 'trimesh.scene.scene', 'trimesh.scene.viewerJS', 'trimesh.scene', 'trimesh.base', 'trimesh.io.misc', 'trimesh.io.assimp', 'trimesh.io.threemf', 'trimesh.io.openctm', 'trimesh.io.xml_based', 'trimesh.path.util', 'PIL.ImageChops', 'trimesh.path.raster', 'trimesh.path.intersections', 'trimesh.path.arc', 'trimesh.path.curve', 'trimesh.path.entities', 'trimesh.path.simplify', 'shapely.prepared', 'shapely.vectorized._vectorized', 'shapely.vectorized', 'trimesh.io.load', 'shapely.wkb', 'trimesh.creation', 'trimesh.primitives', 'trimesh', 'mmdet3d.core.visualizer.image_vis', 'matplotlib', 'matplotlib._api.deprecation', 'matplotlib._api', 'matplotlib._c_internal_utils', 'matplotlib.cbook', 'matplotlib.docstring', 'matplotlib._animation_data', 'matplotlib.animation', 'PIL.ImageFile', 'PIL.GimpGradientFile', 'PIL.GimpPaletteFile', 'PIL.PaletteFile', 'PIL.ImagePalette', 'PIL.ImageSequence', 'PIL.PngImagePlugin', 'matplotlib._path', 'matplotlib.bezier', 'matplotlib.path', 'matplotlib.transforms', 'matplotlib.ticker', 'matplotlib.scale', 'matplotlib._color_data', 'matplotlib.colors', 'pyparsing', 'matplotlib.fontconfig_pattern', 'matplotlib._enums', 'cycler', 'matplotlib.rcsetup', 'matplotlib._version', 'matplotlib.ft2font', 'dateutil._version', 'dateutil', 'kiwisolver', 'dateutil._common', 'dateutil.rrule', 'dateutil.relativedelta', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.tz.tz', 'dateutil.tz', 'dateutil.parser._parser', 'dateutil.parser.isoparser', 'dateutil.parser', 'matplotlib.units', 'matplotlib.dates']
2022-05-13:09:35:19,matplotlib DEBUG    [__init__.py:224] CACHEDIR=/root/.cache/matplotlib
2022-05-13:09:35:19,matplotlib.font_manager DEBUG    [font_manager.py:1435] Using fontManager instance from /root/.cache/matplotlib/fontlist-v330.json
2022-05-13:09:35:19,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend tkagg version unknown.
2022-05-13:09:35:19,matplotlib.pyplot DEBUG    [pyplot.py:290] Loaded backend TkAgg version unknown.
NOTE! Installing ujson may make loading annotations faster.
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/backbones/mink_resnet.py:9: UserWarning: Please follow `getting_started.md` to install MinkowskiEngine.`
  warnings.warn(
/data/pointcloud_alg/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:84: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
  warnings.warn(
load checkpoint from local path: /data/pointcloud_alg/mmdetection3d/configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:387] 1 items cleared from cache: ['face_normals']
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2089] mesh transformed by matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] nodes_geometry was not in cache, executed in 0.000016
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000002
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [caching.py:94] is_empty was not in cache, executed in 0.000001
2022-05-13:09:35:22,trimesh DEBUG    [base.py:2002] apply_tranform passed identity matrix
2022-05-13:09:35:22,trimesh DEBUG    [export.py:43] Exporting 120 faces as OBJ
2022-05-13 09:35:23,246 - mmdeploy - INFO - visualize pytorch model success.
2022-05-13 09:35:23,247 - mmdeploy - INFO - All process success.

Process finished with exit code 0
Tartisan commented 2 years ago

When I used cuda11.3 + pytorch1.10 + tensorrt8.2.3 , I also got ERROR [utils.py:43] Failed to parse onnx, In node 97 (parseGraph): INVALID_NODE: Invalid Node Finally I changed to cuda11.1 + pytorch1.9 + tensorrt8.2.3, the error disappeared. I don't know why

alexandrealmin commented 2 years ago

Sorry for the late answer, @VVsssssk @chenxyyy @Tartisan thank you for your help, indeed it works better with a downgrade of pytorch. Output of check_env.py for more details:

2022-06-07 16:50:43,851 - mmdeploy - INFO -

2022-06-07 16:50:43,851 - mmdeploy - INFO - **Environmental information** 2022-06-07 16:50:44,047 - mmdeploy - INFO - sys.platform: linux 2022-06-07 16:50:44,048 - mmdeploy - INFO - Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] 2022-06-07 16:50:44,048 - mmdeploy - INFO - CUDA available: True 2022-06-07 16:50:44,048 - mmdeploy - INFO - GPU 0,1: NVIDIA GeForce RTX 2080 Ti 2022-06-07 16:50:44,048 - mmdeploy - INFO - CUDA_HOME: /usr/local/cuda 2022-06-07 16:50:44,048 - mmdeploy - INFO - NVCC: Cuda compilation tools, release 10.2, V10.2.8 2022-06-07 16:50:44,048 - mmdeploy - INFO - GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 2022-06-07 16:50:44,048 - mmdeploy - INFO - PyTorch: 1.9.1+cu111 2022-06-07 16:50:44,048 - mmdeploy - INFO - PyTorch compiling details: PyTorch built with:

2022-06-07 16:50:44,048 - mmdeploy - INFO - TorchVision: 0.10.1+cu111 2022-06-07 16:50:44,048 - mmdeploy - INFO - OpenCV: 4.5.5 2022-06-07 16:50:44,048 - mmdeploy - INFO - MMCV: 1.5.0 2022-06-07 16:50:44,048 - mmdeploy - INFO - MMCV Compiler: GCC 7.3 2022-06-07 16:50:44,048 - mmdeploy - INFO - MMCV CUDA Compiler: 11.1 2022-06-07 16:50:44,048 - mmdeploy - INFO - MMDeploy: 0.4.0+de3f18f 2022-06-07 16:50:44,048 - mmdeploy - INFO -

2022-06-07 16:50:44,048 - mmdeploy - INFO - **Backend information** 2022-06-07 16:50:44,154 - mmdeploy - INFO - onnxruntime: 1.8.1 ops_is_avaliable : True 2022-06-07 16:50:44,154 - mmdeploy - INFO - tensorrt: 8.2.3.0 ops_is_avaliable : True 2022-06-07 16:50:44,155 - mmdeploy - INFO - ncnn: None ops_is_avaliable : False 2022-06-07 16:50:44,155 - mmdeploy - INFO - pplnn_is_avaliable: False 2022-06-07 16:50:44,155 - mmdeploy - INFO - openvino_is_avaliable: False 2022-06-07 16:50:44,155 - mmdeploy - INFO -

2022-06-07 16:50:44,155 - mmdeploy - INFO - **Codebase information** 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmdet: 2.22.0 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmseg: 0.21.1 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmcls: None 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmocr: None 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmedit: None 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmdet3d: 1.0.0rc2 2022-06-07 16:50:44,157 - mmdeploy - INFO - mmpose: None

alexandrealmin commented 2 years ago

@VVsssssk @Tartisan @chenxyyy Did you also try to test model conversion to trt with pointpillars trained on nuscenes? It fails at converting the model to ONNX. I get this error:

2022-05-03 17:38:10,811 - mmdeploy - WARNING - DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,mmdeploy WARNING  [utils.py:92] DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,root ERROR    [utils.py:43] extract_pts_feat() takes 4 positional arguments but 6 were given
Traceback (most recent call last):
  File "mmlab/MMDeploy/mmdeploy/utils/utils.py", line 38, in target_wrapper
    result = target(*args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 113, in torch2onnx
    output_file=output_file)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 55, in torch2onnx_impl
    verbose=verbose)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/__init__.py", line 309, in export
    export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 122, in export
    custom_opsets=custom_opsets, export_modules_as_functions=export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 724, in _export
    dynamic_axes=dynamic_axes)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 499, in _model_to_graph
    graph, params, torch_out, module = _create_jit_graph(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 440, in _create_jit_graph
    graph, torch_out = _trace_and_get_graph_from_model(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 391, in _trace_and_get_graph_from_model
    torch.jit._get_trace_graph(model, args, strict=False, _force_outplace=False, _return_inputs_states=True)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 1166, in _get_trace_graph
    outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 132, in forward
    self._force_outplace,
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 118, in wrapper
    outs.append(self.inner(*trace_inputs))
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1098, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 23, in base3ddetector__forward
    return self.forward_test(*args)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 16, in base3ddetector__forward_test
    return self.simple_test(voxels, num_points, coors, img_metas, img)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 29, in mvxtwostagedetector__simple_test
    voxels, num_points, coors, img=img, img_metas=img_metas)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 53, in mvxtwostagedetector__extract_feat
    img_metas)
TypeError: extract_pts_feat() takes 4 positional arguments but 6 were given
2022-05-03 17:38:11,339 - mmdeploy - ERROR - torch2onnx failed.
lfxx commented 1 year ago

@VVsssssk @Tartisan @chenxyyy Did you also try to test model conversion to trt with pointpillars trained on nuscenes? It fails at converting the model to ONNX. I get this error:

2022-05-03 17:38:10,811 - mmdeploy - WARNING - DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,mmdeploy WARNING  [utils.py:92] DeprecationWarning: get_onnx_config will be deprecated in the future. 
2022-05-03:17:38:10,root ERROR    [utils.py:43] extract_pts_feat() takes 4 positional arguments but 6 were given
Traceback (most recent call last):
  File "mmlab/MMDeploy/mmdeploy/utils/utils.py", line 38, in target_wrapper
    result = target(*args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 113, in torch2onnx
    output_file=output_file)
  File "mmlab/MMDeploy/mmdeploy/apis/pytorch2onnx.py", line 55, in torch2onnx_impl
    verbose=verbose)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/__init__.py", line 309, in export
    export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 122, in export
    custom_opsets=custom_opsets, export_modules_as_functions=export_modules_as_functions)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 724, in _export
    dynamic_axes=dynamic_axes)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 499, in _model_to_graph
    graph, params, torch_out, module = _create_jit_graph(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 440, in _create_jit_graph
    graph, torch_out = _trace_and_get_graph_from_model(model, args)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/onnx/utils.py", line 391, in _trace_and_get_graph_from_model
    torch.jit._get_trace_graph(model, args, strict=False, _force_outplace=False, _return_inputs_states=True)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 1166, in _get_trace_graph
    outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 132, in forward
    self._force_outplace,
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/jit/_trace.py", line 118, in wrapper
    outs.append(self.inner(*trace_inputs))
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "miniconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1098, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 23, in base3ddetector__forward
    return self.forward_test(*args)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/base.py", line 16, in base3ddetector__forward_test
    return self.simple_test(voxels, num_points, coors, img_metas, img)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 29, in mvxtwostagedetector__simple_test
    voxels, num_points, coors, img=img, img_metas=img_metas)
  File "mmlab/MMDeploy/mmdeploy/core/rewriters/rewriter_utils.py", line 371, in wrapper
    return self.func(self, *args, **kwargs)
  File "mmlab/MMDeploy/mmdeploy/codebase/mmdet3d/models/mvx_two_stage.py", line 53, in mvxtwostagedetector__extract_feat
    img_metas)
TypeError: extract_pts_feat() takes 4 positional arguments but 6 were given
2022-05-03 17:38:11,339 - mmdeploy - ERROR - torch2onnx failed.

Same issue here,Any update on this?

RunningLeon commented 1 year ago

@lfxx Hi, it would be fixed in https://github.com/open-mmlab/mmdeploy/pull/391. You could try on this PR if it's urgent.

alexandrealmin commented 1 year ago

Quick update, pointpillars with kitti is working fine with this setup: cuda11.3 + pytorch1.10 + tensorrt8.4.1.5 (and 8.4.2.4), in case someone needs to upgrade its pytorch version