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Published 20 hours ago • verified publisher icon OpenRobotLab

[Bug] Error occurs while running the train.py in the tools: _pickle.UnpicklingError: pickle data was truncated

Open Mintinson opened this issue 5 months ago • 12 comments

Prerequisite

Task

I'm using the official example scripts/configs for the officially supported tasks/models/datasets.

Branch

main branch https://github.com/open-mmlab/mmdetection3d

Environment

System environment: sys.platform: linux Python: 3.8.19 (default, Mar 20 2024, 19:58:24) [GCC 11.2.0] CUDA available: True MUSA available: False numpy_random_seed: 793778121 GPU 0: NVIDIA A100-PCIE-40GB CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.58 GCC: gcc (Ubuntu 8.4.0-1ubuntu1~18.04) 8.4.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with:

  • GCC 7.3

  • C++ Version: 201402

  • Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 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,

    TorchVision: 0.12.0 OpenCV: 4.10.0 MMEngine: 0.10.4

Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 793778121 Distributed launcher: none Distributed training: False GPU number: 1

Reproduces the problem - code sample

python tools/train.py configs/detection/mv-det3d_8xb4_embodiedscan-3d-284class-9dof.py --work-dir=work_dirs/mv-3ddet

Reproduces the problem - command or script

python tools/train.py configs/detection/mv-det3d_8xb4_embodiedscan-3d-284class-9dof.py --work-dir=work_dirs/mv-3ddet

Reproduces the problem - error message

09/06 03:16:31 - mmengine - WARNING - Failed to search registry with scope "embodiedscan" in the "loop" registry tree. As a workaround, the current "loop" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "embodiedscan" is a correct scope, or whether the registry is initialized.
09/06 03:16:31 - mmengine - WARNING - euler-depth is not a meta file, simply parsed as meta information
Traceback (most recent call last):
  File "tools/train.py", line 133, in <module>
    main()
  File "tools/train.py", line 129, in main
    runner.train()
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1728, in train
    self._train_loop = self.build_train_loop(
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1520, in build_train_loop
    loop = LOOPS.build(
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/registry.py", line 570, in build
    return self.build_func(cfg, *args, **kwargs, registry=self)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
    obj = obj_cls(**args)  # type: ignore
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/loops.py", line 44, in __init__
    super().__init__(runner, dataloader)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/base_loop.py", line 26, in __init__
    self.dataloader = runner.build_dataloader(
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1370, in build_dataloader
    dataset = DATASETS.build(dataset_cfg)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/registry.py", line 570, in build
    return self.build_func(cfg, *args, **kwargs, registry=self)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
    obj = obj_cls(**args)  # type: ignore
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/dataset/dataset_wrapper.py", line 223, in __init__
    self.dataset = DATASETS.build(dataset)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/registry.py", line 570, in build
    return self.build_func(cfg, *args, **kwargs, registry=self)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
    obj = obj_cls(**args)  # type: ignore
  File "/root/wwf/EmbodiedScan/embodiedscan/datasets/embodiedscan_dataset.py", line 59, in __init__
    super().__init__(ann_file=ann_file,
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/dataset/base_dataset.py", line 247, in __init__
    self.full_init()
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/dataset/base_dataset.py", line 298, in full_init
    self.data_list = self.load_data_list()
  File "/root/wwf/EmbodiedScan/embodiedscan/datasets/embodiedscan_dataset.py", line 342, in load_data_list
    data_info = self.parse_data_info(raw_data_info)
  File "/root/wwf/EmbodiedScan/embodiedscan/datasets/embodiedscan_dataset.py", line 147, in parse_data_info
    info['ann_info'] = self.parse_ann_info(info)
  File "/root/wwf/EmbodiedScan/embodiedscan/datasets/embodiedscan_dataset.py", line 238, in parse_ann_info
    occ_masks = mmengine.load(mask_filename)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/fileio/io.py", line 856, in load
    obj = handler.load_from_fileobj(f, **kwargs)
  File "/root/miniconda3/envs/embodiedscan/lib/python3.8/site-packages/mmengine/fileio/handlers/pickle_handler.py", line 12, in load_from_fileobj
    return pickle.load(file, **kwargs)
_pickle.UnpicklingError: pickle data was truncated

Additional information

No response

Mintinson avatar Sep 06 '24 04:09 Mintinson