TypeError: can't pickle dict_keys objects about petr HOT 7 CLOSED

Hi. Can you provide the full training logs?

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For the regulation, I can't upload full logs. but I can provide the useful.

2022-08-16 04:07:43,711 - mmdet - INFO - Environment info:

sys.platform: linux
Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0]
CUDA available: True
GPU 0: Quadro RTX 5000
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.3, V11.3.58
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.8.0
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 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_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 8.0.5
• 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 -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
OpenCV: 4.6.0
MMCV: 1.5.2
MMCV Compiler: GCC 9.4
MMCV CUDA Compiler: 11.3
MMDetection: 2.25.1
MMSegmentation: 0.27.0
MMDetection3D: 1.0.0rc4+33465da
spconv2.0: False

from petr.

total_epochs = 24
find_unused_parameters = False
runner = dict(type='EpochBasedRunner', max_epochs=24)
gpu_ids = range(0, 1)
device = 'cuda'

2022-08-16 04:07:46,570 - mmdet - INFO - Set random seed to 0, deterministic: False
2022-08-16 04:07:48,918 - mmdet - INFO - initialize CPFPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'}
Name of parameter - Initialization information

....
2022-08-16 04:09:41,817 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
2022-08-16 04:09:41,820 - mmdet - INFO - Checkpoints will be saved to /home/gyang/data/PETR/work_dirs/petrv2_BEVseg by HardDiskBackend.

stoped.

from petr.

I change the env as follow:
sys.platform: linux
Python: 3.8.10 (default, Jun 4 2021, 15:09:15) [GCC 7.5.0]
CUDA available: True
GPU 0: Quadro RTX 5000
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.3.r11.3/compiler.29745058_0
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.9.0
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 v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• 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_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 8.0.5
• 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 -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=1.9.0, 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: 0.10.0
OpenCV: 4.6.0
MMCV: 1.4.0
MMCV Compiler: GCC 9.4
MMCV CUDA Compiler: not available
MMDetection: 2.24.1
MMSegmentation: 0.20.2
MMDetection3D: 0.17.1+33465da

the above problem is solved. However, there is a new issue:
RuntimeError: sigmoid_focal_loss_forward_impl: implementation for device cuda:0 not found.

from petr.

For my case, I use mmcv source to install and solve it.

from petr.

I have finish the train. But when I go to test, a wired error happened.
bash tools/dist_test.sh projects/configs/petrv2/petrv2_BEVseg.py work_dirs/petrv2_BEVseg/latest.pth 1 --eval bbox
The error like:
`CHILD PROCESS FAILED WITH NO ERROR_FILE
Child process 2914173 (local_rank 0) FAILED (exitcode 2)
Error msg: Process failed with exitcode 2
Without writing an error file to <N/A>.
While this DOES NOT affect the correctness of your application,
no trace information about the error will be available for inspection.
Consider decorating your top level entrypoint function with
torch.distributed.elastic.multiprocessing.errors.record. Example:

from torch.distributed.elastic.multiprocessing.errors import record

@record
def trainer_main(args):
# do train

warnings.warn(_no_error_file_warning_msg(rank, failure))
Traceback (most recent call last):
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/launch.py", line 173, in
main()
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/launch.py", line 169, in main
run(args)
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/run.py", line 621, in run
elastic_launch(
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 116, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 348, in wrapper
return f(*args, **kwargs)
File "/home/gyang/anaconda3/envs/petr2/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 245, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
FAILED
Root Cause:
[0]:
time: 2022-09-03_01:02:56
rank: 0 (local_rank: 0)
exitcode: 2 (pid: 2914173)
error_file: <N/A>
msg: "Process failed with exitcode 2"
Other Failures:
<NO_OTHER_FAILURES>

tools/dist_test.sh: line 10: tools/test.py: Permission denied`

from petr.

I find the problem is that my local pc is one gpu the original test command is unsuitable for me.
I change dist_test.sh to
python3 -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \ $(dirname "$0")/test.py $CONFIG $CHECKPOINT --launcher none ${@:4}.
The problem is solved.

from petr.