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[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving
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python path in miniconda that causes No module named torch.distributed #120

Closed bzha5848 closed 8 months ago

bzha5848 commented 1 year ago

Hello there, Thanks for the help last time!! But I'm still having issues with python. When I run the sample it shows me the error below. image But when I check the python path I'm using in miniconda it gives me like that. image Just wondering how can I modify ?

Thanks so much!!

ilnehc commented 1 year ago

@bzha5848 I think the sudo command results in using the default python.

bzha5848 commented 1 year ago

Without sudo, I met these errors:

ImportError: /lib/x86_64-linux-gnu/libp11-kit.so.0: undefined symbol: ffi_type_pointer, version LIBFFI_BASE_7.0 /home/tianyu/miniconda3/envs/uniad2/lib/python3.8/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated and will be removed in future. Use torch.distributed.run.

ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 166580) of binary: /home/tianyu/miniconda3/envs/uniad2/bin/python

I'm pretty sure I follow the instruction in Install.md, but I don't understand where's the problem from.

bzha5848 commented 1 year ago

I solved error ImportError: /lib/x86_64-linux-gnu/libp11-kit.so.0: undefined symbol: ffi_type_pointer, version LIBFFI_BASE_7.0

But still have the issue ImportError: numpy.core.multiarray failed to import /home/tianyu/miniconda3/envs/uniad2/lib/python3.8/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated

ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 169057) of binary: /home/tianyu/miniconda3/envs/uniad2/bin/python

I've checked the numpy version, which is 1.20.0, and modified the numpy in mmdet3d as the same, but I'm still having this issue. I can't understand what's happening.

bzha5848 commented 1 year ago

Okay, I manage to solve numpy issues with numpy==1.23.5. I guess it might be weird for requirements setting. As For some components we need numpy==1.20.0. It might be a good question to ask.

yudefu commented 1 year ago

其实可以不用在conda环境安装uniad所需要的环境，只要安装install里面需要的torch、cuda相关的版本，后面随便安装mmcv等包就可以，你可以试一下