MIC-DKFZ/nnDetection

subprocess-exited-with-error when install nndetection

liuxia0725 opened this issue · 4 comments

Obtaining file:///D:/nnDetection
Preparing metadata (setup.py) ... error
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [8 lines of output]
Traceback (most recent call last):
File "", line 2, in
File "", line 34, in
File "D:\nnDetection\setup.py", line 7, in
from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
File "E:\anaconda3\envs\new_env\lib\site-packages\torch\utils\cpp_extension.py", line 25, in
from pkg_resources import packaging # type: ignore[attr-defined]
ImportError: cannot import name 'packaging' from 'pkg_resources' (E:\anaconda3\envs\new_env\lib\site-packages\pkg_resources_init_.py)
[end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

how to solve this problem
pytorch: 1.13.0, python 3.10; cuda 1.17

Dear @liuxia0725 ,

I haven't encountered this Issue before, could you try to run it in a linux based docker container? nnDetection does not officially support Windows and based on your file paths, it looks like you might be using a windows based operating system.

Hi there!

Do you think that using WSL (Windows Subsystem for Linux) would work in that case?

EDIT:
I managed to install docker and CUDA for docker in WSL using this procedure : http://collabnix.com/introducing-new-docker-cli-api-support-for-nvidia-gpus-under-docker-engine-19-03-0-beta-release/

I then installed nnDetection as decribed on the README.

I am currently running the nndet_example so it MAY have worked on Windows using WSL2!

I will follow up with my test if I manage to do the preprocessing and training

EDIT2: I was able to start the training of both the dummy dataset as well as a MSD Task dataset.
So $\color{red}{\textsf{if you are stuck with Windows like I was, using WSL2 is indeed the way to go!}}$

image

This issue is stale because it has been open for 30 days with no activity.

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