thanks.
my gpu is a teslap100 which is supposed to have a compute capa. of 6.0.
i tried with TORCH_CUDA_ARCH_LIST="6.0+PTX" python setup.py build, but nothing changed. i got the same error.
the doc says that by default, torch.utils.cpp_extension.CUDAExtension will build for all the visible archs.
so, it is supposed to build for the right cc. there are 2 gpus with same arch.
found similar issue with a code 1 from another repo.
the error message is so vague. and it does not point to any file.
there is no makefile to change the cc as suggested here.
i tried this on 2 servers with 2 different hardware but similar virtual env.
i dont know how to get what is offending cuda.
either the code of cuda extension does not go well with the current version cuda/pytorch.
or something is wrong with the installation (conda)…
does current cuda version still support old cuda code?
not an expert in cuda, but when writing cuda extensions, does one needs to know before hand the gpu arch? if it is the case, it will make the code almost useless…
when the built of the cuda extension is successful, is there any reason that there will be issues at runtime, provided that the inputs are correct? since the extension is supposed to be built for all arch. i assume at the runtime it will choose the right arch for the current gpu.
i ll try to check their cuda code. when edited, it has to be rebuilt to check the impact.
i still lean toward that this may be caused by nvcc, pytorch, cuda, cc, conda incompatible versions that do not go well with the cuda extension code… but again, i am not an expert.
i thought extensions are easy to use. once the cuda/c++ part were written, which is the hard part, the rest is plug and play as presented in the tutorial. you build and call. what could go wrong? the built is successful, the installation is successful.
i learned somewhere that when importing the extension, when needs to import torch first to prepare some stuff (links to libs …)
so, it seems cuda extension code and pytorch cuda code maybe need to be built with the same versions or compatible versions at least. what it it is not the case? i installed the conda pre-built version, and i compiled this cuda extension on my machine. is there a chance that this difference in compilation could cause any issue?
i cant even tell what is wrong from that message error.
is there a way to make cuda tell a more helpful error? there should be a way to debug extensions, right?
does pytorch has some debugging tools for extensions  to tell what’s wrong?
i really appreciate your help.
been stuck for 6 days at this stage. build and test one of these repos. it is a minor step. it could be done in 10 mins. 6 days later, and here i am unable to run a simple test provided by the authors.
authors didnt reply yet. i also sent an email. some seem in vacation.
will let you know.
thank you again