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Adding compiling environment specs #3

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ztzhang opened this issue May 31, 2019 · 6 comments
Closed

Adding compiling environment specs #3

ztzhang opened this issue May 31, 2019 · 6 comments

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@ztzhang
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ztzhang commented May 31, 2019

Hi,

I tried to compile the mask-rcnn kernels and it seems it does not work with cuda10.0 and gcc versions higher than 6. Switching to gcc 5.3 and cuda9.0 works.

Would it be possible to add this in the README.MD? Thanks!

@art-programmer
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Thank you for the note! Just added.

@ghost
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ghost commented Jul 23, 2019

Hi @ztzhang , I didn't understand what you wrote. You were using GCC version 6 but didn't worked because it does not work with version higher than 6 and then you switched to version 9 and worked? What?! Can you inform yours system specs, please?

I'm trying to use this pytorch repo with AWS Sagemaker p2.xlarge instance (rhel fedora 2018.3 with single GPU K80) which by default has CUDA 10.0 and GCC 4.8.5. So I've installed CUDA 9.0 and as GCC is version 4.8.5 by default (that's not higher than 6) but it didn't worked when trying to compile roialign.

The default configs (CUDA 10.0 and GCC 4.8.5) works with Mask R-CNN backbone using TensorFlow.

What I'm missing here @art-programmer ?

Thanks guys.

@ghost ghost mentioned this issue Jul 23, 2019
@ztzhang
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ztzhang commented Jul 23, 2019

@wullish sorry a typo. I did it with gcc 5.3.0. I never tried older version of gcc, as versions before 5.x may not have c++11 as default.
Under CUDA 10.0 the error message is gcc version higher than 6 is not supported, which I reported faithfully. I simply meant CUDA 10.0 AND gcc version higher than 6, as a combination, fails.

@ghost
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ghost commented Jul 24, 2019

Thanks man. Now, it's much clear! I'm going to try.

@ghost
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ghost commented Jul 24, 2019

I'm still getting "cffi.error.VerificationError: CompileError: command 'gcc' failed with exit status 1" when compiling "python build.py" roialign after updating to 5.3.0 gcc with CUDA 9.0.

I dont know what to do anymore. I've tried with python3.7 and 3.6 but no success. I'm using sm_37 which is the version for K80 according to this guy here.

Can you share yours envs specs or point to where I'm possibly doing wrong?

Thanks!

@ghost
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ghost commented Aug 3, 2019

Solved! Happens that cudatoolkit=9.0 wasn't installed on my Conda environment.

Best.

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