Comments (6)
@sdalton1, @ifrosio do you have any solution to this issue? And in general how to run CuLE with the latest PyTorch?
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Hi there-I got it to work on my laptop (GTX 1650 Ti, CUDA 11.3, PyTorch 1.11.0) by fixing the following lines in setup.py
:
codes = [arch[-2:] for arch in gpus]
arch_gencode = ['-arch=sm_' + codes[0]] + ['-gencode=arch=compute_{0},code=sm_{0}'.format(code) for code in codes]
You might also want to run it with python setup.py install --fastbuild
to reduce the build time.
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@ifrosio, @sdalton1 any updates on the issue? On how to build and run CuLE on Amper GPUs?
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I got more errors:
/usr/local/cuda/bin/nvcc -I/home/denys/Documents/git/ml/cule -I/home/denys/Documents/git/ml/cule/third_party/agency -I/home/denys/Documents/git/ml/cule/third_party/pybind11/include -I/usr/local/cuda/include -I/home/denys/anaconda3/envs/rlgpu/include/python3.7m -c torchcule/backend.cu -o build/temp.linux-x86_64-cpython-37/torchcule/backend.o -arch=sm_70 -gencode=arch=compute_70,code=sm_70 -O3 -Xptxas=-v -Xcompiler=-Wall,-Wextra,-fPIC -allow-unsupported-compiler -ccbin=gcc
/usr/include/stdio.h(189): error: attribute "__malloc__" does not take arguments
/usr/include/stdio.h(201): error: attribute "__malloc__" does not take arguments
/usr/include/stdio.h(223): error: attribute "__malloc__" does not take arguments
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I can't reproduce this error on my machine. I am compiling on Ubuntu 20.04.4, torch 1.12.0, gcc 9.4.0 and the cule main branch. I tried recompiling using an older version the cuda toolkit, version 11.3, from the dockerfile but that also worked on my machine. If anyone has a Dockerfile to generate the failure with the configured software that would help a lot.
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Thanks @sdalton1 I just installed the latest ubuntu ( 22.04 I think). Looks like it is related to the wrong gcc version.
Will try to solve it using this link: https://linuxconfig.org/how-to-switch-between-multiple-gcc-and-g-compiler-versions-on-ubuntu-20-04-lts-focal-fossa
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