Same issue :-(.
free(): invalid pointer /tmp/yaourt-tmp-roach/aur-mxnet/./PKGBUILD: 行 50: 20759 已放弃 (核心已转储)python setup.py build --with-cython ==> 错误: 在 build() 中发生一个错误。 正在放弃... ==> 错误:Makepkg 无法构建 .
Git Clone URL: | https://aur.archlinux.org/mxnet.git (read-only, click to copy) |
---|---|
Package Base: | mxnet |
Description: | Flexible and Efficient Library for Deep Learning (with MKL) |
Upstream URL: | https://mxnet.apache.org/ |
Keywords: | deep_learning deep_neural_networks distributed_systems machine_learning |
Licenses: | Apache |
Conflicts: | mxnet |
Provides: | mxnet |
Submitter: | Godisemo |
Maintainer: | None |
Last Packager: | petronny |
Votes: | 12 |
Popularity: | 0.000000 |
First Submitted: | 2017-02-11 00:12 (UTC) |
Last Updated: | 2020-12-12 11:17 (UTC) |
Same issue :-(.
free(): invalid pointer /tmp/yaourt-tmp-roach/aur-mxnet/./PKGBUILD: 行 50: 20759 已放弃 (核心已转储)python setup.py build --with-cython ==> 错误: 在 build() 中发生一个错误。 正在放弃... ==> 错误:Makepkg 无法构建 .
I've had the same issue as @domanov. Build fails during python setup.py build with segmentation fault. Any suggestions what can be done to narrow this down?
Hi, @domanov I can't reproduce your problem. You can install the binary build from https://mirrors.tuna.tsinghua.edu.cn/arch4edu/
Hi, I am not able to compile mxnet, it fails with segmentation error at the end when python setup.py
PKGBUILD: line 39: 17500 Segmentation error (core dump created) python setup.py build
Any hints?
It's strange. In my system the build is successful. If I remove cblas or -lcblas
flag, I get the same error on 'cblas_ssyrk'. readelf -Ws /usr/lib/libcblas.so | grep cblas_ssyrk
confirms that the symbol is there and I believe the linking should be sucessful.
I have cblas and blas installed, still get the cblas_ssyrk error.
I guess you might not install cblas package. In Arch blas (libblas.so) is a fortran library and cblas (libcblas.so) is a C library. libcblas.so from cblas package contains the symbol cblas_ssyrk
and may solve your build problem. For the dependency, you are right. I had some trouble with openblas and numpy and I thought that it was a dependency problem. But it was my mistake and is not a dependency problem.
I get
ld: build/src/operator/tensor/la_op.o: undefined reference to symbol 'cblas_ssyrk'
/usr/lib/libcblas.so.3: error adding symbols: DSO missing from command line
with USE_BLAS=blas ADD_LDFLAGS=-lcblas USE_LAPACK=1
.
So I use openblas-lapack to build the package.
And openblas-lapack doesn't break dependencies.
Cuda 9 does not support gcc 7 which is the default gcc in the current Arch linux. So we need gcc-6 as a dependency and flags CC=gcc-6 CXX=g++6 to compile the package.
Why openblas? The blas package in the official repository should be used (USE_BLAS=blas ADD_LDFLAGS=-lcblas). Openblas breaks several dependencies of the standard packages such as python-numpy. If one really needs openblas, it could modify the PKGBUILD and do appropriate preparations. This must be optional and the standard blas must be the default.
Pinned Comments
petronny commented on 2019-06-21 08:00 (UTC) (edited on 2019-06-25 07:24 (UTC) by petronny)
And about this package, I've splitted it into mxnet{,-cuda,-mkl}. And it will take lots of time and space to compile.
The pre-built binaries of mxnet{,-cuda,-mkl} and their dependencies can be found in arch4edu.