Package Details: mxnet-mkl-cuda 1.7.0-2

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 and CUDA)
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)

Dependencies (27)

Required by (7)

Sources (15)

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.

Latest Comments

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roachsinai commented on 2018-03-26 21:37 (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 .

domschl commented on 2018-03-04 09:42 (UTC)

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?

petronny commented on 2018-03-04 08:15 (UTC)

Hi, @domanov I can't reproduce your problem. You can install the binary build from https://mirrors.tuna.tsinghua.edu.cn/arch4edu/

domanov commented on 2018-03-02 17:27 (UTC) (edited on 2018-03-02 17:34 (UTC) by domanov)

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?

asitdepends commented on 2018-02-11 15:01 (UTC)

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.

petronny commented on 2018-02-11 11:03 (UTC)

I have cblas and blas installed, still get the cblas_ssyrk error.

asitdepends commented on 2018-02-11 10:19 (UTC)

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.

petronny commented on 2018-02-10 06:06 (UTC) (edited on 2018-02-10 06:12 (UTC) by petronny)

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.

asitdepends commented on 2018-02-09 08:54 (UTC) (edited on 2018-02-09 16:07 (UTC) by asitdepends)

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.

Godisemo commented on 2017-02-28 16:17 (UTC)

Eventually I think it could be a good idea to extract the mklml library to its own AUR package, and make it an optional dependency for this one.

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