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Package Details: caffe 1.0-18
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Git Clone URL: | https://aur.archlinux.org/caffe.git (read-only, click to copy) |
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Package Base: | caffe |
Description: | A deep learning framework made with expression, speed, and modularity in mind (cpu only) |
Upstream URL: | https://caffe.berkeleyvision.org/ |
Keywords: | ai artificial cuda intelligence nvidia |
Licenses: | BSD |
Conflicts: | caffe-cpu |
Provides: | caffe-cpu |
Replaces: | caffe-cpu |
Submitter: | yiuin |
Maintainer: | dbermond |
Last Packager: | dbermond |
Votes: | 18 |
Popularity: | 0.000000 |
First Submitted: | 2015-10-17 05:31 (UTC) |
Last Updated: | 2022-03-01 14:24 (UTC) |
Dependencies (47)
- boost-libs
- gflags (gflags-gitAUR)
- google-glog (glog-gitAUR)
- hdf5 (hdf5-gitAUR, hdf5-openmpi)
- lapack (aocl-libflame-aoccAUR, lapack-gitAUR, atlas-lapackAUR, blas-aocl-gccAUR, blas-aocl-aoccAUR, openblas-lapackAUR, blas-mklAUR, aocl-libflameAUR, blas-openblas)
- leveldb (leveldb-gitAUR)
- lmdb (lumosqlAUR, lmdb-gitAUR)
- openblas (openblas-lapackAUR)
- opencv (opencv-cuda)
- protobuf (protobuf-gitAUR)
- python (python37AUR, python311AUR, python310AUR)
- python-numpy (python-numpy-flameAUR, python-numpy-gitAUR, python-numpy1AUR, python-numpy-mkl-tbbAUR, python-numpy-mklAUR, python-numpy-mkl-binAUR)
- python-pandas
- boost (boost-gitAUR) (make)
- boost-libs (make)
- doxygen (doxygen-gitAUR, doxygen-yapAUR) (make)
- gflags (gflags-gitAUR) (make)
- ghostscript (make)
- google-glog (glog-gitAUR) (make)
- hdf5 (hdf5-gitAUR, hdf5-openmpi) (make)
- lapack (aocl-libflame-aoccAUR, lapack-gitAUR, atlas-lapackAUR, blas-aocl-gccAUR, blas-aocl-aoccAUR, openblas-lapackAUR, blas-mklAUR, aocl-libflameAUR, blas-openblas) (make)
- leveldb (leveldb-gitAUR) (make)
- lmdb (lumosqlAUR, lmdb-gitAUR) (make)
- openblas (openblas-lapackAUR) (make)
- opencv (opencv-cuda) (make)
- protobuf (protobuf-gitAUR) (make)
- python (python37AUR, python311AUR, python310AUR) (make)
- python-numpy (python-numpy-flameAUR, python-numpy-gitAUR, python-numpy1AUR, python-numpy-mkl-tbbAUR, python-numpy-mklAUR, python-numpy-mkl-binAUR) (make)
- python-pandas (make)
- texlive-core (texlive-installerAUR, texlive-fullAUR, texlive-basic) (make)
- texlive-latexextra (texlive-installerAUR, texlive-fullAUR, texlive-dummyAUR) (make)
- cython (cython-gitAUR, cython0AUR) (optional)
- ipython (ipython-gitAUR) (optional)
- python-dateutil (optional)
- python-gflags (optional)
- python-h5py (python-h5py-gitAUR, python-h5py-openmpi) (optional)
- python-leveldbAUR (optional)
- python-matplotlib (python-matplotlib-gitAUR) (optional)
- python-networkx (python-networkx-gitAUR) (optional)
- python-nose (optional)
- python-pillow (python-pillow-gitAUR) (optional)
- python-protobuf (python-protobuf-gitAUR) (optional)
- python-pydotplusAUR (optional)
- python-scikit-imageAUR (optional)
- python-scipy (python-scipy-gitAUR, python-scipy-mklAUR, python-scipy-mkl-tbbAUR, python-scipy-mkl-binAUR) (optional)
- python-six (optional)
- python-yaml (python-yaml-gitAUR) (optional)
Latest Comments
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dbermond commented on 2018-06-08 19:01 (UTC)
@Alf2010 Something should be also wrong in your building tree or system. You need to find what's going on in order to be able to build in a normal environment. Building in a clean chroot assures that everything is fine, eliminating all the interferences.
Alf2010 commented on 2018-06-07 15:32 (UTC)
Hi all, Same error message than Michael with libcudart.so.9.0 I didn't try yet to build it in a clean chroot
dbermond commented on 2018-06-05 15:20 (UTC)
@MichaelChou Good to know that you solved the issue. Thank you for the feedback.
MichaelChou commented on 2018-06-04 06:41 (UTC)
@dbermond Thanks for your informative reply. I succeeded building it in a clean chroot.
I dug around a bit and figured out the cause of this issue. I put it here in case it happen to anyone else:
Caffe indirectly depends on ffmpeg. If you manually built ffmpeg against previous version of cuda, you will have this issue. A simple rebuild of ffmpeg (after upgrading cuda of course) will solve it.
dbermond commented on 2018-06-03 02:04 (UTC)
@MichaelChou I cannot reproduce your issue. Package is building fine for me in a normal working environment as like as in a chroot environment.
Since you're getting an error about a library from cuda 9.1, it smells like a problem in your building tree or even on your system. It should not complain about something from a previous cuda version.
Make sure that you're using a new and clean directory for building (or use makepkg -C/--cleanbuild option). If it still does not work, build in a clean chroot and it should do the job.
MichaelChou commented on 2018-06-02 14:15 (UTC) (edited on 2018-06-02 14:16 (UTC) by MichaelChou)
I failed building with error output like this:
I already have cuda 9.2 installed.
dbermond commented on 2018-03-08 16:31 (UTC)
@nhkrishna This is normal and expected. If you take a look at the PKGBUILD file, you'll see that the supported architecture (the 'arch' array) is x86_64 only. This is because the AUR is in general for the x86_64 architecture, and at most for the i686 architecture. ARM is in general not supported here. ARM can be supported for a specific package if the package maintainer is willing to support it. But I, as the current caffe package maintainer, cannot support ARM architectures.
If you wish to install caffe on ARM, you should use the proper Arch Linux ARM support channels, like their forum.
nhkrishna commented on 2018-03-08 12:44 (UTC)
I'm trying to install caffe on archlinux. I'm using armv7h architecture. But its showing error like "caffe is not available for armv7h architecture". I've tried following steps. 1)git clone https://aur.archlinux.org/caffe.git 2)cd caffe 3)makepkg PKGBUILD I got the error as below ==> ERROR: caffe is not available for the 'armv7h' architecture.
==> ERROR: An unknown error has occurred. Exiting...
dbermond commented on 2018-02-20 14:47 (UTC)
@gamer01 Caffe have official support for nvidia gpus only. There are custom caffe distributions designed for intel and opencl, but as far as I can tell, these are not official ones. This package needs cuda because the binaries links to cuda libraries. cudnn is enabled in the build, so it's also needed for the same reason.
gamer01 commented on 2018-02-20 14:14 (UTC)
Is cudnn and cuda really a strict dependency? I mean you can run caffe also without a Nvidea card in your device, right?
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