tensorflow2 installation error

Hi when I try to install tensorflow2 from official repository by this command:

zypper in tensorflow2

The following error immediately returned:

Loading repository data...
Reading installed packages...
Resolving package dependencies...

Problem: nothing provides libgrpc.so.8()(64bit) needed by tensorflow2-2.1.1-3.5.x86_64
 Solution 1: do not install tensorflow2-2.1.1-3.5.x86_64
 Solution 2: break tensorflow2-2.1.1-3.5.x86_64 by ignoring some of its dependencies

Choose from above solutions by number or cancel [1/2/c/d/?] (c):

I guess it’s a bug and missing dependency. can you confirm this is packageing bug?

more information:
I already installed python3-numpy
python3-pandas python3-matplotlib python3-scikit-learn python3-opencv python3-pylint python3-pip python3-dev cairo-dev
and from pip: pygobject pycairo

I don’t have any dedicated gpu card such as nvidia gpu, my gpu is an old AMD APU (A4-6300)

tensorflow2 fails to build since 2 months, so binaries that you get are outdated and built against older library version. In the meantime grpc was updated, and old version (that was used to build tensorflow2 in the past) is no more available.

The only solution is to fix tensorflow2 to build again.

I don’t know what is the problem in the OBS build,
But you can easily install from PyPi.
Although the official Tensorflow documentation describes installing on Ubuntu, I don’t see any dependencies that would prevent installing on an RPM system like openSUSE.
The CUDA instructions are another matter though… Any viewer should look up and follow the instructions for your version of CUDA.

From the Tensorflow website,


For GPU computing, but use it only as a general setup guide. You should instead install CUDA using nVidia instructions for your version of CUDA.


For those who want to attempt to build from source instead of from PyPi packages (recommended). Skimming the instructions, no mention is made of dependencies that might exist on the system, only packages from PyPi. The procedure to build Tensorflow may have changed since the OBS project was created or something may be left out.