How to Install and Uninstall libtensorflow2-gnu-openmpi2-hpc Package on openSuSE Tumbleweed
Last updated: November 23,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "libtensorflow2-gnu-openmpi2-hpc" package
Please follow the steps below to install libtensorflow2-gnu-openmpi2-hpc on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
libtensorflow2-gnu-openmpi2-hpc
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2. Uninstall "libtensorflow2-gnu-openmpi2-hpc" package
This is a short guide on how to uninstall libtensorflow2-gnu-openmpi2-hpc on openSuSE Tumbleweed:
$
sudo zypper remove
libtensorflow2-gnu-openmpi2-hpc
Copied
3. Information about the libtensorflow2-gnu-openmpi2-hpc package on openSuSE Tumbleweed
Information for package libtensorflow2-gnu-openmpi2-hpc:
--------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libtensorflow2-gnu-openmpi2-hpc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 171,0 MiB
Installed : No
Status : not installed
Source package : tensorflow2_2_6_2-gnu-openmpi2-hpc-2.6.2-1.3.src
Summary : Shared library for tensorflow
Description :
This open source software library for numerical computation is used for data
flow graphs. The graph nodes represent mathematical operations, while the graph
edges represent the multidimensional data arrays (tensors) that flow between
them. This flexible architecture enables you to deploy computation to one or
more CPUs in a desktop, server, or mobile device without rewriting code.
--------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libtensorflow2-gnu-openmpi2-hpc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 171,0 MiB
Installed : No
Status : not installed
Source package : tensorflow2_2_6_2-gnu-openmpi2-hpc-2.6.2-1.3.src
Summary : Shared library for tensorflow
Description :
This open source software library for numerical computation is used for data
flow graphs. The graph nodes represent mathematical operations, while the graph
edges represent the multidimensional data arrays (tensors) that flow between
them. This flexible architecture enables you to deploy computation to one or
more CPUs in a desktop, server, or mobile device without rewriting code.