How to Install and Uninstall libtensorflow_cc2-gnu-openmpi2-hpc Package on openSuSE Tumbleweed
Last updated: December 29,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "libtensorflow_cc2-gnu-openmpi2-hpc" package
This guide let you learn how to install libtensorflow_cc2-gnu-openmpi2-hpc on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
libtensorflow_cc2-gnu-openmpi2-hpc
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2. Uninstall "libtensorflow_cc2-gnu-openmpi2-hpc" package
In this section, we are going to explain the necessary steps to uninstall libtensorflow_cc2-gnu-openmpi2-hpc on openSuSE Tumbleweed:
$
sudo zypper remove
libtensorflow_cc2-gnu-openmpi2-hpc
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3. Information about the libtensorflow_cc2-gnu-openmpi2-hpc package on openSuSE Tumbleweed
Information for package libtensorflow_cc2-gnu-openmpi2-hpc:
-----------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libtensorflow_cc2-gnu-openmpi2-hpc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 211,1 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 : libtensorflow_cc2-gnu-openmpi2-hpc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 211,1 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.