How to Install and Uninstall tensorflow2_2_6_2-gnu-hpc-doc Package on openSuSE Tumbleweed
Last updated: November 08,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "tensorflow2_2_6_2-gnu-hpc-doc" package
Learn how to install tensorflow2_2_6_2-gnu-hpc-doc on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
tensorflow2_2_6_2-gnu-hpc-doc
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2. Uninstall "tensorflow2_2_6_2-gnu-hpc-doc" package
This is a short guide on how to uninstall tensorflow2_2_6_2-gnu-hpc-doc on openSuSE Tumbleweed:
$
sudo zypper remove
tensorflow2_2_6_2-gnu-hpc-doc
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3. Information about the tensorflow2_2_6_2-gnu-hpc-doc package on openSuSE Tumbleweed
Information for package tensorflow2_2_6_2-gnu-hpc-doc:
------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : tensorflow2_2_6_2-gnu-hpc-doc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 207,6 KiB
Installed : No
Status : not installed
Source package : tensorflow2_2_6_2-gnu-hpc-2.6.2-1.3.src
Summary : Examples from the tensorflow website
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.
This package provides examples from the website.
------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : tensorflow2_2_6_2-gnu-hpc-doc
Version : 2.6.2-1.3
Arch : x86_64
Vendor : openSUSE
Installed Size : 207,6 KiB
Installed : No
Status : not installed
Source package : tensorflow2_2_6_2-gnu-hpc-2.6.2-1.3.src
Summary : Examples from the tensorflow website
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.
This package provides examples from the website.