How to Install and Uninstall dlpack-devel Package on openSUSE Leap
Last updated: November 08,2024
1. Install "dlpack-devel" package
Please follow the step by step instructions below to install dlpack-devel on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
dlpack-devel
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2. Uninstall "dlpack-devel" package
Please follow the steps below to uninstall dlpack-devel on openSUSE Leap:
$
sudo zypper remove
dlpack-devel
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3. Information about the dlpack-devel package on openSUSE Leap
Information for package dlpack-devel:
-------------------------------------
Repository : Main Repository
Name : dlpack-devel
Version : 0.6-bp155.2.11
Arch : x86_64
Vendor : openSUSE
Installed Size : 12.9 KiB
Installed : No
Status : not installed
Source package : dlpack-0.6-bp155.2.11.src
Upstream URL : https://github.com/dmlc/dlpack
Summary : DLPack: Open In Memory Tensor Structure
Description :
DLPack is an open in-memory tensor structure to for sharing tensor among frameworks. DLPack enables:
* Easier sharing of operators between deep learning frameworks.
* Easier wrapping of vendor level operator implementations, allowing collaboration when introducing new devices/ops.
* Quick swapping of backend implementations, like different version of BLAS
* For final users, this could bring more operators, and possibility of mixing usage between frameworks.
-------------------------------------
Repository : Main Repository
Name : dlpack-devel
Version : 0.6-bp155.2.11
Arch : x86_64
Vendor : openSUSE
Installed Size : 12.9 KiB
Installed : No
Status : not installed
Source package : dlpack-0.6-bp155.2.11.src
Upstream URL : https://github.com/dmlc/dlpack
Summary : DLPack: Open In Memory Tensor Structure
Description :
DLPack is an open in-memory tensor structure to for sharing tensor among frameworks. DLPack enables:
* Easier sharing of operators between deep learning frameworks.
* Easier wrapping of vendor level operator implementations, allowing collaboration when introducing new devices/ops.
* Quick swapping of backend implementations, like different version of BLAS
* For final users, this could bring more operators, and possibility of mixing usage between frameworks.