How to Install and Uninstall libarmnn22 Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 11,2024

1. Install "libarmnn22" package

Please follow the step by step instructions below to install libarmnn22 on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install libarmnn22

2. Uninstall "libarmnn22" package

Please follow the step by step instructions below to uninstall libarmnn22 on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove libarmnn22 $ sudo apt autoclean && sudo apt autoremove

3. Information about the libarmnn22 package on Ubuntu 21.10 (Impish Indri)

Package: libarmnn22
Architecture: amd64
Version: 20.08-9
Multi-Arch: same
Priority: optional
Section: universe/devel
Source: armnn
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Francis Murtagh
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 3311
Depends: libc6 (>= 2.17), libgcc-s1 (>= 3.0), libstdc++6 (>= 9)
Suggests: libarmnntfliteparser22 (= 20.08-9), python3-pyarmnn (= 20.08-9)
Filename: pool/universe/a/armnn/libarmnn22_20.08-9_amd64.deb
Size: 795256
MD5sum: 661787c782d66023db2968c633077fed
SHA1: 9b93ad35bb662021b3aa8a8022772baaa3ad731f
SHA256: 00413afca9aa5cfd058e4db4361323b621691328ef9ff7b3af0a82f1c685be9d
SHA512: 9744037841856dca347dffe20828531a4298b6de40f3ff063dadf7b749dcbddadbf1a94b446b20c4c58f2796ea79d614b639950fad92c73f5afa4cd306307c04
Description-en: Arm NN is an inference engine for CPUs, GPUs and NPUs
Arm NN is a set of tools that enables machine learning workloads on
any hardware. It provides a bridge between existing neural network
frameworks and whatever hardware is available and supported. On arm
architectures (arm64 and armhf) it utilizes the Arm Compute Library
to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as
possible. On other architectures/hardware it falls back to unoptimised
functions.
.
This release supports Caffe, TensorFlow, TensorFlow Lite, and ONNX.
Arm NN takes networks from these frameworks, translates them
to the internal Arm NN format and then through the Arm Compute Library,
deploys them efficiently on Cortex-A CPUs, and, if present, Mali GPUs.
.
This is the shared library package.
Description-md5: f0e1765f0b724d72e2d92a833be79578