How to Install and Uninstall ensmallen-devel.i686 Package on Fedora 38
Last updated: January 15,2025
1. Install "ensmallen-devel.i686" package
This is a short guide on how to install ensmallen-devel.i686 on Fedora 38
$
sudo dnf update
Copied
$
sudo dnf install
ensmallen-devel.i686
Copied
2. Uninstall "ensmallen-devel.i686" package
Learn how to uninstall ensmallen-devel.i686 on Fedora 38:
$
sudo dnf remove
ensmallen-devel.i686
Copied
$
sudo dnf autoremove
Copied
3. Information about the ensmallen-devel.i686 package on Fedora 38
Last metadata expiration check: 0:27:49 ago on Sun Mar 17 04:59:58 2024.
Available Packages
Name : ensmallen-devel
Version : 2.19.0
Release : 3.fc38
Architecture : i686
Size : 238 k
Source : ensmallen-2.19.0-3.fc38.src.rpm
Repository : fedora
Summary : Header-only C++ library for efficient mathematical optimization
URL : https://www.ensmallen.org
License : BSD
Description : ensmallen is a header-only C++ library for efficient mathematical optimization.
: It provides a simple set of abstractions for writing an objective function to
: optimize. It also provides a large set of standard and cutting-edge optimizers
: that can be used for virtually any mathematical optimization task. These
: include full-batch gradient descent techniques, small-batch techniques,
: gradient-free optimizers, and constrained optimization.
Available Packages
Name : ensmallen-devel
Version : 2.19.0
Release : 3.fc38
Architecture : i686
Size : 238 k
Source : ensmallen-2.19.0-3.fc38.src.rpm
Repository : fedora
Summary : Header-only C++ library for efficient mathematical optimization
URL : https://www.ensmallen.org
License : BSD
Description : ensmallen is a header-only C++ library for efficient mathematical optimization.
: It provides a simple set of abstractions for writing an objective function to
: optimize. It also provides a large set of standard and cutting-edge optimizers
: that can be used for virtually any mathematical optimization task. These
: include full-batch gradient descent techniques, small-batch techniques,
: gradient-free optimizers, and constrained optimization.