How to Install and Uninstall python3-lasagne.noarch Package on Fedora 36
Last updated: November 26,2024
1. Install "python3-lasagne.noarch" package
This tutorial shows how to install python3-lasagne.noarch on Fedora 36
$
sudo dnf update
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$
sudo dnf install
python3-lasagne.noarch
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2. Uninstall "python3-lasagne.noarch" package
Please follow the steps below to uninstall python3-lasagne.noarch on Fedora 36:
$
sudo dnf remove
python3-lasagne.noarch
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$
sudo dnf autoremove
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3. Information about the python3-lasagne.noarch package on Fedora 36
Last metadata expiration check: 1:51:47 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : python3-lasagne
Version : 0.1
Release : 22.fc36
Architecture : noarch
Size : 139 k
Source : python-lasagne-0.1-22.fc36.src.rpm
Repository : fedora
Summary : Lightweight library to build and train neural networks in Theano
URL : https://github.com/Lasagne/Lasagne
License : MIT
Description : Lasagne is a lightweight library to build and train neural networks in Theano.
: Its main features are:
:
: Supports feed-forward networks such as Convolutional Neural Networks (CNNs),
: recurrent networks including Long Short-Term Memory (LSTM), and any combination
: thereof
: Allows architectures of multiple inputs and multiple outputs, including
: auxiliary classifiers
: Many optimization methods including Nesterov momentum, RMSprop and ADAM
: Freely definable cost function and no need to derive gradients due to Theano's
: symbolic differentiation
: Transparent support of CPUs and GPUs due to Theano's expression compiler
:
: This package allows for use of python-lasagne with Python 3.
Available Packages
Name : python3-lasagne
Version : 0.1
Release : 22.fc36
Architecture : noarch
Size : 139 k
Source : python-lasagne-0.1-22.fc36.src.rpm
Repository : fedora
Summary : Lightweight library to build and train neural networks in Theano
URL : https://github.com/Lasagne/Lasagne
License : MIT
Description : Lasagne is a lightweight library to build and train neural networks in Theano.
: Its main features are:
:
: Supports feed-forward networks such as Convolutional Neural Networks (CNNs),
: recurrent networks including Long Short-Term Memory (LSTM), and any combination
: thereof
: Allows architectures of multiple inputs and multiple outputs, including
: auxiliary classifiers
: Many optimization methods including Nesterov momentum, RMSprop and ADAM
: Freely definable cost function and no need to derive gradients due to Theano's
: symbolic differentiation
: Transparent support of CPUs and GPUs due to Theano's expression compiler
:
: This package allows for use of python-lasagne with Python 3.