How to Install and Uninstall python3-skorch Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 22,2024

1. Install "python3-skorch" package

Please follow the guidelines below to install python3-skorch on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-skorch
            
                    
    
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2. Uninstall "python3-skorch" package

This guide covers the steps necessary to uninstall python3-skorch on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python3-skorch
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-skorch package on Ubuntu 21.10 (Impish Indri)

Package: python3-skorch
Architecture: all
Version: 0.9.0-3
Priority: optional
Section: universe/science
Source: skorch
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Deep Learning Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 523
Depends: python3-torch (>= 1.3.1), python3-numpy, python3-scipy, python3-sklearn, python3-tabulate, python3-tqdm, python3.9, python3:any
Filename: pool/universe/s/skorch/python3-skorch_0.9.0-3_all.deb
Size: 91240
MD5sum: 6c82e220b9299ad1b156834029c9051e
SHA1: 311b2670244c9188508fa6ce5f71fc21863a3a41
SHA256: adf77933e5832fa1aa9d2b86486246f8b3806896e25f7c7e37f77fbfd38118b1
SHA512: 5f7c742b880c229f50161002e3839ef042491b6dba27b4be02603eef48a0a944a3257136d4cb1f2894e61ef8d1f1bb56923801f68d1e6d34975c062ccd0e3ba7
Homepage: https://github.com/skorch-dev/skorch
Description-en: scikit-learn compatible neural network library that wraps PyTorch
The goal of skorch is to make it possible to use PyTorch with sklearn. This is
achieved by providing a wrapper around PyTorch that has an sklearn interface.
In that sense, skorch is the spiritual successor to nolearn, but instead of
using Lasagne and Theano, it uses PyTorch.
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skorch does not re-invent the wheel, instead getting as much out of your way as
possible. If you are familiar with sklearn and PyTorch, you don’t have to learn
any new concepts, and the syntax should be well known. (If you’re not familiar
with those libraries, it is worth getting familiarized.)
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Additionally, skorch abstracts away the training loop, making a lot of
boilerplate code obsolete. A simple net.fit(X, y) is enough. Out of the box,
skorch works with many types of data, be it PyTorch Tensors, NumPy arrays,
Python dicts, and so on. However, if you have other data, extending skorch is
easy to allow for that.
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Overall, skorch aims at being as flexible as PyTorch while having a clean
interface as sklearn.
Description-md5: d00e8d2c4b8df23a0241b30376ef2a0e