How to Install and Uninstall python3-autograd.noarch Package on Fedora 39

Last updated: October 12,2024

1. Install "python3-autograd.noarch" package

Please follow the guidelines below to install python3-autograd.noarch on Fedora 39


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                python3-autograd.noarch
            
                    
    
    Copied

2. Uninstall "python3-autograd.noarch" package

This guide covers the steps necessary to uninstall python3-autograd.noarch on Fedora 39:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                python3-autograd.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-autograd.noarch package on Fedora 39

Last metadata expiration check: 1:25:52 ago on Thu Mar 7 17:44:52 2024.
Available Packages
Name : python3-autograd
Version : 1.6.2
Release : 4.fc39
Architecture : noarch
Size : 178 k
Source : python-autograd-1.6.2-4.fc39.src.rpm
Repository : updates
Summary : Efficiently computes derivatives of numpy code
URL : https://github.com/HIPS/autograd
License : MIT
Description : Autograd can automatically differentiate native Python and Numpy code. It can
: handle a large subset of Python's features, including loops, ifs, recursion and
: closures, and it can even take derivatives of derivatives of derivatives. It
: supports reverse-mode differentiation (a.k.a. backpropagation), which means it
: can efficiently take gradients of scalar-valued functions with respect to
: array-valued arguments, as well as forward-mode differentiation, and the two
: can be composed arbitrarily. The main intended application of Autograd is
: gradient-based optimization.