How to Install and Uninstall python310-cotengra Package on openSuSE Tumbleweed

Last updated: September 20,2024

1. Install "python310-cotengra" package

Learn how to install python310-cotengra on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python310-cotengra
            
                    
    
    Copied

2. Uninstall "python310-cotengra" package

Please follow the step by step instructions below to uninstall python310-cotengra on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python310-cotengra
            
                    
    
    Copied

3. Information about the python310-cotengra package on openSuSE Tumbleweed

Information for package python310-cotengra:
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Repository : openSUSE-Tumbleweed-Oss
Name : python310-cotengra
Version : 0.5.6-1.1
Arch : noarch
Vendor : openSUSE
Installed Size : 1.2 MiB
Installed : No
Status : not installed
Source package : python-cotengra-0.5.6-1.1.src
Upstream URL : https://github.com/jcmgray/cotengra
Summary : Hyper optimized contraction trees for large tensor networks and einsums
Description :
A python library for contracting tensor networks or einsum expressions involving large numbers of tensors.
Some of the key feautures of cotengra include:
* drop-in einsum replacement
* an explicit contraction tree object that can be flexibly built, modified and visualized
* a 'hyper optimizer' that samples trees while tuning the generating meta-paremeters
* dynamic slicing for massive memory savings and parallelism
* support for hyper edge tensor networks and thus arbitrary einsum equations
* paths that can be supplied to numpy.einsum, opt_einsum, quimb among others
* performing contractions with tensors from many libraries via cotengra, even if they don't provide einsum
or tensordot but do have (batch) matrix multiplication