Paquet : python3-torch-cluster (1.6.3-2)

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PyTorch extension library of optimized graph cluster algorithms (Python 3)

This package consists of a small extension library of highly optimized graph cluster algorithms for the use in PyTorch. The package consists of the following clustering algorithms:

 * Graclus from Dhillon et al.: Weighted Graph Cuts without Eigenvectors: A
   Multilevel Approach
 * Voxel Grid Pooling from, e.g., Simonovsky and Komodakis: Dynamic
   Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
 * Iterative Farthest Point Sampling from, e.g. Qi et al.: PointNet++: Deep
   Hierarchical Feature Learning on Point Sets in a Metric Space
 * k-NN and Radius graph generation
 * Clustering based on nearest points
 * Random Walk Sampling from, e.g., Grover and Leskovec: node2vec: Scalable
   Feature Learning for Networks

All included operations work on varying data types and are implemented both for CPU and GPU.

This package installs the library for Python 3.

Autres paquets associés à python3-torch-cluster

dépendances

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enhances

dep: libc6 (>= 2.32)

GNU C Library: Shared libraries
un paquet virtuel est également fourni par libc6-udeb
dep: libgcc-s1 (>= 3.0)

GCC support library
dep: libstdc++6 (>= 14)

GNU Standard C++ Library v3
dep: libtorch2.6 (>= 2.6.0+dfsg)

Tensors and Dynamic neural networks in Python (Shared Objects)
dep: python3

interactive high-level object-oriented language (default python3 version)

dep: python3 (<< 3.14)

dep: python3 (>= 3.13~)
dep: python3-scipy

scientific tools for Python 3
dep: python3-torch

Tensors and Dynamic neural networks in Python (Python Interface)

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Architecture	Taille du paquet	Espace occupé une fois installé	Fichiers
amd64	322,8 ko	2 173,0 ko	[liste des fichiers]
arm64	295,7 ko	2 535,0 ko	[liste des fichiers]