Пакет: python3-torch-cluster (1.6.3-1 и други)

Връзки за python3-torch-cluster

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Изтегляне на пакет-източник pytorch-cluster.

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Начална страница [github.com]

Подобни пакети:

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.

Други пакети, свързани с python3-torch-cluster

зависимости

препоръчани

предложени

enhances

dep: libc6 (>= 2.32)

GNU C Library: Shared libraries
също и виртуален пакет, предлаган от libc6-udeb
dep: libgcc-s1 (>= 3.0)

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

GNU Standard C++ Library v3
dep: libtorch2.5 (>= 2.5.0+dfsg)

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

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

dep: python3 (<< 3.13)

dep: python3 (>= 3.12~)
dep: python3-scipy

scientific tools for Python 3
dep: python3-torch

Tensors and Dynamic neural networks in Python (Python Interface)

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Архитектура	Версия	Големина на пакета	Големина след инсталиране	Файлове
ppc64el	1.6.3-1+b3	320,0 кБ	2 789,0 кБ	[списък на файловете]