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[ 原始碼: pytorch-cluster  ]

套件:python3-torch-cluster(1.6.3-1 以及其他的)

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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.

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下載 python3-torch-cluster

下載可用於所有硬體架構的
硬體架構 版本 套件大小 安裝後大小 檔案
amd64 1.6.3-1+b1 264。5 kB1,797。0 kB [檔案列表]
arm64 1.6.3-1+b1 241。2 kB2,085。0 kB [檔案列表]
ppc64el 1.6.3-1 262。2 kB2,340。0 kB [檔案列表]
s390x 1.6.3-1+b1 267。7 kB1,933。0 kB [檔案列表]