Package: python3-torch-cluster
Source: pytorch-cluster
Version: 1.6.3-2build1
Architecture: amd64
Maintainer: Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
Original-Maintainer: Debian Deep Learning Team <debian-science-maintainers@lists.alioth.debian.org>
Installed-Size: 944
Depends: python3-torch, python3 (<< 3.15), python3 (>= 3.14~), python3-scipy, python3:any, libc6 (>= 2.32), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 14), libtorch2.9 (>= 2.9.1+dfsg) | libtorch-cuda-2.9 (>= 2.9.1+dfsg) | libtorch-rocm-2.9 (>= 2.9.1+dfsg)
Section: science
Priority: optional
Multi-Arch: foreign
Homepage: https://github.com/rusty1s/pytorch_cluster
Description: 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.
