Source code for torch_geometric.nn.pool.graclus

from typing import Optional

import torch

    from torch_cluster import graclus_cluster
except ImportError:
    graclus_cluster = None

[docs]def graclus(edge_index, weight: Optional[torch.Tensor] = None, num_nodes: Optional[int] = None): r"""A greedy clustering algorithm from the `"Weighted Graph Cuts without Eigenvectors: A Multilevel Approach" < inderjit/public_papers/multilevel_pami.pdf>`_ paper of picking an unmarked vertex and matching it with one of its unmarked neighbors (that maximizes its edge weight). The GPU algoithm is adapted from the `"A GPU Algorithm for Greedy Graph Matching" <>`_ paper. Args: edge_index (LongTensor): The edge indices. weight (Tensor, optional): One-dimensional edge weights. (default: :obj:`None`) num_nodes (int, optional): The number of nodes, *i.e.* :obj:`max_val + 1` of :attr:`edge_index`. (default: :obj:`None`) :rtype: :class:`LongTensor` """ if graclus_cluster is None: raise ImportError('`graclus` requires `torch-cluster`.') return graclus_cluster(edge_index[0], edge_index[1], weight, num_nodes)