dmlc--dgl
brett koonce
147 行
4.4 KiB
Python
147 行
4.4 KiB
Python
"""Module for message propagation."""
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from __future__ import absolute_import
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from . import traversal as trv
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__all__ = ['prop_nodes', 'prop_nodes_bfs', 'prop_nodes_topo',
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'prop_edges', 'prop_edges_dfs']
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def prop_nodes(graph,
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nodes_generator,
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message_func='default',
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reduce_func='default',
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apply_node_func='default'):
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"""Functional method for :func:`dgl.DGLGraph.prop_nodes`.
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Parameters
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----------
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node_generators : generator
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The generator of node frontiers.
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message_func : callable, optional
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The message function.
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reduce_func : callable, optional
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The reduce function.
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apply_node_func : callable, optional
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The update function.
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See Also
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--------
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dgl.DGLGraph.prop_nodes
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"""
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graph.prop_nodes(nodes_generator, message_func, reduce_func, apply_node_func)
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def prop_edges(graph,
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edges_generator,
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message_func='default',
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reduce_func='default',
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apply_node_func='default'):
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"""Functional method for :func:`dgl.DGLGraph.prop_edges`.
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Parameters
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----------
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edges_generator : generator
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The generator of edge frontiers.
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message_func : callable, optional
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The message function.
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reduce_func : callable, optional
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The reduce function.
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apply_node_func : callable, optional
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The update function.
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See Also
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--------
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dgl.DGLGraph.prop_edges
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"""
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graph.prop_edges(edges_generator, message_func, reduce_func, apply_node_func)
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def prop_nodes_bfs(graph,
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source,
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reverse=False,
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message_func='default',
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reduce_func='default',
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apply_node_func='default'):
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"""Message propagation using node frontiers generated by BFS.
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Parameters
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----------
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graph : DGLGraph
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The graph object.
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source : list, tensor of nodes
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Source nodes.
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reverse : bool, optional
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If true, traverse following the in-edge direction.
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message_func : callable, optional
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The message function.
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reduce_func : callable, optional
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The reduce function.
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apply_node_func : callable, optional
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The update function.
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See Also
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--------
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dgl.traversal.bfs_nodes_generator
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"""
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nodes_gen = trv.bfs_nodes_generator(graph, source, reverse)
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prop_nodes(graph, nodes_gen, message_func, reduce_func, apply_node_func)
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def prop_nodes_topo(graph,
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reverse=False,
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message_func='default',
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reduce_func='default',
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apply_node_func='default'):
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"""Message propagation using node frontiers generated by topological order.
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Parameters
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----------
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graph : DGLGraph
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The graph object.
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reverse : bool, optional
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If true, traverse following the in-edge direction.
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message_func : callable, optional
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The message function.
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reduce_func : callable, optional
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The reduce function.
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apply_node_func : callable, optional
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The update function.
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See Also
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--------
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dgl.traversal.topological_nodes_generator
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"""
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nodes_gen = trv.topological_nodes_generator(graph, reverse)
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prop_nodes(graph, nodes_gen, message_func, reduce_func, apply_node_func)
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def prop_edges_dfs(graph,
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source,
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reverse=False,
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has_reverse_edge=False,
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has_nontree_edge=False,
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message_func='default',
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reduce_func='default',
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apply_node_func='default'):
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"""Message propagation using edge frontiers generated by labeled DFS.
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Parameters
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----------
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graph : DGLGraph
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The graph object.
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source : list, tensor of nodes
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Source nodes.
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reverse : bool, optional
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If true, traverse following the in-edge direction.
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message_func : callable, optional
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The message function.
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reduce_func : callable, optional
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The reduce function.
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apply_node_func : callable, optional
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The update function.
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See Also
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--------
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dgl.traversal.dfs_labeled_edges_generator
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"""
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edges_gen = trv.dfs_labeled_edges_generator(
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graph, source, reverse, has_reverse_edge, has_nontree_edge,
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return_labels=False)
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prop_edges(graph, edges_gen, message_func, reduce_func, apply_node_func)
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