dmlc--dgl
be444e52d9
* Update graph * Fix for dgl.graph * from_scipy * Replace canonical_etypes with relations * from_networkx * Update for hetero_from_relations * Roll back the change of canonical_etypes to relations * heterograph * bipartite * Update doc * Fix lint * Fix lint * Fix test cases * Fix * Fix * Fix * Fix * Fix * Fix * Update * Fix test * Fix * Update * Use DGLError * Update * Update * Update * Update * Fix * Fix * Fix * Fix * Fix * Fix * Fix * Fix * Update * Fix * Update * Fix * Fix * Fix * Update * Fix * Update * Fix * Update * Update * Update * Update * Update * Update * Update * Fix * Fix * Update * Update * Update * Update * Update * Update * rewrite sanity checks * delete unnecessary checks * Update * Update * Update * Update * Update * Update * Update * Update * Fix * Update * Update * Update * Fix * Fix * Fix * Update * Fix * Update * Fix * Fix * Update * Fix * Update * Fix Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com> Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com> Co-authored-by: Quan Gan <coin2028@hotmail.com>
132 行
4.5 KiB
C++
132 行
4.5 KiB
C++
/*!
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* Copyright (c) 2019 by Contributors
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* \file dgl/transform.h
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* \brief DGL graph transformations
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*/
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#ifndef DGL_TRANSFORM_H_
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#define DGL_TRANSFORM_H_
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#include <vector>
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#include <tuple>
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#include <utility>
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#include "base_heterograph.h"
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#include "array.h"
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namespace dgl {
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namespace transform {
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/*!
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* \brief Given a list of graphs, remove the common nodes that do not have inbound and
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* outbound edges.
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*
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* The graphs should have identical node ID space (i.e. should have the same set of nodes,
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* including types and IDs).
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*
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* \param graphs The list of graphs.
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* \param always_preserve The list of nodes to preserve regardless of whether the inbound
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* or outbound edges exist.
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*
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* \return A pair. The first element is the list of compacted graphs, and the second
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* element is the mapping from the compacted graphs and the original graph.
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*/
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std::pair<std::vector<HeteroGraphPtr>, std::vector<IdArray>>
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CompactGraphs(
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const std::vector<HeteroGraphPtr> &graphs,
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const std::vector<IdArray> &always_preserve);
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/*!
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* \brief Convert a graph into a bipartite-structured graph for message passing.
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*
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* Specifically, we create one node type \c ntype_l on the "left" side and another
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* node type \c ntype_r on the "right" side for each node type \c ntype. The nodes of
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* type \c ntype_r would contain the nodes designated by the caller, and node type
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* \c ntype_l would contain the nodes that has an edge connecting to one of the
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* designated nodes.
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*
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* The nodes of \c ntype_l would also contain the nodes in node type \c ntype_r.
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*
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* This function is often used for constructing a series of dependency graphs for
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* multi-layer message passing, where we first construct a series of frontier graphs
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* on the original node space, and run the following to get the bipartite graph needed
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* for message passing with each GNN layer:
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*
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* <code>
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* bipartites = [None] * len(num_layers)
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* for l in reversed(range(len(layers))):
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* bipartites[l], seeds = to_bipartite(frontier[l], seeds)
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* x = graph.ndata["h"][seeds]
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* for g, layer in zip(bipartites, layers):
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* x_src = x
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* x_dst = x[:len(g.dsttype)]
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* x = sageconv(g, (x_src, x_dst))
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* output = x
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* </code>
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*
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* \param graph The graph.
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* \param rhs_nodes Designated nodes that would appear on the right side.
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* \param include_rhs_in_lhs If false, do not include the nodes of node type \c ntype_r
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* in \c ntype_l.
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*
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* \return A triplet containing
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* * The bipartite-structured graph,
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* * The induced node from the left side for each graph,
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* * The induced edges.
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*
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* \note If include_rhs_in_lhs is true, then for each node type \c ntype, the nodes
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* in rhs_nodes[ntype] would always appear first in the nodes of type \c ntype_l
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* in the new graph.
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*/
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std::tuple<HeteroGraphPtr, std::vector<IdArray>, std::vector<IdArray>>
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ToBlock(HeteroGraphPtr graph, const std::vector<IdArray> &rhs_nodes, bool include_rhs_in_lhs);
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/*!
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* \brief Convert a multigraph to a simple graph.
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*
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* \return A triplet of
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* * \c hg : The said simple graph.
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* * \c count : The array of edge occurrences per edge type.
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* * \c edge_map : The mapping from original edge IDs to new edge IDs per edge type.
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*
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* \note Example: consider a graph with the following edges
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*
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* [(0, 1), (1, 3), (2, 2), (1, 3), (1, 4), (1, 4)]
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*
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* Then ToSimpleGraph(g) would yield the following elements:
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*
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* * The first element would be the simple graph itself with the following edges
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*
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* [(0, 1), (1, 3), (1, 4), (2, 2)]
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*
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* * The second element is an array \c count. \c count[i] stands for the number of edges
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* connecting simple_g.src[i] and simple_g.dst[i] in the original graph.
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*
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* count[0] = [1, 2, 2, 1]
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*
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* * One can find the mapping between edges from the original graph to the new simple
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* graph.
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*
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* edge_map[0] = [0, 1, 3, 1, 2, 2]
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*/
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std::tuple<HeteroGraphPtr, std::vector<IdArray>, std::vector<IdArray>>
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ToSimpleGraph(const HeteroGraphPtr graph);
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/*!
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* \brief Remove edges from a graph.
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*
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* \param graph The graph.
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* \param eids The edge IDs to remove per edge type.
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*
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* \return A pair of the graph with edges removed, as well as the edge ID mapping from
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* the original graph to the new graph per edge type.
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*/
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std::pair<HeteroGraphPtr, std::vector<IdArray>>
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RemoveEdges(const HeteroGraphPtr graph, const std::vector<IdArray> &eids);
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}; // namespace transform
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}; // namespace dgl
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#endif // DGL_TRANSFORM_H_
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