[Feature] find the existence of negative edges. (#875)

* find the existence of negative edges.

* add comment.

* fix test.

include/dgl/graph_interface.h

@@ -372,6 +372,12 @@ struct Subgraph : public runtime::Object {
   DGL_DECLARE_OBJECT_TYPE_INFO(Subgraph, runtime::Object);
 };
 
+/*! \brief Subgraph data structure for negative subgraph */
+struct NegSubgraph: public Subgraph {
+  /*! \brief The existence of the negative edges in the parent graph. */
+  IdArray exist;
+};
+
 // Define SubgraphRef
 DGL_DEFINE_OBJECT_REF(SubgraphRef, Subgraph);
 

python/dgl/contrib/sampling/sampler.py

@@ -7,6 +7,7 @@ from numbers import Integral
 import traceback
 
 from ..._ffi.function import _init_api
+from ..._ffi.ndarray import empty
 from ... import utils
 from ...nodeflow import NodeFlow
 from ... import backend as F
@@ -496,11 +497,20 @@ class EdgeSampler(object):
             prefetch=False,
             negative_mode="",
             neg_sample_size=0,
-            exclude_positive=False):
+            exclude_positive=False,
+            relations=None):
         self._g = g
         if self.immutable_only and not g._graph.is_readonly():
             raise NotImplementedError("This loader only support read-only graphs.")
 
+        if relations is None:
+            relations = empty((0,), 'int64')
+        else:
+            relations = utils.toindex(relations)
+            relations = relations.todgltensor()
+            assert g.number_of_edges() == len(relations)
+        self._relations = relations
+
         self._batch_size = int(batch_size)
 
         if seed_edges is None:
@@ -544,7 +554,8 @@ class EdgeSampler(object):
             self._num_workers,      # num batches
             self._negative_mode,
             self._neg_sample_size,
-            self._exclude_positive)
+            self._exclude_positive,
+            self._relations)
 
         if len(subgs) == 0:
             return []
@@ -559,6 +570,8 @@ class EdgeSampler(object):
             for i in range(num_pos):
                 pos_subg = subgraph.DGLSubGraph(self.g, subgs[i])
                 neg_subg = subgraph.DGLSubGraph(self.g, subgs[i + num_pos])
+                exist = _CAPI_GetNegEdgeExistence(subgs[i + num_pos]);
+                neg_subg.edata['exist'] = utils.toindex(exist).tousertensor()
                 rets.append((pos_subg, neg_subg))
             return rets
 

src/graph/sampler.cc

@@ -907,9 +907,63 @@ inline bool is_neg_head_mode(const std::string &mode) {
   return mode == "head";
 }
 
-Subgraph NegEdgeSubgraph(GraphPtr gptr, const Subgraph &pos_subg,
-                         const std::string &neg_mode,
-                         int neg_sample_size, bool exclude_positive) {
+IdArray GetGlobalVid(IdArray induced_nid, IdArray subg_nid) {
+  IdArray gnid = IdArray::Empty({subg_nid->shape[0]}, subg_nid->dtype, subg_nid->ctx);
+  const dgl_id_t *induced_nid_data = static_cast<dgl_id_t *>(induced_nid->data);
+  const dgl_id_t *subg_nid_data = static_cast<dgl_id_t *>(subg_nid->data);
+  dgl_id_t *gnid_data = static_cast<dgl_id_t *>(gnid->data);
+  for (int64_t i = 0; i < subg_nid->shape[0]; i++) {
+    gnid_data[i] = induced_nid_data[subg_nid_data[i]];
+  }
+  return gnid;
+}
+
+IdArray CheckExistence(GraphPtr gptr, IdArray neg_src, IdArray neg_dst,
+                       IdArray induced_nid) {
+  return gptr->HasEdgesBetween(GetGlobalVid(induced_nid, neg_src),
+                               GetGlobalVid(induced_nid, neg_dst));
+}
+
+IdArray CheckExistence(GraphPtr gptr, IdArray relations,
+                       IdArray neg_src, IdArray neg_dst,
+                       IdArray induced_nid, IdArray neg_eid) {
+  neg_src = GetGlobalVid(induced_nid, neg_src);
+  neg_dst = GetGlobalVid(induced_nid, neg_dst);
+  BoolArray exist = gptr->HasEdgesBetween(neg_src, neg_dst);
+  dgl_id_t *neg_dst_data = static_cast<dgl_id_t *>(neg_dst->data);
+  dgl_id_t *neg_src_data = static_cast<dgl_id_t *>(neg_src->data);
+  dgl_id_t *neg_eid_data = static_cast<dgl_id_t *>(neg_eid->data);
+  dgl_id_t *relation_data = static_cast<dgl_id_t *>(relations->data);
+  // TODO(zhengda) is this right?
+  dgl_id_t *exist_data = static_cast<dgl_id_t *>(exist->data);
+  int64_t num_neg_edges = neg_src->shape[0];
+  for (int64_t i = 0; i < num_neg_edges; i++) {
+    // If the edge doesn't exist, we don't need to do anything.
+    if (!exist_data[i])
+      continue;
+    // If the edge exists, we need to double check if the relations match.
+    // If they match, this negative edge isn't really a negative edge.
+    dgl_id_t eid1 = neg_eid_data[i];
+    dgl_id_t orig_neg_rel1 = relation_data[eid1];
+    IdArray eids = gptr->EdgeId(neg_src_data[i], neg_dst_data[i]);
+    dgl_id_t *eid_data = static_cast<dgl_id_t *>(eids->data);
+    int64_t num_edges_between = eids->shape[0];
+    bool same_rel = false;
+    for (int64_t j = 0; j < num_edges_between; j++) {
+      dgl_id_t neg_rel1 = relation_data[eid_data[j]];
+      if (neg_rel1 == orig_neg_rel1) {
+        same_rel = true;
+        break;
+      }
+    }
+    exist_data[i] = same_rel;
+  }
+  return exist;
+}
+
+NegSubgraph NegEdgeSubgraph(GraphPtr gptr, IdArray relations, const Subgraph &pos_subg,
+                            const std::string &neg_mode,
+                            int neg_sample_size, bool exclude_positive) {
   int64_t num_tot_nodes = gptr->NumVertices();
   bool is_multigraph = gptr->IsMultigraph();
   std::vector<IdArray> adj = pos_subg.graph->GetAdj(false, "coo");
@@ -991,20 +1045,28 @@ Subgraph NegEdgeSubgraph(GraphPtr gptr, const Subgraph &pos_subg,
     induced_neg_vid_data[it->second] = it->first;
   }
 
-  Subgraph neg_subg;
+  NegSubgraph neg_subg;
   // We sample negative vertices without replacement.
   // There shouldn't be duplicated edges.
   COOPtr neg_coo(new COO(num_neg_nodes, neg_src, neg_dst, is_multigraph));
   neg_subg.graph = GraphPtr(new ImmutableGraph(neg_coo));
   neg_subg.induced_vertices = induced_neg_vid;
   neg_subg.induced_edges = induced_neg_eid;
+  // TODO(zhengda) we should provide an array of 1s if exclude_positive
+  if (relations->shape[0] == 0) {
+    neg_subg.exist = CheckExistence(gptr, neg_src, neg_dst, induced_neg_vid);
+  } else {
+    neg_subg.exist = CheckExistence(gptr, relations, neg_src, neg_dst,
+                                    induced_neg_vid, induced_neg_eid);
+  }
   return neg_subg;
 }
 
-Subgraph PBGNegEdgeSubgraph(int64_t num_tot_nodes, const Subgraph &pos_subg,
+NegSubgraph PBGNegEdgeSubgraph(GraphPtr gptr, IdArray relations, const Subgraph &pos_subg,
                             const std::string &neg_mode,
                             int neg_sample_size, bool is_multigraph,
                             bool exclude_positive) {
+  int64_t num_tot_nodes = gptr->NumVertices();
   std::vector<IdArray> adj = pos_subg.graph->GetAdj(false, "coo");
   IdArray coo = adj[0];
   int64_t num_pos_edges = coo->shape[0] / 2;
@@ -1107,13 +1169,19 @@ Subgraph PBGNegEdgeSubgraph(int64_t num_tot_nodes, const Subgraph &pos_subg,
     induced_neg_vid_data[it->second] = it->first;
   }
 
-  Subgraph neg_subg;
+  NegSubgraph neg_subg;
   // We sample negative vertices without replacement.
   // There shouldn't be duplicated edges.
   COOPtr neg_coo(new COO(num_neg_nodes, neg_src, neg_dst, is_multigraph));
   neg_subg.graph = GraphPtr(new ImmutableGraph(neg_coo));
   neg_subg.induced_vertices = induced_neg_vid;
   neg_subg.induced_edges = induced_neg_eid;
+  if (relations->shape[0] == 0) {
+    neg_subg.exist = CheckExistence(gptr, neg_src, neg_dst, induced_neg_vid);
+  } else {
+    neg_subg.exist = CheckExistence(gptr, relations, neg_src, neg_dst,
+                                    induced_neg_vid, induced_neg_eid);
+  }
   return neg_subg;
 }
 
@@ -1121,6 +1189,10 @@ inline SubgraphRef ConvertRef(const Subgraph &subg) {
     return SubgraphRef(std::shared_ptr<Subgraph>(new Subgraph(subg)));
 }
 
+inline SubgraphRef ConvertRef(const NegSubgraph &subg) {
+    return SubgraphRef(std::shared_ptr<Subgraph>(new NegSubgraph(subg)));
+}
+
 }  // namespace
 
 DGL_REGISTER_GLOBAL("sampling._CAPI_UniformEdgeSampling")
@@ -1134,6 +1206,7 @@ DGL_REGISTER_GLOBAL("sampling._CAPI_UniformEdgeSampling")
     const std::string neg_mode = args[5];
     const int neg_sample_size = args[6];
     const bool exclude_positive = args[7];
+    IdArray relations = args[8];
     // process args
     auto gptr = std::dynamic_pointer_cast<ImmutableGraph>(g.sptr());
     CHECK(gptr) << "sampling isn't implemented in mutable graph";
@@ -1165,13 +1238,13 @@ DGL_REGISTER_GLOBAL("sampling._CAPI_UniformEdgeSampling")
       // For PBG negative sampling, we accept "PBG-head" for corrupting head
       // nodes and "PBG-tail" for corrupting tail nodes.
       if (neg_mode.substr(0, 3) == "PBG") {
-        Subgraph neg_subg = PBGNegEdgeSubgraph(gptr->NumVertices(), subg,
-                                               neg_mode.substr(4), neg_sample_size,
-                                               gptr->IsMultigraph(), exclude_positive);
+        NegSubgraph neg_subg = PBGNegEdgeSubgraph(gptr, relations, subg,
+                                                  neg_mode.substr(4), neg_sample_size,
+                                                  gptr->IsMultigraph(), exclude_positive);
         negative_subgs[i] = ConvertRef(neg_subg);
       } else if (neg_mode.size() > 0) {
-        Subgraph neg_subg = NegEdgeSubgraph(gptr, subg, neg_mode, neg_sample_size,
-                                            exclude_positive);
+        NegSubgraph neg_subg = NegEdgeSubgraph(gptr, relations, subg, neg_mode, neg_sample_size,
+                                               exclude_positive);
         negative_subgs[i] = ConvertRef(neg_subg);
       }
     }
@@ -1181,4 +1254,12 @@ DGL_REGISTER_GLOBAL("sampling._CAPI_UniformEdgeSampling")
     *rv = List<SubgraphRef>(positive_subgs);
   });
 
+
+DGL_REGISTER_GLOBAL("sampling._CAPI_GetNegEdgeExistence")
+.set_body([] (DGLArgs args, DGLRetValue* rv) {
+  SubgraphRef g = args[0];
+  auto gptr = std::dynamic_pointer_cast<NegSubgraph>(g.sptr());
+  *rv = gptr->exist;
+});
+
 }  // namespace dgl

tests/compute/test_sampler.py

@@ -222,6 +222,8 @@ def test_setseed():
 
 def check_negative_sampler(mode, exclude_positive):
     g = generate_rand_graph(100)
+    etype = np.random.randint(0, 10, size=g.number_of_edges(), dtype=np.int64)
+    g.edata['etype'] = F.tensor(etype)
 
     pos_gsrc, pos_gdst, pos_geid = g.all_edges(form='all', order='eid')
     pos_map = {}
@@ -232,25 +234,20 @@ def check_negative_sampler(mode, exclude_positive):
 
     EdgeSampler = getattr(dgl.contrib.sampling, 'EdgeSampler')
     neg_size = 10
+    # Test the homogeneous graph.
     for pos_edges, neg_edges in EdgeSampler(g, 50,
                                             negative_mode=mode,
                                             neg_sample_size=neg_size,
                                             exclude_positive=exclude_positive):
-        pos_nid = pos_edges.parent_nid
-        pos_eid = pos_edges.parent_eid
         pos_lsrc, pos_ldst, pos_leid = pos_edges.all_edges(form='all', order='eid')
-        pos_src = pos_nid[pos_lsrc]
-        pos_dst = pos_nid[pos_ldst]
-        pos_eid = pos_eid[pos_leid]
-        assert_array_equal(F.asnumpy(pos_eid), F.asnumpy(g.edge_ids(pos_src, pos_dst)))
+        assert_array_equal(F.asnumpy(pos_edges.parent_eid[pos_leid]),
+                           F.asnumpy(g.edge_ids(pos_edges.parent_nid[pos_lsrc],
+                                                pos_edges.parent_nid[pos_ldst])))
 
         neg_lsrc, neg_ldst, neg_leid = neg_edges.all_edges(form='all', order='eid')
-        neg_nid = neg_edges.parent_nid
-        neg_eid = neg_edges.parent_eid
-        neg_src = neg_nid[neg_lsrc]
-        neg_dst = neg_nid[neg_ldst]
-        neg_eid = neg_eid[neg_leid]
-
+        neg_src = neg_edges.parent_nid[neg_lsrc]
+        neg_dst = neg_edges.parent_nid[neg_ldst]
+        neg_eid = neg_edges.parent_eid[neg_leid]
         for i in range(len(neg_eid)):
             neg_d = int(F.asnumpy(neg_dst[i]))
             neg_e = int(F.asnumpy(neg_eid[i]))
@@ -258,6 +255,32 @@ def check_negative_sampler(mode, exclude_positive):
             if exclude_positive:
                 assert int(F.asnumpy(neg_src[i])) != pos_map[(neg_d, neg_e)]
 
+        exist = neg_edges.edata['exist']
+        if exclude_positive:
+            assert np.sum(F.asnumpy(exist) == 0) == len(exist)
+        else:
+            assert F.array_equal(g.has_edges_between(neg_src, neg_dst), exist)
+
+    # Test the knowledge graph.
+    for _, neg_edges in EdgeSampler(g, 50,
+                                    negative_mode=mode,
+                                    neg_sample_size=neg_size,
+                                    exclude_positive=exclude_positive,
+                                    relations=g.edata['etype']):
+        neg_lsrc, neg_ldst, neg_leid = neg_edges.all_edges(form='all', order='eid')
+        neg_src = neg_edges.parent_nid[neg_lsrc]
+        neg_dst = neg_edges.parent_nid[neg_ldst]
+        neg_eid = neg_edges.parent_eid[neg_leid]
+        exists = neg_edges.edata['exist']
+        neg_edges.edata['etype'] = g.edata['etype'][neg_eid]
+        for i in range(len(neg_eid)):
+            u, v = F.asnumpy(neg_src[i]), F.asnumpy(neg_dst[i])
+            if g.has_edge_between(u, v):
+                eid = g.edge_id(u, v)
+                etype = g.edata['etype'][eid]
+                exist = neg_edges.edata['etype'][i] == etype
+                assert F.asnumpy(exists[i]) == F.asnumpy(exist)
+
 def test_negative_sampler():
     check_negative_sampler('head', True)
     check_negative_sampler('PBG-head', False)