[Dataset] Citation graph (#1902)

* citation graph

* GCN example use new citatoin dataset

* mxnet gat

* triger

* Fix

* Fix gat

* fix

* Fix tensorflow dgi

* Fix appnp, graphsage for mxnet

* fix monet and sgc for mxnet

* Fix tagcn

* update sgc, appnp
Co-authored-by: Ubuntu <ubuntu@ip-172-31-51-214.ec2.internal>

python/dgl/data/__init__.py

@@ -17,6 +17,7 @@ from .bitcoinotc import BitcoinOTC
 from .gdelt import GDELT
 from .icews18 import ICEWS18
 from .qm7b import QM7b
+from .citation_graph import CoraGraphDataset, CiteseerGraphDataset, PubmedGraphDataset
 
 
 def register_data_args(parser):
@@ -27,7 +28,6 @@ def register_data_args(parser):
         help=
         "The input dataset. Can be cora, citeseer, pubmed, syn(synthetic dataset) or reddit"
     )
-    citegrh.register_args(parser)
 
 
 def load_data(args):
@@ -37,8 +37,6 @@ def load_data(args):
         return citegrh.load_citeseer()
     elif args.dataset == 'pubmed':
         return citegrh.load_pubmed()
-    elif args.dataset == 'syn':
-        return citegrh.load_synthetic(args)
     elif args.dataset is not None and args.dataset.startswith('reddit'):
         return RedditDataset(self_loop=('self-loop' in args.dataset))
     else:

python/dgl/data/rdf.py

@@ -249,6 +249,7 @@ class RDFGraphDataset(DGLBuiltinDataset):
         # save for compatability
         self._train_idx = F.tensor(train_idx)
         self._test_idx = F.tensor(test_idx)
+        self._labels = labels
 
     def build_graph(self, mg, src, dst, ntid, etid, ntypes, etypes):
         """Build the graphs
@@ -638,17 +639,17 @@ class AIFBDataset(RDFGraphDataset):
 
         Return
         -------
-            dgl.DGLGraph
-                graph structure, node features and labels.
-                - ndata['train_mask']: mask for training node set
-                - ndata['test_mask']: mask for testing node set
-                - ndata['labels']: mask for labels
+        dgl.DGLGraph
+            graph structure, node features and labels.
+            - ndata['train_mask']: mask for training node set
+            - ndata['test_mask']: mask for testing node set
+            - ndata['labels']: mask for labels
         """
         return super(AIFBDataset, self).__getitem__(idx)
 
     def __len__(self):
         r"""The number of graphs in the dataset."""
-        return super(AIFBDataset, self).__len__(idx)
+        return super(AIFBDataset, self).__len__()
 
     def parse_entity(self, term):
         if isinstance(term, rdf.Literal):
@@ -801,17 +802,17 @@ class MUTAGDataset(RDFGraphDataset):
 
         Return
         -------
-            dgl.DGLGraph
-                graph structure, node features and labels.
-                - ndata['train_mask']: mask for training node set
-                - ndata['test_mask']: mask for testing node set
-                - ndata['labels']: mask for labels
+        dgl.DGLGraph
+            graph structure, node features and labels.
+            - ndata['train_mask']: mask for training node set
+            - ndata['test_mask']: mask for testing node set
+            - ndata['labels']: mask for labels
         """
         return super(MUTAGDataset, self).__getitem__(idx)
 
     def __len__(self):
         r"""The number of graphs in the dataset."""
-        return super(MUTAGDataset, self).__len__(idx)
+        return super(MUTAGDataset, self).__len__()
 
     def parse_entity(self, term):
         if isinstance(term, rdf.Literal):
@@ -980,17 +981,17 @@ class BGSDataset(RDFGraphDataset):
 
         Return
         -------
-            dgl.DGLGraph
-                graph structure, node features and labels.
-                - ndata['train_mask']: mask for training node set
-                - ndata['test_mask']: mask for testing node set
-                - ndata['labels']: mask for labels
+        dgl.DGLGraph
+            graph structure, node features and labels.
+            - ndata['train_mask']: mask for training node set
+            - ndata['test_mask']: mask for testing node set
+            - ndata['labels']: mask for labels
         """
         return super(BGSDataset, self).__getitem__(idx)
 
     def __len__(self):
         r"""The number of graphs in the dataset."""
-        return super(BGSDataset, self).__len__(idx)
+        return super(BGSDataset, self).__len__()
 
     def parse_entity(self, term):
         if isinstance(term, rdf.Literal):
@@ -1155,17 +1156,17 @@ class AMDataset(RDFGraphDataset):
 
         Return
         -------
-            dgl.DGLGraph
-                graph structure, node features and labels.
-                - ndata['train_mask']: mask for training node set
-                - ndata['test_mask']: mask for testing node set
-                - ndata['labels']: mask for labels
+        dgl.DGLGraph
+            graph structure, node features and labels.
+            - ndata['train_mask']: mask for training node set
+            - ndata['test_mask']: mask for testing node set
+            - ndata['labels']: mask for labels
         """
         return super(AMDataset, self).__getitem__(idx)
 
     def __len__(self):
         r"""The number of graphs in the dataset."""
-        return super(AMDataset, self).__len__(idx)
+        return super(AMDataset, self).__len__()
 
     def parse_entity(self, term):
         if isinstance(term, rdf.Literal):