Vassilis N. Ioannidis comments

Results 4 comments of


                                            Vassilis N. Ioannidis

Different behavior of the MultiLayerNeighborSampler when the graph has one node type and edge type and when the graph is heterogenous.

Also the dataloader we define needs to be different other wise the sampling will fail. When the ntypes and etypes are 1 we need to give the tensor with node...

Different behavior of the MultiLayerNeighborSampler when the graph has one node type and edge type and when the graph is heterogenous.

The specific error is the following ``` return forward_call(*input, **kwargs) File "/home/ivasilei/m5-gnn/python/m5gnn/model/rgcn_encoder.py", line 102, in forward return self._graph.number_of_nodes(self.get_ntype_id_from_dst(ntype)) File "/home/ivasilei/.local/lib/python3.9/site-packages/dgl/heterograph.py", line 1239, in get_ntype_id_from_dst inputs_dst = {k: v[:g.number_of_dst_nodes(k)] for k,...

Different behavior of the MultiLayerNeighborSampler when the graph has one node type and edge type and when the graph is heterogenous.

Ok thanks for this. I understand the need for the dictionary. The question is why it does not work with the dictionary when the graph is homogenous

Different behavior of the MultiLayerNeighborSampler when the graph has one node type and edge type and when the graph is heterogenous.

By the way this is a distGraph and hence AttributeError: 'DistGraph' object has no attribute 'is_homogeneous'