[Doc] Add Pseudo Code for HeteroGraphConv (#2729)

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Co-authored-by: Ubuntu <ubuntu@ip-172-31-15-8.us-west-2.compute.internal>

python/dgl/nn/mxnet/hetero.py

@@ -11,9 +11,26 @@ class HeteroGraphConv(nn.Block):
     relation graphs, which reads the features from source nodes and writes the
     updated ones to destination nodes. If multiple relations have the same
     destination node types, their results are aggregated by the specified method.
-
     If the relation graph has no edge, the corresponding module will not be called.
 
+    Pseudo-code:
+
+    .. code::
+
+        outputs = {nty : [] for nty in g.dsttypes}
+        # Apply sub-modules on their associating relation graphs in parallel
+        for relation in g.canonical_etypes:
+            stype, etype, dtype = relation
+            dstdata = relation_submodule(g[relation], ...)
+            outputs[dtype].append(dstdata)
+
+        # Aggregate the results for each destination node type
+        rsts = {}
+        for ntype, ntype_outputs in outputs.items():
+            if len(ntype_outputs) != 0:
+                rsts[ntype] = aggregate(ntype_outputs)
+        return rsts
+
     Examples
     --------
 

python/dgl/nn/pytorch/hetero.py

@@ -11,9 +11,26 @@ class HeteroGraphConv(nn.Module):
     relation graphs, which reads the features from source nodes and writes the
     updated ones to destination nodes. If multiple relations have the same
     destination node types, their results are aggregated by the specified method.
-
     If the relation graph has no edge, the corresponding module will not be called.
 
+    Pseudo-code:
+
+    .. code::
+
+        outputs = {nty : [] for nty in g.dsttypes}
+        # Apply sub-modules on their associating relation graphs in parallel
+        for relation in g.canonical_etypes:
+            stype, etype, dtype = relation
+            dstdata = relation_submodule(g[relation], ...)
+            outputs[dtype].append(dstdata)
+
+        # Aggregate the results for each destination node type
+        rsts = {}
+        for ntype, ntype_outputs in outputs.items():
+            if len(ntype_outputs) != 0:
+                rsts[ntype] = aggregate(ntype_outputs)
+        return rsts
+
     Examples
     --------
 

python/dgl/nn/tensorflow/hetero.py

@@ -11,9 +11,26 @@ class HeteroGraphConv(layers.Layer):
     relation graphs, which reads the features from source nodes and writes the
     updated ones to destination nodes. If multiple relations have the same
     destination node types, their results are aggregated by the specified method.
-
     If the relation graph has no edge, the corresponding module will not be called.
 
+    Pseudo-code:
+
+    .. code::
+
+        outputs = {nty : [] for nty in g.dsttypes}
+        # Apply sub-modules on their associating relation graphs in parallel
+        for relation in g.canonical_etypes:
+            stype, etype, dtype = relation
+            dstdata = relation_submodule(g[relation], ...)
+            outputs[dtype].append(dstdata)
+
+        # Aggregate the results for each destination node type
+        rsts = {}
+        for ntype, ntype_outputs in outputs.items():
+            if len(ntype_outputs) != 0:
+                rsts[ntype] = aggregate(ntype_outputs)
+        return rsts
+
     Examples
     --------