add con ops control for graphnasspace

autogl/module/nas/space/graph_nas.py

@@ -39,6 +39,8 @@ GRAPHNAS_DEFAULT_ACT_OPS = [
     "elu",
 ]
 
+GRAPHNAS_DEFAULT_CON_OPS=["add", "product", "concat"]
+# GRAPHNAS_DEFAULT_CON_OPS=[ "concat"] # for darts
 
 class LambdaModule(nn.Module):
     def __init__(self, lambd):
@@ -83,6 +85,7 @@ class GraphNasNodeClassificationSpace(BaseSpace):
         output_dim: _typ.Optional[int] = None,
         gnn_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = GRAPHNAS_DEFAULT_GNN_OPS,
         act_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = GRAPHNAS_DEFAULT_ACT_OPS,
+        con_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = GRAPHNAS_DEFAULT_CON_OPS
     ):
         super().__init__()
         self.layer_number = layer_number
@@ -91,6 +94,7 @@ class GraphNasNodeClassificationSpace(BaseSpace):
         self.output_dim = output_dim
         self.gnn_ops = gnn_ops
         self.act_ops = act_ops
+        self.con_ops = con_ops
         self.dropout = dropout
 
     def instantiate(
@@ -102,6 +106,7 @@ class GraphNasNodeClassificationSpace(BaseSpace):
         output_dim: _typ.Optional[int] = None,
         gnn_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = None,
         act_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = None,
+        con_ops: _typ.Sequence[_typ.Union[str, _typ.Any]] = None,
     ):
         super().instantiate()
         self.dropout = dropout or self.dropout
@@ -111,6 +116,7 @@ class GraphNasNodeClassificationSpace(BaseSpace):
         self.output_dim = output_dim or self.output_dim
         self.gnn_ops = gnn_ops or self.gnn_ops
         self.act_ops = act_ops or self.act_ops
+        self.con_ops = con_ops or self.con_ops
         self.preproc0 = nn.Linear(self.input_dim, self.hidden_dim)
         self.preproc1 = nn.Linear(self.input_dim, self.hidden_dim)
         node_labels = [mutables.InputChoice.NO_KEY, mutables.InputChoice.NO_KEY]
@@ -146,13 +152,15 @@ class GraphNasNodeClassificationSpace(BaseSpace):
                 2 * layer, [act_map_nn(a) for a in self.act_ops], key="act"
             ),
         )
-        setattr(
-            self,
-            "concat",
-            self.setLayerChoice(
-                2 * layer + 1, map_nn(["add", "product", "concat"]), key="concat"
-            ),
-        )
+        # for DARTS, len(con_ops) can only <=1, for dimension problems 
+        if len(self.con_ops)>1:
+            setattr(
+                self,
+                "concat",
+                self.setLayerChoice(
+                    2 * layer + 1, map_nn(self.con_ops), key="concat"
+                ),
+            )
         self._initialized = True
         self.classifier1 = nn.Linear(
             self.hidden_dim * self.layer_number, self.output_dim
@@ -172,7 +180,13 @@ class GraphNasNodeClassificationSpace(BaseSpace):
             node_out = bk_gconv(op,data,node_in)
             prev_nodes_out.append(node_out)
         act = getattr(self, "act")
-        con = getattr(self, "concat")()
+        if len(self.con_ops)>1:
+            con = getattr(self, "concat")()
+        elif len(self.con_ops)==1:
+            con=self.con_ops[0]
+        else:
+            con="concat"
+
         states = prev_nodes_out
         if con == "concat":
             x = torch.cat(states[2:], dim=1)