To answer issue #119

xautodl/models/cell_searchs/search_cells.py

@@ -85,6 +85,20 @@ class NAS201SearchCell(nn.Module):
             nodes.append(sum(inter_nodes))
         return nodes[-1]
 
+    # GDAS Variant: https://github.com/D-X-Y/AutoDL-Projects/issues/119
+    def forward_gdas_v1(self, inputs, hardwts, index):
+        nodes = [inputs]
+        for i in range(1, self.max_nodes):
+            inter_nodes = []
+            for j in range(i):
+                node_str = "{:}<-{:}".format(i, j)
+                weights = hardwts[self.edge2index[node_str]]
+                argmaxs = index[self.edge2index[node_str]].item()
+                weigsum = weights[argmaxs] * self.edges[node_str](nodes[j])
+                inter_nodes.append(weigsum)
+            nodes.append(sum(inter_nodes))
+        return nodes[-1]
+
     # joint
     def forward_joint(self, inputs, weightss):
         nodes = [inputs]
@@ -152,6 +166,9 @@ class NAS201SearchCell(nn.Module):
         return nodes[-1]
 
 
+# Learning Transferable Architectures for Scalable Image Recognition, CVPR 2018
+
+
 class MixedOp(nn.Module):
     def __init__(self, space, C, stride, affine, track_running_stats):
         super(MixedOp, self).__init__()
@@ -167,7 +184,6 @@ class MixedOp(nn.Module):
         return sum(w * op(x) for w, op in zip(weights, self._ops))
 
 
-# Learning Transferable Architectures for Scalable Image Recognition, CVPR 2018
 class NASNetSearchCell(nn.Module):
     def __init__(
         self,