Zhijxu/fix toposort (#18705)

in training, shape/size need to be executed immediately when it's ok to
be executed and thus to save memory if possible;

the toposort logic is enhanced before, while didn't take of the
"shape->size" pattern, which make the following size op will not show up
in toposort result.

onnxruntime/core/graph/graph_viewer.cc

@@ -57,12 +57,14 @@ GraphViewer::GraphViewer(const Graph& graph, const IndexedSubGraph* filter_info)
                       : ConstGraphNodes::NodeFilterFunc(nullptr))},
       filter_info_{filter_info} {
   std::vector<const Node*> leaf_nodes;
+#ifdef ENABLE_TRAINING
   // Keep the info of shape and size nodes and their parents so that after topological sort, we can move them
   // right after their parents. This is to make sure the shape and size nodes are executed right after their parents
   // so it's possible the input tensor memory can be released as soon as possible. This is especially important
   // for non-CPU devices or for training case where some gradient graphs use only shape/size of tensors from forward.
   InlinedHashSet<NodeIndex> shape_size_nodes;
   InlinedHashMap<NodeIndex, InlinedVector<NodeIndex>> shape_size_parents;
+#endif
   for (auto& node : graph_->Nodes()) {
     // This is a leaf node (without any output node)
     if (node.OutputNodesBegin() == node.OutputNodesEnd()) {
@@ -72,6 +74,7 @@ GraphViewer::GraphViewer(const Graph& graph, const IndexedSubGraph* filter_info)
     if (node.InputEdgesBegin() == node.InputEdgesEnd()) {
       root_nodes_.push_back(node.Index());
     }
+#ifdef ENABLE_TRAINING
     if ((node.OpType() == "Shape" || node.OpType() == "Size") && node.InputEdgesBegin() != node.InputEdgesEnd()) {
       shape_size_nodes.insert(node.Index());
       NodeIndex parent = node.InputNodesBegin()->Index();
@@ -81,6 +84,7 @@ GraphViewer::GraphViewer(const Graph& graph, const IndexedSubGraph* filter_info)
         shape_size_parents[parent].push_back(node.Index());
       }
     }
+#endif
   }
 
   graph.ReverseDFSFrom(
@@ -90,21 +94,24 @@ GraphViewer::GraphViewer(const Graph& graph, const IndexedSubGraph* filter_info)
         nodes_in_topological_order_.push_back(n->Index());
       },
       NodeCompare());
-
+#ifdef ENABLE_TRAINING
   auto original = std::move(nodes_in_topological_order_);
   nodes_in_topological_order_.reserve(original.size());
+  InlinedHashSet<NodeIndex> visited;
   for (auto& node : original) {
-    if (shape_size_nodes.find(node) != shape_size_nodes.end()) {
+    if (visited.find(node) != visited.end()) {
       continue;
     }
     nodes_in_topological_order_.push_back(node);
+    visited.insert(node);
     if (shape_size_parents.find(node) != shape_size_parents.end()) {
       for (auto& following_node : shape_size_parents[node]) {
         nodes_in_topological_order_.push_back(following_node);
+        visited.insert(following_node);
       }
     }
   }
-
+#endif
 #if !defined(ORT_MINIMAL_BUILD)
   graph.KahnsTopologicalSort(
       [this](const Node* n) {