[IR] Implement model.graphs() (#2200)

Implement model.graphs() as a way to retrieve the main graph and all
subgraphs of it in the model.

Given

(1) how useful the method is
(2) I couldn't find an appropriate name for it in `traversal.py`
(3) Users familiar with onnxruntime optimization tools expect this
method. In PyTorch a similar `modules()` method exists.

I created this method as a core method instead of an iterator in
`traversal.py`.

Depends on #2183

Author: justinchuby

onnxscript/ir/_core.py

@@ -2563,6 +2563,25 @@ def __repr__(self) -> str:
     graph={textwrap.indent(repr(self.graph), " " * 4).strip()}
 )"""
 
+    def graphs(self) -> Iterable[Graph]:
+        """Get all graphs and subgraphs in the model.
+
+        This is a convenience method to traverse the model. Consider using
+        `onnxscript.ir.traversal.RecursiveGraphIterator` for more advanced
+        traversals on nodes.
+        """
+        # NOTE(justinchuby): Given
+        # (1) how useful the method is
+        # (2) I couldn't find an appropriate name for it in `traversal.py`
+        # (3) Users familiar with onnxruntime optimization tools expect this method
+        # I created this method as a core method instead of an iterator in
+        # `traversal.py`.
+        seen_graphs: set[Graph] = set()
+        for node in onnxscript.ir.traversal.RecursiveGraphIterator(self.graph):
+            if node.graph is not None and node.graph not in seen_graphs:
+                seen_graphs.add(node.graph)
+                yield node.graph
+
 
 class Function(_protocols.FunctionProtocol, Sequence[Node], _display.PrettyPrintable):
     """IR functions.

onnxscript/ir/_core_test.py

@@ -1152,6 +1152,61 @@ def test_topological_sort_subgraph(self):
         )
 
 
+class ModelTest(unittest.TestCase):
+    def test_graphs_returns_all_subgraphs(self):
+        # main_graph: nodes=[a,b,c,d,>,if], edges=[(a,>),(b,>),(>,if)], subgraphs={if:[then_graph,else_graph]}
+        # then_graph: nodes=[sub], edges=[(c,sub),(d,sub)]
+        # else_graph: nodes=[add], edges=[(c,add),(d,add)]
+        v0 = _core.Value(name="va")
+        v1 = _core.Value(name="vb")
+        v2 = _core.Value(name="vc")
+        v3 = _core.Value(name="vd")
+        node0 = _core.Node("", "a", inputs=(v0,), num_outputs=1)
+        node1 = _core.Node("", "b", inputs=(v1,), num_outputs=1)
+        node2 = _core.Node("", "c", inputs=(v2,), num_outputs=1)
+        node3 = _core.Node("", "d", inputs=(v3,), num_outputs=1)
+        node4 = _core.Node(
+            "", "sub", inputs=(node2.outputs[0], node3.outputs[0]), num_outputs=1
+        )
+        node5 = _core.Node(
+            "", "add", inputs=(node2.outputs[0], node3.outputs[0]), num_outputs=1
+        )
+        node6 = _core.Node("", ">", inputs=(node0.outputs[0], node1.outputs[0]), num_outputs=1)
+        then_graph = _core.Graph(
+            inputs=(node2.outputs[0], node3.outputs[0]),
+            outputs=(node4.outputs[0],),
+            nodes=(node4,),
+            name="then_graph",
+        )
+        else_graph = _core.Graph(
+            inputs=(node2.outputs[0], node3.outputs[0]),
+            outputs=(node5.outputs[0],),
+            nodes=(node5,),
+            name="else_graph",
+        )
+        node7 = _core.Node(
+            "",
+            "if",
+            inputs=(node6.outputs[0],),
+            num_outputs=1,
+            attributes=[
+                ir.AttrGraph("then_branch", then_graph),
+                ir.AttrGraph("else_branch", else_graph),
+            ],
+        )
+        main_graph = _core.Graph(
+            inputs=(v0, v1, v2, v3),
+            outputs=(node7.outputs[0],),
+            nodes=(node0, node1, node2, node6, node7),
+            name="main_graph",
+        )
+        model = _core.Model(main_graph, ir_version=10)
+        self.assertEqual(
+            tuple(model.graphs()),
+            (main_graph, then_graph, else_graph),
+        )
+
+
 class TypeTest(unittest.TestCase):
     @parameterized.parameterized.expand(
         [