Generalize view_copy fusion.

backends/cadence/aot/fuse_ops.py

@@ -526,34 +526,14 @@ class FuseCascadedViewOps(ExportPass):
     Fuse a cascaded chain of view ops
     """
 
-    # Find a chain of view ops, and fuse them into a single permute op.
-
     def fuse_cascaded_view_ops(self, graph_module: torch.fx.GraphModule):
-        graph = graph_module.graph
-        for node in graph.nodes:
-            # We are only interested in view ops
-            if node.target != exir_ops.edge.aten.view_copy.default:
-                continue
-
-            # Get the cascaded chain of view ops starting at node
-            cascaded_view_ops = get_cascaded_ops(
-                [node], [exir_ops.edge.aten.view_copy.default]
-            )
-            # The chain must have more than 1 node
-            if len(cascaded_view_ops) == 1:
+        view_target = exir_ops.edge.aten.view_copy.default
+        for view_node in graph_module.graph.find_nodes(op="call_function", target=view_target, sort=True):
+            input_view = view_node.args[0]
+            if input_view.op != "call_function" or input_view.target != view_target:
                 continue
 
-            last_view_node = cascaded_view_ops[-1]
-            with graph.inserting_before(last_view_node):
-                new_view = graph.call_function(
-                    exir_ops.edge.aten.view_copy.default,
-                    args=(node.args[0], last_view_node.args[1]),
-                )
-                last_view_node.replace_all_uses_with(new_view)
-
-            # Now erase the chain
-            for v in reversed(cascaded_view_ops):
-                graph.erase_node(v)
+            view_node.replace_input_with(input_view, input_view.args[0])
 
         graph_module.recompile()
 

backends/cadence/aot/tests/test_fusion_ops_passes.py

@@ -220,6 +220,26 @@ def forward(self, x):
             count_node(graph_module, exir_ops.edge.aten.view_copy.default), 1
         )
 
+    def test_view_fusion_branched(self):
+        class ViewFusion(torch.nn.Module):
+            def forward(self, x):
+                y = x.view([1, 8, 15])
+                z = y.view([1, 1, 120])
+                t = y.view([120, 1, 1])
+                return z, t
+
+        x = torch.randn(8, 5, 3)
+        graph_module = (
+            compiler.export_to_cadence(ViewFusion(), (x,))
+            .exported_program()
+            .graph_module
+        )
+        graph_module.graph.eliminate_dead_code()
+        # z and t should be fused and y should be eliminated.
+        self.assertEqual(
+            count_node(graph_module, exir_ops.edge.aten.view_copy.default), 2
+        )
+
     def test_force_quant_dequant_fusion(self):
         class M(torch.nn.Module):
             def __init__(self):