From fb7dea46ac11c6535826bc8ef24f9a54d4c7459c Mon Sep 17 00:00:00 2001
From: "G. Ramalingam" <grama@microsoft.com>
Date: Tue, 16 Jul 2024 10:14:13 -0700
Subject: [PATCH] Add test case for unsupported input-variable reuse in
 multi-output pattern matcher (#1731)

The multi-output pattern does not support a useful case, where the
pattern's input variables are reused elsewhere.

This PR adds a test-case illustrating the scenario. I was hoping that
some changes in the in-progress PR #1636 by Xavier might fix this. But I
don't think it does. Adding the test-case for now. Need to figure out
how to support this.

---------

Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
---
 onnxscript/rewriter/generic_pattern_test.py | 35 +++++++++++++++++++++
 1 file changed, 35 insertions(+)

diff --git a/onnxscript/rewriter/generic_pattern_test.py b/onnxscript/rewriter/generic_pattern_test.py
index 04a7f4f69..d65f01c8d 100644
--- a/onnxscript/rewriter/generic_pattern_test.py
+++ b/onnxscript/rewriter/generic_pattern_test.py
@@ -281,6 +281,41 @@ def apply_pattern(op, x, **_):
         self.assertEqual(len(graph.node), 2)
         self.assertEqual(graph.node[0].op_type, "SinCos")
 
+    @unittest.skip("Input variable reuse not supported yet")
+    def test_shared_root_value_extra_use(self):
+        def match_pattern(op, x):
+            t1 = op.Sin(x)
+            t2 = op.Cos(x)
+            return t1, t2
+
+        def apply_pattern(op, x, **_):
+            return op.SinCos(x, domain="com.microsoft", outputs=2)
+
+        rule = pattern.RewriteRule(
+            match_pattern,
+            apply_pattern,
+            matcher=generic_pattern.GenericPatternMatcher,
+        )
+        model_proto = onnx.parser.parse_model(
+            """
+            <ir_version: 7, opset_import: [ "" : 17]>
+            agraph (float[N] y) => (float[N] z)
+            {
+                temp1 = Sin(y)
+                temp2 = Cos(y)
+                w = Add(temp1, temp2)
+                z = Mul(w, y)
+            }
+        """
+        )
+        onnx.checker.check_model(model_proto)
+        model = onnx.shape_inference.infer_shapes(model_proto)
+        ir_model = ir.serde.deserialize_model(model)
+        rule.apply_to_model(ir_model)
+        graph = ir_model.graph
+        self.assertEqual(len(graph), 3)
+        self.assertEqual(graph.node[0].op_type, "SinCos")
+
     def test_rotary_embedding(self):
         # The test work on a model if it has the expected name.
         # A dummy model is used if not present (not implemented yet).