[ONNX] Add test for decomp_table update (#153671)

Added a test to strengthen the case for cherry-picking #153168. The original PR didn’t include this test since the fix for decomp_table and the registry was already covered by existing tests. However, it's reasonable to include a dedicated test for the specific issue (https://github.com/pytorch/pytorch/issues/150367 ) when considering the cherry-pick.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/153671
Approved by: https://github.com/justinchuby

test/onnx/exporter/test_api.py

@@ -374,6 +374,51 @@ class TestCustomTranslationTable(common_utils.TestCase):
         self.assertIn("Sub", all_nodes)
         self.assertNotIn("Add", all_nodes)
 
+    def test_custom_translation_table_supports_custom_op_with_its_decomp(self):
+        with torch.library._scoped_library("mylib", "FRAGMENT") as lib:
+            torch.library.define(
+                "mylib::foo",
+                "(Tensor a, Tensor b) -> Tensor",
+                tags=torch.Tag.pt2_compliant_tag,
+                lib=lib,
+            )
+
+            @torch.library.impl("mylib::foo", "CompositeImplicitAutograd", lib=lib)
+            @torch.library.register_fake("mylib::foo")
+            def foo_impl(a, b):
+                return a + b
+
+            class M(torch.nn.Module):
+                def forward(self, x, y):
+                    return torch.ops.mylib.foo(x, y)
+
+            def onnx_add(self: FLOAT, other: FLOAT) -> FLOAT:
+                # Replace add with Sub
+                return op.Sub(self, other)
+
+            # With the custom op defined, we can use it in the model
+            # and replace it with a custom translation table
+            custom_translation_table = {
+                torch.ops.mylib.foo.default: onnx_add,
+            }
+            onnx_program = torch.onnx.export(
+                M(),
+                (torch.ones(3, 3), torch.ones(3, 3)),
+                custom_translation_table=custom_translation_table,
+                dynamo=True,
+            )
+            all_nodes = [n.op_type for n in onnx_program.model.graph]
+            self.assertIn("Sub", all_nodes)
+            self.assertNotIn("Add", all_nodes)
+
+            # Without the custom op defined, it's going to be decomposed
+            onnx_program_decomp = torch.onnx.export(
+                M(), (torch.ones(3, 3), torch.ones(3, 3)), dynamo=True
+            )
+            all_nodes_decomp = [n.op_type for n in onnx_program_decomp.model.graph]
+            self.assertIn("Add", all_nodes_decomp)
+            self.assertNotIn("Sub", all_nodes_decomp)
+
 
 class TestFakeTensorExport(common_utils.TestCase):
     """Test exporting in fake mode."""