Edit test onnx model to properly test mutable alias (buffer reuse for Relu).

Author: adrianlizarraga

onnxruntime/test/autoep/test_execution.cc

@@ -251,16 +251,16 @@ TEST(OrtEpLibrary, KernelPluginEp_Inference) {
   std::unordered_map<std::string, std::string> ep_options;
   session_options.AppendExecutionProvider_V2(*ort_env, {plugin_ep_device}, ep_options);
 
-  // This model has Squeeze -> Mul. The example plugin EP supports both using registered kernels.
+  // This model has Squeeze, Mul, and Relu nodes. The example plugin EP supports all nodes using registered kernels.
   Ort::Session session(*ort_env, ORT_TSTR("testdata/squeeze_mul_relu.onnx"), session_options);
 
   // Create inputs
   Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
   std::array<int64_t, 3> a_shape = {3, 1, 2};
   std::array<int64_t, 2> b_shape = {3, 2};
 
-  std::array<float, 6> a_data = {1.f, 2.f, 3.f, 4.f, 5.f, 6.f};
-  std::array<float, 6> b_data = {2.f, 3.f, 4.f, -5.f, -6.f, 7.f};
+  std::array<float, 6> a_data = {1.f, -2.f, 3.f, 4.f, -5.f, 6.f};
+  std::array<float, 6> b_data = {2.f, 3.f, 4.f, -5.f, 6.f, 7.f};
 
   std::vector<Ort::Value> ort_inputs{};
   ort_inputs.emplace_back(
@@ -279,7 +279,7 @@ TEST(OrtEpLibrary, KernelPluginEp_Inference) {
   Ort::Value& ort_output = ort_outputs[0];
   const float* output_data = ort_output.GetTensorData<float>();
   gsl::span<const float> output_span(output_data, 6);
-  EXPECT_THAT(output_span, ::testing::ElementsAre(2, 6, 12, 0, 0, 42));
+  EXPECT_THAT(output_span, ::testing::ElementsAre(4, 0, 24, 0, 0, 84));
 }
 }  // namespace test
 }  // namespace onnxruntime

onnxruntime/test/testdata/squeeze_mul_relu.onnx

@@ -1,6 +1,6 @@
 from onnx import TensorProto, checker, helper, save, shape_inference
 
-# A --> Squeeze --> Mul --> Relu --> C
+# A --> Squeeze --> Mul --> Relu --> Mul(2x) --> C
 #                   ^
 #                   |
 # B ----------------+
@@ -9,21 +9,27 @@
         helper.make_node(
             "Squeeze",
             inputs=["A"],
-            outputs=["squeeze_output"],
+            outputs=["squeeze0_output"],
             name="squeeze_0",
         ),
         helper.make_node(
             "Mul",
-            inputs=["squeeze_output", "B"],
-            outputs=["mul_output"],
+            inputs=["squeeze0_output", "B"],
+            outputs=["mul0_output"],
             name="mul_0",
         ),
         helper.make_node(
             "Relu",
-            inputs=["mul_output"],
-            outputs=["C"],
+            inputs=["mul0_output"],
+            outputs=["relu0_output"],
             name="relu_0",
         ),
+        helper.make_node(
+            "Mul",
+            inputs=["relu0_output", "Const2"],
+            outputs=["C"],
+            name="mul_1",
+        ),
     ],
     name="Main_graph",
     inputs=[
@@ -33,6 +39,9 @@
     outputs=[
         helper.make_tensor_value_info("C", TensorProto.FLOAT, [3, 2]),
     ],
+    initializer=[
+        helper.make_tensor("Const2", TensorProto.FLOAT, [3, 2], [2.0] * 6),
+    ],
 )
 
 model = helper.make_model(graph_proto)