[QNN EP] Ensure QNN EP rejects nodes with I/O of dynamic shape (microsoft#22066)

### Description
Updates QNN EP to properly reject nodes that have inputs or outputs with
dynamic shapes.


### Motivation and Context
Currently, QNN EP does not properly offload subgraphs with dynamic
shapes to the CPU EP. This PR ensures that QNN EP rejects nodes that
consume or generate I/O with dynamic shapes.

Author: adrianlizarraga

onnxruntime/core/providers/qnn/builder/qnn_model_wrapper.cc

@@ -308,8 +308,10 @@ bool QnnModelWrapper::GetOnnxShape(const NodeArg& node_arg, std::vector<uint32_t
     return true;
   }
 
-  // We already checked the shape has no dynamic dimension
   for (const auto& dim : shape_proto->dim()) {
+    if (!dim.has_dim_value()) {
+      return false;  // Do not support dynamic shapes.
+    }
     shape.push_back(SafeInt<uint32_t>(dim.dim_value()));
   }
 

onnxruntime/test/providers/qnn/qnn_basic_test.cc

@@ -948,6 +948,63 @@ TEST_F(QnnHTPBackendTests, Float32ModelWithFP16PrecisionTest) {
                   0.008f);
 }
 
+// Test that QNN EP only handles nodes with static shapes and rejects nodes with dynamic shape I/O.
+TEST_F(QnnHTPBackendTests, EPRejectsDynamicShapesF32) {
+  // Local function that builds a model in which the last two nodes use dynamic shapes.
+  auto model_build_fn = [](ModelTestBuilder& builder) {
+    NodeArg* input1 = builder.MakeInput<float>(std::vector<int64_t>{1, 2, 8, 8},
+                                               GetFloatDataInRange(0.0f, 1.0f, 128));
+    NodeArg* input2 = builder.MakeInput<int64_t>(std::vector<int64_t>{3}, std::vector<int64_t>{1, 2, 49});
+
+    // Add a Conv with known shapes. QNN EP should support it.
+    NodeArg* weight = builder.MakeInitializer<float>(std::vector<int64_t>{2, 2, 2, 2},
+                                                     GetFloatDataInRange(-0.3f, 0.3f, 16));
+    NodeArg* bias = builder.MakeInitializer<float>(std::vector<int64_t>{2}, {0.0f, 1.0f});
+
+    auto* conv_output = builder.MakeIntermediate();
+    builder.AddNode("Conv", {input1, weight, bias}, {conv_output});
+
+    // Add a Reshape to a dynamic shape. QNN EP should reject this node.
+    auto* reshape_output = builder.MakeIntermediate();
+    builder.AddNode("Reshape", {conv_output, input2}, {reshape_output});
+
+    // Add a Softmax. QNN EP should reject this node because its input has a dynamic shape.
+    NodeArg* output = builder.MakeOutput();
+    builder.AddNode("Softmax", {reshape_output}, {output});
+  };
+
+  // Local function that checks that the nodes with dynamic shape I/O were assigned to CPU EP.
+  std::function<void(const Graph&)> ep_graph_checker = [](const Graph& graph) {
+    for (const Node& node : graph.Nodes()) {
+      const std::string& ep_name = node.GetExecutionProviderType();
+      const std::string& op_type = node.OpType();
+      if (op_type == "Reshape" || op_type == "Softmax") {
+        EXPECT_EQ(ep_name, kCpuExecutionProvider);
+      } else {
+        EXPECT_EQ(ep_name, kQnnExecutionProvider);
+      }
+    }
+  };
+
+  ProviderOptions provider_options;
+#if defined(_WIN32)
+  provider_options["backend_path"] = "QnnHtp.dll";
+#else
+  provider_options["backend_path"] = "libQnnHtp.so";
+#endif
+  provider_options["enable_htp_fp16_precision"] = "1";  // QNN EP will use fp16 precision.
+                                                        // CPU EP will use fp32, so we can relax accuracy requirements.
+
+  RunQnnModelTest(model_build_fn,
+                  provider_options,
+                  /*opset*/ 19,
+                  ExpectedEPNodeAssignment::Some,
+                  /*abs_err*/ 1e-4f,
+                  logging::Severity::kERROR,
+                  /*verify_output*/ true,
+                  &ep_graph_checker);
+}
+
 #endif  // defined(__aarch64__) || defined(_M_ARM64) || defined(__linux__)
 #endif  // !defined(ORT_MINIMAL_BUILD)
 

onnxruntime/test/providers/qnn/qnn_test_utils.cc

@@ -98,10 +98,12 @@ void TryEnableQNNSaver(ProviderOptions& qnn_options) {
 
 void RunQnnModelTest(const GetTestModelFn& build_test_case, ProviderOptions provider_options,
                      int opset_version, ExpectedEPNodeAssignment expected_ep_assignment,
-                     float fp32_abs_err, logging::Severity log_severity, bool verify_outputs) {
+                     float fp32_abs_err, logging::Severity log_severity, bool verify_outputs,
+                     std::function<void(const Graph&)>* ep_graph_checker) {
   EPVerificationParams verification_params;
   verification_params.ep_node_assignment = expected_ep_assignment;
   verification_params.fp32_abs_err = fp32_abs_err;
+  verification_params.graph_verifier = ep_graph_checker;
   // Add kMSDomain to cover contrib op like Gelu
   const std::unordered_map<std::string, int> domain_to_version = {{"", opset_version}, {kMSDomain, 1}};
 

onnxruntime/test/providers/qnn/qnn_test_utils.h

@@ -1033,12 +1033,16 @@ inline GetTestQDQModelFn<QuantType> BuildQDQOpTestCase(
  * \param expected_ep_assignment How many nodes are expected to be assigned to QNN (All, Some, or None).
  * \param fp32_abs_err The acceptable error between CPU EP and QNN EP.
  * \param log_severity The logger's minimum severity level.
+ * \param verify_outputs True to verify that the outputs match (within tolerance).
+ * \param ep_graph_checker Function called on the Graph generated for the EP's session. Used to check node
+ *                         EP assignment.
  */
 void RunQnnModelTest(const GetTestModelFn& build_test_case, ProviderOptions provider_options,
                      int opset_version, ExpectedEPNodeAssignment expected_ep_assignment,
                      float fp32_abs_err = 1e-5f,
                      logging::Severity log_severity = logging::Severity::kERROR,
-                     bool verify_outputs = true);
+                     bool verify_outputs = true,
+                     std::function<void(const Graph&)>* ep_graph_checker = nullptr);
 
 enum class BackendSupport {
   SUPPORT_UNKNOWN,