[QNN EP] Enable offline x64 compilation with memhandle IO type

onnxruntime/core/providers/qnn/builder/qnn_def.h

@@ -257,7 +257,7 @@ class QnnTensorWrapper {
     dimensions_.assign(shape_data, shape_data + shape_rank);
     SetQnnTensorDim(qnn_tensor_, dimensions_);
 
-    SetQnnTensorMemType(qnn_tensor_, QNN_TENSORMEMTYPE_RAW);
+    SetQnnTensorMemType(qnn_tensor_, GetQnnTensorMemType(qnn_tensor));
 
     return Status::OK();
   }

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

@@ -68,13 +68,9 @@ Status QnnModelWrapper::MakeTensorWrapper(const NodeUnitIODef& tensor, QnnTensor
     ORT_RETURN_IF_ERROR(UnpackInitializerData(*tensor_info.initializer_tensor, unpacked_tensor));
   }
 
-  Qnn_TensorMemType_t mem_type = QNN_TENSORMEMTYPE_RAW;
-  if (true == model_settings_.htp_shared_memory && (IsGraphInput(tensor_name) || IsGraphOutput(tensor_name))) {
-    mem_type = QNN_TENSORMEMTYPE_MEMHANDLE;
-  }
   tensor_wrapper = QnnTensorWrapper(tensor_name, GetTensorType(tensor_name), tensor_info.qnn_data_type,
                                     std::move(tensor_info.quant_param), std::move(tensor_info.shape),
-                                    std::move(unpacked_tensor), mem_type);
+                                    std::move(unpacked_tensor));
   return Status::OK();
 }
 
@@ -92,6 +88,15 @@ Status QnnModelWrapper::MakeTensorWrapper(const TensorInfo& tensor_info,
   return Status::OK();
 }
 
+void QnnModelWrapper::SetTensorMemTypeFromSettings(QnnTensorWrapper& tensor_wrapper,
+                                                   const std::string& tensor_name) {
+  Qnn_TensorMemType_t mem_type = QNN_TENSORMEMTYPE_RAW;
+  if (true == model_settings_.htp_shared_memory && (IsGraphInput(tensor_name) || IsGraphOutput(tensor_name))) {
+    mem_type = QNN_TENSORMEMTYPE_MEMHANDLE;
+  }
+  SetQnnTensorMemType(tensor_wrapper.GetQnnTensor(), mem_type);
+}
+
 bool QnnModelWrapper::AddTensorWrapper(QnnTensorWrapper&& tensor_wrapper) {
   // Keep a copy of tensor name sine it will be moved with the wrapper into model_tensors_map_
   std::string tensor_name = tensor_wrapper.GetName();
@@ -105,6 +110,8 @@ bool QnnModelWrapper::AddTensorWrapper(QnnTensorWrapper&& tensor_wrapper) {
     return true;
   }
 
+  SetTensorMemTypeFromSettings(tensor_wrapper, tensor_name);
+
   const Qnn_TensorType_t& qnn_tensor_type = tensor_wrapper.GetTensorType();
   // save created tensors for later lookup to populate graph node construction
   model_tensors_map_.emplace(tensor_name, std::move(tensor_wrapper));

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

@@ -77,6 +77,9 @@ class QnnModelWrapper {
                            const std::string& tensor_name,
                            QnnTensorWrapper& tensor_wrapper) const;
 
+  // Sets the QNN tensor memory type based on model settings and whether the tensor is a graph input/output.
+  void SetTensorMemTypeFromSettings(QnnTensorWrapper& tensor_wrapper, const std::string& tensor_name);
+
   // Add to internal tensor wrapper table
   bool AddTensorWrapper(QnnTensorWrapper&& tensor_wrapper);
 

onnxruntime/core/providers/qnn/qnn_execution_provider.cc

@@ -570,8 +570,11 @@ QNNExecutionProvider::QNNExecutionProvider(const ProviderOptions& provider_optio
   enable_htp_shared_mem_allocator_ = ParseBoolOption(QNN_HTP_SHARED_MEMORY_ALLOCATOR_ENABLED, false, provider_options_map);
   if (enable_htp_shared_mem_allocator_) {
     // Initialize rpcmem_library_.
-    // This is necessary for HtpSharedMemoryAllocator to function and also indicates that the allocator is available.
-    rpcmem_library_ = std::make_shared<qnn::RpcMemLibrary>();
+    // This library is only necessary for the inference (for the shared memory allocator), if we are in context
+    // generation stage, there is no need to load it as no allocations will be made.
+    if (!context_cache_enabled_) {
+      rpcmem_library_ = std::make_shared<qnn::RpcMemLibrary>();
+    }
     model_settings_.htp_shared_memory = enable_htp_shared_mem_allocator_;
   }
 

onnxruntime/test/providers/qnn/qnn_model_wrapper_test.cc

@@ -0,0 +1,220 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "gtest/gtest.h"
+
+// These tests require direct access to both real ORT internals (Model, Graph, GraphViewer)
+// and QNN EP builder internals (QnnModelWrapper, QnnTensorWrapper). This is only possible
+// when QNN EP is built as a static library, because the shared library build redefines
+// ORT types as opaque wrappers in provider_api.h / provider_wrappedtypes.h.
+#if !defined(ORT_MINIMAL_BUILD) && BUILD_QNN_EP_STATIC_LIB
+
+#include "core/graph/model.h"
+#include "core/providers/qnn/builder/qnn_model_wrapper.h"
+#include "core/providers/qnn/builder/qnn_def.h"
+#include "test/util/include/default_providers.h"
+#include "test/util/include/test_environment.h"
+
+using namespace onnxruntime;
+using namespace onnxruntime::qnn;
+
+namespace onnxruntime {
+namespace test {
+
+namespace {
+
+// Helper to create a minimal QnnModelWrapper for unit testing.
+// AddTensorWrapper does not invoke any QNN SDK functions, so we can use
+// null handles and a zeroed-out interface struct.
+struct QnnModelWrapperTestContext {
+  std::unique_ptr<onnxruntime::Model> model;
+  std::unique_ptr<GraphViewer> graph_viewer;
+  QNN_INTERFACE_VER_TYPE qnn_interface;
+  Qnn_BackendHandle_t backend_handle;
+  std::unordered_map<std::string, size_t> input_index_map;
+  std::unordered_map<std::string, size_t> output_index_map;
+
+  QnnModelWrapperTestContext() : qnn_interface(QNN_INTERFACE_VER_TYPE_INIT),
+                                 backend_handle(nullptr) {
+    model = std::make_unique<onnxruntime::Model>("test", false, DefaultLoggingManager().DefaultLogger());
+    Graph& graph = model->MainGraph();
+    graph_viewer = std::make_unique<GraphViewer>(graph);
+  }
+
+  std::unique_ptr<QnnModelWrapper> CreateWrapper(const ModelSettings& settings) {
+    return std::make_unique<QnnModelWrapper>(
+        *graph_viewer,
+        DefaultLoggingManager().DefaultLogger(),
+        qnn_interface,
+        backend_handle,
+        input_index_map,
+        output_index_map,
+        QnnBackendType::HTP,
+        settings);
+  }
+};
+
+}  // namespace
+
+// Verifies that when htp_shared_memory is disabled (default), the mem type of a
+// graph input tensor remains QNN_TENSORMEMTYPE_RAW.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryDisabled_GraphInput_MemTypeIsRaw) {
+  QnnModelWrapperTestContext ctx;
+  ctx.input_index_map = {{"input0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = false;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("input0", QNN_TENSOR_TYPE_APP_WRITE, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 3, 224, 224});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor)));
+
+  const auto& stored = wrapper->GetQnnTensorWrapper("input0");
+  EXPECT_EQ(GetQnnTensorMemType(stored.GetQnnTensor()), QNN_TENSORMEMTYPE_RAW);
+}
+
+// Verifies that when htp_shared_memory is enabled, a graph input tensor
+// gets mem type set to QNN_TENSORMEMTYPE_MEMHANDLE.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryEnabled_GraphInput_MemTypeIsMemHandle) {
+  QnnModelWrapperTestContext ctx;
+  ctx.input_index_map = {{"input0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = true;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("input0", QNN_TENSOR_TYPE_APP_WRITE, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 3, 224, 224});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor)));
+
+  const auto& stored = wrapper->GetQnnTensorWrapper("input0");
+  EXPECT_EQ(GetQnnTensorMemType(stored.GetQnnTensor()), QNN_TENSORMEMTYPE_MEMHANDLE);
+}
+
+// Verifies that when htp_shared_memory is enabled, a graph output tensor
+// gets mem type set to QNN_TENSORMEMTYPE_MEMHANDLE.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryEnabled_GraphOutput_MemTypeIsMemHandle) {
+  QnnModelWrapperTestContext ctx;
+  ctx.output_index_map = {{"output0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = true;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("output0", QNN_TENSOR_TYPE_APP_READ, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 1000});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor)));
+
+  const auto& stored = wrapper->GetQnnTensorWrapper("output0");
+  EXPECT_EQ(GetQnnTensorMemType(stored.GetQnnTensor()), QNN_TENSORMEMTYPE_MEMHANDLE);
+}
+
+// Verifies that when htp_shared_memory is enabled, an intermediate (native) tensor
+// that is neither a graph input nor output retains QNN_TENSORMEMTYPE_RAW.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryEnabled_IntermediateTensor_MemTypeIsRaw) {
+  QnnModelWrapperTestContext ctx;
+  // "intermediate0" is NOT in input_index_map or output_index_map.
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = true;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("intermediate0", QNN_TENSOR_TYPE_NATIVE, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 256});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor)));
+
+  const auto& stored = wrapper->GetQnnTensorWrapper("intermediate0");
+  EXPECT_EQ(GetQnnTensorMemType(stored.GetQnnTensor()), QNN_TENSORMEMTYPE_RAW);
+}
+
+// Verifies that when htp_shared_memory is disabled, a graph output tensor
+// retains QNN_TENSORMEMTYPE_RAW.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryDisabled_GraphOutput_MemTypeIsRaw) {
+  QnnModelWrapperTestContext ctx;
+  ctx.output_index_map = {{"output0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = false;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("output0", QNN_TENSOR_TYPE_APP_READ, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 1000});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor)));
+
+  const auto& stored = wrapper->GetQnnTensorWrapper("output0");
+  EXPECT_EQ(GetQnnTensorMemType(stored.GetQnnTensor()), QNN_TENSORMEMTYPE_RAW);
+}
+
+// Verifies that both graph input and output tensors get MEMHANDLE when
+// htp_shared_memory is enabled, within the same wrapper instance.
+TEST(QnnModelWrapperTest, AddTensorWrapper_SharedMemoryEnabled_BothInputAndOutput_MemTypeIsMemHandle) {
+  QnnModelWrapperTestContext ctx;
+  ctx.input_index_map = {{"input0", 0}};
+  ctx.output_index_map = {{"output0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = true;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper input_tensor("input0", QNN_TENSOR_TYPE_APP_WRITE, QNN_DATATYPE_FLOAT_32,
+                                QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 3, 224, 224});
+  QnnTensorWrapper output_tensor("output0", QNN_TENSOR_TYPE_APP_READ, QNN_DATATYPE_FLOAT_32,
+                                 QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 1000});
+
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(input_tensor)));
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(output_tensor)));
+
+  const auto& stored_input = wrapper->GetQnnTensorWrapper("input0");
+  EXPECT_EQ(GetQnnTensorMemType(stored_input.GetQnnTensor()), QNN_TENSORMEMTYPE_MEMHANDLE);
+
+  const auto& stored_output = wrapper->GetQnnTensorWrapper("output0");
+  EXPECT_EQ(GetQnnTensorMemType(stored_output.GetQnnTensor()), QNN_TENSORMEMTYPE_MEMHANDLE);
+}
+
+// Verifies that adding a duplicate tensor (same name) returns true
+// and does not overwrite the existing entry.
+TEST(QnnModelWrapperTest, AddTensorWrapper_DuplicateTensor_ReturnsTrueWithoutOverwrite) {
+  QnnModelWrapperTestContext ctx;
+  ctx.input_index_map = {{"input0", 0}};
+
+  ModelSettings settings{};
+  settings.htp_shared_memory = false;
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor1("input0", QNN_TENSOR_TYPE_APP_WRITE, QNN_DATATYPE_FLOAT_32,
+                           QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 3, 224, 224});
+  ASSERT_TRUE(wrapper->AddTensorWrapper(std::move(tensor1)));
+
+  // Attempt to add another tensor with the same name
+  QnnTensorWrapper tensor2("input0", QNN_TENSOR_TYPE_APP_WRITE, QNN_DATATYPE_FLOAT_16,
+                           QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 3, 112, 112});
+  EXPECT_TRUE(wrapper->AddTensorWrapper(std::move(tensor2)));
+
+  // Should still have the original data type
+  const auto& stored = wrapper->GetQnnTensorWrapper("input0");
+  EXPECT_EQ(stored.GetTensorDataType(), QNN_DATATYPE_FLOAT_32);
+}
+
+// Verifies that adding a tensor with an empty name returns false.
+TEST(QnnModelWrapperTest, AddTensorWrapper_EmptyName_ReturnsFalse) {
+  QnnModelWrapperTestContext ctx;
+
+  ModelSettings settings{};
+  auto wrapper = ctx.CreateWrapper(settings);
+
+  QnnTensorWrapper tensor("", QNN_TENSOR_TYPE_NATIVE, QNN_DATATYPE_FLOAT_32,
+                          QnnQuantParamsWrapper(), std::vector<uint32_t>{1, 256});
+
+  EXPECT_FALSE(wrapper->AddTensorWrapper(std::move(tensor)));
+}
+
+}  // namespace test
+}  // namespace onnxruntime
+
+#endif  // !defined(ORT_MINIMAL_BUILD) && BUILD_QNN_EP_STATIC_LIB