diff --git a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
index e721683ba9..a223ba729b 100644
--- a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
+++ b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
@@ -464,11 +464,11 @@ SubGraphCollection_t TensorrtExecutionProvider::GetSupportedList(SubGraphCollect
         // Get supported node list recursively
         SubGraphCollection_t parser_nodes_list;
         TensorrtLogger& trt_logger = GetTensorrtLogger();
-        auto trt_builder = unique_pointer<nvinfer1::IBuilder>(nvinfer1::createInferBuilder(trt_logger));
+        auto trt_builder = tensorrt_ptr::unique_pointer<nvinfer1::IBuilder>(nvinfer1::createInferBuilder(trt_logger));
         const auto explicitBatch = 1U << static_cast<uint32_t>(nvinfer1::NetworkDefinitionCreationFlag::kEXPLICIT_BATCH);
-        auto trt_network = unique_pointer<nvinfer1::INetworkDefinition>(trt_builder->createNetworkV2(explicitBatch));
+        auto trt_network = tensorrt_ptr::unique_pointer<nvinfer1::INetworkDefinition>(trt_builder->createNetworkV2(explicitBatch));
 
-        auto trt_parser = unique_pointer<nvonnxparser::IParser>(nvonnxparser::createParser(*trt_network, trt_logger));
+        auto trt_parser = tensorrt_ptr::unique_pointer<nvonnxparser::IParser>(nvonnxparser::createParser(*trt_network, trt_logger));
         trt_parser->supportsModel(string_buf.data(), string_buf.size(), parser_nodes_list);
 
         SubGraphCollection_t next_nodes_list;
@@ -682,11 +682,11 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector<onnxruntime:
 
     // Create TensorRT engine
     TensorrtLogger& trt_logger = GetTensorrtLogger();
-    auto trt_builder = unique_pointer<nvinfer1::IBuilder>(nvinfer1::createInferBuilder(trt_logger));
+    auto trt_builder = tensorrt_ptr::unique_pointer<nvinfer1::IBuilder>(nvinfer1::createInferBuilder(trt_logger));
     const auto explicitBatch = 1U << static_cast<uint32_t>(nvinfer1::NetworkDefinitionCreationFlag::kEXPLICIT_BATCH);
-    auto trt_network = unique_pointer<nvinfer1::INetworkDefinition>(trt_builder->createNetworkV2(explicitBatch));
-    auto trt_config = unique_pointer<nvinfer1::IBuilderConfig>(trt_builder->createBuilderConfig());
-    auto trt_parser = unique_pointer<nvonnxparser::IParser>(nvonnxparser::createParser(*trt_network, trt_logger));
+    auto trt_network = tensorrt_ptr::unique_pointer<nvinfer1::INetworkDefinition>(trt_builder->createNetworkV2(explicitBatch));
+    auto trt_config = tensorrt_ptr::unique_pointer<nvinfer1::IBuilderConfig>(trt_builder->createBuilderConfig());
+    auto trt_parser = tensorrt_ptr::unique_pointer<nvonnxparser::IParser>(nvonnxparser::createParser(*trt_network, trt_logger));
     trt_parser->parse(string_buf.data(), string_buf.size());
     trt_config->setMaxWorkspaceSize(max_workspace_size_);
 
@@ -734,14 +734,14 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector<onnxruntime:
       trt_config->setFlag(nvinfer1::BuilderFlag::kFP16);
     }
 
-    auto trt_engine = unique_pointer<nvinfer1::ICudaEngine>(trt_builder->buildEngineWithConfig(*trt_network, *trt_config));
+    auto trt_engine = tensorrt_ptr::unique_pointer<nvinfer1::ICudaEngine>(trt_builder->buildEngineWithConfig(*trt_network, *trt_config));
     if (trt_engine == nullptr) {
       return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
                              "TensorRT EP could not build Engine for fused node: " + fused_node->Name());
     }
 
     // Build TensorRT context
-    auto trt_context = unique_pointer<nvinfer1::IExecutionContext>(trt_engine->createExecutionContext());
+    auto trt_context = tensorrt_ptr::unique_pointer<nvinfer1::IExecutionContext>(trt_engine->createExecutionContext());
     if (trt_context == nullptr) {
       return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
                              "TensorRT EP could not build Execution Context for fused node: " + fused_node->Name());
@@ -815,7 +815,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector<onnxruntime:
     compute_info.create_state_func = [=](ComputeContext* context, FunctionState* state) {
       std::unique_ptr<TensorrtFuncState> p = onnxruntime::make_unique<TensorrtFuncState>();
       *p = {context->allocate_func, context->release_func, context->allocator_handle, parsers_[context->node_name].get(),
-            engines_[context->node_name].get(), contexts_[context->node_name].get(), builders_[context->node_name].get(),
+            &engines_[context->node_name], &contexts_[context->node_name], builders_[context->node_name].get(),
             networks_[context->node_name].get(), input_info_[context->node_name], output_info_[context->node_name],
             input_shape_ranges_[context->node_name], output_shapes_[context->node_name], &tensorrt_mu_, &fp16_enable_,
             &max_workspace_size_};
@@ -845,7 +845,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector<onnxruntime:
 
       // Update shape ranges
       bool dimension_update = false;
-      auto trt_context = trt_state->context;
+      auto trt_context = trt_state->context->get();
       auto trt_builder = trt_state->builder;
       nvinfer1::IOptimizationProfile* trt_profile = nullptr;
       for (int i = 0, end = num_binding_inputs; i < end; ++i) {
@@ -913,21 +913,26 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector<onnxruntime:
       // Regenerate engine and context
       // Only one profile is generated, so no need to explicitly set optimization profile
       if (dimension_update) {
-        auto trt_config = unique_pointer<nvinfer1::IBuilderConfig>(trt_builder->createBuilderConfig());
+        auto trt_config = tensorrt_ptr::unique_pointer<nvinfer1::IBuilderConfig>(trt_builder->createBuilderConfig());
         trt_config->setMaxWorkspaceSize(*(trt_state->max_workspace_size_ptr));
         trt_config->addOptimizationProfile(trt_profile);
         if (*(trt_state->fp16_enable_ptr) && trt_builder->platformHasFastFp16()) {
           trt_config->setFlag(nvinfer1::BuilderFlag::kFP16);
         }
-        trt_state->engine = trt_builder->buildEngineWithConfig(*trt_state->network, *trt_config);
-        if (trt_state->engine == nullptr) {
+        trt_state->context->reset();
+        trt_state->engine->reset();
+        *(trt_state->engine) =  tensorrt_ptr::unique_pointer<nvinfer1::ICudaEngine>(
+                                  trt_builder->buildEngineWithConfig(*trt_state->network, *trt_config));
+
+        if (trt_state->engine->get() == nullptr) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP Failed to Build Engine.");
         }
-        trt_state->context = trt_state->engine->createExecutionContext();
-        if (trt_state->context == nullptr) {
+        *(trt_state->context) = tensorrt_ptr::unique_pointer<nvinfer1::IExecutionContext>(
+                                  trt_state->engine->get()->createExecutionContext());
+        if (trt_state->context->get() == nullptr) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP Failed to Create Context.");
         }
-        trt_context = trt_state->context;
+        trt_context = trt_state->context->get();
       }
 
       // Set input shapes and assign input buffers
diff --git a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.h b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.h
index c3a50ae0de..33d7eb1532 100644
--- a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.h
+++ b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.h
@@ -38,6 +38,21 @@ class TensorrtLogger : public nvinfer1::ILogger {
   }
 };
 
+namespace tensorrt_ptr {
+
+  struct TensorrtInferDeleter {
+    template <typename T>
+    void operator()(T* obj) const {
+      if (obj) {
+        obj->destroy();
+      }
+    }
+  };
+
+  template <typename T>
+  using unique_pointer = std::unique_ptr<T, TensorrtInferDeleter>;
+};
+
 // Information needed to construct trt execution providers.
 struct TensorrtExecutionProviderInfo {
   int device_id{0};
@@ -45,12 +60,13 @@ struct TensorrtExecutionProviderInfo {
 
 // Information to construct kernel function state.
 struct TensorrtFuncState {
+
   AllocateFunc test_allocate_func = nullptr;
   DestroyFunc test_release_func = nullptr;
   AllocatorHandle allocator = nullptr;
   nvonnxparser::IParser* parser = nullptr;
-  nvinfer1::ICudaEngine* engine = nullptr;
-  nvinfer1::IExecutionContext* context = nullptr;
+  tensorrt_ptr::unique_pointer<nvinfer1::ICudaEngine> * engine = nullptr;
+  tensorrt_ptr::unique_pointer<nvinfer1::IExecutionContext> * context = nullptr;
   nvinfer1::IBuilder* builder = nullptr;
   nvinfer1::INetworkDefinition* network = nullptr;
   std::vector<std::vector<int>> input_info;
@@ -89,25 +105,14 @@ class TensorrtExecutionProvider : public IExecutionProvider {
   bool fp16_enable_ = false;
   bool dump_subgraphs_ = false;
 
-  struct InferDeleter {
-    template <typename T>
-    void operator()(T* obj) const {
-      if (obj) {
-        obj->destroy();
-      }
-    }
-  };
-
-  template <typename T>
-  using unique_pointer = std::unique_ptr<T, InferDeleter>;
 
   OrtMutex tensorrt_mu_;
   int device_id_;
-  std::unordered_map<std::string, unique_pointer<nvonnxparser::IParser>> parsers_;
-  std::unordered_map<std::string, unique_pointer<nvinfer1::ICudaEngine>> engines_;
-  std::unordered_map<std::string, unique_pointer<nvinfer1::IExecutionContext>> contexts_;
-  std::unordered_map<std::string, unique_pointer<nvinfer1::IBuilder>> builders_;
-  std::unordered_map<std::string, unique_pointer<nvinfer1::INetworkDefinition>> networks_;
+  std::unordered_map<std::string, tensorrt_ptr::unique_pointer<nvonnxparser::IParser>> parsers_;
+  std::unordered_map<std::string, tensorrt_ptr::unique_pointer<nvinfer1::ICudaEngine>> engines_;
+  std::unordered_map<std::string, tensorrt_ptr::unique_pointer<nvinfer1::IExecutionContext>> contexts_;
+  std::unordered_map<std::string, tensorrt_ptr::unique_pointer<nvinfer1::IBuilder>> builders_;
+  std::unordered_map<std::string, tensorrt_ptr::unique_pointer<nvinfer1::INetworkDefinition>> networks_;
   std::unordered_map<std::string, std::vector<std::vector<int>>> input_info_;
   std::unordered_map<std::string, std::vector<std::vector<int>>> output_info_;
   std::unordered_map<std::string, std::unordered_map<int, std::unordered_map<int, std::pair<int64_t, int64_t>>>> input_shape_ranges_;