lintrunner -a

onnxruntime/core/providers/tensorrt/onnx_ctx_model_helper.cc

@@ -137,23 +137,23 @@ ONNX_NAMESPACE::ModelProto* CreateCtxNodeModel(const GraphViewer& graph_viewer,
 
 /*
  * Get "EP context node" model path
- * 
- * 
+ *
+ *
  * If ep_context_file_path is provided:
  *     - If ep_context_file_path is a file:
  *         - If it's a file name without any path associated with it, return "engine_cache_path/ep_context_file_path".
            - If it's a file name with path associated with it, return "ep_context_file_path".
  *     - If ep_context_file_path is a directory, return "ep_context_file_path/original_model_name_ctx.onnx".
  * If ep_context_file_path is not provided:
  *     - Return "engine_cache_path/original_model_name_ctx.onnx".
- * 
- * 
+ *
+ *
  * Example 1:
  * ep_context_file_path = "/home/user/ep_context_model_foler"
  * engine_cache_path = "trt_engine.engine"
  * original_model_path = "model.onnx"
  * => return "/home/user/ep_context_model_folder/model_ctx.onnx"
- * 
+ *
  * Example 2:
  * ep_context_file_path = "my_ctx_model.onnx"
  * engine_cache_path = "/home/user/cache_folder/trt_engine.engine"
@@ -165,13 +165,13 @@ ONNX_NAMESPACE::ModelProto* CreateCtxNodeModel(const GraphViewer& graph_viewer,
  * engine_cache_path = "trt_engine.engine"
  * original_model_path = "model.onnx"
  * => return "/home/user2/ep_context_model_foler/my_ctx_model.onnx"
- * 
+ *
  * Example 4:
  * ep_context_file_path = ""
  * engine_cache_path = "/home/user3/cache_folder/trt_engine.engine"
  * original_model_path = "model.onnx"
  * => return "/home/user3/cache_folder/model_ctx.onnx"
- * 
+ *
  */
 std::string GetCtxNodeModelPath(const std::string& ep_context_file_path,
                                 const std::string& engine_cache_path,

onnxruntime/core/providers/tensorrt/onnx_ctx_model_helper.h

@@ -16,7 +16,8 @@ static const std::string EMBED_MODE = "embed_mode";
 static const std::string EP_CACHE_CONTEXT = "ep_cache_context";
 static const std::string COMPUTE_CAPABILITY = "hardware_architecture";
 static const std::string EPCONTEXT_OP_DOMAIN = "com.microsoft";
-static const std::string EPCONTEXT_WARNING = "It's suggested to set the ORT graph optimization level to 0 and  \
+static const std::string EPCONTEXT_WARNING =
+    "It's suggested to set the ORT graph optimization level to 0 and  \
                                               make \"embed_mode\" to 0 (\"ep_cache_context\" is the cache path)\
                                               for the best model loading time";
 

onnxruntime/core/session/provider_bridge_ort.cc

@@ -1480,10 +1480,10 @@ std::shared_ptr<IExecutionProviderFactory> TensorrtProviderFactoryCreator::Creat
 
 std::shared_ptr<IExecutionProviderFactory> TensorrtProviderFactoryCreator::Create(void* session_options, const OrtTensorRTProviderOptionsV2* provider_options) {
   // We need to create a new provider options V2 object and copy from provider_options, due to the "const" object pointed by provider_options can't be modified.
-  // 
+  //
   // Note: No need to worry about tensorrt_options being a local variable, CreateExecutionProviderFactory() in TRT EP will
   // create a factory object that copies any provider options from tensorrt_options including "const char*" provider options.
-  OrtTensorRTProviderOptionsV2 tensorrt_options = *provider_options; // copy and assign from provider_options
+  OrtTensorRTProviderOptionsV2 tensorrt_options = *provider_options;  // copy and assign from provider_options
 
 #if !defined(ORT_MINIMAL_BUILD) && defined(USE_TENSORRT)
   onnxruntime::UpdateOrtTensorRTProviderOptionsV2FromSessionOptionsConfigs(reinterpret_cast<OrtSessionOptions*>(session_options), &tensorrt_options);
@@ -1768,7 +1768,7 @@ ORT_API_STATUS_IMPL(OrtSessionOptionsAppendExecutionProvider_MIGraphX, _In_ OrtS
 
 ORT_API_STATUS_IMPL(OrtApis::SessionOptionsAppendExecutionProvider_TensorRT, _In_ OrtSessionOptions* options, _In_ const OrtTensorRTProviderOptions* tensorrt_options) {
   API_IMPL_BEGIN
-  
+
   std::shared_ptr<onnxruntime::IExecutionProviderFactory> factory;
 
 #if !defined(ORT_MINIMAL_BUILD) && defined(USE_TENSORRT)

onnxruntime/python/onnxruntime_pybind_state.cc

@@ -729,12 +729,12 @@ std::unique_ptr<IExecutionProvider> CreateExecutionProviderInstance(
               ORT_THROW("[ERROR] [TensorRT] The value for the key 'trt_dump_ep_context_model' should be 'True' or 'False'. Default value is 'False'.\n");
             }
           } else if (option.first == "trt_ep_context_file_path") {
-              if (!option.second.empty()) {
-                ep_context_file_path = option.second;
-                params.trt_ep_context_file_path = ep_context_file_path.c_str();
-              } else {
-                ORT_THROW("[ERROR] [TensorRT] The value for the key 'trt_ep_context_file_path' should be a string.\n");
-              }
+            if (!option.second.empty()) {
+              ep_context_file_path = option.second;
+              params.trt_ep_context_file_path = ep_context_file_path.c_str();
+            } else {
+              ORT_THROW("[ERROR] [TensorRT] The value for the key 'trt_ep_context_file_path' should be a string.\n");
+            }
           } else if (option.first == "trt_ep_context_embed_mode") {
             if (!option.second.empty()) {
               params.trt_ep_context_embed_mode = std::stoi(option.second);

onnxruntime/python/tools/tensorrt/gen_trt_engine_wrapper_onnx_model.py

@@ -32,6 +32,7 @@ def __init__(self, args):
         trt.init_libnvinfer_plugins(logger, "")
         if len(self.plugins):
             import ctypes
+
             ctypes.CDLL(self.plugins)
 
         # Deserialize an TRT engine

onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc

@@ -123,7 +123,7 @@ void CreateBaseModel(std::string model_name,
 }
 
 bool HasCacheFileWithPrefix(const std::string& prefix, std::string file_dir = "") {
-  std::filesystem::path target_dir; 
+  std::filesystem::path target_dir;
   if (file_dir.empty()) {
     target_dir = std::filesystem::current_path();
   } else {