Run clang-format in CI (#15524)

### Description Run clang-format in CI. Formatted all c/c++, objective-c/c++ files. Excluded ``` 'onnxruntime/core/mlas/**', 'onnxruntime/contrib_ops/cuda/bert/tensorrt_fused_multihead_attention/**', ``` because they contain assembly or is data heavy ### Motivation and Context Coding style consistency
microsoft · Apr 18, 2023 · cf19c36 · cf19c36
1 parent 2700d01
commit cf19c36
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diff --git a/.clang-format b/.clang-format
@@ -19,4 +19,3 @@ DerivePointerAlignment: false
 # NamespaceIndentation: All
 
 ...
-
diff --git a/.lintrunner.toml b/.lintrunner.toml
@@ -14,7 +14,7 @@
 # To lint local changes:
 #
 # ```bash
-# lintrunner -m main
+# lintrunner
 # ```
 #
 # To lint all files:
@@ -33,6 +33,8 @@
 # To update an existing linting rule or create a new one, modify this file or create a
 # new adapter following examples in https://github.com/justinchuby/lintrunner-adapters.
 
+merge_base_with = 'origin/main'
+
 [[linter]]
 code = 'RUFF'
 include_patterns = [
@@ -168,3 +170,44 @@ command = [
     '@{{PATHSFILE}}'
 ]
 is_formatter = true
+
+[[linter]]
+code = 'CLANGFORMAT'
+include_patterns = [
+    '**/*.h',
+    '**/*.cc',
+    '**/*.hpp',
+    '**/*.cpp',
+    '**/*.m',
+    '**/*.mm',
+]
+exclude_patterns = [
+    'java/**', # FIXME: Enable clang-format for java
+    'js/**',
+    'onnxruntime/contrib_ops/cuda/bert/tensorrt_fused_multihead_attention/**', # Contains data chunks
+    'onnxruntime/core/flatbuffers/schema/ort.fbs.h', # Generated code
+    'onnxruntime/core/graph/contrib_ops/quantization_defs.cc',
+    'onnxruntime/core/mlas/**', # Contains assembly code
+    'winml/**', # FIXME: Enable clang-format for winml
+]
+command = [
+    'python',
+    '-m',
+    'lintrunner_adapters',
+    'run',
+    'clangformat_linter',
+    '--binary=clang-format',
+    '--fallback',
+    '--',
+    '@{{PATHSFILE}}'
+]
+init_command = [
+    'python',
+    '-m',
+    'lintrunner_adapters',
+    'run',
+    'pip_init',
+    '--dry-run={{DRYRUN}}',
+    'clang-format==16.0.1',
+]
+is_formatter = true
diff --git a/cmake/uwp_stubs.h b/cmake/uwp_stubs.h
@@ -6,6 +6,6 @@
 // Extending the std namespace is undefined behavior
 // NOLINTNEXTLINE
 namespace std {
-    inline char *getenv(const char*) { return nullptr; }
-}
+inline char* getenv(const char*) { return nullptr; }
+}  // namespace std
 #endif
diff --git a/csharp/test/Microsoft.AI.MachineLearning.Tests/main.cpp b/csharp/test/Microsoft.AI.MachineLearning.Tests/main.cpp
@@ -1,11 +1,11 @@
-#include <stdio.h>
-#include "winrt/microsoft.ai.machinelearning.h"
-#include "winrt/windows.storage.h"
-#include "winrt/windows.foundation.h"
-#include "winrt/windows.foundation.collections.h"
-#include "winrt/Windows.Graphics.h"
 #include "winrt/Windows.Graphics.Imaging.h"
+#include "winrt/Windows.Graphics.h"
 #include "winrt/Windows.Media.h"
+#include "winrt/microsoft.ai.machinelearning.h"
+#include "winrt/windows.foundation.collections.h"
+#include "winrt/windows.foundation.h"
+#include "winrt/windows.storage.h"
+#include <stdio.h>
 #include <windows.h>
 
 EXTERN_C IMAGE_DOS_HEADER __ImageBase;
@@ -15,42 +15,44 @@ using namespace winrt::Windows::Storage;
 using namespace winrt::Windows::Media;
 using namespace winrt::Windows::Graphics::Imaging;
 
-std::wstring GetModulePath() {
-  std::wstring val;
-  wchar_t modulePath[MAX_PATH] = {0};
-  GetModuleFileNameW((HINSTANCE)&__ImageBase, modulePath, _countof(modulePath));
-  wchar_t drive[_MAX_DRIVE];
-  wchar_t dir[_MAX_DIR];
-  wchar_t filename[_MAX_FNAME];
-  wchar_t ext[_MAX_EXT];
-  _wsplitpath_s(modulePath, drive, _MAX_DRIVE, dir, _MAX_DIR, filename, _MAX_FNAME, ext, _MAX_EXT);
+std::wstring GetModulePath()
+{
+    std::wstring val;
+    wchar_t modulePath[MAX_PATH] = {0};
+    GetModuleFileNameW((HINSTANCE)&__ImageBase, modulePath, _countof(modulePath));
+    wchar_t drive[_MAX_DRIVE];
+    wchar_t dir[_MAX_DIR];
+    wchar_t filename[_MAX_FNAME];
+    wchar_t ext[_MAX_EXT];
+    _wsplitpath_s(modulePath, drive, _MAX_DRIVE, dir, _MAX_DIR, filename, _MAX_FNAME, ext, _MAX_EXT);
 
-  val = drive;
-  val += dir;
+    val = drive;
+    val += dir;
 
-  return val;
+    return val;
 }
 
-int main() {
-  printf("Load squeezenet.onnx.\n");
-  auto model = LearningModel::LoadFromFilePath(L"squeezenet.onnx");
-  printf("Load kitten_224.png as StorageFile.\n");
-  auto name = GetModulePath() + L"kitten_224.png";
-  auto image = StorageFile::GetFileFromPathAsync(name).get();
-  printf("Load StorageFile into Stream.\n");
-  auto stream = image.OpenAsync(FileAccessMode::Read).get();
-  printf("Create SoftwareBitmap from decoded Stream.\n");
-  auto softwareBitmap = BitmapDecoder::CreateAsync(stream).get().GetSoftwareBitmapAsync().get();
-  printf("Create VideoFrame.\n");
-  auto frame = VideoFrame::CreateWithSoftwareBitmap(softwareBitmap);
-  printf("Create LearningModelSession.\n");
-  auto session = LearningModelSession(model);
-  printf("Create LearningModelBinding.\n");
-  auto binding = LearningModelBinding(session);
-  printf("Bind data_0.\n");
-  binding.Bind(L"data_0", frame);
-  printf("Evaluate.\n");
-  auto results = session.Evaluate(binding, L"");
-  printf("Success!\n");
-  return 0;
+int main()
+{
+    printf("Load squeezenet.onnx.\n");
+    auto model = LearningModel::LoadFromFilePath(L"squeezenet.onnx");
+    printf("Load kitten_224.png as StorageFile.\n");
+    auto name = GetModulePath() + L"kitten_224.png";
+    auto image = StorageFile::GetFileFromPathAsync(name).get();
+    printf("Load StorageFile into Stream.\n");
+    auto stream = image.OpenAsync(FileAccessMode::Read).get();
+    printf("Create SoftwareBitmap from decoded Stream.\n");
+    auto softwareBitmap = BitmapDecoder::CreateAsync(stream).get().GetSoftwareBitmapAsync().get();
+    printf("Create VideoFrame.\n");
+    auto frame = VideoFrame::CreateWithSoftwareBitmap(softwareBitmap);
+    printf("Create LearningModelSession.\n");
+    auto session = LearningModelSession(model);
+    printf("Create LearningModelBinding.\n");
+    auto binding = LearningModelBinding(session);
+    printf("Bind data_0.\n");
+    binding.Bind(L"data_0", frame);
+    printf("Evaluate.\n");
+    auto results = session.Evaluate(binding, L"");
+    printf("Success!\n");
+    return 0;
 }
diff --git a/include/onnxruntime/core/common/code_location.h b/include/onnxruntime/core/common/code_location.h
@@ -47,10 +47,10 @@ struct CodeLocation {
     out << (format == Format::kFilename ? FileNoPath() : file_and_path) << ":" << line_num << " " << function;
     return out.str();
   }
-  //utf-8. Because on Windows we compile our code with "/utf-8". And we assume the other platforms only use utf-8.
+  // utf-8. Because on Windows we compile our code with "/utf-8". And we assume the other platforms only use utf-8.
   const std::string file_and_path;
   const int line_num;
-  //utf-8
+  // utf-8
   const std::string function;
   const std::vector<std::string> stacktrace;
 };

diff --git a/include/onnxruntime/core/common/common.h b/include/onnxruntime/core/common/common.h
@@ -37,7 +37,6 @@
 #include "core/common/make_string.h"
 #include "core/common/status.h"
 
-
 namespace onnxruntime {
 
 using TimePoint = std::chrono::high_resolution_clock::time_point;

diff --git a/include/onnxruntime/core/common/inlined_containers.h b/include/onnxruntime/core/common/inlined_containers.h
@@ -158,9 +158,9 @@ class NodeHashSet : public std::unordered_set<T,
 
 template <typename Key, typename Value, typename Allocator>
 class NodeHashMap : public std::unordered_map<Key, Value,
-                                       std::hash<Key>,
-                                       std::equal_to<Key>,
-                                       Allocator> {
+                                              std::hash<Key>,
+                                              std::equal_to<Key>,
+                                              Allocator> {
   using Base = std::unordered_map<Key, Value,
                                   std::hash<Key>,
                                   std::equal_to<Key>,

diff --git a/include/onnxruntime/core/common/logging/macros.h b/include/onnxruntime/core/common/logging/macros.h
@@ -255,15 +255,17 @@
 #else
 // Disabled in Release builds.
 #define VLOGS(logger, level) \
-  if constexpr (true) {} else LOGS_CATEGORY(logger, VERBOSE, "VLOG" #level)
+  if constexpr (true) {      \
+  } else                     \
+    LOGS_CATEGORY(logger, VERBOSE, "VLOG" #level)
 #define VLOGS_USER(logger, level) \
-  if constexpr (true) {} else LOGS_USER_CATEGORY(logger, VERBOSE, "VLOG" #level)
+  if constexpr (true) {           \
+  } else                          \
+    LOGS_USER_CATEGORY(logger, VERBOSE, "VLOG" #level)
 #define VLOGF(logger, level, format_str, ...)
 #define VLOGF_USER(logger, level, format_str, ...)
 #endif
 
-
-
 // Default logger variants
 #define VLOGS_DEFAULT(level) \
   VLOGS(::onnxruntime::logging::LoggingManager::DefaultLogger(), level)

diff --git a/include/onnxruntime/core/common/profiler_common.h b/include/onnxruntime/core/common/profiler_common.h
@@ -75,7 +75,7 @@ struct EventRecord {
 
 using Events = std::vector<EventRecord>;
 
-//Execution Provider Profiler
+// Execution Provider Profiler
 class EpProfiler {
  public:
   virtual ~EpProfiler() = default;

diff --git a/include/onnxruntime/core/common/status.h b/include/onnxruntime/core/common/status.h
@@ -121,10 +121,10 @@ class [[nodiscard]] Status {
 
   Status(StatusCategory category, int code);
 
-  GSL_SUPPRESS(r.11)
+  GSL_SUPPRESS(r .11)
   Status(const Status& other)
       : state_((other.state_ == nullptr) ? nullptr : new State(*other.state_)) {}
-  GSL_SUPPRESS(r.11)
+  GSL_SUPPRESS(r .11)
   Status& operator=(const Status& other) {
     if (state_ != other.state_) {
       if (other.state_ == nullptr) {

diff --git a/include/onnxruntime/core/eager/ort_kernel_invoker.h b/include/onnxruntime/core/eager/ort_kernel_invoker.h
@@ -22,12 +22,11 @@ namespace onnxruntime {
 
 class ORTInvoker {
  public:
-  ORTInvoker(std::shared_ptr<IExecutionProvider> execution_provider, 
+  ORTInvoker(std::shared_ptr<IExecutionProvider> execution_provider,
              const logging::Logger& logger,
-             const IOnnxRuntimeOpSchemaRegistryList& custom_op_registries) : 
-      execution_provider_(std::move(execution_provider)), logger_(logger), custom_op_registries_(custom_op_registries) {
+             const IOnnxRuntimeOpSchemaRegistryList& custom_op_registries) : execution_provider_(std::move(execution_provider)), logger_(logger), custom_op_registries_(custom_op_registries) {
     if (!execution_provider_) {
-    ORT_THROW("Execution provider is nullptr");
+      ORT_THROW("Execution provider is nullptr");
     }
   }
 
@@ -36,7 +35,7 @@ class ORTInvoker {
   }
 
   common::Status Invoke(const std::string& op_name,
-                        //optional inputs / outputs?
+                        // optional inputs / outputs?
                         const std::vector<OrtValue>& inputs,
                         std::vector<OrtValue>& outputs,
                         const NodeAttributes* attributes,

diff --git a/include/onnxruntime/core/framework/data_types.h b/include/onnxruntime/core/framework/data_types.h
@@ -386,8 +386,8 @@ void AssignOpaqueDomainName(const char* domain, const char* name,
 
 }  // namespace data_types_internal
 
-//The suppressed warning is: "The type with a virtual function needs either public virtual or protected nonvirtual destructor."
-//However, we do not allocate this type on heap.
+// The suppressed warning is: "The type with a virtual function needs either public virtual or protected nonvirtual destructor."
+// However, we do not allocate this type on heap.
 #if defined(_MSC_VER) && !defined(__clang__)
 #pragma warning(push)
 #pragma warning(disable : 26436)
@@ -614,7 +614,7 @@ class OptionalType :
 #if !defined(DISABLE_OPTIONAL_TYPE)
   OptionalType()
 #else
-  OptionalType() : DisabledTypeBase { DataTypeImpl::GeneralType::kOptional, 0 }
+  OptionalType() : DisabledTypeBase{DataTypeImpl::GeneralType::kOptional, 0}
 #endif
   {
     using namespace data_types_internal;

diff --git a/include/onnxruntime/core/framework/data_types_internal.h b/include/onnxruntime/core/framework/data_types_internal.h
@@ -29,17 +29,17 @@
 namespace onnxruntime {
 namespace utils {
 
-  // The following primitives are strongly recommended for switching on tensor input datatypes for
-  // kernel implementations.
-  //
-  //  1) If you need to handle all of the primitive tensor contained datatypes, the best choice would be macros
-  //     DispatchOnTensorType or DispatchOnTensorTypeWithReturn. Use inline wrappers so your function can be invoked as function<T>().
-  //  2) if you have a few types, use Tensor.IsDataType<T>()/IsDataTypeString() or use utils::IsPrimitiveDataType<T>()
-  //     if you have a standalone MLDatatType with a sequence of if/else statements.
-  //  3) For something in between, we suggest to use CallDispatcher pattern.
-  //
-  // Invoking DataTypeImpl::GetType<T>() for switching on input types is discouraged and should be avoided.
-  // Every primitive type carries with it an integer constant that can be used for quick switching on types.
+// The following primitives are strongly recommended for switching on tensor input datatypes for
+// kernel implementations.
+//
+//  1) If you need to handle all of the primitive tensor contained datatypes, the best choice would be macros
+//     DispatchOnTensorType or DispatchOnTensorTypeWithReturn. Use inline wrappers so your function can be invoked as function<T>().
+//  2) if you have a few types, use Tensor.IsDataType<T>()/IsDataTypeString() or use utils::IsPrimitiveDataType<T>()
+//     if you have a standalone MLDatatType with a sequence of if/else statements.
+//  3) For something in between, we suggest to use CallDispatcher pattern.
+//
+// Invoking DataTypeImpl::GetType<T>() for switching on input types is discouraged and should be avoided.
+// Every primitive type carries with it an integer constant that can be used for quick switching on types.
 
 #define DispatchOnTensorType(tensor_type, function, ...)          \
   switch (tensor_type->AsPrimitiveDataType()->GetDataType()) {    \
@@ -498,11 +498,10 @@ class ContainerChecker {
         ORT_ENFORCE(++index < c.size(), "Sequence is missing type entry for its element");
         constexpr int32_t prim_type = ToTensorProtoElementType<T>();
         // Check if this is a primitive type and it matches
-        if constexpr(prim_type != ONNX_NAMESPACE::TensorProto_DataType_UNDEFINED) {
+        if constexpr (prim_type != ONNX_NAMESPACE::TensorProto_DataType_UNDEFINED) {
           return c[index].IsType(data_types_internal::ContainerType::kTensor) &&
                  c[index].IsPrimType(prim_type);
-        }
-        else {
+        } else {
           // T is not primitive, check next entry for non-primitive proto
           return IsContainerOfType<T>::check(c, index);
         }
@@ -528,11 +527,11 @@ class ContainerChecker {
       }
       ORT_ENFORCE(++index < c.size(), "Map is missing type entry for its value");
       constexpr int32_t val_type = ToTensorProtoElementType<V>();
-      if constexpr(val_type != ONNX_NAMESPACE::TensorProto_DataType_UNDEFINED) {
+      if constexpr (val_type != ONNX_NAMESPACE::TensorProto_DataType_UNDEFINED) {
         return c[index].IsType(data_types_internal::ContainerType::kTensor) &&
                c[index].IsPrimType(val_type);
-      }
-      else return IsContainerOfType<V>::check(c, index);
+      } else
+        return IsContainerOfType<V>::check(c, index);
     }
   };
 

diff --git a/include/onnxruntime/core/framework/float16.h b/include/onnxruntime/core/framework/float16.h
@@ -69,10 +69,9 @@ struct BFloat16 {
       val = static_cast<uint16_t>((U32 + rounding_bias) >> 16);
     }
 #else
-    if constexpr(endian::native == endian::little) {
+    if constexpr (endian::native == endian::little) {
       std::memcpy(&val, reinterpret_cast<char*>(&v) + sizeof(uint16_t), sizeof(uint16_t));
-    }
-    else {
+    } else {
       std::memcpy(&val, &v, sizeof(uint16_t));
     }
 #endif
@@ -93,11 +92,10 @@ struct BFloat16 {
     float result;
     char* const first = reinterpret_cast<char*>(&result);
     char* const second = first + sizeof(uint16_t);
-    if constexpr(endian::native == endian::little) {
+    if constexpr (endian::native == endian::little) {
       std::memset(first, 0, sizeof(uint16_t));
       std::memcpy(second, &val, sizeof(uint16_t));
-    }
-    else {
+    } else {
       std::memcpy(first, &val, sizeof(uint16_t));
       std::memset(second, 0, sizeof(uint16_t));
     }
@@ -117,7 +115,6 @@ inline ORT_HOST_DEVICE bool operator==(const BFloat16& left, const BFloat16& rig
 inline ORT_HOST_DEVICE bool operator!=(const BFloat16& left, const BFloat16& right) { return left.val != right.val; }
 inline ORT_HOST_DEVICE bool operator<(const BFloat16& left, const BFloat16& right) { return left.val < right.val; }
 
-
 // User defined suffixes to make it easier to declare
 // initializers with MLFloat16 and BFloat16 from unsigned short
 // E.g 10_f16 or 10_b16

diff --git a/include/onnxruntime/core/framework/func_api.h b/include/onnxruntime/core/framework/func_api.h
@@ -10,7 +10,7 @@ using DestroyFunc = void (*)(void*, void*);
 using AllocatorHandle = void*;
 
 typedef struct {
-  //right now we only include allocation for host memory
+  // right now we only include allocation for host memory
   AllocateFunc allocate_func;
   DestroyFunc release_func;
   AllocatorHandle allocator_handle;
Original file line number	Diff line number	Diff line change
Expand Up		@@ -19,4 +19,3 @@ DerivePointerAlignment: false
		# NamespaceIndentation: All

		...