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microsoft · Nov 8, 2023 · f2ffca0 · f2ffca0
1 parent 5d53ba2
commit f2ffca0
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Showing 30 changed files with 93 additions and 70 deletions.
diff --git a/include/onnxruntime/core/platform/EigenNonBlockingThreadPool.h b/include/onnxruntime/core/platform/EigenNonBlockingThreadPool.h
@@ -278,7 +278,7 @@ class ThreadPoolProfiler {
   int num_threads_;
 #ifdef _MSC_VER
 #pragma warning(push)
-// C4324: structure was padded due to alignment specifier
+  // C4324: structure was padded due to alignment specifier
 #pragma warning(disable : 4324)
 #endif  // _MSC_VER
   struct ORT_ALIGN_TO_AVOID_FALSE_SHARING ChildThreadStat {

diff --git a/onnxruntime/python/backend/backend.py b/onnxruntime/python/backend/backend.py
@@ -63,7 +63,7 @@ def is_opset_supported(cls, model):
                         error_message = (
                             "Skipping this test as only released onnx opsets are supported."
                             "To run this test set env variable ALLOW_RELEASED_ONNX_OPSET_ONLY to 0."
-                            " Got Domain '{}' version '{}'.".format(domain, opset.version)
+                            f" Got Domain '{domain}' version '{opset.version}'."
                         )
                         return False, error_message
                 except AttributeError:
@@ -74,7 +74,7 @@ def is_opset_supported(cls, model):
                         error_message = (
                             "Skipping this test as only released onnx opsets are supported."
                             "To run this test set env variable ALLOW_RELEASED_ONNX_OPSET_ONLY to 0."
-                            " Got Domain '{}' version '{}'.".format(domain, opset.version)
+                            f" Got Domain '{domain}' version '{opset.version}'."
                         )
                         return False, error_message
         return True, ""

diff --git a/onnxruntime/python/tools/transformers/models/stable_diffusion/diffusion_models.py b/onnxruntime/python/tools/transformers/models/stable_diffusion/diffusion_models.py
@@ -448,7 +448,7 @@ def add_hidden_states_graph_output(self, model: ModelProto, optimized_onnx_path,
 
         assert self.clip_skip >= 0 and self.clip_skip < hidden_layers
 
-        node_output_name = "/text_model/encoder/layers.{}/Add_1_output_0".format(hidden_layers - 1 - self.clip_skip)
+        node_output_name = f"/text_model/encoder/layers.{hidden_layers - 1 - self.clip_skip}/Add_1_output_0"
 
         # search the name in outputs of all node
         found = False

diff --git a/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc b/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc
@@ -1238,7 +1238,7 @@ TEST(MathOpTest, Sum_8_Test1) {
   // This test runs fine on CPU Plugin
   test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider});
 #else
-  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});                    // TensorRT: Expected output shape [{3,3,3}] did not match run output shape [{3,1,1}] for sum
+  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});  // TensorRT: Expected output shape [{3,3,3}] did not match run output shape [{3,1,1}] for sum
 #endif
 }
 
@@ -1264,7 +1264,7 @@ TEST(MathOpTest, Sum_8_Test1_double) {
   // This test runs fine on CPU Plugin
   test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider});
 #else
-  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});                    // TensorRT: Expected output shape [{3,3,3}] did not match run output shape [{3,1,1}] for sum
+  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});  // TensorRT: Expected output shape [{3,3,3}] did not match run output shape [{3,1,1}] for sum
 #endif
 }
 TEST(MathOpTest, Sum_8_Test2) {

diff --git a/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc b/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc
@@ -1086,7 +1086,7 @@ TEST(ReductionOpTest, ReduceMax_int32) {
 #if defined(OPENVINO_CONFIG_GPU_FP32) || defined(OPENVINO_CONFIG_GPU_FP16)
   test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider});  // OpenVINO: Disabled temporarily
 #else
-  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});                          // TensorRT: axis must be 0
+  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});  // TensorRT: axis must be 0
 #endif
 }
 
@@ -1107,7 +1107,7 @@ TEST(ReductionOpTest, ReduceMax_int64) {
 #if defined(OPENVINO_CONFIG_GPU_FP32) || defined(OPENVINO_CONFIG_GPU_FP16)
   test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider});  // OpenVINO: Disabled temporarily
 #else
-  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});                          // TensorRT: axis must be 0
+  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider});  // TensorRT: axis must be 0
 #endif
 }
 

diff --git a/orttraining/orttraining/python/training/ortmodule/_fallback.py b/orttraining/orttraining/python/training/ortmodule/_fallback.py
@@ -175,9 +175,9 @@ def fallback(self, log_level: _logger.LogLevel, *inputs, **kwargs):
 
             # This warning will not be raised again if retry is not enabled
             self._logger.warning(
-                "Fallback to PyTorch due to exception {} was triggered. "
+                f"Fallback to PyTorch due to exception {exception_type} was triggered. "
                 "Report this issue with a minimal repro at https://www.github.com/microsoft/onnxruntime. "
-                "See details below:\n\n{}".format(exception_type, exception_string)
+                f"See details below:\n\n{exception_string}"
             )
 
             self._raised_fallback_exception = True

diff --git a/tools/ci_build/build.py b/tools/ci_build/build.py
@@ -1637,9 +1637,7 @@ def run_adb_shell(cmd):
         # GCOV_PREFIX specifies the root directory
         # for creating the runtime code coverage files.
         if args.code_coverage:
-            adb_shell(
-                "cd {0} && GCOV_PREFIX={0} GCOV_PREFIX_STRIP={1} {2}".format(device_dir, cwd.count(os.sep) + 1, cmd)
-            )
+            adb_shell(f"cd {device_dir} && GCOV_PREFIX={device_dir} GCOV_PREFIX_STRIP={cwd.count(os.sep) + 1} {cmd}")
         else:
             adb_shell(f"cd {device_dir} && {cmd}")
 
@@ -1689,7 +1687,7 @@ def run_adb_shell(cmd):
                 )
 
             if args.use_nnapi:
-                run_adb_shell("{0}/onnx_test_runner -e nnapi {0}/test".format(device_dir))
+                run_adb_shell(f"{device_dir}/onnx_test_runner -e nnapi {device_dir}/test")
             else:
                 run_adb_shell(f"{device_dir}/onnx_test_runner {device_dir}/test")
 
@@ -1702,9 +1700,9 @@ def run_adb_shell(cmd):
                 adb_push("onnxruntime_customopregistration_test", device_dir, cwd=cwd)
                 adb_shell(f"chmod +x {device_dir}/onnxruntime_shared_lib_test")
                 adb_shell(f"chmod +x {device_dir}/onnxruntime_customopregistration_test")
-                run_adb_shell("LD_LIBRARY_PATH=$LD_LIBRARY_PATH:{0} {0}/onnxruntime_shared_lib_test".format(device_dir))
+                run_adb_shell(f"LD_LIBRARY_PATH=$LD_LIBRARY_PATH:{device_dir} {device_dir}/onnxruntime_shared_lib_test")
                 run_adb_shell(
-                    "LD_LIBRARY_PATH=$LD_LIBRARY_PATH:{0} {0}/onnxruntime_customopregistration_test".format(device_dir)
+                    f"LD_LIBRARY_PATH=$LD_LIBRARY_PATH:{device_dir} {device_dir}/onnxruntime_customopregistration_test"
                 )
 
 

diff --git a/tools/python/find_optimizer_opset_version_updates_required.py b/tools/python/find_optimizer_opset_version_updates_required.py
@@ -54,7 +54,7 @@ def get_call_args_from_file(filename: str, function_or_declaration: str) -> typi
                     # TODO: handle automatically by merging lines
                     log.error(
                         "Call/Declaration is split over multiple lines. Please check manually."
-                        "File:{} Line:{}".format(filename, line_num)
+                        f"File:{filename} Line:{line_num}"
                     )
                     continue
 

diff --git a/winml/lib/Api.Image/inc/ImageConversionHelpers.h b/winml/lib/Api.Image/inc/ImageConversionHelpers.h
@@ -52,5 +52,6 @@ bool VideoFramesHaveSameDevice(const wm::IVideoFrame& video_frame_1, const wm::I
 wgdx::Direct3D11::IDirect3DDevice GetDeviceFromDirect3DSurface(const wgdx::Direct3D11::IDirect3DSurface& d3dSurface);
 
 constexpr std::array<DXGI_FORMAT, 3> supportedWinMLFormats = {
-  DXGI_FORMAT_R8G8B8A8_UNORM, DXGI_FORMAT_B8G8R8A8_UNORM, DXGI_FORMAT_B8G8R8X8_UNORM};
+  DXGI_FORMAT_R8G8B8A8_UNORM, DXGI_FORMAT_B8G8R8A8_UNORM, DXGI_FORMAT_B8G8R8X8_UNORM
+};
 }  // namespace _winml::Imaging
diff --git a/winml/lib/Api.Image/inc/TensorToVideoFrameConverter.h b/winml/lib/Api.Image/inc/TensorToVideoFrameConverter.h
@@ -40,10 +40,7 @@ class TensorToVideoFrameConverter : public ImageConverter {
 
  private:
   GUID _d3d11TextureGUID = {
-    0x14bf1054,
-    0x6ce7,
-    0x4c00,
-    {0xa1, 0x32, 0xb0, 0xf2, 0x11, 0x5D, 0xE0, 0x7f}
+    0x14bf1054, 0x6ce7, 0x4c00, {0xa1, 0x32, 0xb0, 0xf2, 0x11, 0x5D, 0xE0, 0x7f}
   };  // {14BF1054-6CE7-4C00-A132-B0F2115DE07F}
   GUID _handleGUID = {
     0x700148fc, 0xc0cb, 0x4a7e, {0xa7, 0xc0, 0xe7, 0x43, 0xc1, 0x9, 0x9d, 0x62}

diff --git a/winml/lib/Api.Image/inc/VideoFrameToTensorConverter.h b/winml/lib/Api.Image/inc/VideoFrameToTensorConverter.h
@@ -50,10 +50,7 @@ class VideoFrameToTensorConverter : public ImageConverter {
 
  private:
   GUID d3d11_texture_GUID_ = {
-    0x485e4bb3,
-    0x3fe8,
-    0x497b,
-    {0x85, 0x9e, 0xc7, 0x5, 0x18, 0xdb, 0x11, 0x2a}
+    0x485e4bb3, 0x3fe8, 0x497b, {0x85, 0x9e, 0xc7, 0x5, 0x18, 0xdb, 0x11, 0x2a}
   };  // {485E4BB3-3FE8-497B-859E-C70518DB112A}
   GUID handle_GUID_ = {
     0xce43264e, 0x41f7, 0x4882, {0x9e, 0x20, 0xfa, 0xa5, 0x1e, 0x37, 0x64, 0xfc}

diff --git a/winml/lib/Api.Ort/OnnxruntimeModel.cpp b/winml/lib/Api.Ort/OnnxruntimeModel.cpp
@@ -81,7 +81,8 @@ HRESULT ModelInfo::RuntimeClassInitialize(_In_ OnnxruntimeEngineFactory* engine_
     winml_adapter_api->ModelGetInputCount,
     winml_adapter_api->ModelGetInputName,
     winml_adapter_api->ModelGetInputDescription,
-    winml_adapter_api->ModelGetInputTypeInfo};
+    winml_adapter_api->ModelGetInputTypeInfo
+  };
 
   // Create inputs
   std::vector<OnnxruntimeValueInfoWrapper> inputs;
@@ -93,7 +94,8 @@ HRESULT ModelInfo::RuntimeClassInitialize(_In_ OnnxruntimeEngineFactory* engine_
     winml_adapter_api->ModelGetOutputCount,
     winml_adapter_api->ModelGetOutputName,
     winml_adapter_api->ModelGetOutputDescription,
-    winml_adapter_api->ModelGetOutputTypeInfo};
+    winml_adapter_api->ModelGetOutputTypeInfo
+  };
 
   std::vector<OnnxruntimeValueInfoWrapper> outputs;
   RETURN_IF_FAILED(CreateFeatureDescriptors(engine_factory, &output_helpers, ort_model, outputs));

diff --git a/winml/lib/Api/impl/TensorBase.h b/winml/lib/Api/impl/TensorBase.h
@@ -217,7 +217,8 @@ struct TensorBase : TBase {
     }
 
     D3D12_HEAP_PROPERTIES heapProperties = {
-      D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0};
+      D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0
+    };
     D3D12_RESOURCE_DESC resourceDesc = {
       D3D12_RESOURCE_DIMENSION_BUFFER,
       0,

diff --git a/winml/test/adapter/AdapterDmlEpTest.cpp b/winml/test/adapter/AdapterDmlEpTest.cpp
@@ -116,7 +116,8 @@ std::array<float, tensor_size> tensor_values = {};
 winrt::com_ptr<ID3D12Resource> CreateD3D12Resource(ID3D12Device& device) {
   constexpr uint64_t buffer_size = tensor_size * sizeof(float);
   constexpr D3D12_HEAP_PROPERTIES heap_properties = {
-    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0};
+    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0
+  };
   constexpr D3D12_RESOURCE_DESC resource_desc = {
     D3D12_RESOURCE_DIMENSION_BUFFER,
     0,
@@ -365,6 +366,7 @@ const AdapterDmlEpTestApi& getapi() {
     DmlCopyTensor,
     CreateCustomRegistry,
     ValueGetDeviceId,
-    SessionGetInputRequiredDeviceId};
+    SessionGetInputRequiredDeviceId
+  };
   return api;
 }
diff --git a/winml/test/adapter/AdapterSessionTest.cpp b/winml/test/adapter/AdapterSessionTest.cpp
@@ -368,7 +368,8 @@ const AdapterSessionTestAPI& getapi() {
     Profiling,
     CopyInputAcrossDevices,
     CopyInputAcrossDevices_DML,
-    GetNumberOfIntraOpThreads};
+    GetNumberOfIntraOpThreads
+  };
 
   if (SkipGpuTests()) {
     api.AppendExecutionProvider_DML = SkipTest;

diff --git a/winml/test/api/LearningModelAPITest.cpp b/winml/test/api/LearningModelAPITest.cpp
@@ -247,9 +247,11 @@ static void CheckLearningModelPixelRange() {
                                           // Normalized_0_1 and image output
                                           L"Add_ImageNet1920WithImageMetadataBgr8_SRGB_0_1.onnx",
                                           // Normalized_1_1 and image output
-                                          L"Add_ImageNet1920WithImageMetadataBgr8_SRGB_1_1.onnx"};
+                                          L"Add_ImageNet1920WithImageMetadataBgr8_SRGB_1_1.onnx"
+  };
   std::vector<LearningModelPixelRange> pixelRanges = {
-    LearningModelPixelRange::ZeroTo255, LearningModelPixelRange::ZeroToOne, LearningModelPixelRange::MinusOneToOne};
+    LearningModelPixelRange::ZeroTo255, LearningModelPixelRange::ZeroToOne, LearningModelPixelRange::MinusOneToOne
+  };
   for (uint32_t model_i = 0; model_i < modelPaths.size(); model_i++) {
     LearningModel learningModel = nullptr;
     WINML_EXPECT_NO_THROW(APITest::LoadModel(modelPaths[model_i], learningModel));
@@ -329,7 +331,8 @@ const LearningModelApiTestsApi& getapi() {
     CloseModelCheckEval,
     CloseModelNoNewSessions,
     CheckMetadataCaseInsensitive,
-    CreateCorruptModel};
+    CreateCorruptModel
+  };
 
   if (RuntimeParameterExists(L"noVideoFrameTests")) {
     api.CloseModelCheckEval = SkipTest;

diff --git a/winml/test/api/LearningModelBindingAPITest.cpp b/winml/test/api/LearningModelBindingAPITest.cpp
@@ -669,7 +669,8 @@ const LearningModelBindingAPITestsApi& getapi() {
     VerifyOutputAfterEvaluateAsyncCalledTwice,
     VerifyOutputAfterImageBindCalledTwice,
     SequenceLengthTensorFloat,
-    SequenceConstructTensorString};
+    SequenceConstructTensorString
+  };
 
   if (SkipGpuTests()) {
     api.GpuSqueezeNet = SkipTest;

diff --git a/winml/test/api/LearningModelSessionAPITest.cpp b/winml/test/api/LearningModelSessionAPITest.cpp
@@ -793,7 +793,8 @@ static void STFT(
   auto n_dfts = static_cast<size_t>(1 + floor((signal_size - dft_size) / hop_size));
   auto input_shape = std::vector<int64_t>{1, INT64(signal_size)};
   auto output_shape = std::vector<int64_t>{
-    INT64(batch_size), INT64(n_dfts), is_onesided ? ((INT64(dft_size) >> 1) + 1) : INT64(dft_size), 2};
+    INT64(batch_size), INT64(n_dfts), is_onesided ? ((INT64(dft_size) >> 1) + 1) : INT64(dft_size), 2
+  };
   auto dft_length = TensorInt64Bit::CreateFromArray({}, {INT64(dft_size)});
 
   auto model =
@@ -1372,7 +1373,8 @@ static void ModelBuilding_GridSample_Internal(LearningModelDeviceKind kind) {
     5.0000f,
     5.0000f,
     10.0000f,
-    10.0000f};
+    10.0000f
+  };
   input_dims = {1, 1, 3, 2};
   grid_dims = {1, 2, 4, 2};
 
@@ -2312,7 +2314,8 @@ const LearningModelSessionAPITestsApi& getapi() {
     ModelBuilding_STFT,
     ModelBuilding_MelSpectrogramOnThreeToneSignal,
     ModelBuilding_MelWeightMatrix,
-    SetName};
+    SetName
+  };
 
   if (SkipGpuTests()) {
     api.CreateSessionDeviceDirectX = SkipTest;

diff --git a/winml/test/api/RawApiHelpers.cpp b/winml/test/api/RawApiHelpers.cpp
@@ -38,7 +38,8 @@ void RunOnDevice(ml::learning_model& model, ml::learning_model_device& device, I
     auto channel_buffers_pointers = std::vector<float*>{
       &input_data.at(0),
       &input_data.at(0) + channel_buffers_sizes[0],
-      &input_data.at(0) + channel_buffers_sizes[0] + +channel_buffers_sizes[1]};
+      &input_data.at(0) + channel_buffers_sizes[0] + +channel_buffers_sizes[1]
+    };
 
     WINML_EXPECT_HRESULT_SUCCEEDED(binding->bind_as_references<float>(
       input_name,

diff --git a/winml/test/api/RawApiTestsGpu.cpp b/winml/test/api/RawApiTestsGpu.cpp
@@ -165,7 +165,8 @@ const RawApiTestsGpuApi& getapi() {
     CreateDirectXMinPowerDevice,
     Evaluate,
     EvaluateNoInputCopy,
-    EvaluateManyBuffers};
+    EvaluateManyBuffers
+  };
 
   if (SkipGpuTests()) {
     api.CreateDirectXDevice = SkipTest;

diff --git a/winml/test/concurrency/ConcurrencyTests.cpp b/winml/test/concurrency/ConcurrencyTests.cpp
@@ -141,7 +141,8 @@ void EvalAsyncDifferentBindings() {
   std::vector<EvaluationUnit> evaluation_units(num_units, EvaluationUnit());
 
   std::vector<ImageFeatureValue> ifvs = {
-    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")};
+    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")
+  };
 
   // same session, different binding
   auto model = LearningModel::LoadFromFilePath(FileHelpers::GetModulePath() + L"model.onnx");
@@ -191,7 +192,8 @@ void MultiThreadMultiSessionOnDevice(const LearningModelDevice& device) {
   auto path = FileHelpers::GetModulePath() + L"model.onnx";
   auto model = LearningModel::LoadFromFilePath(path);
   std::vector<ImageFeatureValue> ivfs = {
-    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")};
+    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")
+  };
   std::vector<int> max_indices = {
     281,  // tabby, tabby cat
     0     // tench, Tinca tinca
@@ -257,7 +259,8 @@ void MultiThreadSingleSessionOnDevice(const LearningModelDevice& device) {
   LearningModelSession model_session = nullptr;
   WINML_EXPECT_NO_THROW(model_session = LearningModelSession(model, device));
   std::vector<ImageFeatureValue> ivfs = {
-    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")};
+    FileHelpers::LoadImageFeatureValue(L"kitten_224.png"), FileHelpers::LoadImageFeatureValue(L"fish.png")
+  };
   std::vector<int> max_indices = {
     281,  // tabby, tabby cat
     0     // tench, Tinca tinca
@@ -322,7 +325,8 @@ const ConcurrencyTestsApi& getapi() {
     MultiThreadSingleSessionGpu,
     EvalAsyncDifferentModels,
     EvalAsyncDifferentSessions,
-    EvalAsyncDifferentBindings};
+    EvalAsyncDifferentBindings
+  };
 
   if (SkipGpuTests()) {
     api.MultiThreadMultiSessionGpu = SkipTest;

diff --git a/winml/test/image/imageTestHelper.cpp b/winml/test/image/imageTestHelper.cpp
@@ -148,7 +148,8 @@ TensorFloat LoadInputImageFromGPU(SoftwareBitmap softwareBitmap, const std::wstr
   // 3 is number of channels we use. R G B without alpha.
   UINT64 bufferbytesize = 3 * sizeof(float) * softwareBitmap.PixelWidth() * softwareBitmap.PixelHeight();
   D3D12_HEAP_PROPERTIES heapProperties = {
-    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0};
+    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0
+  };
   D3D12_RESOURCE_DESC resourceDesc = {
     D3D12_RESOURCE_DIMENSION_BUFFER,
     0,

diff --git a/winml/test/image/imagetests.cpp b/winml/test/image/imagetests.cpp
@@ -939,7 +939,8 @@ TEST_F(ImageTests, ImageBindingAsGPUTensor) {
   UINT64 buffer_byte_size =
     static_cast<uint64_t>(software_bitmap.PixelWidth()) * software_bitmap.PixelHeight() * 3 * sizeof(float);
   D3D12_HEAP_PROPERTIES heap_properties = {
-    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0};
+    D3D12_HEAP_TYPE_DEFAULT, D3D12_CPU_PAGE_PROPERTY_UNKNOWN, D3D12_MEMORY_POOL_UNKNOWN, 0, 0
+  };
   D3D12_RESOURCE_DESC resource_desc = {
     D3D12_RESOURCE_DIMENSION_BUFFER,
     0,

diff --git a/winml/test/model/model_tests.cpp b/winml/test/model/model_tests.cpp
@@ -232,7 +232,8 @@ static std::vector<ITestCase*> GetAllTestCases() {
     ORT_TSTR("tf_resnet_v2_152"),
     ORT_TSTR("vgg19"),
     ORT_TSTR("yolov3"),
-    ORT_TSTR("zfnet512")};
+    ORT_TSTR("zfnet512")
+  };
   allDisabledTests.insert(std::begin(x86DisabledTests), std::end(x86DisabledTests));
 #endif
   // Bad onnx test output caused by previously wrong SAME_UPPER/SAME_LOWER for ConvTranspose

diff --git a/winml/test/model/skip_model_tests.h b/winml/test/model/skip_model_tests.h
@@ -161,10 +161,8 @@ std::unordered_map<std::string, std::pair<std::string, std::string>> disabledGpu
     test name -> absolute difference sampleTolerance
 */
 std::unordered_map<std::string, double> sampleTolerancePerTests({
-  {"fp16_inception_v1_opset7_GPU",0.005                                  },
-  {"fp16_inception_v1_opset8_GPU", 0.005},
-  {            "candy_opset9_GPU",
-   0.00150000                           }, // Intel(R) UHD Graphics 630 (29.20.100.9020) AP machine has inaccurate GPU results for FNS Candy opset 9 https://microsoft.visualstudio.com/OS/_workitems/edit/30696168/
-  { "fp16_tiny_yolov2_opset8_GPU",
-   0.109000                             }, // Intel(R) UHD Graphics 630 (29.20.100.9020) AP machine has inaccurate GPU results for FNS Candy opset 9 https://microsoft.visualstudio.com/OS/_workitems/edit/30696168/
+  {"fp16_inception_v1_opset7_GPU",      0.005},
+  {"fp16_inception_v1_opset8_GPU",      0.005},
+  {            "candy_opset9_GPU", 0.00150000}, // Intel(R) UHD Graphics 630 (29.20.100.9020) AP machine has inaccurate GPU results for FNS Candy opset 9 https://microsoft.visualstudio.com/OS/_workitems/edit/30696168/
+  { "fp16_tiny_yolov2_opset8_GPU",   0.109000}, // Intel(R) UHD Graphics 630 (29.20.100.9020) AP machine has inaccurate GPU results for FNS Candy opset 9 https://microsoft.visualstudio.com/OS/_workitems/edit/30696168/
 });
diff --git a/winml/test/scenario/cppwinrt/CustomNullOp.h b/winml/test/scenario/cppwinrt/CustomNullOp.h
@@ -69,7 +69,8 @@ struct NullOperatorFactory : winrt::implements<NullOperatorFactory, IMLOperatorK
     std::vector<MLOperatorEdgeDescription> allowedEdges{
       CreateEdgeDescriptor(MLOperatorEdgeType::Tensor, MLOperatorTensorDataType::Double),
       CreateEdgeDescriptor(MLOperatorEdgeType::Tensor, MLOperatorTensorDataType::Float),
-      CreateEdgeDescriptor(MLOperatorEdgeType::Tensor, MLOperatorTensorDataType::Float16)};
+      CreateEdgeDescriptor(MLOperatorEdgeType::Tensor, MLOperatorTensorDataType::Float16)
+    };
     typeConstraint.allowedTypes = allowedEdges.data();
     typeConstraint.allowedTypeCount = static_cast<uint32_t>(allowedEdges.size());