Cherry pick outstanding changes into release branch (round 2) (#7921)

* [OpenVINO-EP] Adding OpenVINO-EP samples to Msft Repo (#7826)

* Added ONNX_OV_EP samples

->Added cpp, python and csharp samples
using OpenVINO Execution Provider.

Signed-off-by: MaajidKhan <[email protected]>

* [js/web] update README.md (#7894)

* Add API_IMPL_* blocks around shared provider methods as they are C APIs (#7908)

* Missing logic for cuda nuget package (#7911)

Co-authored-by: Maajid khan <[email protected]>
Co-authored-by: Yulong Wang <[email protected]>
Co-authored-by: Ryan Hill <[email protected]>

js/web/README.md

@@ -10,9 +10,9 @@ The [Open Neural Network Exchange](http://onnx.ai/) (ONNX) is an open standard f
 
 ### Why ONNX Runtime Web
 
-With ONNX Runtime Web, web developers can score pre-trained ONNX models directly on browsers with various benefits of reducing server-client communication and protecting user privacy, as well as offering install-free and cross-platform in-browser ML experience.
+With ONNX Runtime Web, web developers can score models directly on browsers with various benefits including reducing server-client communication and protecting user privacy, as well as offering install-free and cross-platform in-browser ML experience.
 
-ONNX Runtime Web can run on both CPU and GPU. For running on CPU, [WebAssembly](https://developer.mozilla.org/en-US/docs/WebAssembly) is adopted to execute the model at near-native speed. Furthermore, ONNX Runtime Web utilizes [Web Workers](https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers) to provide a "multi-threaded" environment to parallelize data processing. Empirical evaluation shows very promising performance gains on CPU by taking full advantage of WebAssembly and Web Workers. For running on GPUs, a popular standard for accessing GPU capabilities - WebGL is adopted. ONNX Runtime Web has further adopted several novel optimization techniques for reducing data transfer between CPU and GPU, as well as some techniques to reduce GPU processing cycles to further push the performance to the maximum.
+ONNX Runtime Web can run on both CPU and GPU. On CPU side, [WebAssembly](https://developer.mozilla.org/en-US/docs/WebAssembly) is adopted to execute the model at near-native speed. ONNX Runtime Web complies the native ONNX Runtime CPU engine into WebAssembly backend by using Emscripten, so it supports most functionalities native ONNX Runtime offers, including full ONNX operator coverage, multi-threading, [ONNX Runtime Quantization](https://www.onnxruntime.ai/docs/how-to/quantization.html) as well as [ONNX Runtime Mobile](http://www.onnxruntime.ai/docs/how-to/deploy-on-mobile.html). For performance acceleration with GPUs, ONNX Runtime Web leverages WebGL, a popular standard for accessing GPU capabilities. We are keeping improving op coverage and optimizing performance in WebGL backend.
 
 See [Compatibility](#Compatibility) and [Operators Supported](#Operators) for a list of platforms and operators ONNX Runtime Web currently supports.
 

onnxruntime/core/framework/provider_bridge_ort.cc

@@ -7,6 +7,7 @@
 #include "core/framework/compute_capability.h"
 #include "core/framework/data_types.h"
 #include "core/framework/data_transfer_manager.h"
+#include "core/framework/error_code_helper.h"
 #include "core/framework/execution_provider.h"
 #include "core/framework/kernel_registry.h"
 #include "core/framework/provider_bridge_ort.h"
@@ -1084,47 +1085,55 @@ INcclService& INcclService::GetInstance() {
 }  // namespace onnxruntime
 
 ORT_API_STATUS_IMPL(OrtSessionOptionsAppendExecutionProvider_Dnnl, _In_ OrtSessionOptions* options, int use_arena) {
+  API_IMPL_BEGIN
   auto factory = onnxruntime::CreateExecutionProviderFactory_Dnnl(use_arena);
   if (!factory) {
     return OrtApis::CreateStatus(ORT_FAIL, "OrtSessionOptionsAppendExecutionProvider_Dnnl: Failed to load shared library");
   }
 
   options->provider_factories.push_back(factory);
   return nullptr;
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtSessionOptionsAppendExecutionProvider_Tensorrt, _In_ OrtSessionOptions* options, int device_id) {
+  API_IMPL_BEGIN
   auto factory = onnxruntime::CreateExecutionProviderFactory_Tensorrt(device_id);
   if (!factory) {
     return OrtApis::CreateStatus(ORT_FAIL, "OrtSessionOptionsAppendExecutionProvider_Tensorrt: Failed to load shared library");
   }
 
   options->provider_factories.push_back(factory);
   return nullptr;
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtApis::SessionOptionsAppendExecutionProvider_TensorRT, _In_ OrtSessionOptions* options, _In_ const OrtTensorRTProviderOptions* tensorrt_options) {
+  API_IMPL_BEGIN
   auto factory = onnxruntime::CreateExecutionProviderFactory_Tensorrt(tensorrt_options);
   if (!factory) {
     return OrtApis::CreateStatus(ORT_FAIL, "SessionOptionsAppendExecutionProvider_Tensorrt: Failed to load shared library");
   }
 
   options->provider_factories.push_back(factory);
   return nullptr;
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtApis::SessionOptionsAppendExecutionProvider_OpenVINO, _In_ OrtSessionOptions* options, _In_ const OrtOpenVINOProviderOptions* provider_options) {
+  API_IMPL_BEGIN
   auto factory = onnxruntime::CreateExecutionProviderFactory_OpenVINO(provider_options);
   if (!factory) {
     return OrtApis::CreateStatus(ORT_FAIL, "SessionOptionsAppendExecutionProvider_OpenVINO: Failed to load shared library");
   }
 
   options->provider_factories.push_back(factory);
   return nullptr;
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtSessionOptionsAppendExecutionProvider_OpenVINO, _In_ OrtSessionOptions* options, _In_ const char* device_type) {
-  OrtOpenVINOProviderOptions provider_options;
+  OrtOpenVINOProviderOptions provider_options{};
   provider_options.device_type = device_type;
   return OrtApis::SessionOptionsAppendExecutionProvider_OpenVINO(options, &provider_options);
 }
@@ -1137,23 +1146,29 @@ ORT_API_STATUS_IMPL(OrtSessionOptionsAppendExecutionProvider_CUDA, _In_ OrtSessi
 }
 
 ORT_API_STATUS_IMPL(OrtApis::SetCurrentGpuDeviceId, _In_ int device_id) {
+  API_IMPL_BEGIN
   if (auto* info = onnxruntime::GetProviderInfo_CUDA())
     return info->SetCurrentGpuDeviceId(device_id);
   return CreateStatus(ORT_FAIL, "CUDA execution provider is not enabled.");
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtApis::GetCurrentGpuDeviceId, _In_ int* device_id) {
+  API_IMPL_BEGIN
   if (auto* info = onnxruntime::GetProviderInfo_CUDA())
     return info->GetCurrentGpuDeviceId(device_id);
   return CreateStatus(ORT_FAIL, "CUDA execution provider is not enabled.");
+  API_IMPL_END
 }
 
 ORT_API_STATUS_IMPL(OrtApis::SessionOptionsAppendExecutionProvider_CUDA, _In_ OrtSessionOptions* options, _In_ const OrtCUDAProviderOptions* cuda_options) {
+  API_IMPL_BEGIN
   auto factory = onnxruntime::CreateExecutionProviderFactory_Cuda(cuda_options);
   if (!factory) {
     return OrtApis::CreateStatus(ORT_FAIL, "OrtSessionOptionsAppendExecutionProvider_Cuda: Failed to load shared library");
   }
 
   options->provider_factories.push_back(factory);
   return nullptr;
+  API_IMPL_END
 }