diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..7c886f9 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,3 @@ +{ + "cmake.sourceDirectory": "/home/gyk/sishu-yolo-sdk/cpp" +} \ No newline at end of file diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt index 8a52448..edc1bac 100644 --- a/cpp/CMakeLists.txt +++ b/cpp/CMakeLists.txt @@ -6,31 +6,49 @@ set(CMAKE_CXX_STANDARD 17) find_package(JNI REQUIRED) # --- 2. -find_package(OpenCV REQUIRED) +if(WIN32) + message(STATUS "Configuring for Windows (using vcpkg OpenCV + manual ONNX)") + + # + find_package(OpenCV REQUIRED) + + # + set(ORT_MANUAL_PATH ${CMAKE_SOURCE_DIR}/../prebuilt_libs/onnxruntime-win-x64-1.23.2) + +elseif(UNIX) + message(STATUS "Configuring for Linux (using apt OpenCV + manual ONNX)") + + # + # + find_package(OpenCV REQUIRED) + + # + set(ORT_MANUAL_PATH ${CMAKE_SOURCE_DIR}/../prebuilt_libs/onnxruntime-linux-x64-1.23.2) +endif() + # --- 3. -# -set(ORT_MANUAL_PATH ${CMAKE_SOURCE_DIR}/../prebuilt_libs/onnxruntime-win-x64-1.23.2) - # find_path(ONNXRuntime_INCLUDE_DIRS NAMES onnxruntime_cxx_api.h HINTS ${ORT_MANUAL_PATH}/include ) - -# find_library(ONNXRuntime_LIBRARY NAMES onnxruntime HINTS ${ORT_MANUAL_PATH}/lib ) # +if(NOT OpenCV_FOUND) + message(FATAL_ERROR "Failed to find OpenCV. On Linux, run 'sudo apt install libopencv-dev'. On Windows, ensure vcpkg is setup.") +endif() if(NOT ONNXRuntime_INCLUDE_DIRS OR NOT ONNXRuntime_LIBRARY) message(FATAL_ERROR "Failed to find manual ONNX Runtime at ${ORT_MANUAL_PATH}") endif() -message(STATUS "Found Manual ONNX Runtime Include: ${ONNXRuntime_INCLUDE_DIRS}") -message(STATUS "Found Manual ONNX Runtime Library: ${ONNXRuntime_LIBRARY}") +message(STATUS "Found OpenCV: ${OpenCV_LIBS}") +message(STATUS "Found ONNX Runtime Include: ${ONNXRuntime_INCLUDE_DIRS}") +message(STATUS "Found ONNX Runtime Library: ${ONNXRuntime_LIBRARY}") # --- 4. @@ -43,19 +61,20 @@ add_library(my_yolo_sdk SHARED target_include_directories(my_yolo_sdk PUBLIC ${JNI_INCLUDE_DIRS} ${OpenCV_INCLUDE_DIRS} - ${ONNXRuntime_INCLUDE_DIRS} # + ${ONNXRuntime_INCLUDE_DIRS} include ) target_link_libraries(my_yolo_sdk PRIVATE ${JNI_LIBRARIES} - ${OpenCV_LIBS} - ${ONNXRuntime_LIBRARY} # + ${OpenCV_LIBS} # + ${ONNXRuntime_LIBRARY} ) # --- 6. if(UNIX) + message(STATUS "Setting RPATH for Linux") set_target_properties(my_yolo_sdk PROPERTIES - INSTALL_RPATH "$ORIGIN" + INSTALL_RPATH "$ORIGIN" # ) endif() \ No newline at end of file diff --git a/cpp/include/YoloCore.h b/cpp/include/YoloCore.h index f0a8a3d..5f82593 100644 --- a/cpp/include/YoloCore.h +++ b/cpp/include/YoloCore.h @@ -1,4 +1,3 @@ -// #pragma once #include @@ -8,7 +7,7 @@ #include #include -// + struct Detection { int class_id; @@ -19,23 +18,23 @@ struct Detection int height; }; -// + cv::Mat preprocess(const cv::Mat& img, int target_width, int target_height, int& pad_w, int& pad_h, float& scale); std::vector postprocess(Ort::Value& output_tensor, float scale, int pad_w, int pad_h, int img_w, int img_h, float conf_threshold, float iou_threshold); -// + class YoloDetector { public: - // + Ort::Env env; std::unique_ptr session; - // + int input_width = 0; int input_height = 0; - // + Ort::AllocatorWithDefaultOptions allocator; std::string input_name_str; std::string output_name_str; @@ -43,7 +42,7 @@ public: std::vector output_node_names; public: - YoloDetector(const wchar_t* model_path, int in_width, int in_height); + YoloDetector(const char* model_path, int in_width, int in_height); std::vector detect( unsigned char* image_bytes, diff --git a/cpp/src/YoloCore.cpp b/cpp/src/YoloCore.cpp index e020b9d..34fd424 100644 --- a/cpp/src/YoloCore.cpp +++ b/cpp/src/YoloCore.cpp @@ -1,11 +1,11 @@ -#include "YoloCore.h" // -#include // -#include // -#include // +#include "YoloCore.h" +#include +#include +#include /** - * @brief - * @details + * @brief + * @details */ cv::Mat preprocess(const cv::Mat& img, int target_width, int target_height, int& pad_w, int& pad_h, float& scale) { cv::Mat resized_img; @@ -16,25 +16,25 @@ cv::Mat preprocess(const cv::Mat& img, int target_width, int target_height, int& int new_h = static_cast(h * scale); cv::resize(img, resized_img, cv::Size(new_w, new_h), 0, 0, cv::INTER_AREA); - pad_w = target_width - new_w; // - pad_h = target_height - new_h; // + pad_w = target_width - new_w; + pad_h = target_height - new_h; - // + int top = pad_h / 2; int bottom = pad_h - top; int left = pad_w / 2; int right = pad_w - left; - // + cv::Mat padded_img; - // + cv::copyMakeBorder(resized_img, padded_img, top, bottom, left, right, cv::BORDER_CONSTANT, cv::Scalar(114, 114, 114)); return padded_img; } /** - * @brief - * @details + * @brief + * @details */ std::vector postprocess(Ort::Value& output_tensor, float scale, int pad_w, int pad_h, int img_w, int img_h, float conf_threshold, float iou_threshold) { const auto output_shape = output_tensor.GetTensorTypeAndShapeInfo().GetShape(); @@ -63,7 +63,7 @@ std::vector postprocess(Ort::Value& output_tensor, float scale, int p float w = proposal[2]; float h = proposal[3]; int left = static_cast((cx - w / 2 - (pad_w / 2.0f)) / scale); - int top = static_cast((cy - h / 2 - (pad_h / 2.0f)) / scale); // + int top = static_cast((cy - h / 2 - (pad_h / 2.0f)) / scale); int width = static_cast(w / scale); int height = static_cast(h / scale); left = std::max(0, std::min(left, img_w - 1)); @@ -88,23 +88,24 @@ std::vector postprocess(Ort::Value& output_tensor, float scale, int p /** * @brief YoloDetector */ -YoloDetector::YoloDetector(const wchar_t* model_path, int in_width, int in_height) - : env(ORT_LOGGING_LEVEL_WARNING, "YOLOv8-ONNX-CPU"), // +YoloDetector::YoloDetector(const char* model_path, int in_width, int in_height) + : env(ORT_LOGGING_LEVEL_WARNING, "YOLOv8-ONNX-CPU"), input_width(in_width), input_height(in_height) { - // + Ort::SessionOptions session_options; - // - // OrtCUDAProviderOptions cuda_options; - // session_options.AppendExecutionProvider_CUDA(cuda_options); + + OrtCUDAProviderOptions cuda_options; + session_options.AppendExecutionProvider_CUDA(cuda_options); - // + + session = std::make_unique(env, model_path, session_options); - // - // + + input_name_str = session->GetInputNameAllocated(0, allocator).get(); output_name_str = session->GetOutputNameAllocated(0, allocator).get(); input_node_names.push_back(input_name_str.c_str()); @@ -121,34 +122,29 @@ std::vector YoloDetector::detect( float conf_threshold, float iou_threshold) { - // + cv::Mat image(image_height, image_width, CV_8UC3, image_bytes); if (image.empty()) { throw std::runtime_error("Input image is empty."); } - // + int pad_w, pad_h; float scale; - cv::Mat preprocessed_img = preprocess(image, input_width, input_height, pad_w, pad_h, scale); // + cv::Mat preprocessed_img = preprocess(image, input_width, input_height, pad_w, pad_h, scale); - // + cv::Mat blob; cv::dnn::blobFromImage(preprocessed_img, blob, 1 / 255.0, cv::Size(), cv::Scalar(), true, false); std::vector input_shape = { 1, 3, (int64_t)input_height, (int64_t)input_width }; - // + auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault); Ort::Value input_tensor = Ort::Value::CreateTensor(memory_info, blob.ptr(), blob.total(), input_shape.data(), input_shape.size()); - // + auto output_tensors = session->Run(Ort::RunOptions{ nullptr }, input_node_names.data(), &input_tensor, 1, output_node_names.data(), 1); - // + return postprocess(output_tensors[0], scale, pad_w, pad_h, image_width, image_height, conf_threshold, iou_threshold); -} - -// -// -// -// \ No newline at end of file +} \ No newline at end of file diff --git a/cpp/src/YoloSdk_JNI.cpp b/cpp/src/YoloSdk_JNI.cpp index ee8a01a..1bbfad9 100644 --- a/cpp/src/YoloSdk_JNI.cpp +++ b/cpp/src/YoloSdk_JNI.cpp @@ -1,56 +1,54 @@ -// -#include "com_bonus_sdk_YoloSdk.h" -#include "YoloCore.h" // +#include "com_bonus_sdk_YoloSdk.h" +#include "YoloCore.h" #include #include #include #include -// --- -// -std::wstring jstringToWString(JNIEnv* env, jstring jStr) { - if (!jStr) return L""; - const jchar* raw = env->GetStringChars(jStr, nullptr); - if (!raw) return L""; - jsize len = env->GetStringLength(jStr); - std::wstring wStr(reinterpret_cast(raw), len); - env->ReleaseStringChars(jStr, raw); - - return wStr; -} - -// -void throwJavaException(JNIEnv* env, const char* message) { +void throwJavaException(JNIEnv *env, const char *message) { env->ThrowNew(env->FindClass("java/lang/RuntimeException"), message); } -// --- /* - * Class: com_mycompany_sdk_YoloSdk + * Class: com_bonus_sdk_YoloSdk * Method: nativeInit * Signature: (Ljava/lang/String;II)J */ -JNIEXPORT jlong JNICALL Java_com_mycompany_sdk_YoloSdk_nativeInit -(JNIEnv* env, jobject thiz, jstring modelPath, jint inputWidth, jint inputHeight) { - try { - std::wstring wpath = jstringToWString(env, modelPath); - YoloDetector* detector = new YoloDetector(wpath.c_str(), inputWidth, inputHeight); - return reinterpret_cast(detector); +JNIEXPORT jlong JNICALL Java_com_bonus_sdk_YoloSdk_nativeInit + (JNIEnv *env, jobject thiz, jstring modelPath, jint inputWidth, jint inputHeight) { + + + const char* c_model_path = env->GetStringUTFChars(modelPath, nullptr); + if (c_model_path == nullptr) { + throwJavaException(env, "Failed to get model path from Java string."); + return 0; } - catch (const std::exception& e) { - std::string errMsg = "Failed to initialize C++ YoloDetector: " + std::string(e.what()); + + try { + + YoloDetector* detector = new YoloDetector(c_model_path, inputWidth, inputHeight); + + + env->ReleaseStringUTFChars(modelPath, c_model_path); + + return reinterpret_cast(detector); + } catch (const std::exception& e) { + + env->ReleaseStringUTFChars(modelPath, c_model_path); + + std::string errMsg = "Failed to initialize C++ YoloDetector: " + std::string(e.what()); throwJavaException(env, errMsg.c_str()); return 0; } } /* - * Class: com_mycompany_sdk_YoloSdk + * Class: com_bonus_sdk_YoloSdk * Method: nativeRelease * Signature: (J)V */ -JNIEXPORT void JNICALL Java_com_mycompany_sdk_YoloSdk_nativeRelease -(JNIEnv* env, jobject thiz, jlong handle) { +JNIEXPORT void JNICALL Java_com_bonus_sdk_YoloSdk_nativeRelease + (JNIEnv *env, jobject thiz, jlong handle) { YoloDetector* detector = reinterpret_cast(handle); if (detector) { delete detector; @@ -58,14 +56,14 @@ JNIEXPORT void JNICALL Java_com_mycompany_sdk_YoloSdk_nativeRelease } /* - * Class: com_mycompany_sdk_YoloSdk + * Class: com_bonus_sdk_YoloSdk * Method: nativePredict - * Signature: (J[BIIFF)[Lcom/mycompany/sdk/Detection; + * Signature: (J[BIIFF)[Lcom/bonus/sdk/Detection; */ -JNIEXPORT jobjectArray JNICALL Java_com_mycompany_sdk_YoloSdk_nativePredict -(JNIEnv* env, jobject thiz, jlong handle, jbyteArray bgrBytes, - jint imageWidth, jint imageHeight, jfloat confThreshold, jfloat iouThreshold) { - +JNIEXPORT jobjectArray JNICALL Java_com_bonus_sdk_YoloSdk_nativePredict + (JNIEnv *env, jobject thiz, jlong handle, jbyteArray bgrBytes, + jint imageWidth, jint imageHeight, jfloat confThreshold, jfloat iouThreshold) { + YoloDetector* detector = reinterpret_cast(handle); if (!detector) { throwJavaException(env, "Native handle is null."); @@ -73,39 +71,35 @@ JNIEXPORT jobjectArray JNICALL Java_com_mycompany_sdk_YoloSdk_nativePredict } try { - // 1. + jbyte* bytes = env->GetByteArrayElements(bgrBytes, nullptr); - // 2. std::vector results_cpp = detector->detect( reinterpret_cast(bytes), imageWidth, imageHeight, confThreshold, iouThreshold ); - // 3. env->ReleaseByteArrayElements(bgrBytes, bytes, JNI_ABORT); - // 4. - jclass detClass = env->FindClass("com/mycompany/sdk/Detection"); - if (!detClass) return nullptr; // - + jclass detClass = env->FindClass("com/bonus/sdk/Detection"); + if (!detClass) return nullptr; + jmethodID detConstructor = env->GetMethodID(detClass, "", "(IFFIIII)V"); - if (!detConstructor) return nullptr; // + if (!detConstructor) return nullptr; jobjectArray resultArray = env->NewObjectArray(results_cpp.size(), detClass, nullptr); for (size_t i = 0; i < results_cpp.size(); ++i) { const auto& d = results_cpp[i]; jobject javaDet = env->NewObject(detClass, detConstructor, - d.class_id, d.score, - d.x, d.y, d.width, d.height); + d.class_id, d.score, + d.x, d.y, d.width, d.height); env->SetObjectArrayElement(resultArray, i, javaDet); env->DeleteLocalRef(javaDet); } return resultArray; - } - catch (const std::exception& e) { - std::string errMsg = "Error during native prediction: " + std::string(e.what()); + } catch (const std::exception& e) { + std::string errMsg = "Error during native prediction: " + std::string(e.what()); throwJavaException(env, errMsg.c_str()); return nullptr; } diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/GIT_COMMIT_ID b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/GIT_COMMIT_ID new file mode 100644 index 0000000..e2061ee --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/GIT_COMMIT_ID @@ -0,0 +1 @@ +a83fc4d58cb48eb68890dd689f94f28288cf2278 diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/LICENSE b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/LICENSE new file mode 100644 index 0000000..48bc6bb --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) Microsoft Corporation + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/Privacy.md b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/Privacy.md new file mode 100644 index 0000000..fcc8468 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/Privacy.md @@ -0,0 +1,21 @@ +# Privacy + +## Data Collection +The software may collect information about you and your use of the software and send it to Microsoft. Microsoft may use this information to provide services and improve our products and services. You may turn off the telemetry as described in the repository. There are also some features in the software that may enable you and Microsoft to collect data from users of your applications. If you use these features, you must comply with applicable law, including providing appropriate notices to users of your applications together with a copy of Microsoft's privacy statement. Our privacy statement is located at https://go.microsoft.com/fwlink/?LinkID=824704. You can learn more about data collection and use in the help documentation and our privacy statement. Your use of the software operates as your consent to these practices. + +*** + +### Private Builds +No data collection is performed when using your private builds built from source code. + +### Official Builds +ONNX Runtime does not maintain any independent telemetry collection mechanisms outside of what is provided by the platforms it supports. However, where applicable, ONNX Runtime will take advantage of platform-supported telemetry systems to collect trace events with the goal of improving product quality. + +Currently telemetry is only implemented for Windows builds and is turned **ON** by default in the official builds distributed in their respective package management repositories ([see here](../README.md#binaries)). This may be expanded to cover other platforms in the future. Data collection is implemented via 'Platform Telemetry' per vendor platform providers (see [telemetry.h](../onnxruntime/core/platform/telemetry.h)). + +#### Technical Details +The Windows provider uses the [TraceLogging](https://docs.microsoft.com/en-us/windows/win32/tracelogging/trace-logging-about) API for its implementation. This enables ONNX Runtime trace events to be collected by the operating system, and based on user consent, this data may be periodically sent to Microsoft servers following GDPR and privacy regulations for anonymity and data access controls. + +Windows ML and onnxruntime C APIs allow Trace Logging to be turned on/off (see [API pages](../README.md#api-documentation) for details). +For information on how to enable and disable telemetry, see [C API: Telemetry](./C_API.md#telemetry). +There are equivalent APIs in the C#, Python, and Java language bindings as well. diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/README.md b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/README.md new file mode 100644 index 0000000..019bc82 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/README.md @@ -0,0 +1,49 @@ +

+ +**ONNX Runtime is a cross-platform inference and training machine-learning accelerator**. + +**ONNX Runtime inference** can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. [Learn more →](https://www.onnxruntime.ai/docs/#onnx-runtime-for-inferencing) + +**ONNX Runtime training** can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. [Learn more →](https://www.onnxruntime.ai/docs/#onnx-runtime-for-training) + +## Get Started & Resources + +* **General Information**: [onnxruntime.ai](https://onnxruntime.ai) + +* **Usage documentation and tutorials**: [onnxruntime.ai/docs](https://onnxruntime.ai/docs) + +* **YouTube video tutorials**: [youtube.com/@ONNXRuntime](https://www.youtube.com/@ONNXRuntime) + +* [**Upcoming Release Roadmap**](https://onnxruntime.ai/roadmap) + +* **Companion sample repositories**: + - ONNX Runtime Inferencing: [microsoft/onnxruntime-inference-examples](https://github.com/microsoft/onnxruntime-inference-examples) + - ONNX Runtime Training: [microsoft/onnxruntime-training-examples](https://github.com/microsoft/onnxruntime-training-examples) + +## Releases + +The current release and past releases can be found here: https://github.com/microsoft/onnxruntime/releases. + +For details on the upcoming release, including release dates, announcements, features, and guidance on submitting feature requests, please visit the release roadmap: https://onnxruntime.ai/roadmap. + +## Data/Telemetry + +Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the [privacy statement](docs/Privacy.md) for more details. + +## Contributions and Feedback + +We welcome contributions! Please see the [contribution guidelines](CONTRIBUTING.md). + +For feature requests or bug reports, please file a [GitHub Issue](https://github.com/Microsoft/onnxruntime/issues). + +For general discussion or questions, please use [GitHub Discussions](https://github.com/microsoft/onnxruntime/discussions). + +## Code of Conduct + +This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). +For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) +or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments. + +## License + +This project is licensed under the [MIT License](LICENSE). diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/ThirdPartyNotices.txt b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/ThirdPartyNotices.txt new file mode 100644 index 0000000..7b2bbdd --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/ThirdPartyNotices.txt @@ -0,0 +1,6156 @@ +THIRD PARTY SOFTWARE NOTICES AND INFORMATION + +Do Not Translate or Localize + +This software incorporates material from third parties. 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All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + * Redistributions of source code must retain the above copyright +notice, this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above +copyright notice, this list of conditions and the following disclaimer +in the documentation and/or other materials provided with the +distribution. + + * Neither the name of Google Inc. nor the names of its +contributors may be used to endorse or promote products derived from +this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +Code generated by the Protocol Buffer compiler is owned by the owner +of the input file used when generating it. This code is not +standalone and requires a support library to be linked with it. This +support library is itself covered by the above license. + +_____ + +madler/zlib + +The deflate format used by zlib was defined by Phil Katz. The deflate and +zlib specifications were written by L. Peter Deutsch. Thanks to all the +people who reported problems and suggested various improvements in zlib; they +are too numerous to cite here. + +Copyright notice: + + (C) 1995-2017 Jean-loup Gailly and Mark Adler + + This software is provided 'as-is', without any express or implied + warranty. In no event will the authors be held liable for any damages + arising from the use of this software. + + Permission is granted to anyone to use this software for any purpose, + including commercial applications, and to alter it and redistribute it + freely, subject to the following restrictions: + + 1. The origin of this software must not be misrepresented; you must not + claim that you wrote the original software. If you use this software + in a product, an acknowledgment in the product documentation would be + appreciated but is not required. + + 2. Altered source versions must be plainly marked as such, and must not be + misrepresented as being the original software. + + 3. This notice may not be removed or altered from any source distribution. + + Jean-loup Gailly Mark Adler + jloup@gzip.org madler@alumni.caltech.edu + +If you use the zlib library in a product, we would appreciate *not* receiving +lengthy legal documents to sign. The sources are provided for free but without +warranty of any kind. The library has been entirely written by Jean-loup +Gailly and Mark Adler; it does not include third-party code. + +If you redistribute modified sources, we would appreciate that you include in +the file ChangeLog history information documenting your changes. Please read +the FAQ for more information on the distribution of modified source versions. + +_____ + +pybind/pybind11 + +Copyright (c) 2016 Wenzel Jakob , All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +Please also refer to the file CONTRIBUTING.md, which clarifies licensing of +external contributions to this project including patches, pull requests, etc. + +_____ + +onnx +Open Neural Network Exchange + +Copyright (c) Facebook, Inc. and Microsoft Corporation. All rights reserved. + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +_____ + +Eigen + +MPL v2.0 +Mozilla Public License Version 2.0 + + +================================== + +1. Definitions + +-------------- + +1.1. "Contributor" + means each individual or legal entity that creates, contributes to + the creation of, or owns Covered Software. + +1.2. "Contributor Version" + means the combination of the Contributions of others (if any) used + by a Contributor and that particular Contributor's Contribution. + +1.3. "Contribution" + means Covered Software of a particular Contributor. + +1.4. "Covered Software" + means Source Code Form to which the initial Contributor has attached + the notice in Exhibit A, the Executable Form of such Source Code + Form, and Modifications of such Source Code Form, in each case + including portions thereof. + +1.5. "Incompatible With Secondary Licenses" + means + + (a) that the initial Contributor has attached the notice described + in Exhibit B to the Covered Software; or + + (b) that the Covered Software was made available under the terms of + version 1.1 or earlier of the License, but not also under the + terms of a Secondary License. + +1.6. "Executable Form" + means any form of the work other than Source Code Form. + +1.7. "Larger Work" + means a work that combines Covered Software with other material, in + a separate file or files, that is not Covered Software. + +1.8. "License" + means this document. + +1.9. "Licensable" + means having the right to grant, to the maximum extent possible, + whether at the time of the initial grant or subsequently, any and + all of the rights conveyed by this License. + +1.10. "Modifications" + means any of the following: + + (a) any file in Source Code Form that results from an addition to, + deletion from, or modification of the contents of Covered + Software; or + + (b) any new file in Source Code Form that contains any Covered + Software. + +1.11. "Patent Claims" of a Contributor + means any patent claim(s), including without limitation, method, + process, and apparatus claims, in any patent Licensable by such + Contributor that would be infringed, but for the grant of the + License, by the making, using, selling, offering for sale, having + made, import, or transfer of either its Contributions or its + Contributor Version. + +1.12. "Secondary License" + means either the GNU General Public License, Version 2.0, the GNU + Lesser General Public License, Version 2.1, the GNU Affero General + Public License, Version 3.0, or any later versions of those + licenses. + +1.13. "Source Code Form" + means the form of the work preferred for making modifications. + +1.14. "You" (or "Your") + means an individual or a legal entity exercising rights under this + License. For legal entities, "You" includes any entity that + controls, is controlled by, or is under common control with You. For + purposes of this definition, "control" means (a) the power, direct + or indirect, to cause the direction or management of such entity, + whether by contract or otherwise, or (b) ownership of more than + fifty percent (50%) of the outstanding shares or beneficial + ownership of such entity. + +2. License Grants and Conditions + +-------------------------------- + +2.1. Grants + +Each Contributor hereby grants You a world-wide, royalty-free, +non-exclusive license: + +(a) under intellectual property rights (other than patent or trademark) + Licensable by such Contributor to use, reproduce, make available, + modify, display, perform, distribute, and otherwise exploit its + Contributions, either on an unmodified basis, with Modifications, or + as part of a Larger Work; and + +(b) under Patent Claims of such Contributor to make, use, sell, offer + for sale, have made, import, and otherwise transfer either its + Contributions or its Contributor Version. + +2.2. Effective Date + +The licenses granted in Section 2.1 with respect to any Contribution +become effective for each Contribution on the date the Contributor first +distributes such Contribution. + +2.3. Limitations on Grant Scope + +The licenses granted in this Section 2 are the only rights granted under +this License. No additional rights or licenses will be implied from the +distribution or licensing of Covered Software under this License. +Notwithstanding Section 2.1(b) above, no patent license is granted by a +Contributor: + +(a) for any code that a Contributor has removed from Covered Software; + or + +(b) for infringements caused by: (i) Your and any other third party's + modifications of Covered Software, or (ii) the combination of its + Contributions with other software (except as part of its Contributor + Version); or + +(c) under Patent Claims infringed by Covered Software in the absence of + its Contributions. + +This License does not grant any rights in the trademarks, service marks, +or logos of any Contributor (except as may be necessary to comply with +the notice requirements in Section 3.4). + +2.4. Subsequent Licenses + +No Contributor makes additional grants as a result of Your choice to +distribute the Covered Software under a subsequent version of this +License (see Section 10.2) or under the terms of a Secondary License (if +permitted under the terms of Section 3.3). + +2.5. Representation + +Each Contributor represents that the Contributor believes its +Contributions are its original creation(s) or it has sufficient rights +to grant the rights to its Contributions conveyed by this License. + +2.6. Fair Use + +This License is not intended to limit any rights You have under +applicable copyright doctrines of fair use, fair dealing, or other +equivalents. + +2.7. Conditions + +Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted +in Section 2.1. + +3. Responsibilities + +------------------- + +3.1. Distribution of Source Form + +All distribution of Covered Software in Source Code Form, including any +Modifications that You create or to which You contribute, must be under +the terms of this License. You must inform recipients that the Source +Code Form of the Covered Software is governed by the terms of this +License, and how they can obtain a copy of this License. You may not +attempt to alter or restrict the recipients' rights in the Source Code +Form. + +3.2. Distribution of Executable Form + +If You distribute Covered Software in Executable Form then: + +(a) such Covered Software must also be made available in Source Code + Form, as described in Section 3.1, and You must inform recipients of + the Executable Form how they can obtain a copy of such Source Code + Form by reasonable means in a timely manner, at a charge no more + than the cost of distribution to the recipient; and + +(b) You may distribute such Executable Form under the terms of this + License, or sublicense it under different terms, provided that the + license for the Executable Form does not attempt to limit or alter + the recipients' rights in the Source Code Form under this License. + +3.3. Distribution of a Larger Work + +You may create and distribute a Larger Work under terms of Your choice, +provided that You also comply with the requirements of this License for +the Covered Software. If the Larger Work is a combination of Covered +Software with a work governed by one or more Secondary Licenses, and the +Covered Software is not Incompatible With Secondary Licenses, this +License permits You to additionally distribute such Covered Software +under the terms of such Secondary License(s), so that the recipient of +the Larger Work may, at their option, further distribute the Covered +Software under the terms of either this License or such Secondary +License(s). + +3.4. Notices + +You may not remove or alter the substance of any license notices +(including copyright notices, patent notices, disclaimers of warranty, +or limitations of liability) contained within the Source Code Form of +the Covered Software, except that You may alter any license notices to +the extent required to remedy known factual inaccuracies. + +3.5. Application of Additional Terms + +You may choose to offer, and to charge a fee for, warranty, support, +indemnity or liability obligations to one or more recipients of Covered +Software. However, You may do so only on Your own behalf, and not on +behalf of any Contributor. You must make it absolutely clear that any +such warranty, support, indemnity, or liability obligation is offered by +You alone, and You hereby agree to indemnify every Contributor for any +liability incurred by such Contributor as a result of warranty, support, +indemnity or liability terms You offer. You may include additional +disclaimers of warranty and limitations of liability specific to any +jurisdiction. + +4. Inability to Comply Due to Statute or Regulation + +--------------------------------------------------- + +If it is impossible for You to comply with any of the terms of this +License with respect to some or all of the Covered Software due to +statute, judicial order, or regulation then You must: (a) comply with +the terms of this License to the maximum extent possible; and (b) +describe the limitations and the code they affect. Such description must +be placed in a text file included with all distributions of the Covered +Software under this License. Except to the extent prohibited by statute +or regulation, such description must be sufficiently detailed for a +recipient of ordinary skill to be able to understand it. + +5. Termination + +-------------- + +5.1. The rights granted under this License will terminate automatically +if You fail to comply with any of its terms. However, if You become +compliant, then the rights granted under this License from a particular +Contributor are reinstated (a) provisionally, unless and until such +Contributor explicitly and finally terminates Your grants, and (b) on an +ongoing basis, if such Contributor fails to notify You of the +non-compliance by some reasonable means prior to 60 days after You have +come back into compliance. Moreover, Your grants from a particular +Contributor are reinstated on an ongoing basis if such Contributor +notifies You of the non-compliance by some reasonable means, this is the +first time You have received notice of non-compliance with this License +from such Contributor, and You become compliant prior to 30 days after +Your receipt of the notice. + +5.2. If You initiate litigation against any entity by asserting a patent +infringement claim (excluding declaratory judgment actions, +counter-claims, and cross-claims) alleging that a Contributor Version +directly or indirectly infringes any patent, then the rights granted to +You by any and all Contributors for the Covered Software under Section +2.1 of this License shall terminate. + +5.3. In the event of termination under Sections 5.1 or 5.2 above, all +end user license agreements (excluding distributors and resellers) which +have been validly granted by You or Your distributors under this License +prior to termination shall survive termination. + +************************************************************************ +* * +* 6. Disclaimer of Warranty * +* ------------------------- * +* * +* Covered Software is provided under this License on an "as is" * +* basis, without warranty of any kind, either expressed, implied, or * +* statutory, including, without limitation, warranties that the * +* Covered Software is free of defects, merchantable, fit for a * +* particular purpose or non-infringing. The entire risk as to the * +* quality and performance of the Covered Software is with You. * +* Should any Covered Software prove defective in any respect, You * +* (not any Contributor) assume the cost of any necessary servicing, * +* repair, or correction. This disclaimer of warranty constitutes an * +* essential part of this License. No use of any Covered Software is * +* authorized under this License except under this disclaimer. * +* * +************************************************************************ + +************************************************************************ +* * +* 7. Limitation of Liability * +* -------------------------- * +* * +* Under no circumstances and under no legal theory, whether tort * +* (including negligence), contract, or otherwise, shall any * +* Contributor, or anyone who distributes Covered Software as * +* permitted above, be liable to You for any direct, indirect, * +* special, incidental, or consequential damages of any character * +* including, without limitation, damages for lost profits, loss of * +* goodwill, work stoppage, computer failure or malfunction, or any * +* and all other commercial damages or losses, even if such party * +* shall have been informed of the possibility of such damages. This * +* limitation of liability shall not apply to liability for death or * +* personal injury resulting from such party's negligence to the * +* extent applicable law prohibits such limitation. Some * +* jurisdictions do not allow the exclusion or limitation of * +* incidental or consequential damages, so this exclusion and * +* limitation may not apply to You. * +* * +************************************************************************ +8. Litigation +------------- + +Any litigation relating to this License may be brought only in the +courts of a jurisdiction where the defendant maintains its principal +place of business and such litigation shall be governed by laws of that +jurisdiction, without reference to its conflict-of-law provisions. +Nothing in this Section shall prevent a party's ability to bring +cross-claims or counter-claims. + +9. Miscellaneous +---------------- + +This License represents the complete agreement concerning the subject +matter hereof. If any provision of this License is held to be +unenforceable, such provision shall be reformed only to the extent +necessary to make it enforceable. Any law or regulation which provides +that the language of a contract shall be construed against the drafter +shall not be used to construe this License against a Contributor. + +10. Versions of the License +--------------------------- + +10.1. New Versions + +Mozilla Foundation is the license steward. Except as provided in Section +10.3, no one other than the license steward has the right to modify or +publish new versions of this License. Each version will be given a +distinguishing version number. + +10.2. Effect of New Versions + +You may distribute the Covered Software under the terms of the version +of the License under which You originally received the Covered Software, +or under the terms of any subsequent version published by the license +steward. + +10.3. Modified Versions + +If you create software not governed by this License, and you want to +create a new license for such software, you may create and use a +modified version of this License if you rename the license and remove +any references to the name of the license steward (except to note that +such modified license differs from this License). + +10.4. Distributing Source Code Form that is Incompatible With Secondary +Licenses + +If You choose to distribute Source Code Form that is Incompatible With +Secondary Licenses under the terms of this version of the License, the +notice described in Exhibit B of this License must be attached. + +Exhibit A - Source Code Form License Notice +------------------------------------------- + + This Source Code Form is subject to the terms of the Mozilla Public + License, v. 2.0. If a copy of the MPL was not distributed with this + file, You can obtain one at http://mozilla.org/MPL/2.0/. + +If it is not possible or desirable to put the notice in a particular +file, then You may include the notice in a location (such as a LICENSE +file in a relevant directory) where a recipient would be likely to look +for such a notice. + +You may add additional accurate notices of copyright ownership. + +Exhibit B - "Incompatible With Secondary Licenses" Notice +--------------------------------------------------------- + + This Source Code Form is "Incompatible With Secondary Licenses", as + defined by the Mozilla Public License, v. 2.0. + +_____ + +intel/dnnl + +Copyright 2016-2018 Intel Corporation + +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. 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Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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IN NO EVENT +SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE +FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, +ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER +DEALINGS IN THE SOFTWARE. + + +_____ + +JDAI-CV/DNNLibrary + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [2019] [JD.com Inc. JD AI] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + + +_____ + +google/flatbuffers + + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2014 Google Inc. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + + +_____ + +google/glog + +Copyright (c) 2008, Google Inc. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + * Redistributions of source code must retain the above copyright +notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above +copyright notice, this list of conditions and the following disclaimer +in the documentation and/or other materials provided with the +distribution. + * Neither the name of Google Inc. nor the names of its +contributors may be used to endorse or promote products derived from +this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + +A function gettimeofday in utilities.cc is based on + +http://www.google.com/codesearch/p?hl=en#dR3YEbitojA/COPYING&q=GetSystemTimeAsFileTime%20license:bsd + +The license of this code is: + +Copyright (c) 2003-2008, Jouni Malinen and contributors +All Rights Reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + +3. Neither the name(s) of the above-listed copyright holder(s) nor the + names of its contributors may be used to endorse or promote products + derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +_____ + +abseil-cpp +https://github.com/abseil/abseil-cpp + + Apache License + Version 2.0, January 2004 + https://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + https://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + + +_____ + +microsoft/wil + +MIT License + +Copyright (c) Microsoft Corporation. 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In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +_____ +msgpack/msgpack-python + +Copyright (C) 2008-2011 INADA Naoki + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +_____ +lanpa/tensorboardX + +MIT License + +Copyright (c) 2017 Tzu-Wei Huang + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. 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If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2017, The TensorFlow Authors. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + + +_____ + +cerberus + +Cerberus is a lightweight and extensible data validation library for Python. + +ISC License + +Copyright (c) 2012-2016 Nicola Iarocci. + +Permission to use, copy, modify, and/or distribute this software for any +purpose with or without fee is hereby granted, provided that the above +copyright notice and this permission notice appear in all copies. + +THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH +REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND +FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, +INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM +LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR +OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR +PERFORMANCE OF THIS SOFTWARE. + +_____ + +MurmurHash3 + +MIT license + +https://github.com/aappleby/smhasher + +SMHasher is a test suite designed to test the distribution, collision, and +performance properties of non-cryptographic hash functions. +This is the home for the MurmurHash family of hash functions along with the +SMHasher test suite used to verify them. +SMHasher is released under the MIT license. +All MurmurHash versions are public domain software, and the author disclaims all copyright to their code. + +_____ + +gtest-ios-framework + +https://github.com/mestevens/gtest-ios-framework + +Copyright (c) 2013 Matthew Stevens + +Permission is hereby granted, free of charge, to any person obtaining +a copy of this software and associated documentation files (the +"Software"), to deal in the Software without restriction, including +without limitation the rights to use, copy, modify, merge, publish, +distribute, sublicense, and/or sell copies of the Software, and to +permit persons to whom the Software is furnished to do so, subject to +the following conditions: + +The above copyright notice and this permission notice shall be +included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE +LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION +OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION +WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +_____ + +DLPack + +https://github.com/dmlc/dlpack + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "{}" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2017 by Contributors + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +_____ + +emsdk + +MIT/Expat license + +https://github.com/emscripten-core/emsdk + +Copyright (c) 2018 Emscripten authors (see AUTHORS in Emscripten) + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. 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Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +_____ + +Triton Inference Server & Client, https://github.com/triton-inference-server + +Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + * Neither the name of NVIDIA CORPORATION nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY +EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR +PURPOSE ARE DISCLAIMED. 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IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +_____ + +TensorFlow.js + +https://github.com/tensorflow/tfjs + + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + +—— + +curl/curl + +https://github.com/curl + +COPYRIGHT AND PERMISSION NOTICE + +Copyright (C) Daniel Stenberg, , and many +contributors, see the THANKS file. + +All rights reserved. + +Permission to use, copy, modify, and distribute this software for any purpose +with or without fee is hereby granted, provided that the above copyright +notice and this permission notice appear in all copies. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF THIRD PARTY RIGHTS. IN +NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, +DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR +OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE +OR OTHER DEALINGS IN THE SOFTWARE. + +Except as contained in this notice, the name of a copyright holder shall not +be used in advertising or otherwise to promote the sale, use or other dealings +in this Software without prior written authorization of the copyright holder. + +_____ + +Intel neural-compressor + +https://github.com/intel/neural-compressor + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. For the purposes of this definition, + "control" means (i) the power, direct or indirect, to cause the + direction or management of such entity, whether by contract or + otherwise, or (ii) ownership of fifty percent (50%) or more of the + outstanding shares, or (iii) beneficial ownership of such entity. + + "You" (or "Your") shall mean an individual or Legal Entity + exercising permissions granted by this License. + + "Source" form shall mean the preferred form for making modifications, + including but not limited to software source code, documentation + source, and configuration files. + + "Object" form shall mean any form resulting from mechanical + transformation or translation of a Source form, including but + not limited to compiled object code, generated documentation, + and conversions to other media types. + + "Work" shall mean the work of authorship, whether in Source or + Object form, made available under the License, as indicated by a + copyright notice that is included in or attached to the work + (an example is provided in the Appendix below). + + "Derivative Works" shall mean any work, whether in Source or Object + form, that is based on (or derived from) the Work and for which the + editorial revisions, annotations, elaborations, or other modifications + represent, as a whole, an original work of authorship. For the purposes + of this License, Derivative Works shall not include works that remain + separable from, or merely link (or bind by name) to the interfaces of, + the Work and Derivative Works thereof. + + "Contribution" shall mean any work of authorship, including + the original version of the Work and any modifications or additions + to that Work or Derivative Works thereof, that is intentionally + submitted to Licensor for inclusion in the Work by the copyright owner + or by an individual or Legal Entity authorized to submit on behalf of + the copyright owner. For the purposes of this definition, "submitted" + means any form of electronic, verbal, or written communication sent + to the Licensor or its representatives, including but not limited to + communication on electronic mailing lists, source code control systems, + and issue tracking systems that are managed by, or on behalf of, the + Licensor for the purpose of discussing and improving the Work, but + excluding communication that is conspicuously marked or otherwise + designated in writing by the copyright owner as "Not a Contribution." + + "Contributor" shall mean Licensor and any individual or Legal Entity + on behalf of whom a Contribution has been received by Licensor and + subsequently incorporated within the Work. + + 2. Grant of Copyright License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + copyright license to reproduce, prepare Derivative Works of, + publicly display, publicly perform, sublicense, and distribute the + Work and such Derivative Works in Source or Object form. + + 3. Grant of Patent License. Subject to the terms and conditions of + this License, each Contributor hereby grants to You a perpetual, + worldwide, non-exclusive, no-charge, royalty-free, irrevocable + (except as stated in this section) patent license to make, have made, + use, offer to sell, sell, import, and otherwise transfer the Work, + where such license applies only to those patent claims licensable + by such Contributor that are necessarily infringed by their + Contribution(s) alone or by combination of their Contribution(s) + with the Work to which such Contribution(s) was submitted. If You + institute patent litigation against any entity (including a + cross-claim or counterclaim in a lawsuit) alleging that the Work + or a Contribution incorporated within the Work constitutes direct + or contributory patent infringement, then any patent licenses + granted to You under this License for that Work shall terminate + as of the date such litigation is filed. + + 4. Redistribution. You may reproduce and distribute copies of the + Work or Derivative Works thereof in any medium, with or without + modifications, and in Source or Object form, provided that You + meet the following conditions: + + (a) You must give any other recipients of the Work or + Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices + stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works + that You distribute, all copyright, patent, trademark, and + attribution notices from the Source form of the Work, + excluding those notices that do not pertain to any part of + the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its + distribution, then any Derivative Works that You distribute must + include a readable copy of the attribution notices contained + within such NOTICE file, excluding those notices that do not + pertain to any part of the Derivative Works, in at least one + of the following places: within a NOTICE text file distributed + as part of the Derivative Works; within the Source form or + documentation, if provided along with the Derivative Works; or, + within a display generated by the Derivative Works, if and + wherever such third-party notices normally appear. The contents + of the NOTICE file are for informational purposes only and + do not modify the License. You may add Your own attribution + notices within Derivative Works that You distribute, alongside + or as an addendum to the NOTICE text from the Work, provided + that such additional attribution notices cannot be construed + as modifying the License. + + You may add Your own copyright statement to Your modifications and + may provide additional or different license terms and conditions + for use, reproduction, or distribution of Your modifications, or + for any such Derivative Works as a whole, provided Your use, + reproduction, and distribution of the Work otherwise complies with + the conditions stated in this License. + + 5. Submission of Contributions. Unless You explicitly state otherwise, + any Contribution intentionally submitted for inclusion in the Work + by You to the Licensor shall be under the terms and conditions of + this License, without any additional terms or conditions. + Notwithstanding the above, nothing herein shall supersede or modify + the terms of any separate license agreement you may have executed + with Licensor regarding such Contributions. + + 6. Trademarks. This License does not grant permission to use the trade + names, trademarks, service marks, or product names of the Licensor, + except as required for reasonable and customary use in describing the + origin of the Work and reproducing the content of the NOTICE file. + + 7. Disclaimer of Warranty. Unless required by applicable law or + agreed to in writing, Licensor provides the Work (and each + Contributor provides its Contributions) on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or + implied, including, without limitation, any warranties or conditions + of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A + PARTICULAR PURPOSE. You are solely responsible for determining the + appropriateness of using or redistributing the Work and assume any + risks associated with Your exercise of permissions under this License. + + 8. Limitation of Liability. In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + ============================================================================ + + Copyright 2016-2019 Intel Corporation + Copyright 2018 YANDEX LLC + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. + + This distribution includes third party software ("third party programs"). + This third party software, even if included with the distribution of + the Intel software, may be governed by separate license terms, including + without limitation, third party license terms, other Intel software license + terms, and open source software license terms. These separate license terms + govern your use of the third party programs as set forth in the + "THIRD-PARTY-PROGRAMS" file. + +_____ + +FlashAttention, https://github.com/Dao-AILab/flash-attention + +BSD 3-Clause License + +Copyright (c) 2022, the respective contributors, as shown by the AUTHORS file. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +* Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +* Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +* Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +_____ + +composable_kernel + +https://github.com/ROCmSoftwarePlatform/composable_kernel + +Copyright (c) 2018- , Advanced Micro Devices, Inc. (Chao Liu, Jing Zhang) +Copyright (c) 2019- , Advanced Micro Devices, Inc. (Letao Qin, Qianfeng Zhang, Liang Huang, Shaojie Wang) +Copyright (c) 2022- , Advanced Micro Devices, Inc. (Anthony Chang, Chunyu Lai, Illia Silin, Adam Osewski, Poyen Chen, Jehandad Khan) +Copyright (c) 2019-2021, Advanced Micro Devices, Inc. (Hanwen Chang) +Copyright (c) 2019-2020, Advanced Micro Devices, Inc. (Tejash Shah) +Copyright (c) 2020 , Advanced Micro Devices, Inc. (Xiaoyan Zhou) +Copyright (c) 2021-2022, Advanced Micro Devices, Inc. (Jianfeng Yan) + +SPDX-License-Identifier: MIT +Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. + +3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. + +4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: + + (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. + + You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. + +5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. + +6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. + +7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. + +8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. + +9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. + +END OF TERMS AND CONDITIONS + +Copyright 2024-2025 Arm Limited and/or its affiliates + +Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/VERSION_NUMBER b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/VERSION_NUMBER new file mode 100644 index 0000000..14bee92 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/VERSION_NUMBER @@ -0,0 +1 @@ +1.23.2 diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/custom_op_context.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/custom_op_context.h new file mode 100644 index 0000000..b10126d --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/custom_op_context.h @@ -0,0 +1,10 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +// CustomOpContext defines an interface allowing a custom op to access ep-specific resources. +struct CustomOpContext { + CustomOpContext() = default; + virtual ~CustomOpContext() {}; +}; \ No newline at end of file diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/resource.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/resource.h new file mode 100644 index 0000000..bd123e1 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/core/providers/resource.h @@ -0,0 +1,14 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +enum ResourceOffset { + cpu_resource_offset = 0, + cuda_resource_offset = 10000, + dml_resource_offset = 20000, + rocm_resource_offset = 30000, + // offsets for other ort eps + custom_ep_resource_offset = 10000000, + // offsets for customized eps +}; \ No newline at end of file diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/cpu_provider_factory.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/cpu_provider_factory.h new file mode 100644 index 0000000..2926786 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/cpu_provider_factory.h @@ -0,0 +1,19 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "onnxruntime_c_api.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** + * \param use_arena zero: false. non-zero: true. + */ +ORT_EXPORT +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_CPU, _In_ OrtSessionOptions* options, int use_arena) +ORT_ALL_ARGS_NONNULL; + +#ifdef __cplusplus +} +#endif diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_c_api.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_c_api.h new file mode 100644 index 0000000..8561de9 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_c_api.h @@ -0,0 +1,7429 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +// See docs\c_cxx\README.md on generating the Doxygen documentation from this file + +/** \mainpage ONNX Runtime + * + * ONNX Runtime is a high-performance inference and training graph execution engine for deep learning models. + * + * ONNX Runtime's C, C++ APIs offer an easy to use interface to onboard and execute onnx models. + * - \subpage c_cpp_api "Core C, C++ APIs" + * - \subpage training_c_cpp_api "Training C, C++ APIs for on-device training" + * + * \page c_cpp_api Core C, C++ APIs + *

C

+ * + * ::OrtApi - Click here to go to the structure with all C API functions. + * + *

C++

+ * + * ::Ort - Click here to go to the namespace holding all of the C++ wrapper classes + * + * It is a set of header only wrapper classes around the C API. The goal is to turn the C style return value error codes into C++ exceptions, and to + * automate memory management through standard C++ RAII principles. + * + * \addtogroup Global + * ONNX Runtime C API + * @{ + */ + +#pragma once +#include +#include +#include +#include + +/** \brief The API version defined in this header + * + * This value is used by some API functions to behave as this version of the header expects. + */ +#define ORT_API_VERSION 23 + +#ifdef __cplusplus +extern "C" { +#endif + +//! @} +// SAL2 Definitions +#ifndef _MSC_VER +#define _In_ +#define _In_z_ +#define _In_opt_ +#define _In_opt_z_ +#define _Out_ +#define _Out_opt_ +#define _Outptr_ +#define _Outptr_opt_ +#define _Inout_ +#define _Inout_opt_ +#define _Frees_ptr_opt_ +#define _Ret_maybenull_ +#define _Ret_notnull_ +#define _Check_return_ +#define _Outptr_result_maybenull_ +#define _Outptr_result_maybenull_z_ +#define _In_reads_(X) +#define _In_reads_opt_ +#define _Inout_updates_(X) +#define _Out_writes_(X) +#define _Out_writes_opt_(X) +#define _Inout_updates_all_(X) +#define _Out_writes_bytes_all_(X) +#define _Out_writes_all_(X) +#define _Success_(X) +#define _Outptr_result_buffer_maybenull_(X) +#define ORT_ALL_ARGS_NONNULL __attribute__((nonnull)) +#else +#include +#define ORT_ALL_ARGS_NONNULL +#endif + +#ifdef _WIN32 +// Define ORT_DLL_IMPORT if your program is dynamically linked to Ort. +// dllexport is not used, we use a .def file. +#ifdef ORT_DLL_IMPORT +#define ORT_EXPORT __declspec(dllimport) +#else +#define ORT_EXPORT +#endif +#define ORT_API_CALL _stdcall +#define ORT_MUST_USE_RESULT +#define ORTCHAR_T wchar_t +#else +// To make symbols visible on macOS/iOS +#ifdef __APPLE__ +#define ORT_EXPORT __attribute__((visibility("default"))) +#else +#define ORT_EXPORT +#endif +#define ORT_API_CALL +#define ORT_MUST_USE_RESULT __attribute__((warn_unused_result)) +#define ORTCHAR_T char +#endif + +/// ORTCHAR_T, ORT_TSTR are reserved specifically for path handling. +/// All other strings are UTF-8 encoded, use char and std::string +#ifndef ORT_TSTR +#ifdef _WIN32 +#define ORT_TSTR(X) L##X +// When X is a macro, L##X is not defined. In this case, we need to use ORT_TSTR_ON_MACRO. +#define ORT_TSTR_ON_MACRO(X) L"" X +#else +#define ORT_TSTR(X) X +#define ORT_TSTR_ON_MACRO(X) X +#endif +#endif + +// On Windows, ORT_FILE is a wchar_t version of the __FILE__ macro. +// Otherwise, ORT_FILE is equivalent to __FILE__. +#ifndef ORT_FILE +#define ORT_FILE_INTERNAL(x) ORT_TSTR(x) +#define ORT_FILE ORT_FILE_INTERNAL(__FILE__) +#endif + +// Any pointer marked with _In_ or _Out_, cannot be NULL. + +// Windows users should use unicode paths when possible to bypass the MAX_PATH limitation +// Every pointer marked with _In_ or _Out_, cannot be NULL. Caller should ensure that. +// for ReleaseXXX(...) functions, they can accept NULL pointer. + +#ifdef __cplusplus +// For any compiler with C++11 support, MSVC 2015 and greater, or Clang version supporting noexcept. +// Such complex condition is needed because compilers set __cplusplus value differently. +#ifndef __has_feature +#define __has_feature(x) 0 +#endif +#if ((__cplusplus >= 201103L) || (_MSC_VER >= 1900) || (defined(__has_feature) && __has_feature(cxx_noexcept))) +#define NO_EXCEPTION noexcept +#else +#define NO_EXCEPTION throw() +#endif +#else +#define NO_EXCEPTION +#endif + +// __VA_ARGS__ on Windows and Linux are different +#define ORT_API(RETURN_TYPE, NAME, ...) RETURN_TYPE ORT_API_CALL NAME(__VA_ARGS__) NO_EXCEPTION + +#define ORT_API_T(RETURN_TYPE, NAME, ...) \ + RETURN_TYPE(ORT_API_CALL* NAME)(__VA_ARGS__) NO_EXCEPTION + +#define ORT_API_STATUS(NAME, ...) \ + _Success_(return == 0) _Check_return_ _Ret_maybenull_ OrtStatusPtr ORT_API_CALL NAME(__VA_ARGS__) \ + NO_EXCEPTION ORT_MUST_USE_RESULT + +// XXX: Unfortunately, SAL annotations are known to not work with function pointers +#define ORT_API2_STATUS(NAME, ...) \ + _Check_return_ _Ret_maybenull_ OrtStatusPtr(ORT_API_CALL* NAME)(__VA_ARGS__) NO_EXCEPTION ORT_MUST_USE_RESULT + +// Used in *.cc files. Almost as same as ORT_API_STATUS, except without ORT_MUST_USE_RESULT and ORT_EXPORT +#define ORT_API_STATUS_IMPL(NAME, ...) \ + _Success_(return == 0) _Check_return_ _Ret_maybenull_ OrtStatusPtr ORT_API_CALL NAME(__VA_ARGS__) NO_EXCEPTION + +#define ORT_CLASS_RELEASE(X) void(ORT_API_CALL * Release##X)(_Frees_ptr_opt_ Ort##X * input) + +#ifdef __DOXYGEN__ +#undef ORT_API_STATUS +#define ORT_API_STATUS(NAME, ...) OrtStatus* NAME(__VA_ARGS__) +#undef ORT_API2_STATUS +#define ORT_API2_STATUS(NAME, ...) OrtStatus* NAME(__VA_ARGS__) +#undef ORT_CLASS_RELEASE +#define ORT_CLASS_RELEASE(X) void Release##X(Ort##X* input) +#undef NO_EXCEPTION +#define NO_EXCEPTION +#endif +/** \addtogroup Global + * ONNX Runtime C API + * @{ + */ + +/** Copied from TensorProto::DataType + * Currently, Ort doesn't support complex64, complex128 + */ +typedef enum ONNXTensorElementDataType { + ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED, + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT, // maps to c type float + ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8, // maps to c type uint8_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8, // maps to c type int8_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16, // maps to c type uint16_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16, // maps to c type int16_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32, // maps to c type int32_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64, // maps to c type int64_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING, // maps to c++ type std::string + ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL, + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16, + ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE, // maps to c type double + ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32, // maps to c type uint32_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64, // maps to c type uint64_t + ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX64, // complex with float32 real and imaginary components + ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX128, // complex with float64 real and imaginary components + ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16, // Non-IEEE floating-point format based on IEEE754 single-precision + // float 8 types were introduced in onnx 1.14, see https://onnx.ai/onnx/technical/float8.html + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FN, // Non-IEEE floating-point format based on IEEE754 single-precision + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FNUZ, // Non-IEEE floating-point format based on IEEE754 single-precision + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2, // Non-IEEE floating-point format based on IEEE754 single-precision + ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2FNUZ, // Non-IEEE floating-point format based on IEEE754 single-precision + // Int4 types were introduced in ONNX 1.16. See https://onnx.ai/onnx/technical/int4.html + ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT4, // maps to a pair of packed uint4 values (size == 1 byte) + ONNX_TENSOR_ELEMENT_DATA_TYPE_INT4 // maps to a pair of packed int4 values (size == 1 byte) +} ONNXTensorElementDataType; + +// Synced with onnx TypeProto oneof +typedef enum ONNXType { + ONNX_TYPE_UNKNOWN, + ONNX_TYPE_TENSOR, + ONNX_TYPE_SEQUENCE, + ONNX_TYPE_MAP, + ONNX_TYPE_OPAQUE, + ONNX_TYPE_SPARSETENSOR, + ONNX_TYPE_OPTIONAL +} ONNXType; + +// These types are synced with internal +// SparseFormatFlags +typedef enum OrtSparseFormat { + ORT_SPARSE_UNDEFINED = 0, + ORT_SPARSE_COO = 0x1, + ORT_SPARSE_CSRC = 0x2, + ORT_SPARSE_BLOCK_SPARSE = 0x4 +} OrtSparseFormat; + +// Enum allows to query sparse tensor indices +enum OrtSparseIndicesFormat { + ORT_SPARSE_COO_INDICES, + ORT_SPARSE_CSR_INNER_INDICES, + ORT_SPARSE_CSR_OUTER_INDICES, + ORT_SPARSE_BLOCK_SPARSE_INDICES +}; + +/** \brief Logging severity levels + * + * In typical API usage, specifying a logging severity level specifies the minimum severity of log messages to show. + */ +typedef enum OrtLoggingLevel { + ORT_LOGGING_LEVEL_VERBOSE, ///< Verbose informational messages (least severe). + ORT_LOGGING_LEVEL_INFO, ///< Informational messages. + ORT_LOGGING_LEVEL_WARNING, ///< Warning messages. + ORT_LOGGING_LEVEL_ERROR, ///< Error messages. + ORT_LOGGING_LEVEL_FATAL, ///< Fatal error messages (most severe). +} OrtLoggingLevel; + +typedef enum OrtErrorCode { + ORT_OK, + ORT_FAIL, + ORT_INVALID_ARGUMENT, + ORT_NO_SUCHFILE, + ORT_NO_MODEL, + ORT_ENGINE_ERROR, + ORT_RUNTIME_EXCEPTION, + ORT_INVALID_PROTOBUF, + ORT_MODEL_LOADED, + ORT_NOT_IMPLEMENTED, + ORT_INVALID_GRAPH, + ORT_EP_FAIL, + ORT_MODEL_LOAD_CANCELED, + ORT_MODEL_REQUIRES_COMPILATION, + ORT_NOT_FOUND, +} OrtErrorCode; + +typedef enum OrtOpAttrType { + ORT_OP_ATTR_UNDEFINED = 0, + ORT_OP_ATTR_INT, + ORT_OP_ATTR_INTS, + ORT_OP_ATTR_FLOAT, + ORT_OP_ATTR_FLOATS, + ORT_OP_ATTR_STRING, + ORT_OP_ATTR_STRINGS, + ORT_OP_ATTR_GRAPH, + ORT_OP_ATTR_TENSOR, +} OrtOpAttrType; + +//! @} +#define ORT_RUNTIME_CLASS(X) \ + struct Ort##X; \ + typedef struct Ort##X Ort##X + +/** \addtogroup Global + * ONNX Runtime C API + * @{ + */ +// The actual types defined have an Ort prefix +ORT_RUNTIME_CLASS(Env); +ORT_RUNTIME_CLASS(Status); // nullptr for Status* indicates success +ORT_RUNTIME_CLASS(MemoryInfo); +ORT_RUNTIME_CLASS(IoBinding); +ORT_RUNTIME_CLASS(Session); // Don't call ReleaseSession from Dllmain (because session owns a thread pool) +ORT_RUNTIME_CLASS(Value); +ORT_RUNTIME_CLASS(RunOptions); +ORT_RUNTIME_CLASS(TypeInfo); +ORT_RUNTIME_CLASS(TensorTypeAndShapeInfo); +ORT_RUNTIME_CLASS(MapTypeInfo); +ORT_RUNTIME_CLASS(SequenceTypeInfo); +ORT_RUNTIME_CLASS(OptionalTypeInfo); +ORT_RUNTIME_CLASS(SessionOptions); +ORT_RUNTIME_CLASS(CustomOpDomain); +ORT_RUNTIME_CLASS(ModelMetadata); +ORT_RUNTIME_CLASS(ThreadPoolParams); +ORT_RUNTIME_CLASS(ThreadingOptions); +ORT_RUNTIME_CLASS(ArenaCfg); +ORT_RUNTIME_CLASS(PrepackedWeightsContainer); +ORT_RUNTIME_CLASS(TensorRTProviderOptionsV2); +ORT_RUNTIME_CLASS(NvTensorRtRtxProviderOptions); +ORT_RUNTIME_CLASS(CUDAProviderOptionsV2); +ORT_RUNTIME_CLASS(CANNProviderOptions); +ORT_RUNTIME_CLASS(DnnlProviderOptions); +ORT_RUNTIME_CLASS(Op); +ORT_RUNTIME_CLASS(OpAttr); +ORT_RUNTIME_CLASS(Logger); +ORT_RUNTIME_CLASS(ShapeInferContext); +ORT_RUNTIME_CLASS(LoraAdapter); +ORT_RUNTIME_CLASS(ValueInfo); +ORT_RUNTIME_CLASS(Node); +ORT_RUNTIME_CLASS(Graph); +ORT_RUNTIME_CLASS(Model); +ORT_RUNTIME_CLASS(ModelCompilationOptions); +ORT_RUNTIME_CLASS(HardwareDevice); +ORT_RUNTIME_CLASS(EpDevice); +ORT_RUNTIME_CLASS(KeyValuePairs); +ORT_RUNTIME_CLASS(SyncStream); // Opaque class to create an onnxruntime::Stream. +ORT_RUNTIME_CLASS(ExternalInitializerInfo); + +#ifdef _MSC_VER +typedef _Return_type_success_(return == 0) OrtStatus* OrtStatusPtr; +#else +typedef OrtStatus* OrtStatusPtr; +#endif + +/** \brief Memory allocation interface + * + * Structure of function pointers that defines a memory allocator. This can be created and filled in by the user for custom allocators. + * + * When an allocator is passed to any function, be sure that the allocator object is not destroyed until the last allocated object using it is freed. + */ +typedef struct OrtAllocator { + uint32_t version; ///< Must be initialized to ORT_API_VERSION + + /// Returns a pointer to an allocated block of `size` bytes + void*(ORT_API_CALL* Alloc)(struct OrtAllocator* this_, size_t size); + + /// Free a block of memory previously allocated with OrtAllocator::Alloc + void(ORT_API_CALL* Free)(struct OrtAllocator* this_, void* p); + + /// Return a pointer to an ::OrtMemoryInfo that describes this allocator + const struct OrtMemoryInfo*(ORT_API_CALL* Info)(const struct OrtAllocator* this_); + /** + * @brief Optional allocation function to use for memory allocations made during session initialization. + * Use this function if you want to separate allocations made by ORT during Run() calls from + * those made during session initialization. This allows for separate memory management strategies for these + * allocations. + * + * \return pointer to an allocated block of `size` bytes. nullptr if size was 0 or allocation failed. + * + * \since 1.18 + */ + void*(ORT_API_CALL* Reserve)(struct OrtAllocator* this_, size_t size); + + /** + * @brief Function used to get the statistics of the allocator. + * + * Return a pointer to the OrtKeyValuePairs structure that contains the statistics of the allocator. + * The user should call OrtApi::ReleaseKeyValuePairs when done. + * + * Current known keys are: + * - Limit: Bytes limit of the allocator. -1 if no limit is set. + * - InUse: Number of bytes in use. + * - TotalAllocated: The total number of allocated bytes by the allocator. + * - MaxInUse: The maximum bytes in use. + * - NumAllocs: Number of allocations. + * - NumReserves: Number of reserves. (Number of calls to Reserve() in arena-based allocators) + * - NumArenaExtensions: Number of arena extensions (Relevant only for arena based allocators) + * - NumArenaShrinkages: Number of arena shrinkages (Relevant only for arena based allocators) + * - MaxAllocSize: The max single allocation seen. + * + * The allocator is free to add other entries as appropriate. + * + * \note Implementation of this function is optional and GetStats may be set to a nullptr. + * If the OrtAllocator is wrapping an internal ORT allocator that does not implement GetStats + * the returned OrtKeyValuePairs instance will be empty. + * + * \since 1.23 + */ + ORT_API2_STATUS(GetStats, _In_ const struct OrtAllocator* this_, _Outptr_ OrtKeyValuePairs** out); + + /** \brief Allocate using a stream. + * + * If the allocator is stream aware this performs allocation using a stream. + * + * Alloc will be used if this is nullptr. + * + * \param[in] this_ OrtAllocator instance + * \param[in] size Size of the allocation in bytes. nullptr if size was 0 or allocation failed. + * \param[in] stream The stream to allocate on. + * + * \return pointer to an allocated block of `size` bytes + * + * \note Implementation of this function is optional and AllocOnStream may be set to a nullptr. + * \since 1.23 + */ + void*(ORT_API_CALL* AllocOnStream)(struct OrtAllocator* this_, size_t size, OrtSyncStream* stream); +} OrtAllocator; + +typedef void(ORT_API_CALL* OrtLoggingFunction)( + void* param, OrtLoggingLevel severity, const char* category, const char* logid, const char* code_location, + const char* message); + +/** \brief Graph optimization level + * + * Refer to https://www.onnxruntime.ai/docs/performance/graph-optimizations.html#graph-optimization-levels + * for an in-depth understanding of the Graph Optimization Levels. + */ +typedef enum GraphOptimizationLevel { + ORT_DISABLE_ALL = 0, + ORT_ENABLE_BASIC = 1, + ORT_ENABLE_EXTENDED = 2, + ORT_ENABLE_LAYOUT = 3, + ORT_ENABLE_ALL = 99 +} GraphOptimizationLevel; + +typedef enum ExecutionMode { + ORT_SEQUENTIAL = 0, + ORT_PARALLEL = 1, +} ExecutionMode; + +/** \brief Language projection identifiers + * /see OrtApi::SetLanguageProjection + */ +typedef enum OrtLanguageProjection { + ORT_PROJECTION_C = 0, + ORT_PROJECTION_CPLUSPLUS = 1, + ORT_PROJECTION_CSHARP = 2, + ORT_PROJECTION_PYTHON = 3, + ORT_PROJECTION_JAVA = 4, + ORT_PROJECTION_WINML = 5, + ORT_PROJECTION_NODEJS = 6, +} OrtLanguageProjection; + +struct OrtKernelInfo; +typedef struct OrtKernelInfo OrtKernelInfo; +struct OrtKernelContext; +typedef struct OrtKernelContext OrtKernelContext; +struct OrtCustomOp; +typedef struct OrtCustomOp OrtCustomOp; + +typedef enum OrtAllocatorType { + OrtInvalidAllocator = -1, + OrtDeviceAllocator = 0, + OrtArenaAllocator = 1, + OrtReadOnlyAllocator = 2, +} OrtAllocatorType; + +/** \brief Memory types for allocated memory, execution provider specific types should be extended in each provider. + */ +// Whenever this struct is updated, please also update the MakeKey function in onnxruntime / core / framework / execution_provider.cc +typedef enum OrtMemType { + /// Any CPU memory used by non-CPU execution provider + OrtMemTypeCPUInput = -2, + /// CPU accessible memory outputted by non-CPU execution provider, i.e. HOST_ACCESSIBLE + OrtMemTypeCPUOutput = -1, + /// CPU accessible memory allocated by non-CPU execution provider, i.e. HOST_ACCESSIBLE + OrtMemTypeCPU = OrtMemTypeCPUOutput, + /// The default allocator for execution provider + OrtMemTypeDefault = 0, +} OrtMemType; + +/** \brief This matches OrtDevice::MemoryType values */ +typedef enum OrtDeviceMemoryType { + OrtDeviceMemoryType_DEFAULT = 0, ///< Device memory + OrtDeviceMemoryType_HOST_ACCESSIBLE = 5, ///< Shared/pinned memory for transferring between CPU and the device +} OrtDeviceMemoryType; + +/** \brief This mimics OrtDevice type constants so they can be returned in the API + */ +typedef enum OrtMemoryInfoDeviceType { + OrtMemoryInfoDeviceType_CPU = 0, + OrtMemoryInfoDeviceType_GPU = 1, + OrtMemoryInfoDeviceType_FPGA = 2, + OrtMemoryInfoDeviceType_NPU = 3, +} OrtMemoryInfoDeviceType; + +typedef enum OrtHardwareDeviceType { + OrtHardwareDeviceType_CPU, + OrtHardwareDeviceType_GPU, + OrtHardwareDeviceType_NPU +} OrtHardwareDeviceType; + +/** \brief These are the default EP selection policies used by ORT when doing automatic EP selection. + */ +typedef enum OrtExecutionProviderDevicePolicy { + OrtExecutionProviderDevicePolicy_DEFAULT, + OrtExecutionProviderDevicePolicy_PREFER_CPU, + OrtExecutionProviderDevicePolicy_PREFER_NPU, + OrtExecutionProviderDevicePolicy_PREFER_GPU, + OrtExecutionProviderDevicePolicy_MAX_PERFORMANCE, + OrtExecutionProviderDevicePolicy_MAX_EFFICIENCY, + OrtExecutionProviderDevicePolicy_MIN_OVERALL_POWER, +} OrtExecutionProviderDevicePolicy; + +/** \brief Delegate to allow providing custom OrtEpDevice selection logic + * + * This delegate is called by the EP selection code to allow the user to provide custom device selection logic. + * The user can use this to select OrtEpDevice instances from the list of available devices. + * + * \param ep_devices The list of available devices. + * \param num_devices The number of available devices. + * \param model_metadata The model metadata. + * \param runtime_metadata The runtime metadata. May be nullptr. + * \param selected Pre-allocated array to populate with selected OrtEpDevice pointers from ep_devices. + * \param max_selected The maximum number of devices that can be selected in the pre-allocated array. + Currently the maximum is 8. + * \param num_selected The number of selected devices. + * \param state Opaque pointer. Required to use the delegate from other languages like C# and python. + * + * \return OrtStatus* Selection status. Return nullptr on success. + * Use CreateStatus to provide error info. Use ORT_FAIL as the error code. + * ORT will release the OrtStatus* if not null. + */ +typedef OrtStatus*(ORT_API_CALL* EpSelectionDelegate)(_In_ const OrtEpDevice** ep_devices, + _In_ size_t num_devices, + _In_ const OrtKeyValuePairs* model_metadata, + _In_opt_ const OrtKeyValuePairs* runtime_metadata, + _Inout_ const OrtEpDevice** selected, + _In_ size_t max_selected, + _Out_ size_t* num_selected, + _In_ void* state); + +/** \brief Function called by ORT to write a buffer to a custom destination (e.g., file, stream, etc.). + * + * \param state Opaque pointer holding the user's state. + * \param buffer The buffer to write. + * \param buffer_num_bytes The size of the buffer in bytes. + * + * \return OrtStatus* Write status. Return nullptr on success. + * Use CreateStatus to provide error info. Use ORT_FAIL as the error code. + * ORT will release the OrtStatus* if not null. + */ +typedef OrtStatus*(ORT_API_CALL* OrtWriteBufferFunc)(_In_ void* state, + _In_ const void* buffer, + _In_ size_t buffer_num_bytes); + +/** \brief Function called by ORT to allow user to specify how an initializer should be saved, that is, either + * written to an external file or stored within the model. ORT calls this function for every initializer when + * generating a model. + * + * If the function implementation sets the `new_external_info` output parameter to NULL, ORT stores the initializer data + * within the generated model. + * + * Otherwise, if the function implementation sets `new_external_info` to a valid OrtExternalInitializerInfo instance, + * ORT assumes that this function stores the initializer data in a file. In this case, ORT configures the model's + * initializer to point to the location specified by the `new_external_info` output parameter. + * + * \param[in] state Opaque pointer holding the user's state. + * \param[in] initializer_name The initializer's name as a null-terminated string. + * \param[in] initializer_value OrtValue containing the initializer's data, type, and shape. + * \param[in] external_info If the initializer is originally stored in an external file, `external_info` contains + * the file path, file offset, and the data's byte size within the file. Otherwise, + * `external_info` is NULL if the initializer is not originally stored in a file. + * \param[out] new_external_info Output parameter set to a new OrtExternalInitializerInfo instance indicating the + * location where the function implementation stored the initializer data. + * The function implementation must use `OrtApi::CreateExternalInitializerInfo()` to + * create the instance. + * If the function implementation sets `new_external_info` to NULL, + * ORT stores the initializers within the model. + * + * \note ORT takes ownership of the `new_external_info` output parameter. + * + * \return OrtStatus* Write status. Return nullptr on success. + * Use CreateStatus to provide error info. Use ORT_FAIL as the error code. + * ORT will release the OrtStatus* if not null. + */ +typedef OrtStatus*(ORT_API_CALL* OrtGetInitializerLocationFunc)( + _In_ void* state, + _In_ const char* initializer_name, + _In_ const OrtValue* initializer_value, + _In_opt_ const OrtExternalInitializerInfo* external_info, + _Outptr_result_maybenull_ OrtExternalInitializerInfo** new_external_info); + +/** \brief Algorithm to use for cuDNN Convolution Op + */ +typedef enum OrtCudnnConvAlgoSearch { + OrtCudnnConvAlgoSearchExhaustive, // expensive exhaustive benchmarking using cudnnFindConvolutionForwardAlgorithmEx + OrtCudnnConvAlgoSearchHeuristic, // lightweight heuristic based search using cudnnGetConvolutionForwardAlgorithm_v7 + OrtCudnnConvAlgoSearchDefault, // default algorithm using CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM +} OrtCudnnConvAlgoSearch; + +/** \brief CUDA Provider Options + * + * \see OrtApi::SessionOptionsAppendExecutionProvider_CUDA + */ +typedef struct OrtCUDAProviderOptions { +#ifdef __cplusplus + OrtCUDAProviderOptions() + : device_id{}, + cudnn_conv_algo_search{OrtCudnnConvAlgoSearchExhaustive}, + gpu_mem_limit{SIZE_MAX}, + arena_extend_strategy{}, + do_copy_in_default_stream{1}, + has_user_compute_stream{}, + user_compute_stream{}, + default_memory_arena_cfg{}, + tunable_op_enable{false}, + tunable_op_tuning_enable{false}, + tunable_op_max_tuning_duration_ms{} {} +#endif + + /** \brief CUDA device Id + * Defaults to 0. + */ + int device_id; + + /** \brief CUDA Convolution algorithm search configuration. + * See enum OrtCudnnConvAlgoSearch for more details. + * Defaults to OrtCudnnConvAlgoSearchExhaustive. + */ + OrtCudnnConvAlgoSearch cudnn_conv_algo_search; + + /** \brief CUDA memory limit (To use all possible memory pass in maximum size_t) + * Defaults to SIZE_MAX. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + size_t gpu_mem_limit; + + /** \brief Strategy used to grow the memory arena + * 0 = kNextPowerOfTwo
+ * 1 = kSameAsRequested
+ * Defaults to 0. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + int arena_extend_strategy; + + /** \brief Flag indicating if copying needs to take place on the same stream as the compute stream in the CUDA EP + * 0 = Use separate streams for copying and compute. + * 1 = Use the same stream for copying and compute. + * Defaults to 1. + * WARNING: Setting this to 0 may result in data races for some models. + * Please see issue #4829 for more details. + */ + int do_copy_in_default_stream; + + /** \brief Flag indicating if there is a user provided compute stream + * Defaults to 0. + */ + int has_user_compute_stream; + + /** \brief User provided compute stream. + * If provided, please set `has_user_compute_stream` to 1. + */ + void* user_compute_stream; + + /** \brief CUDA memory arena configuration parameters + */ + OrtArenaCfg* default_memory_arena_cfg; + + /** \brief Enable TunableOp for using. + * Set it to 1/0 to enable/disable TunableOp. Otherwise, it is disabled by default. + * This option can be overridden by environment variable ORT_CUDA_TUNABLE_OP_ENABLE. + */ + int tunable_op_enable; + + /** \brief Enable TunableOp for tuning. + * Set it to 1/0 to enable/disable TunableOp tuning. Otherwise, it is disabled by default. + * This option can be overridden by environment variable ORT_CUDA_TUNABLE_OP_TUNING_ENABLE. + */ + int tunable_op_tuning_enable; + + /** \brief Max tuning duration time limit for each instance of TunableOp. + * Defaults to 0 to disable the limit. + */ + int tunable_op_max_tuning_duration_ms; + +} OrtCUDAProviderOptions; + +/** \brief ROCM Provider Options + * + * \see OrtApi::SessionOptionsAppendExecutionProvider_ROCM + */ +typedef struct OrtROCMProviderOptions { +#ifdef __cplusplus + OrtROCMProviderOptions() + : device_id{}, + miopen_conv_exhaustive_search{0}, + gpu_mem_limit{SIZE_MAX}, + arena_extend_strategy{}, + do_copy_in_default_stream{1}, + has_user_compute_stream{}, + user_compute_stream{}, + default_memory_arena_cfg{}, + enable_hip_graph{false}, + tunable_op_enable{false}, + tunable_op_tuning_enable{false}, + tunable_op_max_tuning_duration_ms{} {} +#endif + + /** \brief ROCM device Id + * Defaults to 0. + */ + int device_id; + + /** \brief ROCM MIOpen Convolution algorithm exhaustive search option. + * Defaults to 0 (false). + */ + int miopen_conv_exhaustive_search; + + /** \brief ROCM memory limit (To use all possible memory pass in maximum size_t) + * Defaults to SIZE_MAX. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + size_t gpu_mem_limit; + + /** \brief Strategy used to grow the memory arena + * 0 = kNextPowerOfTwo
+ * 1 = kSameAsRequested
+ * Defaults to 0. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + int arena_extend_strategy; + + /** \brief Flag indicating if copying needs to take place on the same stream as the compute stream in the ROCM EP + * 0 = Use separate streams for copying and compute. + * 1 = Use the same stream for copying and compute. + * Defaults to 1. + * WARNING: Setting this to 0 may result in data races for some models. + * Please see issue #4829 for more details. + */ + int do_copy_in_default_stream; + + /** \brief Flag indicating if there is a user provided compute stream + * Defaults to 0. + */ + int has_user_compute_stream; + + /** \brief User provided compute stream. + * If provided, please set `has_user_compute_stream` to 1. + */ + void* user_compute_stream; + + /** \brief ROCM memory arena configuration parameters + */ + OrtArenaCfg* default_memory_arena_cfg; + + int enable_hip_graph; + + /** \brief Enable TunableOp for using. + * Set it to 1/0 to enable/disable TunableOp. Otherwise, it is disabled by default. + * This option can be overridden by environment variable ORT_ROCM_TUNABLE_OP_ENABLE. + */ + int tunable_op_enable; + + /** \brief Enable TunableOp for tuning. + * Set it to 1/0 to enable/disable TunableOp tuning. Otherwise, it is disabled by default. + * This option can be overridden by environment variable ORT_ROCM_TUNABLE_OP_TUNING_ENABLE. + */ + int tunable_op_tuning_enable; + + /** \brief Max tuning duration time limit for each instance of TunableOp. + * Defaults to 0 to disable the limit. + */ + int tunable_op_max_tuning_duration_ms; + +} OrtROCMProviderOptions; + +/** \brief TensorRT Provider Options + * + * \see OrtApi::SessionOptionsAppendExecutionProvider_TensorRT + */ +typedef struct OrtTensorRTProviderOptions { + int device_id; ///< CUDA device id (0 = default device) + int has_user_compute_stream; // indicator of user specified CUDA compute stream. + void* user_compute_stream; // user specified CUDA compute stream. + int trt_max_partition_iterations; // maximum iterations for TensorRT parser to get capability + int trt_min_subgraph_size; // minimum size of TensorRT subgraphs + size_t trt_max_workspace_size; // maximum workspace size for TensorRT. + int trt_fp16_enable; // enable TensorRT FP16 precision. Default 0 = false, nonzero = true + int trt_int8_enable; // enable TensorRT INT8 precision. Default 0 = false, nonzero = true + const char* trt_int8_calibration_table_name; // TensorRT INT8 calibration table name. + int trt_int8_use_native_calibration_table; // use native TensorRT generated calibration table. Default 0 = false, nonzero = true + int trt_dla_enable; // enable DLA. Default 0 = false, nonzero = true + int trt_dla_core; // DLA core number. Default 0 + int trt_dump_subgraphs; // dump TRT subgraph. Default 0 = false, nonzero = true + int trt_engine_cache_enable; // enable engine caching. Default 0 = false, nonzero = true + const char* trt_engine_cache_path; // specify engine cache path + int trt_engine_decryption_enable; // enable engine decryption. Default 0 = false, nonzero = true + const char* trt_engine_decryption_lib_path; // specify engine decryption library path + int trt_force_sequential_engine_build; // force building TensorRT engine sequentially. Default 0 = false, nonzero = true + // This is the legacy struct and don't add new fields here. + // For new field that can be represented by string, please add it in include/onnxruntime/core/providers/tensorrt/tensorrt_provider_options.h + // For non-string field, need to create a new separate api to handle it. +} OrtTensorRTProviderOptions; + +/** \brief MIGraphX Provider Options + * + * \see OrtApi::SessionOptionsAppendExecutionProvider_MIGraphX + */ +typedef struct OrtMIGraphXProviderOptions { + int device_id; // hip device id. + int migraphx_fp16_enable; // MIGraphX FP16 precision. Default 0 = false, nonzero = true + int migraphx_fp8_enable; // MIGraphX FP8 precision. Default 0 = false, nonzero = true + int migraphx_int8_enable; // MIGraphX INT8 precision. Default 0 = false, nonzero = true + int migraphx_use_native_calibration_table; // MIGraphx INT8 cal table. Default 0 = false, nonzero = true + const char* migraphx_int8_calibration_table_name; // MIGraphx INT8 calibration table name + int migraphx_save_compiled_model; // migraphx save compiled model. Default 0 = false, nonzero = true + const char* migraphx_save_model_path; // migraphx model path name + int migraphx_load_compiled_model; // migraphx int8 cal table. Default 0 = false, nonzero = true + const char* migraphx_load_model_path; // migraphx model path name + bool migraphx_exhaustive_tune; // MIGraphX tuned compile. Default = false, nonzero = true + + /** \brief MIGraphX memory limit (To use all possible memory pass in maximum size_t) + * Defaults to SIZE_MAX. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + size_t migraphx_mem_limit; + + /** \brief Strategy used to grow the memory arena + * 0 = kNextPowerOfTwo
+ * 1 = kSameAsRequested
+ * Defaults to 0. + * \note If a ::OrtArenaCfg has been applied, it will override this field + */ + int migraphx_arena_extend_strategy; + + // This is the legacy struct and don't add new fields here. +} OrtMIGraphXProviderOptions; + +/** \brief OpenVINO Provider Options + * \brief This Struct is frozen since ORT 1.13.0. Its maintained part of Legacy API for compatibility. + * \brief For latest OpenVINO Provider Options update to the ProviderOptions map. + * \brief Latest OpenVINO Provider Options are listed in the + * \htmlonly + * onnxruntime document. + * \endhtmlonly + * \see OrtApi::SessionOptionsAppendExecutionProvider() + */ +typedef struct OrtOpenVINOProviderOptions { +#ifdef __cplusplus + OrtOpenVINOProviderOptions() : device_type{}, + enable_npu_fast_compile{}, + device_id{}, + num_of_threads{}, + cache_dir{}, + context{}, + enable_opencl_throttling{}, + enable_dynamic_shapes{} {} +#endif + /** \brief Device type string + * + * Valid settings are one of: "CPU_FP32", "CPU_FP16", "GPU_FP32", "GPU_FP16" + */ + const char* device_type; + unsigned char enable_npu_fast_compile; ///< 0 = disabled, nonzero = enabled + const char* device_id; + size_t num_of_threads; ///< 0 = Use default number of threads + const char* cache_dir; // path is set to empty by default + void* context; + unsigned char enable_opencl_throttling; ///< 0 = disabled, nonzero = enabled + unsigned char enable_dynamic_shapes; ///< 0 = disabled, nonzero = enabled +} OrtOpenVINOProviderOptions; + +struct OrtApi; +typedef struct OrtApi OrtApi; + +struct OrtTrainingApi; +typedef struct OrtTrainingApi OrtTrainingApi; + +struct OrtModelEditorApi; +typedef struct OrtModelEditorApi OrtModelEditorApi; + +struct OrtCompileApi; +typedef struct OrtCompileApi OrtCompileApi; + +struct OrtEpApi; +typedef struct OrtEpApi OrtEpApi; + +/** \brief The helper interface to get the right version of OrtApi + * + * Get a pointer to this structure through ::OrtGetApiBase + */ +struct OrtApiBase { + /** \brief Get a pointer to the requested version of the ::OrtApi + * + * \param[in] version Must be ::ORT_API_VERSION + * \return The ::OrtApi for the version requested, nullptr will be returned if this version is unsupported, for example when using a runtime + * older than the version created with this header file. + * + * One can call GetVersionString() to get the version of the Onnxruntime library for logging + * and error reporting purposes. + */ + const OrtApi*(ORT_API_CALL* GetApi)(uint32_t version)NO_EXCEPTION; + + /** \brief Returns a null terminated string of the version of the Onnxruntime library (eg: "1.8.1") + * + * \return UTF-8 encoded version string. Do not deallocate the returned buffer. + */ + const char*(ORT_API_CALL* GetVersionString)(void)NO_EXCEPTION; +}; + +typedef struct OrtApiBase OrtApiBase; + +/** \brief The Onnxruntime library's entry point to access the C API + * + * Call this to get the a pointer to an ::OrtApiBase + */ +ORT_EXPORT const OrtApiBase* ORT_API_CALL OrtGetApiBase(void) NO_EXCEPTION; + +/** \brief Thread work loop function + * + * Onnxruntime will provide the working loop on custom thread creation + * Argument is an onnxruntime built-in type which will be provided when thread pool calls OrtCustomCreateThreadFn + */ +typedef void (*OrtThreadWorkerFn)(void* ort_worker_fn_param); + +typedef const struct OrtCustomHandleType { + char __place_holder; +}* OrtCustomThreadHandle; + +/** \brief Ort custom thread creation function + * + * The function should return a thread handle to be used in onnxruntime thread pools + * Onnxruntime will throw exception on return value of nullptr or 0, indicating that the function failed to create a thread + */ +typedef OrtCustomThreadHandle (*OrtCustomCreateThreadFn)(void* ort_custom_thread_creation_options, OrtThreadWorkerFn ort_thread_worker_fn, void* ort_worker_fn_param); + +/** \brief Custom thread join function + * + * Onnxruntime thread pool destructor will call the function to join a custom thread. + * Argument ort_custom_thread_handle is the value returned by OrtCustomCreateThreadFn + */ +typedef void (*OrtCustomJoinThreadFn)(OrtCustomThreadHandle ort_custom_thread_handle); + +typedef OrtStatus*(ORT_API_CALL* RegisterCustomOpsFn)(OrtSessionOptions* options, const OrtApiBase* api); + +/** \brief Callback function for RunAsync + * + * \param[in] user_data User specific data that passed back to the callback + * \param[out] outputs On succeed, outputs host inference results, on error, the value will be nullptr + * \param[out] num_outputs Number of outputs, on error, the value will be zero + * \param[out] status On error, status will provide details + */ +typedef void (*RunAsyncCallbackFn)(void* user_data, OrtValue** outputs, size_t num_outputs, OrtStatusPtr status); + +/** \brief The C API + * + * All C API functions are defined inside this structure as pointers to functions. + * Call OrtApiBase::GetApi to get a pointer to it + * + * \nosubgrouping + */ +/* + * Public enum for compiled model compatibility across EPs. + */ +typedef enum OrtCompiledModelCompatibility { + OrtCompiledModelCompatibility_EP_NOT_APPLICABLE = 0, + OrtCompiledModelCompatibility_EP_SUPPORTED_OPTIMAL, + OrtCompiledModelCompatibility_EP_SUPPORTED_PREFER_RECOMPILATION, + OrtCompiledModelCompatibility_EP_UNSUPPORTED, +} OrtCompiledModelCompatibility; + +struct OrtApi { + /// \name OrtStatus + /// @{ + + /** + * \brief Create an OrtStatus from a null terminated string + * + * \param[in] code + * \param[in] msg A null-terminated string. Its contents will be copied. + * \return A new OrtStatus object, must be destroyed with OrtApi::ReleaseStatus + */ + OrtStatus*(ORT_API_CALL* CreateStatus)(OrtErrorCode code, _In_ const char* msg)NO_EXCEPTION ORT_ALL_ARGS_NONNULL; + + /** \brief Get OrtErrorCode from OrtStatus + * + * \param[in] status + * \return OrtErrorCode that \p status was created with + */ + OrtErrorCode(ORT_API_CALL* GetErrorCode)(_In_ const OrtStatus* status) NO_EXCEPTION ORT_ALL_ARGS_NONNULL; + + /** \brief Get error string from OrtStatus + * + * \param[in] status + * \return The error message inside the `status`. Do not free the returned value. + */ + const char*(ORT_API_CALL* GetErrorMessage)(_In_ const OrtStatus* status)NO_EXCEPTION ORT_ALL_ARGS_NONNULL; + + /// @} + /// \name OrtEnv + /// @{ + + /** \brief Create an OrtEnv + * + * \note Invoking this function will return the same instance of the environment as that returned by a previous call + * to another env creation function; all arguments to this function will be ignored. + * \param[in] log_severity_level The log severity level. + * \param[in] logid The log identifier. + * \param[out] out Returned newly created OrtEnv. Must be freed with OrtApi::ReleaseEnv + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateEnv, OrtLoggingLevel log_severity_level, _In_ const char* logid, _Outptr_ OrtEnv** out); + + /** \brief Create an OrtEnv + * + * \note Invoking this function will return the same instance of the environment as that returned by a previous call + * to another env creation function; all arguments to this function will be ignored. If you want to provide your + * own logging function, consider setting it using the SetUserLoggingFunction API instead. + * \param[in] logging_function A pointer to a logging function. + * \param[in] logger_param A pointer to arbitrary data passed as the ::OrtLoggingFunction `param` parameter to + * `logging_function`. This parameter is optional. + * \param[in] log_severity_level The log severity level. + * \param[in] logid The log identifier. + * \param[out] out Returned newly created OrtEnv. Must be freed with OrtApi::ReleaseEnv + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateEnvWithCustomLogger, _In_ OrtLoggingFunction logging_function, _In_opt_ void* logger_param, + _In_ OrtLoggingLevel log_severity_level, _In_ const char* logid, _Outptr_ OrtEnv** out); + + /** \brief Enable Telemetry + * + * \note Telemetry events are on by default since they are lightweight + * \param[in] env + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(EnableTelemetryEvents, _In_ const OrtEnv* env); + /** \brief Disable Telemetry + * + * \see OrtApi::EnableTelemetryEvents + * \param[in] env + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(DisableTelemetryEvents, _In_ const OrtEnv* env); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief Create an OrtSession from a model file + * + * \param[in] env + * \param[in] model_path + * \param[in] options + * \param[out] out Returned newly created OrtSession. Must be freed with OrtApi::ReleaseSession + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + // TODO: document the path separator convention? '/' vs '\' + // TODO: should specify the access characteristics of model_path. Is this read only during the + // execution of CreateSession, or does the OrtSession retain a handle to the file/directory + // and continue to access throughout the OrtSession lifetime? + // What sort of access is needed to model_path : read or read/write? + ORT_API2_STATUS(CreateSession, _In_ const OrtEnv* env, _In_ const ORTCHAR_T* model_path, + _In_ const OrtSessionOptions* options, _Outptr_ OrtSession** out); + + /** \brief Create an OrtSession from memory + * + * \param[in] env + * \param[in] model_data + * \param[in] model_data_length + * \param[in] options + * \param[out] out Returned newly created OrtSession. Must be freed with OrtApi::ReleaseSession + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSessionFromArray, _In_ const OrtEnv* env, + _In_ const void* model_data, size_t model_data_length, + _In_ const OrtSessionOptions* options, _Outptr_ OrtSession** out); + + /** \brief Run the model in an ::OrtSession + * + * Will not return until the model run has completed. Multiple threads might be used to run the model based on + * the options in the ::OrtSession and settings used when creating the ::OrtEnv + * + * \param[in] session + * \param[in] run_options If nullptr, will use a default ::OrtRunOptions + * \param[in] input_names Array of null terminated UTF8 encoded strings of the input names + * \param[in] inputs Array of ::OrtValue%s of the input values + * \param[in] input_len Number of elements in the input_names and inputs arrays + * \param[in] output_names Array of null terminated UTF8 encoded strings of the output names + * \param[in] output_names_len Number of elements in the output_names and outputs array + * \param[out] outputs Array of ::OrtValue%s that the outputs are stored in. This can also be + * an array of nullptr values, in this case ::OrtValue objects will be allocated and pointers + * to them will be set into the `outputs` array. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(Run, _Inout_ OrtSession* session, _In_opt_ const OrtRunOptions* run_options, + _In_reads_(input_len) const char* const* input_names, + _In_reads_(input_len) const OrtValue* const* inputs, size_t input_len, + _In_reads_(output_names_len) const char* const* output_names, size_t output_names_len, + _Inout_updates_all_(output_names_len) OrtValue** outputs); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Create an ::OrtSessionOptions object + * + * To use additional providers, you must build ORT with the extra providers enabled. Then call one of these + * functions to enable them in the session:
+ * OrtSessionOptionsAppendExecutionProvider_CPU
+ * OrtSessionOptionsAppendExecutionProvider_CUDA
+ * OrtSessionOptionsAppendExecutionProvider_(remaining providers...)
+ * The order they are called indicates the preference order as well. In other words call this method + * on your most preferred execution provider first followed by the less preferred ones. + * If none are called Ort will use its internal CPU execution provider. + * + * \param[out] options The newly created OrtSessionOptions. Must be freed with OrtApi::ReleaseSessionOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSessionOptions, _Outptr_ OrtSessionOptions** options); + + /** \brief Set filepath to save optimized model after graph level transformations + * + * \param[in] options + * \param[in] optimized_model_filepath + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetOptimizedModelFilePath, _Inout_ OrtSessionOptions* options, + _In_ const ORTCHAR_T* optimized_model_filepath); + + /** \brief Create a copy of an existing ::OrtSessionOptions + * + * \param[in] in_options OrtSessionOptions to copy + * \param[out] out_options Returned newly created ::OrtSessionOptions. Must be freed with OrtApi::ReleaseSessionOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CloneSessionOptions, _In_ const OrtSessionOptions* in_options, + _Outptr_ OrtSessionOptions** out_options); + + /** \brief Set execution mode + * + * Controls whether you want to execute operators in your graph sequentially or in parallel. Usually when the model + * has many branches, setting this option to ExecutionMode.ORT_PARALLEL will give you better performance. + * See [docs/ONNX_Runtime_Perf_Tuning.md] for more details. + * + * \param[in] options + * \param[in] execution_mode + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetSessionExecutionMode, _Inout_ OrtSessionOptions* options, ExecutionMode execution_mode); + + /** \brief Enable profiling for a session + * + * \param[in] options + * \param[in] profile_file_prefix + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(EnableProfiling, _Inout_ OrtSessionOptions* options, _In_ const ORTCHAR_T* profile_file_prefix); + + /** \brief Disable profiling for a session + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(DisableProfiling, _Inout_ OrtSessionOptions* options); + + /** \brief Enable the memory pattern optimization + * + * The idea is if the input shapes are the same, we could trace the internal memory allocation + * and generate a memory pattern for future request. So next time we could just do one allocation + * with a big chunk for all the internal memory allocation. + * \note Memory pattern optimization is only available when Sequential Execution mode is enabled (see OrtApi::SetSessionExecutionMode) + * + * \see OrtApi::DisableMemPattern + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(EnableMemPattern, _Inout_ OrtSessionOptions* options); + + /** \brief Disable the memory pattern optimization + * + * \see OrtApi::EnableMemPattern + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(DisableMemPattern, _Inout_ OrtSessionOptions* options); + + /** \brief Enable the memory arena on CPU + * + * Arena may pre-allocate memory for future usage. + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(EnableCpuMemArena, _Inout_ OrtSessionOptions* options); + + /** \brief Disable the memory arena on CPU + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(DisableCpuMemArena, _Inout_ OrtSessionOptions* options); + + /** \brief Set session log id + * + * \param[in] options + * \param[in] logid The log identifier. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetSessionLogId, _Inout_ OrtSessionOptions* options, const char* logid); + + /** \brief Set session log verbosity level + * + * Applies to session load, initialization, etc + * + * \param[in] options + * \param[in] session_log_verbosity_level \snippet{doc} snippets.dox Log Verbosity Level + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetSessionLogVerbosityLevel, _Inout_ OrtSessionOptions* options, int session_log_verbosity_level); + + /** \brief Set session log severity level + * + * \param[in] options + * \param[in] session_log_severity_level The log severity level (refer to ::OrtLoggingLevel for possible values). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetSessionLogSeverityLevel, _Inout_ OrtSessionOptions* options, int session_log_severity_level); + + /** \brief Set the optimization level to apply when loading a graph + * + * Please see https://onnxruntime.ai/docs/performance/model-optimizations/graph-optimizations.html for an in-depth explanation + * \param[in,out] options The session options object + * \param[in] graph_optimization_level The optimization level + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetSessionGraphOptimizationLevel, _Inout_ OrtSessionOptions* options, + GraphOptimizationLevel graph_optimization_level); + + /** \brief Sets the number of threads used to parallelize the execution within nodes + * + * When running a single node operation, ex. add, this sets the maximum number of threads to use. + * + * \note If built with OpenMP, this has no effect on the number of threads used. In this case + * use the OpenMP env variables to configure the number of intra op num threads. + * + * \param[in] options + * \param[in] intra_op_num_threads Number of threads to use
+ * A value of 0 will use the default number of threads
+ * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetIntraOpNumThreads, _Inout_ OrtSessionOptions* options, int intra_op_num_threads); + + /** \brief Sets the number of threads used to parallelize the execution of the graph + * + * If nodes can be run in parallel, this sets the maximum number of threads to use to run them in parallel. + * + * \note If sequential execution is enabled this value is ignored, it acts as if it was set to 1. + * + * \param[in] options + * \param[in] inter_op_num_threads Number of threads to use
+ * A value of 0 will use the default number of threads
+ * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetInterOpNumThreads, _Inout_ OrtSessionOptions* options, int inter_op_num_threads); + + /// @} + /// \name OrtCustomOpDomain + /// @{ + + /** \brief Create a custom op domain + * + * \param[in] domain + * \param[out] out Newly created domain. Must be freed with OrtApi::ReleaseCustomOpDomain + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateCustomOpDomain, _In_ const char* domain, _Outptr_ OrtCustomOpDomain** out); + + /** \brief Add a custom op to a custom op domain + * + * \note The OrtCustomOp* pointer must remain valid until the ::OrtCustomOpDomain using it is released + * + * \param[in] custom_op_domain + * \param[in] op + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CustomOpDomain_Add, _Inout_ OrtCustomOpDomain* custom_op_domain, _In_ const OrtCustomOp* op); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Add custom op domain to a session options + * + * \note The OrtCustomOpDomain* must not be deleted until all sessions using it are released + * + * \param[in] options + * \param[in] custom_op_domain + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(AddCustomOpDomain, _Inout_ OrtSessionOptions* options, _In_ OrtCustomOpDomain* custom_op_domain); + + /** \deprecated Use OrtApi::RegisterCustomOpsLibrary_V2. + * + * Registers custom ops from a shared library. + * + * Loads a shared library (dll on windows, so on linux, etc) named 'library_path' and looks for this entry point: + * OrtStatus* RegisterCustomOps(OrtSessionOptions * options, const OrtApiBase* api); + * It then passes in the provided session options to this function along with the api base. + * The handle to the loaded library is returned in library_handle. It can be freed by the caller after all sessions using the passed in + * session options are destroyed, or if an error occurs and it is non null. + * + * \param[in] options + * \param[in] library_path + * \param[out] library_handle OS specific handle to the loaded library (Use FreeLibrary on Windows, dlclose on Linux, etc.. to unload) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RegisterCustomOpsLibrary, _Inout_ OrtSessionOptions* options, _In_ const char* library_path, _Outptr_ void** library_handle); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief Get input count for a session + * + * This number must also match the number of inputs passed to OrtApi::Run + * + * \see OrtApi::SessionGetInputTypeInfo, OrtApi::SessionGetInputName, OrtApi::Session + * + * \param[in] session + * \param[out] out Number of inputs + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetInputCount, _In_ const OrtSession* session, _Out_ size_t* out); + + /** \brief Get output count for a session + * + * This number must also match the number of outputs returned by OrtApi::Run + * + * \see OrtApi::SessionGetOutputTypeInfo, OrtApi::SessionGetOutputName, OrtApi::Session + * + * \param[in] session + * \param[out] out Number of outputs + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOutputCount, _In_ const OrtSession* session, _Out_ size_t* out); + + /** \brief Get overridable initializer count + * + * \see OrtApi::SessionGetOverridableInitializerTypeInfo, OrtApi::SessionGetOverridableInitializerName + * + * \param[in] session + * \param[in] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOverridableInitializerCount, _In_ const OrtSession* session, _Out_ size_t* out); + + /** \brief Get input type information + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetInputCount returns (exclusive) + * \param[out] type_info Must be freed with OrtApi::ReleaseTypeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetInputTypeInfo, _In_ const OrtSession* session, size_t index, _Outptr_ OrtTypeInfo** type_info); + + /** \brief Get output type information + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetOutputCount returns (exclusive) + * \param[out] type_info Must be freed with OrtApi::ReleaseTypeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOutputTypeInfo, _In_ const OrtSession* session, size_t index, _Outptr_ OrtTypeInfo** type_info); + + /** \brief Get overridable initializer type information + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetOverridableInitializerCount returns (exclusive) + * \param[out] type_info Must be freed with OrtApi::ReleaseTypeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOverridableInitializerTypeInfo, _In_ const OrtSession* session, size_t index, _Outptr_ OrtTypeInfo** type_info); + + /** \brief Get input name + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetInputCount returns (exclusive) + * \param[in] allocator + * \param[out] value Set to a null terminated UTF-8 encoded string allocated using `allocator`. Must be freed using `allocator`. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetInputName, _In_ const OrtSession* session, size_t index, _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /** \brief Get output name + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetOutputCount returns (exclusive) + * \param[in] allocator + * \param[out] value Set to a null terminated UTF-8 encoded string allocated using `allocator`. Must be freed using `allocator`. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOutputName, _In_ const OrtSession* session, size_t index, _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /** \brief Get overridable initializer name + * + * \param[in] session + * \param[in] index Must be between 0 (inclusive) and what OrtApi::SessionGetOverridableInitializerCount returns (exclusive) + * \param[in] allocator + * \param[out] value Set to a null terminated UTF-8 encoded string allocated using `allocator`. Must be freed using `allocator`. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetOverridableInitializerName, _In_ const OrtSession* session, size_t index, + _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /// @} + /// \name OrtRunOptions + /// @{ + + /** \brief Create an OrtRunOptions + * + * \param[out] out Returned newly created ::OrtRunOptions. Must be freed with OrtApi::ReleaseRunOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateRunOptions, _Outptr_ OrtRunOptions** out); + + /** \brief Set per-run log verbosity level + * + * \see OrtApi::RunOptionsGetRunLogVerbosityLevel + * + * \param[in] options + * \param[in] log_verbosity_level \snippet{doc} snippets.dox Log Verbosity Level + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RunOptionsSetRunLogVerbosityLevel, _Inout_ OrtRunOptions* options, int log_verbosity_level); + + /** \brief Set per-run log severity level + * + * \see OrtApi::RunOptionsGetRunLogSeverityLevel + * + * \param[in] options + * \param[in] log_severity_level The log severity level (refer to ::OrtLoggingLevel for possible values). + */ + ORT_API2_STATUS(RunOptionsSetRunLogSeverityLevel, _Inout_ OrtRunOptions* options, int log_severity_level); + + /** \brief Set per-run tag + * + * This is used in a per-run log identifier. + * + * \see OrtApi::RunOptionsGetRunTag + * + * \param[in] options + * \param[in] run_tag The run tag. + */ + ORT_API2_STATUS(RunOptionsSetRunTag, _Inout_ OrtRunOptions* options, _In_ const char* run_tag); + + /** \brief Get per-run log verbosity level + * + * \see OrtApi::RunOptionsSetRunLogVerbosityLevel + * + * \param[in] options + * \param[out] log_verbosity_level \snippet{doc} snippets.dox Log Verbosity Level + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RunOptionsGetRunLogVerbosityLevel, _In_ const OrtRunOptions* options, + _Out_ int* log_verbosity_level); + + /** \brief Get per-run log severity level + * + * \see OrtApi::RunOptionsSetRunLogSeverityLevel + * + * \param[in] options + * \param[out] log_severity_level The log severity level (refer to ::OrtLoggingLevel for possible values). + */ + ORT_API2_STATUS(RunOptionsGetRunLogSeverityLevel, _In_ const OrtRunOptions* options, _Out_ int* log_severity_level); + + /** \brief Get per-run tag + * + * This is used in a per-run log identifier. + * + * \see OrtApi::RunOptionsSetRunTag + * + * \param[in] options + * \param[out] run_tag The run tag. + * Do not free this value, it is owned by `options`. It will be invalidated if the run tag + * changes (i.e., with OrtApi::RunOptionsSetRunTag) or `options` is freed. + */ + ORT_API2_STATUS(RunOptionsGetRunTag, _In_ const OrtRunOptions* options, _Out_ const char** run_tag); + + /** \brief Set terminate flag + * + * If a currently executing session needs to be force terminated, this can be called from another thread to force it to fail with an error. + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RunOptionsSetTerminate, _Inout_ OrtRunOptions* options); + + /** \brief Clears the terminate flag + * + * Used so the OrtRunOptions instance can be used in a new OrtApi::Run call without it instantly terminating + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RunOptionsUnsetTerminate, _Inout_ OrtRunOptions* options); + + /// @} + /// \name OrtValue + /// @{ + + /** \brief Create a tensor + * + * Create a tensor using a supplied ::OrtAllocator + * + * \param[in] allocator + * \param[in] shape Pointer to the tensor shape dimensions. + * \param[in] shape_len The number of tensor shape dimensions. + * \param[in] type + * \param[out] out Returns newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateTensorAsOrtValue, _Inout_ OrtAllocator* allocator, _In_ const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type, _Outptr_ OrtValue** out); + + /** \brief Create a tensor backed by a user supplied buffer + * + * Create a tensor with user's buffer. You can fill the buffer either before calling this function or after. + * p_data is owned by caller. ReleaseValue won't release p_data. + * + * If you wish to transfer ownership of p_data to ORT use CreateTensorWithDataAndDeleterAsOrtValue. + * + * \param[in] info Memory description of where the p_data buffer resides (CPU vs GPU etc). + * \param[in] p_data Pointer to the data buffer. + * \param[in] p_data_len The number of bytes in the data buffer. + * \param[in] shape Pointer to the tensor shape dimensions. + * \param[in] shape_len The number of tensor shape dimensions. + * \param[in] type The data type. + * \param[out] out Returns newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateTensorWithDataAsOrtValue, _In_ const OrtMemoryInfo* info, _Inout_ void* p_data, + size_t p_data_len, _In_ const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type, + _Outptr_ OrtValue** out); + + /** \brief Return if an ::OrtValue is a tensor type + * + * \param[in] value A tensor type (string tensors are not supported) + * \param[out] out Set to 1 iff ::OrtValue is a tensor, 0 otherwise + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(IsTensor, _In_ const OrtValue* value, _Out_ int* out); + + /** \brief Get a pointer to the raw data inside a tensor + * + * Used to read/write/modify the internal tensor data directly. + * \note The returned pointer is valid until the \p value is destroyed. + * + * \param[in] value A tensor type (string tensors are not supported) + * \param[out] out Filled in with a pointer to the internal storage + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorMutableData, _In_ OrtValue* value, _Outptr_ void** out); + + /** \brief Set all strings at once in a string tensor + * + * \param[in,out] value A tensor of type ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING + * \param[in] s An array of strings. Each string in this array must be null terminated. + * \param[in] s_len Count of strings in s (Must match the size of \p value's tensor shape) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(FillStringTensor, _Inout_ OrtValue* value, _In_ const char* const* s, size_t s_len); + + /** \brief Get total byte length for all strings in a string tensor + * + * Typically used with OrtApi::GetStringTensorContent + * + * \param[in] value A tensor of type ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING + * \param[out] len Total byte length of all strings (does not include trailing nulls) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetStringTensorDataLength, _In_ const OrtValue* value, _Out_ size_t* len); + + /** \brief Get all strings from a string tensor + * + * An example of the results:
+ * Given \p value is a string tensor with the strings { "This" "is" "a" "test" }
+ * \p s must have a size of 11 bytes
+ * \p offsets must have 4 elements
+ * After the call, these values will be filled in:
+ * \p s will contain "Thisisatest"
+ * \p offsets will contain { 0, 4, 6, 7 }
+ * The length of the last string is just s_len - offsets[last] + * + * \param[in] value A tensor of type ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING + * \param[in] s Buffer to sequentially write all tensor strings to. Each string is NOT null-terminated. + * \param[in] s_len Number of bytes of buffer pointed to by \p s (Get it from OrtApi::GetStringTensorDataLength) + * \param[out] offsets Array of start offsets into the strings written to \p s + * \param[in] offsets_len Number of elements in offsets + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetStringTensorContent, _In_ const OrtValue* value, _Out_writes_bytes_all_(s_len) void* s, + size_t s_len, _Out_writes_all_(offsets_len) size_t* offsets, size_t offsets_len); + + /// @} + /// \name OrtTypeInfo + /// @{ + + /** \brief Get ::OrtTensorTypeAndShapeInfo from an ::OrtTypeInfo + * + * \param[in] type_info + * \param[out] out Do not free this value, it will be valid until type_info is freed. + * If type_info does not represent tensor, this value will be set to nullptr. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CastTypeInfoToTensorInfo, _In_ const OrtTypeInfo* type_info, + _Outptr_result_maybenull_ const OrtTensorTypeAndShapeInfo** out); + + /** \brief Get ::ONNXType from ::OrtTypeInfo + * + * \param[in] type_info + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetOnnxTypeFromTypeInfo, _In_ const OrtTypeInfo* type_info, _Out_ enum ONNXType* out); + + /// @} + /// \name OrtTensorTypeAndShapeInfo + /// @{ + + /** \brief Create an ::OrtTensorTypeAndShapeInfo object + * + * \param[out] out Returns newly created ::OrtTensorTypeAndShapeInfo. Must be freed with OrtApi::ReleaseTensorTypeAndShapeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateTensorTypeAndShapeInfo, _Outptr_ OrtTensorTypeAndShapeInfo** out); + + /** \brief Set element type in ::OrtTensorTypeAndShapeInfo + * + * \param[in] info + * \param[in] type + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetTensorElementType, _Inout_ OrtTensorTypeAndShapeInfo* info, enum ONNXTensorElementDataType type); + + /** \brief Set shape information in ::OrtTensorTypeAndShapeInfo + * + * \param[in] info + * \param[in] dim_values Array with `dim_count` elements. Can contain negative values. + * \param[in] dim_count Number of elements in `dim_values` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetDimensions, OrtTensorTypeAndShapeInfo* info, _In_ const int64_t* dim_values, size_t dim_count); + + /** \brief Get element type in ::OrtTensorTypeAndShapeInfo + * + * \see OrtApi::SetTensorElementType + * + * \param[in] info + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorElementType, _In_ const OrtTensorTypeAndShapeInfo* info, + _Out_ enum ONNXTensorElementDataType* out); + + /** \brief Get dimension count in ::OrtTensorTypeAndShapeInfo + * + * \see OrtApi::GetDimensions + * + * \param[in] info + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetDimensionsCount, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ size_t* out); + + /** \brief Get dimensions in ::OrtTensorTypeAndShapeInfo + * + * \param[in] info + * \param[out] dim_values Array with `dim_values_length` elements. On return, filled with the dimensions stored in the ::OrtTensorTypeAndShapeInfo + * \param[in] dim_values_length Number of elements in `dim_values`. Use OrtApi::GetDimensionsCount to get this value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetDimensions, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ int64_t* dim_values, + size_t dim_values_length); + + /** \brief Get symbolic dimension names in ::OrtTensorTypeAndShapeInfo + * + * \param[in] info + * \param[in] dim_params Array with `dim_params_length` elements. On return filled with pointers to null terminated strings of the dimension names + * \param[in] dim_params_length Number of elements in `dim_params`. Use OrtApi::GetDimensionsCount to get this value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSymbolicDimensions, _In_ const OrtTensorTypeAndShapeInfo* info, + _Out_writes_all_(dim_params_length) const char* dim_params[], size_t dim_params_length); + + /** \brief Get total number of elements in a tensor shape from an ::OrtTensorTypeAndShapeInfo + * + * Return the number of elements specified by the tensor shape (all dimensions multiplied by each other). + * For 0 dimensions, 1 is returned. If any dimension is less than 0, the result is always -1. + * + * Examples:
+ * [] = 1
+ * [1,3,4] = 12
+ * [2,0,4] = 0
+ * [-1,3,4] = -1
+ * + * \param[in] info + * \param[out] out Number of elements + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorShapeElementCount, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ size_t* out); + + /// @} + /// \name OrtValue + /// @{ + + /** \brief Get type and shape information from a tensor ::OrtValue + * + * \param[in] value Must be a tensor (not a map/sequence/etc) or will return failure + * \param[out] out Newly created ::OrtTensorTypeAndShapeInfo. Must be freed with OrtApi::ReleaseTensorTypeAndShapeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorTypeAndShape, _In_ const OrtValue* value, _Outptr_ OrtTensorTypeAndShapeInfo** out); + + /** \brief Get type information of an OrtValue + * + * \param[in] value + * \param[out] out Newly created ::OrtTypeInfo. Must be freed with OrtApi::ReleaseTypeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTypeInfo, _In_ const OrtValue* value, _Outptr_result_maybenull_ OrtTypeInfo** out); + + /** \brief Get ONNXType of an ::OrtValue + * + * \param[in] value + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetValueType, _In_ const OrtValue* value, _Out_ enum ONNXType* out); + + /// @} + /// \name OrtMemoryInfo + /// @{ + + /** \brief Create an ::OrtMemoryInfo + * + * \param[in] name + * \param[in] type + * \param[in] id + * \param[in] mem_type + * \param[out] out Newly created ::OrtMemoryInfo. Must be freed with OrtAPi::ReleaseMemoryInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateMemoryInfo, _In_ const char* name, enum OrtAllocatorType type, int id, + enum OrtMemType mem_type, _Outptr_ OrtMemoryInfo** out); + + /** \brief Create an ::OrtMemoryInfo for CPU memory + * + * Special case version of OrtApi::CreateMemoryInfo for CPU based memory. Same as using OrtApi::CreateMemoryInfo with name = "Cpu" and id = 0. + * + * \param[in] type + * \param[in] mem_type + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateCpuMemoryInfo, enum OrtAllocatorType type, enum OrtMemType mem_type, + _Outptr_ OrtMemoryInfo** out); + + /** \brief Compare ::OrtMemoryInfo objects for equality + * + * Compares all settings of each ::OrtMemoryInfo for equality + * + * \param[in] info1 + * \param[in] info2 + * \param[out] out Set to 0 if equal, -1 if not equal + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CompareMemoryInfo, _In_ const OrtMemoryInfo* info1, _In_ const OrtMemoryInfo* info2, _Out_ int* out); + + /** \brief Get name from ::OrtMemoryInfo + * + * \param[in] ptr + * \param[out] out Writes null terminated string to this pointer. Do NOT free the returned pointer. It is valid for the lifetime of the ::OrtMemoryInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(MemoryInfoGetName, _In_ const OrtMemoryInfo* ptr, _Out_ const char** out); + + /** \brief Get the device id from ::OrtMemoryInfo + */ + ORT_API2_STATUS(MemoryInfoGetId, _In_ const OrtMemoryInfo* ptr, _Out_ int* out); + + /** \brief Get the ::OrtMemType from ::OrtMemoryInfo + */ + ORT_API2_STATUS(MemoryInfoGetMemType, _In_ const OrtMemoryInfo* ptr, _Out_ OrtMemType* out); + + /** \brief Get the ::OrtAllocatorType from ::OrtMemoryInfo + */ + ORT_API2_STATUS(MemoryInfoGetType, _In_ const OrtMemoryInfo* ptr, _Out_ OrtAllocatorType* out); + + /// @} + /// \name OrtAllocator + /// @{ + + /// \brief Calls OrtAllocator::Alloc function + ORT_API2_STATUS(AllocatorAlloc, _Inout_ OrtAllocator* ort_allocator, size_t size, _Outptr_ void** out); + /// \brief Calls OrtAllocator::Free function + ORT_API2_STATUS(AllocatorFree, _Inout_ OrtAllocator* ort_allocator, void* p); + /// \brief Calls OrtAllocator::Info function + ORT_API2_STATUS(AllocatorGetInfo, _In_ const OrtAllocator* ort_allocator, _Outptr_ const struct OrtMemoryInfo** out); + + /** \brief Get the default allocator + * + * The default allocator is a CPU based, non-arena. Always returns the same pointer to the same default allocator. + * + * \param[out] out Returned value should NOT be freed + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetAllocatorWithDefaultOptions, _Outptr_ OrtAllocator** out); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Override session symbolic dimensions + * + * Override symbolic dimensions (by specific denotation strings) with actual values if known at session initialization time to enable + * optimizations that can take advantage of fixed values (such as memory planning, etc) + * + * \param[in] options + * \param[in] dim_denotation + * \param[in] dim_value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(AddFreeDimensionOverride, _Inout_ OrtSessionOptions* options, _In_ const char* dim_denotation, + _In_ int64_t dim_value); + + /// @} + /// \name OrtValue + /// @{ + + /* Internal information (not seen in Doxygen) + * + * APIs to support non-tensor types - map and sequence. + * Currently only the following types are supported + * Note: the following types should be kept in sync with data_types.h + * Map types + * ========= + * std::map + * std::map + * std::map + * std::map + * std::map + * std::map + * std::map + * std::map + * + * Sequence types + * ============== + * std::vector + * std::vector + * std::vector + * std::vector + * std::vector> + * std::vector + */ + + /** \brief Get non tensor data from an ::OrtValue + * + * If `value` is of type ONNX_TYPE_MAP, you need to retrieve the keys and values + * separately. Use index=0 to retrieve keys and index=1 to retrieve values. + * If `value` is of type ONNX_TYPE_SEQUENCE, use index to retrieve the index'th element + * of the sequence. + * + * \param[in] value + * \param[in] index See above for usage based on `value` type + * \param[in] allocator Allocator used to allocate ::OrtValue + * \param[out] out Created ::OrtValue that holds the element requested. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetValue, _In_ const OrtValue* value, int index, _Inout_ OrtAllocator* allocator, + _Outptr_ OrtValue** out); + + /** \brief Get non tensor value count from an ::OrtValue + * + * If `value` is of type ONNX_TYPE_MAP 2 will always be returned. For ONNX_TYPE_SEQUENCE + * the number of elements in the sequence will be returned + * + * \param[in] value + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetValueCount, _In_ const OrtValue* value, _Out_ size_t* out); + + /** \brief Create a map or sequence ::OrtValue + * + * To construct a map (ONNX_TYPE_MAP), use num_values = 2 and `in` should be an array of 2 ::OrtValue%s + * representing keys and values.
+ * + * To construct a sequence (ONNX_TYPE_SEQUENCE), use num_values = N where N is the number of the elements in the + * sequence. 'in' should be an array of N ::OrtValue%s. + * + * \param[in] in See above for details + * \param[in] num_values + * \param[in] value_type Must be either ONNX_TYPE_MAP or ONNX_TYPE_SEQUENCE + * \param[out] out Newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateValue, _In_reads_(num_values) const OrtValue* const* in, size_t num_values, + enum ONNXType value_type, _Outptr_ OrtValue** out); + + /** \brief Create an opaque (custom user defined type) ::OrtValue + * + * Constructs an ::OrtValue that contains a value of non-standard type created for + * experiments or while awaiting standardization. ::OrtValue in this case would contain + * an internal representation of the Opaque type. Opaque types are distinguished from + * each other by two strings 1) domain and 2) type name. The combination of the two + * must be unique, so the type representation is properly identified internally. The combination + * must be properly registered from within ORT at both compile/run time or by another API. + * + * To construct the ::OrtValue pass domain and type names, also a pointer to a data container + * the type of which must be known to both ORT and the client program. That data container may or may + * not match the internal representation of the Opaque type. The sizeof(data_container) is passed for + * verification purposes. + * + * \param[in] domain_name Null terminated string of the domain name + * \param[in] type_name Null terminated string of the type name + * \param[in] data_container User pointer Data to populate ::OrtValue + * \param[in] data_container_size Size in bytes of what `data_container` points to + * \param[out] out Newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateOpaqueValue, _In_z_ const char* domain_name, _In_z_ const char* type_name, + _In_ const void* data_container, size_t data_container_size, _Outptr_ OrtValue** out); + + /** \brief Get internal data from an opaque (custom user defined type) ::OrtValue + * + * Copies internal data from an opaque value into a user provided buffer + * + * \see OrtApi::CreateOpaqueValue + * + * \param[in] domain_name Null terminated string of the domain name + * \param[in] type_name Null terminated string of the type name + * \param[in] in The opaque ::OrtValue + * \param[out] data_container Buffer to copy data into + * \param[out] data_container_size Size in bytes of the buffer pointed to by data_container. Must match the size of the internal buffer. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetOpaqueValue, _In_ const char* domain_name, _In_ const char* type_name, _In_ const OrtValue* in, + _Out_ void* data_container, size_t data_container_size); + + /// @} + /// \name OrtKernelInfo + /// Custom operator APIs. + /// @{ + + /** \brief Get a float stored as an attribute in the graph node + * + * \param[in] info ::OrtKernelInfo instance + * \param[in] name Null terminated string of the name of the attribute + * \param[out] out Pointer to memory where the attribute will be stored + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttribute_float, _In_ const OrtKernelInfo* info, _In_ const char* name, + _Out_ float* out); + + /** \brief Fetch a 64-bit int stored as an attribute in the graph node + * + * \param[in] info ::OrtKernelInfo instance + * \param[in] name Null terminated string of the name of the attribute + * \param[out] out Pointer to memory where the attribute will be stored + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttribute_int64, _In_ const OrtKernelInfo* info, _In_ const char* name, + _Out_ int64_t* out); + + /** \brief Fetch a string stored as an attribute in the graph node + * + * If `out` is nullptr, the value of `size` is set to the true size of the string + * attribute, and a success status is returned. + * + * If the `size` parameter is greater than or equal to the actual string attribute's size, + * the value of `size` is set to the true size of the string attribute, the provided memory + * is filled with the attribute's contents, and a success status is returned. + * + * If the `size` parameter is less than the actual string attribute's size and `out` + * is not nullptr, the value of `size` is set to the true size of the string attribute + * and a failure status is returned.) + * + * \param[in] info ::OrtKernelInfo instance + * \param[in] name Null terminated string of the name of the attribute + * \param[out] out Pointer to memory where the attribute will be stored + * \param[in,out] size See above comments for details + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttribute_string, _In_ const OrtKernelInfo* info, _In_ const char* name, _Out_ char* out, + _Inout_ size_t* size); + + /// @} + /// \name OrtKernelContext + /// Custom operator APIs. + /// @{ + + /** \brief Used for custom operators, get the input count of a kernel + * + * \see ::OrtCustomOp + */ + ORT_API2_STATUS(KernelContext_GetInputCount, _In_ const OrtKernelContext* context, _Out_ size_t* out); + + /** \brief Used for custom operators, get the output count of a kernel + * + * \see ::OrtCustomOp + */ + ORT_API2_STATUS(KernelContext_GetOutputCount, _In_ const OrtKernelContext* context, _Out_ size_t* out); + + /** \brief Used for custom operators, get an input of a kernel + * + * The function attempts fetches the input of the kernel. If the input is optional + * and not present, the function returns success and out is set to nullptr. + * + * \param[in] context ::OrtKernelContext instance + * \param[in] index See KernelContext_GetInputCount for boundaries check. + * \param[out] out OrtValue if the input is present otherwise is set nullptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelContext_GetInput, _In_ const OrtKernelContext* context, _In_ size_t index, + _Out_ const OrtValue** out); + + /** \brief Used for custom operators, get an output of a kernel + * + * The function attempts fetches the output of the kernel. If the output is optional + * and not present, the function returns success and out is set to nullptr. + * + * \param[in] context ::OrtKernelContext instance + * \param[in] index See KernelContext_GetOutputCount for boundaries check. + * \param[in] dim_values output dimensions + * \param[in] dim_count number of dimensions + * \param[out] out a ptr to OrtValue to output otherwise set to nullptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelContext_GetOutput, _Inout_ OrtKernelContext* context, _In_ size_t index, + _In_ const int64_t* dim_values, size_t dim_count, _Outptr_ OrtValue** out); + + /// @} + /// \name OrtEnv + /// @{ + ORT_CLASS_RELEASE(Env); + /// @} + /// \name OrtStatus + /// @{ + ORT_CLASS_RELEASE(Status); + /// @} + /// \name OrtMemoryInfo + /// @{ + ORT_CLASS_RELEASE(MemoryInfo); + /// @} + /// \name OrtSession + /// @{ + ORT_CLASS_RELEASE(Session); // Don't call ReleaseSession from Dllmain (because session owns a thread pool) + /// @} + /// \name OrtValue + /// @{ + ORT_CLASS_RELEASE(Value); + /// @} + /// \name OrtRunOptions + /// @{ + ORT_CLASS_RELEASE(RunOptions); + /// @} + /// \name OrtTypeInfo + /// @{ + ORT_CLASS_RELEASE(TypeInfo); + /// @} + /// \name OrtTensorTypeAndShapeInfo + /// @{ + ORT_CLASS_RELEASE(TensorTypeAndShapeInfo); + /// @} + /// \name OrtSessionOptions + /// @{ + ORT_CLASS_RELEASE(SessionOptions); + /// @} + /// \name OrtCustomOpDomain + /// @{ + ORT_CLASS_RELEASE(CustomOpDomain); + + /// @} + /// \name OrtTypeInfo + /// @{ + + /** \brief Get denotation from type information + * + * Augments ::OrtTypeInfo to return denotations on the type. + * + * This is used by WinML to determine if an input/output is intended to be an Image or a Tensor. + * + * \param[in] type_info + * \param[out] denotation Pointer to the null terminated denotation string is written to this pointer. This pointer is valid until the object is destroyed or the name is changed, do not free. + * \param[out] len Length in bytes of the string returned in `denotation` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetDenotationFromTypeInfo, _In_ const OrtTypeInfo* type_info, _Out_ const char** const denotation, + _Out_ size_t* len); + + /** \brief Get detailed map information from an ::OrtTypeInfo + * + * This augments ::OrtTypeInfo to return an ::OrtMapTypeInfo when the type is a map. + * The OrtMapTypeInfo has additional information about the map's key type and value type. + * + * This is used by WinML to support model reflection APIs. + * + * \param[out] type_info + * \param[out] out A pointer to the ::OrtMapTypeInfo. Do not free this value. If type_info + * does not contain a map, this value will be set to nullptr. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CastTypeInfoToMapTypeInfo, _In_ const OrtTypeInfo* type_info, + _Outptr_result_maybenull_ const OrtMapTypeInfo** out); + + /** \brief Cast ::OrtTypeInfo to an ::OrtSequenceTypeInfo + * + * This api augments ::OrtTypeInfo to return an ::OrtSequenceTypeInfo when the type is a sequence. + * The ::OrtSequenceTypeInfo has additional information about the sequence's element type. + * + * This is used by WinML to support model reflection APIs. + * + * \param[in] type_info + * \param[out] out A pointer to the OrtSequenceTypeInfo. Do not free this value. If type_info + * doesn not contain a sequence, this value will be set to nullptr. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CastTypeInfoToSequenceTypeInfo, _In_ const OrtTypeInfo* type_info, + _Outptr_result_maybenull_ const OrtSequenceTypeInfo** out); + + /// @} + /// \name OrtMapTypeInfo + /// @{ + + /** \brief Get key type from an ::OrtMapTypeInfo + * + * Key types are restricted to being scalar types. + * + * This is used by WinML to support model reflection APIs. + * + * \param[in] map_type_info + * \param[out] out + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetMapKeyType, _In_ const OrtMapTypeInfo* map_type_info, _Out_ enum ONNXTensorElementDataType* out); + + /** \brief Get the value type from an ::OrtMapTypeInfo + * + * \param[in] map_type_info + * \param[out] type_info A copy of the OrtTypeInfo for the map value type. + * The user must free this value with ReleaseTypeInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetMapValueType, _In_ const OrtMapTypeInfo* map_type_info, _Outptr_ OrtTypeInfo** type_info); + + /// @} + /// \name OrtSequenceTypeInfo + /// @{ + + /** \brief Get element type from an ::OrtSequenceTypeInfo + * + * This is used by WinML to support model reflection APIs. + * + * \param[in] sequence_type_info + * \param[out] type_info A copy of the OrtTypeInfo for the sequence element type. + * The user must free this value with ReleaseTypeInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSequenceElementType, _In_ const OrtSequenceTypeInfo* sequence_type_info, + _Outptr_ OrtTypeInfo** type_info); + + /// @} + /// \name OrtMapTypeInfo + /// @{ + ORT_CLASS_RELEASE(MapTypeInfo); + /// @} + /// \name OrtSequenceTypeInfo + /// @{ + ORT_CLASS_RELEASE(SequenceTypeInfo); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief End profiling and return filename of the profile data + * + * Profiling is turned on through OrtApi::EnableProfiling + * + * \param[in] session + * \param[in] allocator + * \param[out] out Null terminated string of the filename, allocated using `allocator`. Must be freed using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionEndProfiling, _In_ OrtSession* session, _Inout_ OrtAllocator* allocator, _Outptr_ char** out); + + /** \brief Get ::OrtModelMetadata from an ::OrtSession + * + * \param[in] session + * \param[out] out Newly created ::OrtModelMetadata. Must be freed using OrtApi::ReleaseModelMetadata + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetModelMetadata, _In_ const OrtSession* session, _Outptr_ OrtModelMetadata** out); + + /// @} + /// \name OrtModelMetadata + /// @{ + + /** \brief Get `producer name` from an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[in] allocator + * \param[out] value Set to a null terminated string allocated using `allocator`. Must be freed using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetProducerName, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /** \brief Get `graph name` from an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[in] allocator + * \param[out] value Set to a null terminated string allocated using `allocator`. Must be freed using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetGraphName, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /** \brief Get `domain` from an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[in] allocator + * \param[out] value Set to a null terminated string allocated using `allocator`. Must be freed using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetDomain, _In_ const OrtModelMetadata* model_metadata, _Inout_ OrtAllocator* allocator, + _Outptr_ char** value); + + /** \brief Get `description` from an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[in] allocator + * \param[out] value Set to a null terminated string allocated using `allocator`. Must be freed using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetDescription, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /** \brief Return data for a key in the custom metadata map in an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[in] allocator + * \param[in] key Null terminated string + * \param[out] value Set to a null terminated string allocated using `allocator`. Must be freed using `allocator` + * `value` will be set to nullptr if the given key is not found in the custom metadata map. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataLookupCustomMetadataMap, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _In_ const char* key, _Outptr_result_maybenull_ char** value); + + /** \brief Get version number from an ::OrtModelMetadata + * + * \param[in] model_metadata + * \param[out] value Set to the version number + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetVersion, _In_ const OrtModelMetadata* model_metadata, _Out_ int64_t* value); + + ORT_CLASS_RELEASE(ModelMetadata); + + /// @} + /// \name OrtEnv + /// @{ + + /** \brief Create an OrtEnv + * + * Create an environment with global threadpools that will be shared across sessions. + * Use this in conjunction with OrtApi::DisablePerSessionThreads or else the session will use + * its own thread pools. + * + * \param[in] log_severity_level The log severity level. + * \param[in] logid The log identifier. + * \param[in] tp_options + * \param[out] out Returned newly created OrtEnv. Must be freed with OrtApi::ReleaseEnv + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateEnvWithGlobalThreadPools, OrtLoggingLevel log_severity_level, _In_ const char* logid, + _In_ const OrtThreadingOptions* tp_options, _Outptr_ OrtEnv** out); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Use global thread pool on a session + * + * Disable using per session thread pool and use the shared global threadpool. + * This should be used in conjunction with OrtApi::CreateEnvWithGlobalThreadPools. + * + * \param[in] options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(DisablePerSessionThreads, _Inout_ OrtSessionOptions* options); + + /// @} + /// \name OrtThreadingOptions + /// @{ + + /** \brief Create an ::OrtThreadingOptions + * + * \param[out] out Newly created ::OrtThreadingOptions. Must be freed with OrtApi::ReleaseThreadingOptions + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateThreadingOptions, _Outptr_ OrtThreadingOptions** out); + + ORT_CLASS_RELEASE(ThreadingOptions); + + /// @} + /// \name OrtModelMetadata + /// @{ + + /** + * + * \param[in] model_metadata + * \param[in] allocator + * \param[out] keys Array of null terminated strings (array count = num_keys) allocated using `allocator`. + * The strings and the pointer array must be freed using `allocator` + * `keys` will be set to nullptr if the custom metadata map is empty. + * \param[out] num_keys Set to the number of elements in the `keys` array + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetCustomMetadataMapKeys, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _Outptr_result_buffer_maybenull_(*num_keys) char*** keys, _Out_ int64_t* num_keys); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** + * + * Override symbolic dimensions (by specific name strings) with actual values + * if known at session initialization time to enable optimizations that can + * take advantage of fixed values (such as memory planning, etc) + * + */ + ORT_API2_STATUS(AddFreeDimensionOverrideByName, + _Inout_ OrtSessionOptions* options, _In_ const char* dim_name, + _In_ int64_t dim_value); + + /// @} + /// \name Misc + /// @{ + + /** \brief Get the names of all available providers + * + * \note The providers in the list are not guaranteed to be usable. They may fail to load due to missing system dependencies. + * For example, if the CUDA/cuDNN libraries are not installed, the CUDA provider will report an error when it is added to the session options. + * + * \param[out] out_ptr Set to a pointer to an array of null terminated strings of the available providers. The entries and the + * array itself must be freed using OrtApi::ReleaseAvailableProviders + * \param[out] provider_length Set to the number of entries in the `out_ptr` array + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetAvailableProviders, _Outptr_ char*** out_ptr, _Out_ int* provider_length); + + /** \brief Release data from OrtApi::GetAvailableProviders. This API will never fail + * so you can rely on it in a noexcept code. + * + * \param[in] ptr The `out_ptr` result from OrtApi::GetAvailableProviders. + * \param[in] providers_length The `provider_length` result from OrtApi::GetAvailableProviders + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ReleaseAvailableProviders, _In_ char** ptr, + _In_ int providers_length); + + /// @} + /// \name OrtValue + /// @{ + + /** \brief Get the length of a single string in a string tensor + * + * \param[in] value A string tensor + * \param[in] index Index of the string in the tensor + * \param[out] out Set to number of bytes of the string element + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetStringTensorElementLength, _In_ const OrtValue* value, size_t index, _Out_ size_t* out); + + /** \brief Get a single string from a string tensor + * + * \param[in] value A string tensor + * \param[in] s_len Number of bytes in the `s` buffer. Must match the value returned by OrtApi::GetStringTensorElementLength. + * \param[in] index Index of the string in the tensor + * \param[out] s The string element contents in UTF-8 encoding. The string is NOT null-terminated. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetStringTensorElement, _In_ const OrtValue* value, size_t s_len, size_t index, _Out_writes_bytes_all_(s_len) void* s); + + /** \brief Set a single string in a string tensor + * + * \param[in] value A string tensor + * \param[in] s A null terminated UTF-8 encoded string + * \param[in] index Index of the string in the tensor to set + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(FillStringTensorElement, _Inout_ OrtValue* value, _In_ const char* s, size_t index); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Set a session configuration entry as a pair of strings + * + * If a configuration with same key exists, this will overwrite the configuration with the given config_value. + * + * The config_key and the format of config_value are defined in onnxruntime_session_options_config_keys.h + * + * \param[in] options + * \param[in] config_key A null terminated string representation of the config key + * \param[in] config_value A null terminated string representation of the config value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(AddSessionConfigEntry, _Inout_ OrtSessionOptions* options, + _In_z_ const char* config_key, _In_z_ const char* config_value); + + /// @} + /// \name OrtAllocator + /// @{ + + /** \brief Create an allocator for an ::OrtSession following an ::OrtMemoryInfo + * + * The allocator wraps the internal allocator from the OrtSession and becomes invalid when the session does. + * + * \param[in] session + * \param[in] mem_info valid ::OrtMemoryInfo instance + * \param[out] out Newly created ::OrtAllocator. Must be freed with OrtApi::ReleaseAllocator + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateAllocator, _In_ const OrtSession* session, _In_ const OrtMemoryInfo* mem_info, + _Outptr_ OrtAllocator** out); + + /** \brief Release an ::OrtAllocator obtained from OrtApi::CreateAllocator + */ + ORT_CLASS_RELEASE(Allocator); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief Run a model using Io Bindings for the inputs & outputs + * + * \see OrtApi::Run + * + * \param[in] session + * \param[in] run_options + * \param[in] binding_ptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RunWithBinding, _Inout_ OrtSession* session, _In_ const OrtRunOptions* run_options, _In_ const OrtIoBinding* binding_ptr); + + /** \brief Create an ::OrtIoBinding instance + * + * An IoBinding object allows one to bind pre-allocated ::OrtValue%s to input names. + * Thus if you want to use a raw on device buffer as input or output you can avoid + * extra copy during runtime. + * + * \param[in] session + * \param[out] out Newly created ::OrtIoBinding. Must be freed with OrtApi::ReleaseIoBinding + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateIoBinding, _Inout_ OrtSession* session, _Outptr_ OrtIoBinding** out); + + /// @} + /// \name OrtIoBinding + /// @{ + + /** \brief Release an ::OrtIoBinding obtained from OrtApi::CreateIoBinding + */ + ORT_CLASS_RELEASE(IoBinding); + + /** \brief Bind an ::OrtValue to an ::OrtIoBinding input + * + * When using OrtApi::RunWithBinding this value is used for the named input + * + * \param[in] binding_ptr + * \param[in] name Name for the model input + * \param[in] val_ptr ::OrtValue of Tensor type. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(BindInput, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtValue* val_ptr); + + /** \brief Bind an ::OrtValue to an ::OrtIoBinding output + * + * When using OrtApi::RunWithBinding this value is used for the named output + * + * \param[in] binding_ptr + * \param[in] name Null terminated string of the model output name + * \param[in] val_ptr ::OrtValue of Tensor type. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(BindOutput, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtValue* val_ptr); + + /** \brief Bind an ::OrtIoBinding output to a device + * + * Binds the ::OrtValue to a device which is specified by ::OrtMemoryInfo. + * You can either create an instance of ::OrtMemoryInfo with a device id or obtain one from the allocator that you have created/are using + * This is useful when one or more outputs have dynamic shapes and, it is hard to pre-allocate and bind a chunk of + * memory within ::OrtValue ahead of time. + * + * \see OrtApi::RunWithBinding + * + * \param[in] binding_ptr + * \param[in] name Null terminated string of the device name + * \param[in] mem_info_ptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(BindOutputToDevice, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtMemoryInfo* mem_info_ptr); + + /** \brief Get the names of an ::OrtIoBinding's outputs + * + * Returns the names of the outputs in the order they were bound. This is useful after running the model + * with bound outputs because the returned names are in order in which output ::OrtValue are returned. This is useful if + * the order of outputs and their names is not known. + * + * \param[in] binding_ptr + * \param[in] allocator Allocator used to allocate continuous buffers for output strings and lengths. + * \param[out] buffer Returns an array of non-null terminated UTF-8 strings. The number of strings stored is returned in the count parameter. + * This buffer is allocated using `allocator` and must be freed using it. + * \param[out] lengths Returns an array of `count` lengths of the strings returned in `buffer` + * This buffer is allocated using `allocator` and must be freed using it. + * \param[out] count Number of strings returned. If `binding_ptr` has no bound outputs, zero is returned, + * no memory allocation is performed and buffer and lengths are set to nullptr. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetBoundOutputNames, _In_ const OrtIoBinding* binding_ptr, _In_ OrtAllocator* allocator, + _Out_ char** buffer, _Out_writes_all_(count) size_t** lengths, _Out_ size_t* count); + + /** \brief Get the output ::OrtValue objects from an ::OrtIoBinding + * + * Returns an array of pointers to individually allocated ::OrtValue%s that contain results of a model execution with OrtApi::RunWithBinding + * The array contains the same number of ::OrtValue%s and they are in the same order as they were bound with OrtApi::BindOutput + * or OrtApi::BindOutputToDevice. + * + * The returned ::OrtValue%s must be released using OrtApi::ReleaseValue after they are no longer needed. + * The array is allocated using the specified instance of the allocator and must be freed using the same allocator after + * all the ::OrtValue%s contained therein are individually released. + * + * \param[in] binding_ptr + * \param[in] allocator Allocator used to allocate output array + * \param[out] output Set to the allocated array of allocated ::OrtValue outputs. Set to nullptr if there are 0 outputs. + * \param[out] output_count Set to number of ::OrtValue%s returned + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetBoundOutputValues, _In_ const OrtIoBinding* binding_ptr, _In_ OrtAllocator* allocator, + _Out_writes_all_(output_count) OrtValue*** output, _Out_ size_t* output_count); + + /** \brief Clears any previously set Inputs for an ::OrtIoBinding + */ + void(ORT_API_CALL* ClearBoundInputs)(_Inout_ OrtIoBinding* binding_ptr) NO_EXCEPTION ORT_ALL_ARGS_NONNULL; + + /** \brief Clears any previously set Outputs for an ::OrtIoBinding + */ + void(ORT_API_CALL* ClearBoundOutputs)(_Inout_ OrtIoBinding* binding_ptr) NO_EXCEPTION ORT_ALL_ARGS_NONNULL; + + /// @} + /// \name OrtValue + /// @{ + + /** \brief Direct memory access to a specified tensor element + * + * For example, given a tensor with shape of [3,224,224], a pointer to the element at location [2,150,128] can be retrieved + * + * This function only works for numeric type tensors (No strings, etc). + * This is a no-copy method whose returned pointer is valid until the passed in ::OrtValue is free'd. + * + * \param[in] value + * \param[in] location_values Pointer to an array of index values that specify an element's location relative to its shape + * \param[in] location_values_count Number of elements in location_values. Must match the number of elements in the tensor's shape. + * \param[out] out Set to a pointer to the element specified + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(TensorAt, _Inout_ OrtValue* value, const int64_t* location_values, size_t location_values_count, _Outptr_ void** out); + + /// @} + /// \name OrtEnv + /// @{ + + /** \brief Create an allocator and register it with the ::OrtEnv + * + * Enables sharing the allocator between multiple sessions that use the same env instance. + * Lifetime of the created allocator will be valid for the duration of the environment. + * Returns an error if an allocator with the same ::OrtMemoryInfo is already registered. + * + * See https://onnxruntime.ai/docs/get-started/with-c.html for details. + * + * \param[in] env ::OrtEnv instance + * \param[in] mem_info + * \param[in] arena_cfg Pass nullptr for defaults + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateAndRegisterAllocator, _Inout_ OrtEnv* env, _In_ const OrtMemoryInfo* mem_info, + _In_ const OrtArenaCfg* arena_cfg); + + /** \brief Set language projection + * + * Set the language projection for collecting telemetry data when Env is created. + * + * The default is ORT_PROJECTION_C, which means it will classify the language not in the list to C also. + * + * \param[in] ort_env + * \param[in] projection + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetLanguageProjection, _In_ const OrtEnv* ort_env, _In_ OrtLanguageProjection projection); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief Return the time that profiling was started + * + * \note The timer precision varies per platform. On Windows and MacOS, the precision will be ~100ns + * + * \param[in] session + * \param[out] out nanoseconds of profiling's start time + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionGetProfilingStartTimeNs, _In_ const OrtSession* session, _Outptr_ uint64_t* out); + + /// @} + /// \name OrtThreadingOptions + /// @{ + + /** \brief Set global intra-op thread count + * + * This configures the global thread pool options to be used in the call to OrtApi::CreateEnvWithGlobalThreadPools + * + * \param[in] tp_options + * \param[in] intra_op_num_threads Number of threads, special values:
+ * 0 = Use default thread count
+ * 1 = The invoking thread will be used; no threads will be created in the thread pool. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalIntraOpNumThreads, _Inout_ OrtThreadingOptions* tp_options, int intra_op_num_threads); + + /** \brief Set global inter-op thread count + * + * This configures the global thread pool options to be used in the call to OrtApi::CreateEnvWithGlobalThreadPools + * + * \param[in] tp_options + * \param[in] inter_op_num_threads Number of threads, special values:
+ * 0 = Use default thread count
+ * 1 = The invoking thread will be used; no threads will be created in the thread pool. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalInterOpNumThreads, _Inout_ OrtThreadingOptions* tp_options, int inter_op_num_threads); + + /** \brief Set global spin control options + * + * This will configure the global thread pool options to be used in the call to OrtApi::CreateEnvWithGlobalThreadPools. + * Allow spinning of thread pools when their queues are empty. This will set the value for both + * inter_op and intra_op threadpools. + * + * \param[in] tp_options + * \param[in] allow_spinning Valid values are 0 or 1.
+ * 0 = It won't spin (recommended if CPU usage is high)
+ * 1 = Threadpool will spin to wait for queue to become non-empty + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalSpinControl, _Inout_ OrtThreadingOptions* tp_options, int allow_spinning); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Add a pre-allocated initializer to a session + * + * If a model contains an initializer with a name that is same as the name passed to this call, + * ORT will use this initializer instance instead of deserializing one from the model file. This + * is useful when you want to share the same initializer across sessions. + * + * \param[in] options + * \param[in] name Null terminated string of the initializer name + * \param[in] val ::OrtValue containing the initializer. Its lifetime and the underlying initializer buffer must be + * managed by the user (created using the OrtApi::CreateTensorWithDataAsOrtValue) and it must outlive the session object + * to which it is added. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(AddInitializer, _Inout_ OrtSessionOptions* options, _In_z_ const char* name, + _In_ const OrtValue* val); + + /// @} + /// \name OrtEnv + /// @{ + + /** + * Create a custom environment with global threadpools and logger that will be shared across sessions. + * Use this in conjunction with OrtApi::DisablePerSessionThreads or else the session will use + * its own thread pools. + * + * \param[in] logging_function A pointer to a logging function. + * \param[in] logger_param A pointer to arbitrary data passed as the ::OrtLoggingFunction `param` parameter to + * `logging_function`. + * \param[in] log_severity_level The log severity level. + * \param[in] logid The log identifier. + * \param[in] tp_options + * \param[out] out Newly created OrtEnv. Must be freed with OrtApi::ReleaseEnv + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateEnvWithCustomLoggerAndGlobalThreadPools, OrtLoggingFunction logging_function, _In_opt_ void* logger_param, OrtLoggingLevel log_severity_level, + _In_ const char* logid, _In_ const struct OrtThreadingOptions* tp_options, _Outptr_ OrtEnv** out); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Append CUDA provider to session options + * + * If CUDA is not available (due to a non CUDA enabled build, or if CUDA is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] cuda_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_CUDA, + _In_ OrtSessionOptions* options, _In_ const OrtCUDAProviderOptions* cuda_options); + + /** \brief Append ROCM execution provider to the session options + * + * If ROCM is not available (due to a non ROCM enabled build, or if ROCM is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] rocm_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_ROCM, + _In_ OrtSessionOptions* options, _In_ const OrtROCMProviderOptions* rocm_options); + + /** \brief Append OpenVINO execution provider to the session options + * + * If OpenVINO is not available (due to a non OpenVINO enabled build, or if OpenVINO is not installed on the system), this function will fail. + * + * \param[in] options + * \param[in] provider_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_OpenVINO, + _In_ OrtSessionOptions* options, _In_ const OrtOpenVINOProviderOptions* provider_options); + + /// @} + /// \name OrtThreadingOptions + /// @{ + + /** \brief Set threading flush-to-zero and denormal-as-zero + * + * Sets global thread pool options to be used in the call to OrtApi::CreateEnvWithGlobalThreadPools. + * Flush-to-zero and denormal-as-zero are applied to threads in both intra and inter global thread pool. + * \note This option is not needed if the models used have no denormals. Having no denormals is recommended as this option may hurt model accuracy. + * + * \param[in] tp_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalDenormalAsZero, _Inout_ OrtThreadingOptions* tp_options); + + /// @} + /// \name OrtArenaCfg + /// @{ + + /** \deprecated Use OrtApi::CreateArenaCfgV2 + * + * This will create the configuration of an arena that can eventually be used to define an arena based allocator's behavior + * + * \param[in] max_mem Use 0 to allow ORT to choose the default + * \param[in] arena_extend_strategy Use -1 to allow ORT to choose the default, 0 = kNextPowerOfTwo, 1 = kSameAsRequested + * \param[in] initial_chunk_size_bytes Use -1 to allow ORT to choose the default + * \param[in] max_dead_bytes_per_chunk Use -1 to allow ORT to choose the default + * \param[in] out A pointer to an OrtArenaCfg instance + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateArenaCfg, _In_ size_t max_mem, int arena_extend_strategy, int initial_chunk_size_bytes, + int max_dead_bytes_per_chunk, _Outptr_ OrtArenaCfg** out); + + ORT_CLASS_RELEASE(ArenaCfg); + + /// @} + /// \name OrtModelMetadata + /// @{ + + /** + * Use this to obtain the description of the graph present in the model + * (doc_string field of the GraphProto message within the ModelProto message). + * If it doesn't exist, an empty string will be returned. + * + * \param[in] model_metadata An instance of ::OrtModelMetadata + * \param[in] allocator Allocator used to allocate the string that will be returned back + * \param[out] value Set to a null terminated string allocated using `allocator`. The caller is responsible for freeing it using `allocator` + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(ModelMetadataGetGraphDescription, _In_ const OrtModelMetadata* model_metadata, + _Inout_ OrtAllocator* allocator, _Outptr_ char** value); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Append TensorRT provider to session options + * + * If TensorRT is not available (due to a non TensorRT enabled build, or if TensorRT is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] tensorrt_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_TensorRT, + _In_ OrtSessionOptions* options, _In_ const OrtTensorRTProviderOptions* tensorrt_options); + + /// @} + /// \name Misc + /// @{ + + /** \brief Set current GPU device ID + * + * Set the current device id of the GPU execution provider (CUDA/tensorrt/rocm). The device id should be less + * than the total number of devices available. This is only useful when multiple-GPUs are installed and it is + * required to restrict execution to a single GPU. + * + * \param[in] device_id + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetCurrentGpuDeviceId, _In_ int device_id); + + /** \brief Get current GPU device ID + * + * Get the current device id of the GPU execution provider (CUDA/tensorrt/rocm). + * + * \see OrtApi::SetCurrentGpuDeviceId + * + * \param[out] device_id + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetCurrentGpuDeviceId, _In_ int* device_id); + + /// @} + /// \name OrtKernelInfo + /// Custom operator APIs. + /// @{ + + /** \brief Fetch an array of int64_t values stored as an attribute in the graph node + * + * + * If `out` is nullptr, the value of `size` is set to the true size of the attribute + * array's size, and a success status is returned. + * + * If the `size` parameter is greater than or equal to the actual attribute array's size, + * the value of `size` is set to the true size of the attribute array's size, + * the provided memory is filled with the attribute's contents, + * and a success status is returned. + * + * If the `size` parameter is less than the actual attribute array's size and `out` + * is not nullptr, the value of `size` is set to the true size of the attribute array's size + * and a failure status is returned.) + * + * \param[in] info instance + * \param[in] name name of the attribute to be parsed + * \param[out] out pointer to memory where the attribute's contents are to be stored + * \param[in, out] size actual size of attribute array + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttributeArray_float, _In_ const OrtKernelInfo* info, _In_ const char* name, + _Out_ float* out, _Inout_ size_t* size); + + /** \brief Fetch an array of int64_t values stored as an attribute in the graph node + * + * If `out` is nullptr, the value of `size` is set to the true size of the attribute + * array's size, and a success status is returned. + * + * If the `size` parameter is greater than or equal to the actual attribute array's size, + * the value of `size` is set to the true size of the attribute array's size, + * the provided memory is filled with the attribute's contents, + * and a success status is returned. + * + * If the `size` parameter is less than the actual attribute array's size and `out` + * is not nullptr, the value of `size` is set to the true size of the attribute array's size + * and a failure status is returned.) + * + * \param[in] info instance + * \param[in] name name of the attribute to be parsed + * \param[out] out pointer to memory where the attribute's contents are to be stored + * \param[in, out] size actual size of attribute array + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttributeArray_int64, _In_ const OrtKernelInfo* info, _In_ const char* name, + _Out_ int64_t* out, _Inout_ size_t* size); + + /// @} + /// \name OrtArenaCfg + /// @{ + + /** \brief Create an ::OrtArenaCfg + * + * Create the configuration of an arena that can eventually be used to define an arena based allocator's behavior. + * + * Supported keys are (See https://onnxruntime.ai/docs/get-started/with-c.html for details on what the + * following parameters mean and how to choose these values.): + * "max_mem": Maximum memory that can be allocated by the arena based allocator. + * Use 0 for ORT to pick the best value. Default is 0. + * "arena_extend_strategy": 0 = kNextPowerOfTwo, 1 = kSameAsRequested. + * Use -1 to allow ORT to choose the default. + * "initial_chunk_size_bytes": (Possible) Size of the first allocation in the arena. + * Only relevant if arena strategy is `kNextPowerOfTwo`. Use -1 to allow ORT to choose the default. + * Ultimately, the first allocation size is determined by the allocation memory request. + * "max_dead_bytes_per_chunk": Threshold of unused memory in an allocated chunk of arena memory after + * crossing which the current chunk is chunked into 2. + * "initial_growth_chunk_size_bytes": (Possible) Size of the second allocation in the arena. + * Only relevant if arena strategy is `kNextPowerOfTwo`. Use -1 to allow ORT to choose the default. + * "max_power_of_two_extend_bytes": The maximum extend size if arena strategy is `kNextPowerOfTwo`. + * It is not an allocation limit, it is only a limit for extension when requested byte is less than the limit. + * When requested bytes is more than the limit, allocator will still return as requested. + * Use -1 to allow ORT to choose the default 1GB for max_power_of_two_extend_bytes. + * Ultimately, the allocation size is determined by the allocation memory request. + * Further allocation sizes are governed by the arena extend strategy. + * + * \param[in] arena_config_keys Keys to configure the arena + * \param[in] arena_config_values Values to configure the arena + * \param[in] num_keys Number of keys in `arena_config_keys` and `arena_config_values` + * \param[out] out Newly created ::OrtArenaCfg. Must be freed with OrtApi::ReleaseArenaCfg + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateArenaCfgV2, _In_reads_(num_keys) const char* const* arena_config_keys, + _In_reads_(num_keys) const size_t* arena_config_values, _In_ size_t num_keys, + _Outptr_ OrtArenaCfg** out); + + /// @} + /// \name OrtRunOptions + /// @{ + + /** \brief Set a single run configuration entry as a pair of strings + * + * If a configuration with same key exists, this will overwrite the configuration with the given config_value + * + * The config_key and the format of config_value are defined in onnxruntime_run_options_config_keys.h + * + * \param[in] options + * \param[in] config_key A null terminated string representation of the config key + * \param[in] config_value A null terminated string representation of the config value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(AddRunConfigEntry, _Inout_ OrtRunOptions* options, + _In_z_ const char* config_key, _In_z_ const char* config_value); + + /// @} + /// \name OrtPrepackedWeightsContainer + /// @{ + + /** \brief Create an ::OrtPrepackedWeightsContainer + * + * This container will hold pre-packed buffers of shared initializers for sharing between sessions + * (i.e.) if there are shared initializers that can be shared between sessions, the pre-packed buffers + * of these (if any) may possibly be shared to provide memory footprint savings. Pass this container + * to sessions that you would like to share pre-packed buffers of shared initializers at session + * creation time. + * + * \param[out] out Newly created ::OrtPrepackedWeightsContainer. Must be freed with OrtApi::ReleasePrepackedWeightsContainer + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreatePrepackedWeightsContainer, _Outptr_ OrtPrepackedWeightsContainer** out); + + /** \brief Release OrtPrepackedWeightsContainer instance + * + * \note instance must not be released until the sessions using it are released + */ + ORT_CLASS_RELEASE(PrepackedWeightsContainer); + + /// @} + /// \name OrtSession + /// @{ + + /** \brief Create session with prepacked weights container + * + * Same functionality offered by OrtApi::CreateSession except that a container that contains + * pre-packed weights' buffers is written into/read from by the created session. + * This is useful when used in conjunction with OrtApi::AddInitializer which injects + * shared initializer info into sessions. Wherever possible, the pre-packed versions of these + * shared initializers are cached in this container so that multiple sessions can just re-use + * these instead of duplicating these in memory. + * + * \param[in] env OrtEnv instance instance + * \param[in] model_path Null terminated string of the path (wchar on Windows, char otherwise) + * \param[in] options + * \param[in] prepacked_weights_container + * \param[out] out Newly created ::OrtSession. Must be freed with OrtApi::ReleaseSession + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSessionWithPrepackedWeightsContainer, _In_ const OrtEnv* env, _In_ const ORTCHAR_T* model_path, + _In_ const OrtSessionOptions* options, + _Inout_ OrtPrepackedWeightsContainer* prepacked_weights_container, + _Outptr_ OrtSession** out); + + /** \brief Create session from memory with prepacked weights container + * + * Same functionality offered by OrtApi::CreateSessionFromArray except that a container that contains + * pre-packed weights' buffers is written into/read from by the created session. + * This is useful when used in conjunction with OrtApi::AddInitializer which injects + * shared initializer info into sessions. Wherever possible, the pre-packed versions of these + * shared initializers are cached in this container so that multiple sessions can just re-use + * these instead of duplicating these in memory. + * + * \param[in] env + * \param[in] model_data Array of bytes holding the model + * \param[in] model_data_length Number of bytes in `model_data_model` + * \param[in] options + * \param[in] prepacked_weights_container + * \param[out] out Newly created ::OrtSession. Must be freed with OrtApi::ReleaseSession + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSessionFromArrayWithPrepackedWeightsContainer, _In_ const OrtEnv* env, + _In_ const void* model_data, size_t model_data_length, + _In_ const OrtSessionOptions* options, + _Inout_ OrtPrepackedWeightsContainer* prepacked_weights_container, + _Outptr_ OrtSession** out); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Append TensorRT execution provider to the session options + * + * If TensorRT is not available (due to a non TensorRT enabled build), this function will return failure. + * + * This is slightly different from OrtApi::SessionOptionsAppendExecutionProvider_TensorRT, it takes an + * ::OrtTensorRTProviderOptions which is publicly defined. This takes an opaque ::OrtTensorRTProviderOptionsV2 + * which must be created with OrtApi::CreateTensorRTProviderOptions. + * + * For OrtApi::SessionOptionsAppendExecutionProvider_TensorRT, the user needs to instantiate ::OrtTensorRTProviderOptions + * as well as allocate/release buffers for some members of ::OrtTensorRTProviderOptions. + * Here, OrtApi::CreateTensorRTProviderOptions and Ortapi::ReleaseTensorRTProviderOptions will do the memory management for you. + * + * \param[in] options + * \param[in] tensorrt_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_TensorRT_V2, + _In_ OrtSessionOptions* options, _In_ const OrtTensorRTProviderOptionsV2* tensorrt_options); + + /// @} + /// \name OrtTensorRTProviderOptionsV2 + /// @{ + + /** \brief Create an OrtTensorRTProviderOptionsV2 + * + * \param[out] out Newly created ::OrtTensorRTProviderOptionsV2. Must be released with OrtApi::ReleaseTensorRTProviderOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateTensorRTProviderOptions, _Outptr_ OrtTensorRTProviderOptionsV2** out); + + /** \brief Set options in a TensorRT Execution Provider. + * + * Please refer to https://onnxruntime.ai/docs/execution-providers/TensorRT-ExecutionProvider.html#cc + * to know the available keys and values. Key should be in null terminated string format of the member of ::OrtTensorRTProviderOptionsV2 + * and value should be its related range. Recreates the options and only sets the supplied values. + * + * For example, key="trt_max_workspace_size" and value="2147483648" + * + * \param[in] tensorrt_options + * \param[in] provider_options_keys Array of UTF-8 null-terminated string for provider options keys + * \param[in] provider_options_values Array of UTF-8 null-terminated string for provider options values + * \param[in] num_keys Number of elements in the `provider_option_keys` and `provider_options_values` arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(UpdateTensorRTProviderOptions, _Inout_ OrtTensorRTProviderOptionsV2* tensorrt_options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** \brief Get serialized TensorRT provider options string. + * + * For example, "trt_max_workspace_size=2147483648;trt_max_partition_iterations=10;trt_int8_enable=1;......" + * + * \param tensorrt_options - OrtTensorRTProviderOptionsV2 instance + * \param allocator - a ptr to an instance of OrtAllocator obtained with OrtApi::CreateAllocator or OrtApi::GetAllocatorWithDefaultOptions + * the specified allocator will be used to allocate continuous buffers for output strings and lengths. + * \param ptr - is a UTF-8 null terminated string allocated using 'allocator'. The caller is responsible for using the same allocator to free it. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorRTProviderOptionsAsString, _In_ const OrtTensorRTProviderOptionsV2* tensorrt_options, _Inout_ OrtAllocator* allocator, _Outptr_ char** ptr); + + /** \brief Release an ::OrtTensorRTProviderOptionsV2 + * + * \note This is an exception in the naming convention of other Release* functions, as the name of the method does not have the V2 suffix, but the type does + */ + void(ORT_API_CALL* ReleaseTensorRTProviderOptions)(_Frees_ptr_opt_ OrtTensorRTProviderOptionsV2* input); + + /// @} + /// \name OrtSessionOptions + /// @{ + + /** \brief Enable custom operators + * + * See onnxruntime-extensions: https://github.com/microsoft/onnxruntime-extensions.git + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(EnableOrtCustomOps, _Inout_ OrtSessionOptions* options); + + /// @} + /// \name OrtAllocator + /// @{ + + /** \brief Register a custom allocator + * + * Enables sharing between multiple sessions that use the same env instance. + * Returns an error if an allocator with the same ::OrtMemoryInfo is already registered. + * + * The behavior of this is exactly the same as OrtApi::CreateAndRegisterAllocator except + * instead of ORT creating an allocator based on provided info, in this case + * ORT uses the user-provided custom allocator. + * See https://onnxruntime.ai/docs/get-started/with-c.html for details. + * + * \param[in] env + * \param[in] allocator User provided allocator + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(RegisterAllocator, _Inout_ OrtEnv* env, _In_ OrtAllocator* allocator); + + /** \brief Unregister a custom allocator + * + * It is an error if you provide an ::OrtMemoryInfo not corresponding to any + * registered allocators for sharing. + * + * \param[in] env + * \param[in] mem_info + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(UnregisterAllocator, _Inout_ OrtEnv* env, + _In_ const OrtMemoryInfo* mem_info); + + /// @} + /// \name OrtValue + /// @{ + + /** \brief Sets *out to 1 iff an ::OrtValue is a SparseTensor, and 0 otherwise + * + * \param[in] value existing ::OrtValue + * \param[out] out unless an error occurs, contains 1 iff the value contains an instance + * of sparse tensor or 0 otherwise. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(IsSparseTensor, _In_ const OrtValue* value, _Out_ int* out); + + /** \brief Create an ::OrtValue with a sparse tensor that is empty. + * + * Use FillSparseTensor() functions to populate sparse tensor with non-zero values and + * format specific indices data. + * Use ReleaseValue to destroy the sparse tensor, this will also release the buffer inside the output value + * if any was allocated. + * \param[in,out] allocator allocator to use when performing an allocation. Allocation will be performed + * by FillSparseTensor() APIs. The lifespan of the allocator instance must eclipse the lifespan + * this sparse tensor instance as the same allocator will be used to free memory. + * \param[in] dense_shape shape of the original dense tensor + * \param[in] dense_shape_len number of shape dimensions being passed + * \param[in] type must be one of TENSOR_ELEMENT_DATA_TYPE_xxxx + * \param[out] out Should be freed by calling ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSparseTensorAsOrtValue, _Inout_ OrtAllocator* allocator, _In_ const int64_t* dense_shape, + size_t dense_shape_len, ONNXTensorElementDataType type, _Outptr_ OrtValue** out); + + /** + * This fills populates an empty tensor that was created using OrtApi::CreateSparseTensorAsOrtValue. + * This will allocate required memory and copy the supplied NNZ values and COO indices into that memory allocation. + * Memory allocation is performed using the allocator that was specified with OrtApi::CreateSparseTensorAsOrtValue. + * + * \param[in,out] ort_value ::OrtValue to populate with data + * \param[in] data_mem_info serves to identify the location of the data to be copied. If the allocator specified + * at the creation time has memory info that is not the same as mem_info argument to this function a X-device copy will be performed. + * String data is assumed to be on CPU and will only be copied into a CPU allocated buffer. + * \param[in] values_shape pointer to values shape array + * \param[in] values_shape_len length of the values_shape + * \param[in] values pointer to an array of values. For strings, pass const char**. + * \param[in] indices_data pointer to a location of COO indices + * \param[in] indices_num number of COO indices + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(FillSparseTensorCoo, _Inout_ OrtValue* ort_value, _In_ const OrtMemoryInfo* data_mem_info, + _In_ const int64_t* values_shape, size_t values_shape_len, _In_ const void* values, + _In_ const int64_t* indices_data, size_t indices_num); + + /** + * This fills populates an empty tensor that was created using OrtApi::CreateSparseTensorAsOrtValue. + * This will allocate required memory and copy the supplied NNZ values and CSR indices into that memory allocation. + * Memory allocation is performed using the allocator that was specified with OrtApi::CreateSparseTensorAsOrtValue. + * + * \param[in,out] ort_value ::OrtValue to populate with data + * \param[in] data_mem_info serves to identify the location of the data to be copied. If the allocator specified + * at the creation time has memory info that is not the same as mem_info argument to this function a X-device copy will be performed. + * String data is assumed to be on CPU and will only be copied into a CPU allocated buffer. + * \param[in] values_shape pointer to values shape array + * \param[in] values_shape_len length of the values_shape + * \param[in] values - pointer to an array of values. For strings, pass const char**. + * \param[in] inner_indices_data pointer to a location of CSR inner indices + * \param[in] inner_indices_num number of CSR inner indices + * \param[in] outer_indices_data pointer to a location of CSR outer indices + * \param[in] outer_indices_num number of CSR outer indices + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(FillSparseTensorCsr, _Inout_ OrtValue* ort_value, _In_ const OrtMemoryInfo* data_mem_info, + _In_ const int64_t* values_shape, size_t values_shape_len, _In_ const void* values, + _In_ const int64_t* inner_indices_data, size_t inner_indices_num, + _In_ const int64_t* outer_indices_data, size_t outer_indices_num); + + /** + * This fills populates an empty tensor that was created using OrtApi::CreateSparseTensorAsOrtValue. + * This will allocate required memory and copy the supplied NNZ values and BlockSparse indices into that memory allocation. + * Memory allocation is performed using the allocator that was specified with OrtApi::CreateSparseTensorAsOrtValue. + * + * \param[in,out] ort_value ::OrtValue to populate with data + * \param[in] data_mem_info serves to identify the location of the data to be copied. If the allocator specified + * at the creation time has memory info that is not the same as mem_info argument to this function a X-device copy will be performed. + * String data is assumed to be on CPU and will only be copied into a CPU allocated buffer. + * \param[in] values_shape + * \param[in] values_shape_len + * \param[in] values structure with values information + * \param[in] indices_shape_data pointer to a location of indices shape + * \param[in] indices_shape_len length of the block sparse indices shape + * \param[in] indices_data pointer to a location of indices data. Shape will determine the length of the indices data. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(FillSparseTensorBlockSparse, _Inout_ OrtValue* ort_value, _In_ const OrtMemoryInfo* data_mem_info, + _In_ const int64_t* values_shape, size_t values_shape_len, _In_ const void* values, + _In_ const int64_t* indices_shape_data, size_t indices_shape_len, + _In_ const int32_t* indices_data); + + /** + * Create an ::OrtValue with a sparse tensor. This is the first step. + * Next, use UseIndices() functions to supply sparse tensor with + * format specific indices data and set its sparse format to a specific enum value. + * This will not perform memory allocations. It will + * use supplied user buffer which should outlive the created sparse tensor. + * Use OrtApi::ReleaseValue to destroy the sparse tensor. It would not release the supplied values buffer. + * This function can not be used to map strings from the user allocated memory. Strings must always be copied + * and have UTF-8 encoding. Therefore, use OrtApi::CreateSparseTensorAsOrtValue above and then fill it with data + * using appropriate Make*() function. + * + * \param[in] info memory info where sparse values reside. + * \param[in,out] p_data pointer to a user allocated buffer with values. To create a full sparse tensor with no non-zero + * values, pass nullptr + * \param[in] dense_shape shape of the original dense tensor + * \param[in] dense_shape_len number of shape dimensions being passed + * \param[in] values_shape shape of the values data. To create a fully sparse tensor with no non-zero values, + * pass {0} shape. + * \param[in] values_shape_len number of values shape dimensions + * \param[in] type must be one of TENSOR_ELEMENT_DATA_TYPE_xxxx + * \param[out] out Should be freed by calling ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(CreateSparseTensorWithValuesAsOrtValue, _In_ const OrtMemoryInfo* info, _Inout_ void* p_data, + _In_ const int64_t* dense_shape, size_t dense_shape_len, + _In_ const int64_t* values_shape, size_t values_shape_len, + ONNXTensorElementDataType type, _Outptr_ OrtValue** out); + + /** + * This assigns Coo format indices to the SparseTensor that was created by + * OrtApi::CreateSparseTensorWithValuesAsOrtValue above. It also sets OrtSparseFormat to + * ORT_SPARSE_COO. This will not allocate any additional memory for data. The life span of + * indices_data buffer should eclipse the life span of this ::OrtValue. + * + * \param[in,out] ort_value ::OrtValue instance constructed with OrtApi::CreateSparseTensorWithValuesAsOrtValue + * \param[in,out] indices_data pointer to a user pre-allocated buffer or nullptr for fully sparse tensors. + * \param[in] indices_num number of COO indices. Should either be 0 for fully sparse tensors, be equal + * to the number of nnz values specified to OrtApi::CreateSparseTensorWithValuesAsOrtValue for 1-D {nnz} indices or + * be twice as number of nnz values for a 2-D indices {nnz, 2} + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(UseCooIndices, _Inout_ OrtValue* ort_value, _Inout_ int64_t* indices_data, size_t indices_num); + + /** + * The assigns CSR format indices to the SparseTensor that was created by + * OrtApi::CreateSparseTensorWithValuesAsOrtValue above. It also sets OrtSparseFormat to + * ORT_SPARSE_CSRC. This will not allocate any additional memory for data. The life spans of + * inner_data and outer_data buffers should eclipse the life span of this ::OrtValue. + * + * \param[in,out] ort_value ::OrtValue instance constructed with OrtApi::CreateSparseTensorWithValuesAsOrtValue + * \param[in,out] inner_data pointer to a user pre-allocated buffer or nullptr for fully sparse tensors. + * \param[in] inner_num number of inner CSR indices. Should either be 0 for fully sparse tensors or be equal + * to the number of nnz values specified to OrtApi::CreateSparseTensorWithValuesAsOrtValue. + * \param[in,out] outer_data pointer to user pre-allocated buffer or nullptr for fully sparse tensors. + * \param[in] outer_num number of CSR outer indices. Should either be 0 for fully sparse tensors or + * equal to rows + 1 of the dense shape. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(UseCsrIndices, _Inout_ OrtValue* ort_value, _Inout_ int64_t* inner_data, size_t inner_num, + _Inout_ int64_t* outer_data, size_t outer_num); + + /** + * The assigns BlockSparse format indices to the SparseTensor that was created by + * OrtApi::CreateSparseTensorWithValuesAsOrtValue above. It also sets OrtSparseFormat to + * ORT_SPARSE_BLOCK_SPARSE. This will not allocate any additional memory for data. The life span of + * indices_data buffer must eclipse the lifespan of this ::OrtValue. + * + * \param[in,out] ort_value OrtValue instance constructed with OrtApi::CreateSparseTensorWithValuesAsOrtValue + * \param[in] indices_shape pointer to indices shape. Use {0} for fully sparse tensors + * \param[in] indices_shape_len length of the indices shape + * \param[in,out] indices_data pointer to user pre-allocated buffer or nullptr for fully sparse tensors. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(UseBlockSparseIndices, _Inout_ OrtValue* ort_value, const int64_t* indices_shape, size_t indices_shape_len, _Inout_ int32_t* indices_data); + + /** \brief Returns sparse tensor format enum iff a given ort value contains an instance of sparse tensor. + * + * \param[in] ort_value ::OrtValue that contains an instance of sparse tensor + * \param[out] out pointer to out parameter + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSparseTensorFormat, _In_ const OrtValue* ort_value, _Out_ enum OrtSparseFormat* out); + + /** \brief Returns data type and shape of sparse tensor values (nnz) iff ::OrtValue contains a SparseTensor. + * + * \param[in] ort_value An ::OrtValue that contains a fully constructed sparse tensor + * \param[out] out Must be freed by OrtApi::ReleaseTensorTypeAndShapeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSparseTensorValuesTypeAndShape, _In_ const OrtValue* ort_value, _Outptr_ OrtTensorTypeAndShapeInfo** out); + + /** \brief Returns numeric data for sparse tensor values (nnz). For string values use GetStringTensor*(). + * + * \param[in] ort_value an instance of ::OrtValue containing sparse tensor + * \param[out] out returns a pointer to values data. Do not attempt to free this ptr. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSparseTensorValues, _In_ const OrtValue* ort_value, _Outptr_ const void** out); + + /** \brief Returns data type, shape for the type of indices specified by indices_format. + * + * \param[in] ort_value ::OrtValue containing sparse tensor. + * \param[in] indices_format One of the indices formats. It is an error to request a format that the sparse + * tensor does not contain. + * \param[out] out an instance of ::OrtTensorTypeAndShapeInfo. Must be freed by OrtApi::ReleaseTensorTypeAndShapeInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSparseTensorIndicesTypeShape, _In_ const OrtValue* ort_value, enum OrtSparseIndicesFormat indices_format, _Outptr_ OrtTensorTypeAndShapeInfo** out); + + /** \brief Returns indices data for the type of the indices specified by indices_format + * + * \param[in] ort_value ::OrtValue containing sparse tensor. + * \param[in] indices_format One of the indices formats. It is an error to request a format that the sparse tensor does not contain. + * \param[out] num_indices Pointer to where the number of indices entries is returned + * \param[out] indices Returned pointer to the indices data. Do not free the returned pointer as it refers to internal data owned by the ::OrtValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetSparseTensorIndices, _In_ const OrtValue* ort_value, enum OrtSparseIndicesFormat indices_format, _Out_ size_t* num_indices, _Outptr_ const void** indices); + /// @} + /// \name OrtSessionOptions + /// @{ + + /** + * \brief Sets out to 1 iff an optional type OrtValue has an element, 0 otherwise (OrtValue is None) + * Use this API to find if the optional type OrtValue is None or not. + * If the optional type OrtValue is not None, use the OrtValue just like any other OrtValue. + * For example, if you get an OrtValue that corresponds to Optional(tensor) and + * if HasValue() returns true, use it as tensor and so on. + + * \param[in] value Input OrtValue. + * \param[out] out indicating if the input OrtValue contains data (1) or if it is a None (0) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(HasValue, _In_ const OrtValue* value, _Out_ int* out); + + /// @} + /// \name OrtKernelContext + /// Custom operator APIs. + /// @{ + + /** \brief Used for custom operators, gets the GPU compute stream to use to launch the custom a GPU kernel + * \see ::OrtCustomOp + * \param[in] context OrtKernelContext instance + * \param[out] out Returns pointer to a GPU compute stream that can be used to launch the custom GPU kernel. + * If retrieving the GPU compute stream is not relevant (GPU not enabled in the build, kernel partitioned to + * some other EP), then a nullptr is returned as the output param. + * Do not free or mutate the returned pointer as it refers to internal data owned by the underlying session. + * Only use it for custom kernel launching. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelContext_GetGPUComputeStream, _In_ const OrtKernelContext* context, _Outptr_ void** out); + + /// @} + /// \name GetTensorMemoryInfo + /// @{ + /** \brief Returns a pointer to the ::OrtMemoryInfo of a Tensor + * \param[in] value ::OrtValue containing tensor. + * \param[out] mem_info ::OrtMemoryInfo of the tensor. Do NOT free the returned pointer. It is valid for the lifetime of the ::OrtValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetTensorMemoryInfo, _In_ const OrtValue* value, _Out_ const OrtMemoryInfo** mem_info); + + /// @} + /// \name GetExecutionProviderApi + /// @{ + /** \brief Get a pointer to the requested version of the Execution Provider specific + * API extensions to the OrtApi + * \param[in] provider_name The name of the execution provider name. Currently only the following + * values are supported: "DML". + * \param[in] version Must be ::ORT_API_VERSION. + * \param[out] provider_api A void pointer containing a reference to the execution provider versioned api structure. + * For example, the provider_api pointer can be cast to the OrtDmlApi* when the provider_name is "DML". + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetExecutionProviderApi, _In_ const char* provider_name, _In_ uint32_t version, _Outptr_ const void** provider_api); + + /// @} + + /// \name SessionOptions + /// @{ + /** \brief Set custom thread creation function + * + * \param[in] options Session options + * \param[in] ort_custom_create_thread_fn Custom thread creation function + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsSetCustomCreateThreadFn, _Inout_ OrtSessionOptions* options, _In_ OrtCustomCreateThreadFn ort_custom_create_thread_fn); + + /** \brief Set creation options for custom thread + * + * \param[in] options Session options + * \param[in] ort_custom_thread_creation_options Custom thread creation options (can be nullptr) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsSetCustomThreadCreationOptions, _Inout_ OrtSessionOptions* options, _In_ void* ort_custom_thread_creation_options); + + /** \brief Set custom thread join function + * + * \param[in] options Session options + * \param[in] ort_custom_join_thread_fn Custom join thread function, must not be nullptr when ort_custom_create_thread_fn is set + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SessionOptionsSetCustomJoinThreadFn, _Inout_ OrtSessionOptions* options, _In_ OrtCustomJoinThreadFn ort_custom_join_thread_fn); + /// @} + + /// \name OrtThreadingOptions + /// @{ + /** \brief Set custom thread creation function for global thread pools + * + * \param[inout] tp_options + * \param[in] ort_custom_create_thread_fn Custom thread creation function + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalCustomCreateThreadFn, _Inout_ OrtThreadingOptions* tp_options, _In_ OrtCustomCreateThreadFn ort_custom_create_thread_fn); + + /** \brief Set custom thread creation options for global thread pools + * + * \param[inout] tp_options + * \param[in] ort_custom_thread_creation_options Custom thread creation options (can be nullptr) + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalCustomThreadCreationOptions, _Inout_ OrtThreadingOptions* tp_options, _In_ void* ort_custom_thread_creation_options); + + /** \brief Set custom thread join function for global thread pools + * + * \param[inout] tp_options + * \param[in] ort_custom_join_thread_fn Custom thread join function, must not be nullptr when global ort_custom_create_thread_fn is set + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SetGlobalCustomJoinThreadFn, _Inout_ OrtThreadingOptions* tp_options, _In_ OrtCustomJoinThreadFn ort_custom_join_thread_fn); + /// @} + + /** \brief Synchronize bound inputs. The call may be necessary for some providers, such as cuda, + * in case the system that allocated bound memory operated on a different stream. However, the + * operation is provider specific and could be a no-op. + * + * \param[inout] binding_ptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SynchronizeBoundInputs, _Inout_ OrtIoBinding* binding_ptr); + + /** \brief Synchronize bound outputs. The call may be necessary for some providers, such as cuda, + * in case the system that allocated bound memory operated on a different stream. However, the + * operation is provider specific and could be a no-op. + * + * \param[inout] binding_ptr + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(SynchronizeBoundOutputs, _Inout_ OrtIoBinding* binding_ptr); + + /// \name OrtSessionOptions + /// @{ + + /** \brief Append CUDA execution provider to the session options + * + * If CUDA is not available (due to a non CUDA enabled build), this function will return failure. + * + * This is slightly different from OrtApi::SessionOptionsAppendExecutionProvider_CUDA, it takes an + * ::OrtCUDAProviderOptions which is publicly defined. This takes an opaque ::OrtCUDAProviderOptionsV2 + * which must be created with OrtApi::CreateCUDAProviderOptions. + * + * For OrtApi::SessionOptionsAppendExecutionProvider_CUDA, the user needs to instantiate ::OrtCUDAProviderOptions + * as well as allocate/release buffers for some members of ::OrtCUDAProviderOptions. + * Here, OrtApi::CreateCUDAProviderOptions and Ortapi::ReleaseCUDAProviderOptions will do the memory management for you. + * + * \param[in] options + * \param[in] cuda_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.11. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_CUDA_V2, + _In_ OrtSessionOptions* options, _In_ const OrtCUDAProviderOptionsV2* cuda_options); + + /// @} + /// \name OrtCUDAProviderOptionsV2 + /// @{ + + /** \brief Create an OrtCUDAProviderOptionsV2 + * + * \param[out] out Newly created ::OrtCUDAProviderOptionsV2. Must be released with OrtApi::ReleaseCudaProviderOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.11. + */ + ORT_API2_STATUS(CreateCUDAProviderOptions, _Outptr_ OrtCUDAProviderOptionsV2** out); + + /** \brief Set options in a CUDA Execution Provider. + * + * Please refer to https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#configuration-options + * to know the available keys and values. Key should be in null terminated string format of the member of ::OrtCUDAProviderOptionsV2 + * and value should be its related range. Recreates the options and only sets the supplied values. + * + * For example, key="device_id" and value="0" + * + * \param[in] cuda_options + * \param[in] provider_options_keys Array of UTF-8 null-terminated string for provider options keys + * \param[in] provider_options_values Array of UTF-8 null-terminated string for provider options values + * \param[in] num_keys Number of elements in the `provider_option_keys` and `provider_options_values` arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.11. + */ + ORT_API2_STATUS(UpdateCUDAProviderOptions, _Inout_ OrtCUDAProviderOptionsV2* cuda_options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** + * Get serialized CUDA provider options string. + * + * For example, "device_id=0;arena_extend_strategy=0;......" + * + * \param cuda_options - OrtCUDAProviderOptionsV2 instance + * \param allocator - a ptr to an instance of OrtAllocator obtained with CreateAllocator() or GetAllocatorWithDefaultOptions() + * the specified allocator will be used to allocate continuous buffers for output strings and lengths. + * \param ptr - is a UTF-8 null terminated string allocated using 'allocator'. The caller is responsible for using the same allocator to free it. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.11. + */ + ORT_API2_STATUS(GetCUDAProviderOptionsAsString, _In_ const OrtCUDAProviderOptionsV2* cuda_options, _Inout_ OrtAllocator* allocator, _Outptr_ char** ptr); + + /** \brief Release an ::OrtCUDAProviderOptionsV2 + * + * \note This is an exception in the naming convention of other Release* functions, as the name of the method does not have the V2 suffix, but the type does + * + * \since Version 1.11. + */ + void(ORT_API_CALL* ReleaseCUDAProviderOptions)(_Frees_ptr_opt_ OrtCUDAProviderOptionsV2* input); + + /// @} + + /** \brief Append MIGraphX provider to session options + * + * If MIGraphX is not available (due to a non MIGraphX enabled build, or if MIGraphX is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] migraphx_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.11. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_MIGraphX, + _In_ OrtSessionOptions* options, _In_ const OrtMIGraphXProviderOptions* migraphx_options); + + /** \brief Replace initialized Tensors with external data with the data provided in initializers. + * + * The function will find the initialized TensorProtos with external data in the graph with the provided names and + * replace them with the provided tensors. The API verifies that the TensorProto being replaced + * has an external data reference and has the same name, dimensions and data type as its replacement. The replacement + * will occur before any of the optimizations take place. The data will be copied into the graph + * since TensorProto can't refer to the user provided buffers. + * + * Once the model has been loaded, the OrtValue(s) added to SessionOptions instance will be removed + * from the internal SessionOptions copy to save memory, the user provided buffers can then be deallocated + * and the SessionOptions instance that refers to them can be destroyed. + * + * \param[in] options + * \param[in] initializer_names Array of null terminated UTF-8 encoded strings of the initializers names. + * \param[in] initializers Array of ::OrtValue type + * \param[in] num_initializers Number of elements in the initializer_names and initializers + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.12. + */ + ORT_API2_STATUS(AddExternalInitializers, _In_ OrtSessionOptions* options, + _In_reads_(num_initializers) const char* const* initializer_names, + _In_reads_(num_initializers) const OrtValue* const* initializers, size_t num_initializers); + + /** \brief: Create attribute of onnxruntime operator + * + * \param[in] name Name of the attribute + * \param[in] data Data content of the attribute + * \param[in] len Number of bytes stored in data for ORT_OP_ATTR_STRING. + Number of elements if data represents an array (e.g., ORT_OP_ATTR_INTS). Otherwise, set to 1. + * \param[in] type Data type + * \param[out] op_attr Attribute that has been created, which must be released by OrtApi::ReleaseOpAttr + * + * \since Version 1.12. + */ + ORT_API2_STATUS(CreateOpAttr, + _In_ const char* name, + _In_ const void* data, + _In_ int len, + _In_ OrtOpAttrType type, + _Outptr_ OrtOpAttr** op_attr); + + /* \brief: Release op attribute + * + * \param[in] opAttr Attribute created by OrtApi::CreateOpAttr + * + * \since Version 1.12. + */ + ORT_CLASS_RELEASE(OpAttr); + + /** \brief: Create onnxruntime native operator + * + * \param[in] info Kernel info + * \param[in] op_name Operator name + * \param[in] domain Operator domain + * \param[in] version Operator opset version + * \param[in] type_constraint_names Name of the type constraints, such as "T" or "T1" + * \param[in] type_constraint_values Type of each constraints + * \param[in] type_constraint_count Number of constraints + * \param[in] attr_values Attributes used to initialize the operator + * \param[in] attr_count Number of the attributes + * \param[in] input_count Number of inputs + * \param[in] output_count Number of outputs + * \param[out] ort_op Operator that has been created + * + * \since Version 1.12. + */ + ORT_API2_STATUS(CreateOp, + _In_ const OrtKernelInfo* info, + _In_z_ const char* op_name, + _In_z_ const char* domain, + int version, + _In_reads_(type_constraint_count) const char** type_constraint_names, + _In_reads_(type_constraint_count) const ONNXTensorElementDataType* type_constraint_values, + int type_constraint_count, + _In_reads_(attr_count) const OrtOpAttr* const* attr_values, + int attr_count, + int input_count, + int output_count, + _Outptr_ OrtOp** ort_op); + + /** \brief: Invoke the operator created by OrtApi::CreateOp + * The inputs must follow the order as specified in onnx specification + * + * \param[in] context Kernel context + * \param[in] ort_op Operator that has been created + * \param[in] input_values Array of inputs + * \param[in] input_count Number of inputs + * \param[in] output_values Array of outputs + * \param[in] output_count Number of outputs + * + * \since Version 1.12. + */ + ORT_API2_STATUS(InvokeOp, + _In_ const OrtKernelContext* context, + _In_ const OrtOp* ort_op, + _In_ const OrtValue* const* input_values, + _In_ int input_count, + _Inout_ OrtValue* const* output_values, + _In_ int output_count); + + /* \brief: Release an onnxruntime operator + * + * \param[in] Op Operator created by OrtApi::CreateOp + * + * \since Version 1.12. + */ + ORT_CLASS_RELEASE(Op); + + /** \brief: Append execution provider to the session options. + * \param[in] options + * \param[in] provider_name - provider to add. + * \param[in] provider_options_keys - keys to configure the provider options + * \param[in] provider_options_values - values to configure the provider options + * \param[in] num_keys - number of keys passed in + * + * Currently supported provider names: + * QNNExecutionProvider (or QNN) + * OpenVINOExecutionProvider (or OpenVINO) + * XnnpackExecutionProvider (or XNNPACK) + * WebNNExecutionProvider (or WEBNN) + * WebGpuExecutionProvider (or WebGPU) + * AzureExecutionProvider (or AZURE) + * JsExecutionProvider (or JS) + * VitisAIExecutionProvider (or VitisAI) + * CoreMLExecutionProvider (or CoreML) + * + * Note: If an execution provider has a dedicated SessionOptionsAppendExecutionProvider_ function + * that should be used to add it. + * + * QNN supported keys: + * "backend_type": Type of QNN backend. Specifies a backend path that is the associated QNN backend library file + * name. E.g., given backend type "htp", on Windows, the backend path would be "QnnHtp.dll", and on other + * platforms, it would be "libQnnHtp.so". Mutually exclusive with "backend_path". + * Available options: + * -# "cpu" + * -# "gpu" + * -# "htp": Default. + * -# "saver" + * -# "ir" + * "backend_path": File path to QNN backend library. Mutually exclusive with "backend_type". + * "profiling_level": QNN profiling level. + * Available options: + * -# "off": Default. + * -# "basic" + * -# "detailed" + * "profiling_file_path": QNN profiling file path if ETW not enabled. + * "rpc_control_latency": QNN RPC control latency. + * "vtcm_mb": QNN VTCM size in MB. default to 0(not set). + * "htp_performance_mode": QNN performance mode. + * Available options: + * -# "burst" + * -# "balanced" + * -# "default": Default. + * -# "high_performance" + * -# "high_power_saver" + * -# "low_balanced" + * -# "extreme_power_saver" + * -# "low_power_saver" + * -# "power_saver" + * -# "sustained_high_performance" + * "dump_qnn_ir_dlc": Use the QnnIr backend library to write .dlc files for each subgraph dispatched to QNN. When + * enabled, inference results will be incorrect. Use only for debugging. + * -# "0": Default: disabled + * -# "1": enabled + * "dump_qnn_ir_dlc_dir": Set the directory into which QnnIr will be configured to write QNN graphs as .dlc files. + * Default is current working directory. + * "qnn_ir_backend_path": File path to the QnnIr backend library. If "dump_qnn_ir_dlc" is enabled, use this path + * instead of looking for the Ir backend in the standard location. + * "qnn_saver_path": File path to the QNN Saver backend library. If specified, QNN Saver will be enabled and will + * dump QNN API calls to disk for replay/debugging. QNN Saver produces incorrect model inference results and + * may alter model/EP partitioning. Use only for debugging. + * "qnn_context_priority": QNN context priority. + * Available options: + * -# "low" + * -# "normal": Default. + * -# "normal_high" + * -# "high" + * "htp_graph_finalization_optimization_mode": Set the optimization mode for graph finalization on the HTP backend. + * Available options: + * -# "0": Default. + * -# "1": Faster preparation time, less optimal graph. + * -# "2": Longer preparation time, more optimal graph. + * -# "3": Longest preparation time, most likely even more optimal graph. See QNN SDK documentation for specific + * details. + * "soc_model": The SoC model number. Refer to the QNN SDK documentation for valid values. + * Defaults to "0" (unknown). + * "htp_arch": The minimum HTP architecture the driver will use to select compatible QNN operators. + * Available options: + * -# "0": Default (none). + * -# "68" + * -# "69" + * -# "73" + * -# "75" + * "device_id": The ID of the device to use when setting 'htp_arch'. Defaults to "0" (for single device). + * "enable_htp_fp16_precision": Used for float32 model for HTP backend. + * Enable the float32 model to be inferenced with fp16 precision. Otherwise, it will be fp32 precision. + * -# "0": With fp32 precision. + * -# "1": Default. With fp16 precision. + * "offload_graph_io_quantization": Offload graph input quantization and graph output dequantization to another + * execution provider (typically CPU EP). + * -# "0": Disabled. QNN EP will handle quantization and dequantization of graph I/O. + * -# "1": Enabled. This is the default value. + * "enable_htp_spill_fill_buffer": Enable HTP spill fill buffer setting. The flag is used while generating context + * binary. + * -# "0": Default. Disabled. + * -# "1": Enabled. + * "enable_htp_shared_memory_allocator": Enable the QNN HTP shared memory allocator. Requires libcdsprpc.so/dll to + * be available. + * -# "0": Default. Disabled. + * -# "1": Enabled. + * "dump_json_qnn_graph": Set to "1" to dump QNN graphs generated by QNN EP as JSON files. Each graph partition + * assigned to QNN EP is dumped to a separate file. + * "json_qnn_graph_dir": Directory in which to dump QNN JSON graphs. If not specified, QNN graphs are dumped in the + * program's current working directory. Ignored if "dump_json_qnn_graph" is not set. + * "op_packages": QNN UDO op_package for QNN EP, allowed format: + *   "::[:],::[:]", + *   where op_type is the name of the operation, op_package_path is the path to the op package shared library, + * interface is the symbol name to register the op life cycle functions, and target is the backend type. For more + * details, refer to: https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/op_packages.html + * + * XNNPACK supported keys: + * "intra_op_num_threads": number of thread-pool size to use for XNNPACK execution provider. + * default value is 0, which means to use the session thread-pool size. + * + * \since Version 1.12. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider, _In_ OrtSessionOptions* options, + _In_ const char* provider_name, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /* \brief: Get a copy of kernel info + * + * \param[in] info Kernel info + * \param[out] info_copy Copy of kernel info + * + * \since Version 1.12. + */ + ORT_API2_STATUS(CopyKernelInfo, + _In_ const OrtKernelInfo* info, + _Outptr_ OrtKernelInfo** info_copy); + + /* \brief: Release kernel info + * + * \param[in] KernelInfo A copy of kernel info returned by CopyKernelInfo + * + * \since Version 1.12. + */ + ORT_CLASS_RELEASE(KernelInfo); + + /// \name Ort Training + /// @{ + /** \brief Gets the Training C Api struct + * + * Call this function to access the ::OrtTrainingApi structure that holds pointers to functions that enable + * training with onnxruntime. + * \note A NULL pointer will be returned and no error message will be printed if the training api + * is not supported with this build. A NULL pointer will be returned and an error message will be + * printed if the provided version is unsupported, for example when using a runtime older than the + * version created with this header file. + * + * \param[in] version Must be ::ORT_API_VERSION + * \return The ::OrtTrainingApi struct for the version requested. + * + * \since Version 1.13 + */ + const OrtTrainingApi*(ORT_API_CALL* GetTrainingApi)(uint32_t version)NO_EXCEPTION; + + /// @} + + /** \brief Append CANN provider to session options + * + * If CANN is not available (due to a non CANN enabled build, or if CANN is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] cann_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.13. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_CANN, + _In_ OrtSessionOptions* options, _In_ const OrtCANNProviderOptions* cann_options); + + /** \brief Create an OrtCANNProviderOptions + * + * \param[out] out created ::OrtCANNProviderOptions. Must be released with OrtApi::ReleaseCANNProviderOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.13. + */ + ORT_API2_STATUS(CreateCANNProviderOptions, _Outptr_ OrtCANNProviderOptions** out); + + /** \brief Set options in a CANN Execution Provider. + * + * \param[in] cann_options + * \param[in] provider_options_keys Array of UTF-8 null-terminated string for provider options keys + * \param[in] provider_options_values Array of UTF-8 null-terminated string for provider options values + * \param[in] num_keys Number of elements in the `provider_option_keys` and `provider_options_values` arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.13. + */ + ORT_API2_STATUS(UpdateCANNProviderOptions, _Inout_ OrtCANNProviderOptions* cann_options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** \brief Get serialized CANN provider options string. + * + * \param[in] cann_options OrtCANNProviderOptions instance + * \param[in] allocator a ptr to an instance of OrtAllocator obtained with CreateAllocator() + * or GetAllocatorWithDefaultOptions(), the specified allocator will be used to allocate + * continuous buffers for output strings and lengths. + * \param[out] ptr is a UTF-8 null terminated string allocated using 'allocator'. + * The caller is responsible for using the same allocator to free it. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.13. + */ + ORT_API2_STATUS(GetCANNProviderOptionsAsString, _In_ const OrtCANNProviderOptions* cann_options, + _Inout_ OrtAllocator* allocator, _Outptr_ char** ptr); + + /** \brief Release an OrtCANNProviderOptions + * + * \param[in] input The pointer of OrtCANNProviderOptions which will been deleted + * + * \since Version 1.13. + */ + void(ORT_API_CALL* ReleaseCANNProviderOptions)(_Frees_ptr_opt_ OrtCANNProviderOptions* input); + + /* \brief Get OrtDevice type from MemoryInfo + * + * \since Version 1.14 + */ + void(ORT_API_CALL* MemoryInfoGetDeviceType)(_In_ const OrtMemoryInfo* ptr, _Out_ OrtMemoryInfoDeviceType* out); + + /* \brief Update the OrtEnv instance with custom log severity level + * + * \param[in] ort_env The OrtEnv instance being used + * \param[in] log_severity_level The log severity level. + * + * \since Version 1.14. + */ + ORT_API2_STATUS(UpdateEnvWithCustomLogLevel, _In_ OrtEnv* ort_env, OrtLoggingLevel log_severity_level); + + /* \brief Set affinities for intra op threads + * + * Affinity string follows format: + * logical_processor_id,logical_processor_id;logical_processor_id,logical_processor_id + * Semicolon isolates configurations among threads, while comma split processors where ith thread expected to attach to. + * e.g. 1,2,3;4,5 + * specifies affinities for two threads, with the 1st thread attach to the 1st, 2nd, and 3rd processor, and 2nd thread to the 4th and 5th. + * To ease the configuration, an "interval" is also allowed: + * e.g. 1-8;8-16;17-24 + * orders that the 1st thread runs on first eight processors, 2nd thread runs on next eight processors, and so forth. + * Note: + * 1. Once set, the number of thread affinities must equal to intra_op_num_threads - 1, + * ort does not set affinity on the main thread which is started and managed by the calling app; + * 2. For windows, ort will infer the group id from a logical processor id, for example, assuming there are two groups with each has 64 logical processors, + * an id of 64 will be inferred as the last processor of the 1st group, while 65 will be interpreted as the 1st processor of the second group. + * Hence 64-65 is an invalid configuration, because a windows thread cannot be attached to processors across group boundary. + * + * \since Version 1.14 + */ + ORT_API2_STATUS(SetGlobalIntraOpThreadAffinity, _Inout_ OrtThreadingOptions* tp_options, const char* affinity_string); + + /** \brief Register custom ops from a shared library. + * + * Loads a shared library (.dll on windows, .so on linux, etc) named 'library_name' and looks for this entry point: + * OrtStatus* RegisterCustomOps(OrtSessionOptions * options, const OrtApiBase* api); + * It then passes in the provided session options to this function along with the api base. + * + * The handle to the loaded library is automatically released by ORT when the last OrtSession that references the + * library handle is released. If no OrtSession is created, then the library handle is released when the provided + * OrtSessionOptions is released. + * + * \param[in] options The session options. + * \param[in] library_name The name of the shared library to load and register. Refer to OS-specific dynamic library + * loading utilities (e.g., LoadLibraryEx on Windows or dlopen on Linux/MacOS) for information + * on the format of library names and search paths. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(RegisterCustomOpsLibrary_V2, _Inout_ OrtSessionOptions* options, _In_ const ORTCHAR_T* library_name); + + /** \brief Register custom ops by calling a RegisterCustomOpsFn function. + * + * Searches for registration_func_name and if found calls it. + * + * The library containing the function must either be linked against or previously loaded by the executable. + * + * If you want ONNX Runtime to load the library and manage its lifetime, use RegisterCustomOpsLibrary_V2. + * + * RegisterCustomOpsUsingFunction can be used in scenarios where it may not be possible for ONNX Runtime to load + * the library from a path. e.g. mobile platforms where the library must be linked into the app. + * + * The registration function must have the signature of RegisterCustomOpsFn: + * OrtStatus* (*fn)(OrtSessionOptions* options, const OrtApiBase* api); + * + * See https://onnxruntime.ai/docs/reference/operators/add-custom-op.html for details on how the registration + * function should be implemented. + * + * \param[in] options OrtSessionOptions that is passed through as the first argument in the call to the + * registration function. + * \param[in] registration_func_name Name of registration function to use. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(RegisterCustomOpsUsingFunction, _Inout_ OrtSessionOptions* options, + _In_ const char* registration_func_name); + + /// \name OrtKernelInfo + /// Custom operator APIs. + /// @{ + + /** \brief Get the number of inputs from ::OrtKernelInfo. + * + * Used in the CreateKernel callback of an OrtCustomOp to query the number of inputs + * during kernel/session creation. + * + * \param[in] info Instance of ::OrtKernelInfo. + * \param[out] out Pointer to variable assigned with the result on success. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetInputCount, _In_ const OrtKernelInfo* info, _Out_ size_t* out); + + /** \brief Get the number of outputs from ::OrtKernelInfo. + * + * Used in the CreateKernel callback of an OrtCustomOp to query the number of outputs + * during kernel/session creation. + * + * \param[in] info Instance of ::OrtKernelInfo. + * \param[out] out Pointer to variable assigned with the result on success. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetOutputCount, _In_ const OrtKernelInfo* info, _Out_ size_t* out); + + /** \brief Get the name of a ::OrtKernelInfo's input. + * + * Used in the CreateKernel callback of an OrtCustomOp to query an input's name + * during kernel/session creation. + * + * If `out` is nullptr, the value of `size` is set to the size of the name + * string (including null-terminator), and a success status is returned. + * + * If the `size` parameter is greater than or equal to the name string's size, + * the value of `size` is set to the true size of the string (including null-terminator), + * the provided memory is filled with the string's contents, and a success status is returned. + * + * If the `size` parameter is less than the actual string's size and `out` + * is not nullptr, the value of `size` is set to the true size of the string + * and a failure status is returned. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[in] index The index of the input name to get. Returns a failure status if out-of-bounds. + * \param[out] out Memory location into which to write the UTF-8 null-terminated string representing the input's name. + * \param[in,out] size Pointer to the size of the `out` buffer. See above comments for details. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetInputName, _In_ const OrtKernelInfo* info, size_t index, _Out_ char* out, + _Inout_ size_t* size); + + /** \brief Get the name of a ::OrtKernelInfo's output. + * + * Used in the CreateKernel callback of an OrtCustomOp to query an output's name + * during kernel/session creation. + * + * If `out` is nullptr, the value of `size` is set to the size of the name + * string (including null-terminator), and a success status is returned. + * + * If the `size` parameter is greater than or equal to the name string's size, + * the value of `size` is set to the true size of the string (including null-terminator), + * the provided memory is filled with the string's contents, and a success status is returned. + * + * If the `size` parameter is less than the actual string's size and `out` + * is not nullptr, the value of `size` is set to the true size of the string + * and a failure status is returned. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[in] index The index of the output name to get. Returns a failure status if out-of-bounds. + * \param[out] out Memory location into which to write the UTF-8 null-terminated string representing the output's + * name. + * \param[in,out] size Pointer to the size of the `out` buffer. See above comments for details. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetOutputName, _In_ const OrtKernelInfo* info, size_t index, _Out_ char* out, + _Inout_ size_t* size); + + /** \brief Get the type information for a ::OrtKernelInfo's input. + * + * Used in the CreateKernel callback of an OrtCustomOp to query the shape and type information + * of an input during kernel/session creation. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[in] index Which input to get the type information for + * \param[out] type_info Pointer set to the resulting ::OrtTypeInfo. Must be freed with OrtApi::ReleaseTypeInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetInputTypeInfo, _In_ const OrtKernelInfo* info, size_t index, + _Outptr_ OrtTypeInfo** type_info); + + /** \brief Get the type information for a ::OrtKernelInfo's output. + * + * Used in the CreateKernel callback of an OrtCustomOp to query the shape and type information + * of an output during kernel/session creation. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[in] index Which input to get the type information for + * \param[out] type_info Pointer set to the resulting ::OrtTypeInfo. Must be freed with OrtApi::ReleaseTypeInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(KernelInfo_GetOutputTypeInfo, _In_ const OrtKernelInfo* info, size_t index, + _Outptr_ OrtTypeInfo** type_info); + + /** \brief Get a ::OrtValue tensor stored as an attribute in the graph node. + * + * Used in the CreateKernel callback of an OrtCustomOp to get a tensor attribute. + * + * \param[in] info ::OrtKernelInfo instance. + * \param[in] name UTF-8 null-terminated string representing the attribute's name. + * \param[in] allocator Allocator used to allocate the internal tensor state. + * \param[out] out Returns newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue, + * which will also free internal tensor state allocated with the provided allocator. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(KernelInfoGetAttribute_tensor, _In_ const OrtKernelInfo* info, _In_z_ const char* name, + _Inout_ OrtAllocator* allocator, _Outptr_ OrtValue** out); + + /// @} + /// \name OrtSessionOptions + /// Custom operator APIs + /// @{ + + /** \brief Checks if the given session configuration entry exists. + * + * The config_key formats are defined in onnxruntime_session_options_config_keys.h + * + * Can be used in a custom operator library to check for session configuration entries + * that target one or more custom operators in the library. Example: The config entry + * custom_op.myop.some_key targets a custom op named "myop". + * + * \param[in] options The ::OrtSessionOptions instance. + * \param[in] config_key A null-terminated UTF-8 string representation of the configuration key. + * \param[out] out Pointer set to 1 if the entry exists and 0 otherwise. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(HasSessionConfigEntry, _In_ const OrtSessionOptions* options, + _In_z_ const char* config_key, _Out_ int* out); + + /** \brief Get a session configuration value. + * + * Returns a failure status if the configuration key does not exist. + * The config_key and the format of config_value are defined in onnxruntime_session_options_config_keys.h + * + * If `config_value` is nullptr, the value of `size` is set to the true size of the string + * value (including null-terminator), and a success status is returned. + * + * If the `size` parameter is greater than or equal to the actual string value's size, + * the value of `size` is set to the true size of the string value, the provided memory + * is filled with the value's contents, and a success status is returned. + * + * If the `size` parameter is less than the actual string value's size and `config_value` + * is not nullptr, the value of `size` is set to the true size of the string value + * and a failure status is returned. + * + * Can be used in a custom operator library to get session configuration entries + * that target one or more custom operators in the library. Example: The config entry + * custom_op.myop.some_key targets a custom op named "myop". + * + * \param[in] options The session options. + * \param[in] config_key A null-terminated UTF-8 string representation of the config key. + * \param[in] config_value Pointer to memory where the null-terminated UTF-8 string value will be stored. + * \param[in,out] size Pointer to the size of the `config_value` buffer. See above comments for details. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.14 + */ + ORT_API2_STATUS(GetSessionConfigEntry, _In_ const OrtSessionOptions* options, + _In_z_ const char* config_key, _Out_ char* config_value, _Inout_ size_t* size); + + /// @} + + /** \brief Append dnnl provider to session options + * + * If oneDNN is not available, this function will return failure. + * + * \param[in] options + * \param[in] dnnl_options + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_Dnnl, + _In_ OrtSessionOptions* options, _In_ const OrtDnnlProviderOptions* dnnl_options); + + /** \brief Create an OrtDnnlProviderOptions + * + * \param[out] out Newly created ::OrtDnnlProviderOptions. Must be released with OrtApi::ReleaseDnnlProviderOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(CreateDnnlProviderOptions, _Outptr_ OrtDnnlProviderOptions** out); + + /** \brief Set options in a oneDNN Execution Provider. + * + * Key should be in null terminated string format of the member of ::OrtDnnlProviderOptions + * and value should be its related range. + * + * For example, key="use_arena" and value="1" + * + * \param[in] dnnl_options + * \param[in] provider_options_keys Array of UTF-8 null-terminated string for provider options keys + * \param[in] provider_options_values Array of UTF-8 null-terminated string for provider options values + * \param[in] num_keys Number of elements in the `provider_option_keys` and `provider_options_values` arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(UpdateDnnlProviderOptions, _Inout_ OrtDnnlProviderOptions* dnnl_options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** + * Get serialized oneDNN provider options string. + * + * For example, "use_arena=1;......" + * + * \param dnnl_options - OrtDnnlProviderOptions instance + * \param allocator - a ptr to an instance of OrtAllocator obtained with CreateAllocator() or GetAllocatorWithDefaultOptions() + * the specified allocator will be used to allocate continuous buffers for output strings and lengths. + * \param ptr - is a UTF-8 null terminated string allocated using 'allocator'. The caller is responsible for using the same allocator to free it. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(GetDnnlProviderOptionsAsString, _In_ const OrtDnnlProviderOptions* dnnl_options, _Inout_ OrtAllocator* allocator, _Outptr_ char** ptr); + + /** \brief Release an ::OrtDnnlProviderOptions + * + * \since Version 1.15. + */ + void(ORT_API_CALL* ReleaseDnnlProviderOptions)(_Frees_ptr_opt_ OrtDnnlProviderOptions* input); + + /// \name OrtKernelInfo + /// Custom operator APIs. + /// @{ + + /** \brief Get the graph node name from ::OrtKernelInfo. + * + * If `out` is nullptr, the value of `size` is set to the size of the name + * string (including null-terminator), and a success status is returned. + * + * If the `size` parameter is greater than or equal to the name string's size, + * the value of `size` is set to the true size of the string (including null-terminator), + * the provided memory is filled with the string's contents, and a success status is returned. + * + * If the `size` parameter is less than the actual string's size and `out` + * is not nullptr, the value of `size` is set to the true size of the string + * and a failure status is returned. + * + * Can be used in a custom operator's CreateKernel callback to get the name of the operator's node name in the graph. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[out] out Memory location into which to write the UTF-8 null-terminated string representing the name. + * \param[in,out] size Pointer to the size of the `out` buffer. See above comments for details. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.15 + */ + ORT_API2_STATUS(KernelInfo_GetNodeName, _In_ const OrtKernelInfo* info, _Out_ char* out, _Inout_ size_t* size); + + /** \brief Get the session logger from ::OrtKernelInfo. + * + * Used in the CreateKernel callback of an OrtCustomOp to get a logger that can be used to log + * messages. + * + * \param[in] info An instance of ::OrtKernelInfo. + * \param[out] logger Pointer set to the session's ::OrtLogger. Owned by ONNX Runtime, so do not free. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.15 + */ + ORT_API2_STATUS(KernelInfo_GetLogger, _In_ const OrtKernelInfo* info, _Outptr_ const OrtLogger** logger); + + /// @} + /// \name OrtKernelContext + /// Custom operator APIs. + /// @{ + + /** \brief Get the runtime logger from ::OrtKernelContext. + * + * Used in the KernelCompute callback of an OrtCustomOp to get a logger that can be used to log + * messages during inference. + * + * \param[in] context An instance of ::OrtKernelContext. + * \param[out] logger Pointer set to the kernel context's ::OrtLogger. Owned by ONNX Runtime, so do not free. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.15 + */ + ORT_API2_STATUS(KernelContext_GetLogger, _In_ const OrtKernelContext* context, _Outptr_ const OrtLogger** logger); + + /// @} + /// \name OrtLogger + /// Custom operator APIs. + /// @{ + + /** \brief Logs a message at the given severity level using the provided ::OrtLogger. + * + * Only messages with a severity level equal or greater than the ::OrtLogger's logging severity level + * are logged. Use OrtApi::Logger_GetLoggingSeverityLevel to get the ::OrtLogger's logging severity + * level. + * + * Can be used in custom operators to log messages with the logger retrieved via OrtApi::KernelInfo_GetLogger. + * + * \param[in] logger The ::OrtLogger instance. + * \param[in] log_severity_level The message's severity level. + * \param[in] message The message to log. + * \param[in] file_path The filepath of the file in which the message is logged. Usually the value of ORT_FILE. + * \param[in] line_number The file line number in which the message is logged. Usually the value of __LINE__. + * \param[in] func_name The name of the function in which the message is logged. Usually the value of __FUNCTION__. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.15 + */ + ORT_API2_STATUS(Logger_LogMessage, _In_ const OrtLogger* logger, OrtLoggingLevel log_severity_level, + _In_z_ const char* message, _In_z_ const ORTCHAR_T* file_path, int line_number, + _In_z_ const char* func_name); + + /** \brief Get the logging severity level of the ::OrtLogger. + * + * Can be used in a custom operator to get the logging severity level of the ::OrtLogger associated with + * the ::OrtKernelInfo. + * + * \param[in] logger The ::OrtLogger instance. + * \param[out] out Pointer to variable assigned with the logging severity level on success. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.15 + */ + ORT_API2_STATUS(Logger_GetLoggingSeverityLevel, _In_ const OrtLogger* logger, _Out_ OrtLoggingLevel* out); + + /// @} + + /** \brief Get a ::OrtValue tensor stored as a constant initializer in the graph node. + * + * Used in the CreateKernel callback of an OrtCustomOp to get a tensor value. + * + * \param[in] info ::OrtKernelInfo instance. + * \param[in] index The node index. + * \param[out] is_constant Is it a constant node input or not. + * \param[out] out The OrtValue tensor value. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(KernelInfoGetConstantInput_tensor, _In_ const OrtKernelInfo* info, size_t index, _Out_ int* is_constant, _Outptr_ const OrtValue** out); + + /** \brief Get Optional Type information from an ::OrtTypeInfo + * + * This augments ::OrtTypeInfo to return an ::OrtOptionalTypeInfo when the type is optional. + * The OrtOptionalTypeInfo also has a nested ::OrtTypeInfo that describes the type of the optional value. + * ::OrtOptionalTypeInfo type can only appear within model metadata to describe inputs/outputs. + * The actual OrtValues that are supplied in place of optional type inputs should contain + * specific type that is described by ::OrtOptionalTypeInfo. + * + * So the picture: ::OrtTypeInfo -> ::OrtOptionalTypeInfo -> ::OrtTypeInfo (describes the type that can be supplied + * in place of the optional type when creating the actual ::OrtValue). + * + * \param[in] type_info + * \param[out] out A pointer to the ::OrtOptionalTypeInfo. Do not free this value, + * it is owned by OrtTypeInfo instance. When the type_info does not represent + * optional type, nullptr is returned in out. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(CastTypeInfoToOptionalTypeInfo, _In_ const OrtTypeInfo* type_info, + _Outptr_result_maybenull_ const OrtOptionalTypeInfo** out); + + /** \brief Get OrtTypeInfo for the allowed contained type from an ::OrtOptionalTypeInfo. + * + * This augments ::OrtOptionalTypeInfo to return an ::OrtTypeInfo for the contained type. + * The OrtOptionalTypeInfo has a nested ::OrtTypeInfo that describes the type of the optional value. + * ::OrtOptionalTypeInfo type can only appear within model metadata to describe inputs/outputs. + * The actual OrtValues that are supplied in place of optional type inputs should contain + * specific type that is described by the returned ::OrtTypeInfo. + * + * \param[in] optional_type_info + * \param[out] out A copy of ::OrtTypeInfo for what the optional value could be. + * The user must free this value with ReleaseTypeInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(GetOptionalContainedTypeInfo, _In_ const OrtOptionalTypeInfo* optional_type_info, + _Outptr_ OrtTypeInfo** out); + + /** \brief Set a single string in a string tensor + * Do not zero terminate the string data. + * + * \param[in] value A string tensor + * \param[in] index - flat index of the element + * \param[in] length_in_bytes length of the buffer in utf-8 bytes (without the null terminator) + * \param[inout] buffer - address of return value + * + * \snippet{doc} snippets.dox OrtStatus Return Value + */ + ORT_API2_STATUS(GetResizedStringTensorElementBuffer, _Inout_ OrtValue* value, _In_ size_t index, _In_ size_t length_in_bytes, _Inout_ char** buffer); + + /** \brief Get Allocator from KernelContext for a specific memoryInfo. Please use C API ReleaseAllocator to release out object + * + * \param[in] context OrtKernelContext instance + * \param[in] mem_info OrtMemoryInfo instance + * \param[out] out A pointer to OrtAllocator. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.15. + */ + ORT_API2_STATUS(KernelContext_GetAllocator, _In_ const OrtKernelContext* context, _In_ const OrtMemoryInfo* mem_info, _Outptr_ OrtAllocator** out); + + /** \brief Returns a null terminated string of the build info including git info and cxx flags + * + * \return UTF-8 encoded version string. Do not deallocate the returned buffer. + * + * \since Version 1.15. + */ + const char*(ORT_API_CALL* GetBuildInfoString)(void); + + /// \name OrtROCMProviderOptions + /// @{ + + /** \brief Create an OrtROCMProviderOptions + * + * \param[out] out Newly created ::OrtROCMProviderOptions. Must be released with OrtApi::ReleaseROCMProviderOptions + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.16. + */ + ORT_API2_STATUS(CreateROCMProviderOptions, _Outptr_ OrtROCMProviderOptions** out); + + /** \brief Set options in a ROCm Execution Provider. + * + * Please refer to https://onnxruntime.ai/docs/execution-providers/ROCm-ExecutionProvider.html + * to know the available keys and values. Key should be in null terminated string format of the member of + * ::OrtROCMProviderOptions and value should be its related range. + * + * For example, key="device_id" and value="0" + * + * \param[in] rocm_options + * \param[in] provider_options_keys Array of UTF-8 null-terminated string for provider options keys + * \param[in] provider_options_values Array of UTF-8 null-terminated string for provider options values + * \param[in] num_keys Number of elements in the `provider_option_keys` and `provider_options_values` arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.16. + */ + ORT_API2_STATUS(UpdateROCMProviderOptions, _Inout_ OrtROCMProviderOptions* rocm_options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** + * Get serialized ROCm provider options string. + * + * For example, "device_id=0;arena_extend_strategy=0;......" + * + * \param rocm_options - OrtROCMProviderOptions instance + * \param allocator - a ptr to an instance of OrtAllocator obtained with CreateAllocator() or GetAllocatorWithDefaultOptions() + * the specified allocator will be used to allocate continuous buffers for output strings and lengths. + * \param ptr - is a UTF-8 null terminated string allocated using 'allocator'. The caller is responsible for using the same allocator to free it. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.16. + */ + ORT_API2_STATUS(GetROCMProviderOptionsAsString, _In_ const OrtROCMProviderOptions* rocm_options, _Inout_ OrtAllocator* allocator, _Outptr_ char** ptr); + + /** \brief Release an ::OrtROCMProviderOptions + * + * \note This is an exception in the naming convention of other Release* functions, as the name of the method does not have the V2 suffix, but the type does + * + * \since Version 1.16. + */ + void(ORT_API_CALL* ReleaseROCMProviderOptions)(_Frees_ptr_opt_ OrtROCMProviderOptions* input); + + /** \brief Create an allocator with specific type and register it with the ::OrtEnv + * This API enhance CreateAndRegisterAllocator that it can create an allocator with specific type, not just CPU allocator + * Enables sharing the allocator between multiple sessions that use the same env instance. + * Lifetime of the created allocator will be valid for the duration of the environment. + * Returns an error if an allocator with the same ::OrtMemoryInfo is already registered. + * \param[in] env OrtEnv instance + * \param[in] provider_type ExecutionProvider type + * \param[in] mem_info OrtMemoryInfo instance + * \param[in] arena_cfg Arena configuration + * \param[in] provider_options_keys key of the provider options map + * \param[in] provider_options_values value of the provider options map + * \param[in] num_keys Length of the provider options map + */ + ORT_API2_STATUS(CreateAndRegisterAllocatorV2, _Inout_ OrtEnv* env, _In_ const char* provider_type, + _In_ const OrtMemoryInfo* mem_info, _In_ const OrtArenaCfg* arena_cfg, + _In_reads_(num_keys) const char* const* provider_options_keys, _In_reads_(num_keys) const char* const* provider_options_values, _In_ size_t num_keys); + + /** \brief Run the model asynchronously in a thread owned by intra op thread pool + * + * \param[in] session + * \param[in] run_options If nullptr, will use a default ::OrtRunOptions + * \param[in] input_names Array of null terminated UTF8 encoded strings of the input names + * \param[in] input Array of ::OrtValue%s of the input values + * \param[in] input_len Number of elements in the input_names and inputs arrays + * \param[in] output_names Array of null terminated UTF8 encoded strings of the output names + * \param[in] output_names_len Number of elements in the output_names and outputs array + * \param[out] output OrtValue* array of size output_names_len. + * On calling RunAsync, output[i] could either be a null or a pointer to a preallocated OrtValue. + * Later, the output array will be passed to run_async_callback with all null(s) filled with valid + * OrtValue pointer(s) allocated by onnxruntime. + * NOTE: it is customer's duty to finally release the output array and each of its member, + * regardless of whether the member (OrtValue*) is allocated by onnxruntime or preallocated by the customer. + * \param[in] run_async_callback Callback function on model run completion + * \param[in] user_data User data that pass back to run_async_callback + */ + ORT_API2_STATUS(RunAsync, _Inout_ OrtSession* session, _In_opt_ const OrtRunOptions* run_options, + _In_reads_(input_len) const char* const* input_names, + _In_reads_(input_len) const OrtValue* const* input, size_t input_len, + _In_reads_(output_names_len) const char* const* output_names, size_t output_names_len, + _Inout_updates_all_(output_names_len) OrtValue** output, + _In_ RunAsyncCallbackFn run_async_callback, _In_opt_ void* user_data); + + /** + * Update TensorRT EP provider option where its data type is pointer, for example 'user_compute_stream'. + * If the data type of the provider option can be represented by string please use UpdateTensorRTProviderOptions. + * + * Note: It's caller's responsibility to properly manage the lifetime of the instance pointed by this pointer. + * + * \param tensorrt_options - OrtTensorRTProviderOptionsV2 instance + * \param key - Name of the provider option + * \param value - A pointer to the instance that will be assigned to this provider option + * + * \since Version 1.16. + */ + ORT_API2_STATUS(UpdateTensorRTProviderOptionsWithValue, _Inout_ OrtTensorRTProviderOptionsV2* tensorrt_options, _In_ const char* key, _In_ void* value); + + /** + * Get TensorRT EP provider option where its data type is pointer. + * If the data type of the provider option can be represented by string please use GetTensorRTProviderOptionsAsString. + * + * \param tensorrt_options - OrtTensorRTProviderOptionsV2 instance + * \param key - Name of the provider option + * \param ptr - A pointer to the instance that is kept by the provider option + * + * \since Version 1.16. + */ + ORT_API2_STATUS(GetTensorRTProviderOptionsByName, _In_ const OrtTensorRTProviderOptionsV2* tensorrt_options, _In_ const char* key, _Outptr_ void** ptr); + + /** + * Update CUDA EP provider option where its data type is pointer, for example 'user_compute_stream'. + * If the data type of the provider option can be represented by string please use UpdateCUDAProviderOptions. + * + * Note: It's caller's responsibility to properly manage the lifetime of the instance pointed by this pointer. + * + * \param cuda_options - OrtCUDAProviderOptionsV2 instance + * \param key - Name of the provider option + * \param value - A pointer to the instance that will be assigned to this provider option + * + * \since Version 1.16. + */ + ORT_API2_STATUS(UpdateCUDAProviderOptionsWithValue, _Inout_ OrtCUDAProviderOptionsV2* cuda_options, _In_ const char* key, _In_ void* value); + + /** + * Get CUDA EP provider option where its data type is pointer. + * If the data type of the provider option can be represented by string please use GetCUDAProviderOptionsAsString. + * + * \param cuda_options - OrtCUDAProviderOptionsV2 instance + * \param key - Name of the provider option + * \param ptr - A pointer to the instance that is kept by the provider option + * + * \since Version 1.16. + */ + ORT_API2_STATUS(GetCUDAProviderOptionsByName, _In_ const OrtCUDAProviderOptionsV2* cuda_options, _In_ const char* key, _Outptr_ void** ptr); + + /** + * Get a EP resource. + * E.g. a cuda stream or a cublas handle + * + * \param context - Kernel context + * \param resource_version - Version of the resource + * \param resource_id - Type of resource + * \param resource - A pointer to returned resource + * + * \since Version 1.16. + */ + ORT_API2_STATUS(KernelContext_GetResource, _In_ const OrtKernelContext* context, _In_ int resource_version, + _In_ int resource_id, _Outptr_ void** resource); + + /** \brief Set user logging function + * + * By default the logger created by the CreateEnv* functions is used to create the session logger as well. + * This function allows a user to override this default session logger with a logger of their own choosing. This way + * the user doesn't have to create a separate environment with a custom logger. This addresses the problem when + * the user already created an env but now wants to use a different logger for a specific session (for debugging or + * other reasons). + * + * \param[in] options + * \param[in] user_logging_function A pointer to a logging function. + * \param[in] user_logging_param A pointer to arbitrary data passed as the ::OrtLoggingFunction `param` parameter to + * `user_logging_function`. This parameter is optional. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.17. + */ + ORT_API2_STATUS(SetUserLoggingFunction, _Inout_ OrtSessionOptions* options, + _In_ OrtLoggingFunction user_logging_function, _In_opt_ void* user_logging_param); + + /** + * Get number of input from OrtShapeInferContext + * + * \param[in] context + * \param[out] out The number of inputs + * + * \since Version 1.17. + */ + ORT_API2_STATUS(ShapeInferContext_GetInputCount, _In_ const OrtShapeInferContext* context, _Out_ size_t* out); + + /** + * Get type and shape info of an input + * + * \param[in] context + * \param[in] index The index of the input + * \param[out] info Type shape info of the input + * + * \since Version 1.17. + */ + ORT_API2_STATUS(ShapeInferContext_GetInputTypeShape, _In_ const OrtShapeInferContext* context, _In_ size_t index, _Outptr_ OrtTensorTypeAndShapeInfo** info); + + /** + * Get attribute from OrtShapeInferContext. Note that OrtShapeInferContext is a per-node context, one could only read attribute from current node. + * + * \param[in] context + * \param[in] attr_name Name of the attribute + * \param[out] attr Handle of the attribute fetched + * + * \since Version 1.17. + */ + ORT_API2_STATUS(ShapeInferContext_GetAttribute, _In_ const OrtShapeInferContext* context, _In_ const char* attr_name, _Outptr_ const OrtOpAttr** attr); + + /** + * Set type and shape info of an output + * + * \param[in] context + * \param[in] index The index of the output + * \param[out] info Type shape info of the output + * + * \since Version 1.17. + */ + ORT_API2_STATUS(ShapeInferContext_SetOutputTypeShape, _In_ const OrtShapeInferContext* context, _In_ size_t index, _In_ const OrtTensorTypeAndShapeInfo* info); + + /** + * Set symbolic shape to type shape info + * + * \param[in] info Type shape info + * \param[in] dim_params Symbolic strings + * \param[in] dim_params_length Number of strings + * + * \since Version 1.17. + */ + ORT_API2_STATUS(SetSymbolicDimensions, _In_ OrtTensorTypeAndShapeInfo* info, _In_ const char* dim_params[], _In_ size_t dim_params_length); + + /** + * Read contents of an attribute to data + * + * \param[in] op_attr + * \param[in] type Attribute type + * \param[out] data Memory address to save raw content of the attribute + * \param[in] len Number of bytes allowed to store in data + * \param[out] out Number of bytes required to save the data when the call failed, or the real number of bytes saved to data on success + * + * \note Does not support reading graph attributes. Refer to Node_GetSubgraphs. + * + * \since Version 1.17. + */ + ORT_API2_STATUS(ReadOpAttr, _In_ const OrtOpAttr* op_attr, _In_ OrtOpAttrType type, _Inout_ void* data, _In_ size_t len, _Out_ size_t* out); + + /** \brief Set whether to use deterministic compute. + * + * Default is false. If set to true, this will enable deterministic compute for GPU kernels where possible. + * Note that this most likely will have a performance cost. + * + * \param[in] options + * \param[in] value + * + * \since Version 1.17. + */ + ORT_API2_STATUS(SetDeterministicCompute, _Inout_ OrtSessionOptions* options, bool value); + + /** + * Run fn in parallel + * + * \param[in] context + * \param[in] fn Function accepting usr_data and an integer as iterator + * \param[in] total The number of times fn is to be invoked + * \param[in] num_batch Number of batches by which the "total" is to be divided in maximum. When zero, there is no limit + * \param[in] usr_data User data to be passed back to fn + * + * \since Version 1.17. + */ + ORT_API2_STATUS(KernelContext_ParallelFor, _In_ const OrtKernelContext* context, _In_ void (*fn)(void*, size_t), _In_ size_t total, _In_ size_t num_batch, _In_ void* usr_data); + + /** \brief Append OpenVINO execution provider to the session options + * + * If OpenVINO is not available (due to a non OpenVINO enabled build, or if OpenVINO is not installed on the system), this function will fail. + * + * \param[in] options + * \param[in] provider_options_keys + * \param[in] provider_options_values + * \param[in] num_keys + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.17. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_OpenVINO_V2, + _In_ OrtSessionOptions* options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** \brief Append VitisAI provider to session options + * + * If VitisAI is not available (due to a non VitisAI enabled build, or if VitisAI is not installed on the system), this function will return failure. + * + * \param[in] options + * \param[in] provider_options_keys + * \param[in] provider_options_values + * \param[in] num_keys + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.18. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_VitisAI, + _In_ OrtSessionOptions* options, + _In_reads_(num_keys) const char* const* provider_options_keys, + _In_reads_(num_keys) const char* const* provider_options_values, + _In_ size_t num_keys); + + /** \brief Get scratch buffer from the corresponding allocator under the specific OrtMemoryInfo object. + * NOTE: callers are responsible to release this scratch buffer from the corresponding allocator + * \param[in] context OrtKernelContext instance + * \param[in] mem_info OrtMemoryInfo instance + * \param[in] count_or_bytes How many bytes is this scratch buffer + * \param[out] out A pointer to the scratch buffer + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.18. + */ + ORT_API2_STATUS(KernelContext_GetScratchBuffer, _In_ const OrtKernelContext* context, _In_ const OrtMemoryInfo* mem_info, _In_ size_t count_or_bytes, _Outptr_ void** out); + + /** \brief Get allocator from KernelInfo for a specific memory type. Please use C API ReleaseAllocator to release out object + * + * \param[in] info OrtKernelInfo instance + * \param[in] mem_type OrtMemType object + * \param[out] out A pointer to OrtAllocator + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.18. + */ + ORT_API2_STATUS(KernelInfoGetAllocator, _In_ const OrtKernelInfo* info, _In_ OrtMemType mem_type, _Outptr_ OrtAllocator** out); + + /** \brief Replace initialized Tensors with external data with the provided files in memory + * + * The function will find the initialized TensorProtos with external data in the graph with the provided + * external file names and the file content in memory. The API gets the external file name, offset, data length + * from TensorProto, and locate the tensor data from the file in memory buffer. + * It creates a Tensor to replace the existing Tensor in graph. The replacement + * will occur before any of the optimizations take place. The data will be copied into the graph + * since TensorProto can't refer to the user provided buffers. + * + * \param[in] options + * \param[in] external_initializer_file_names Array of null terminated UTF-8 encoded strings of the file names + * which holds the external initializers. + * \param[in] external_initializer_file_buffer_array Array of pointers to the buffer of the file content. + * The buffer can be freed after session creation. + * \param[in] external_initializer_file_lengths Array of size_t to indicate the length of file content + * \param[in] num_external_initializer_files Number of external files + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.18. + */ + ORT_API2_STATUS(AddExternalInitializersFromFilesInMemory, _In_ OrtSessionOptions* options, + _In_reads_(num_external_initializer_files) const ORTCHAR_T* const* external_initializer_file_names, + _In_reads_(num_external_initializer_files) char* const* external_initializer_file_buffer_array, + _In_reads_(num_external_initializer_files) const size_t* external_initializer_file_lengths, + size_t num_external_initializer_files); + + /** \brief Create an OrtLoraAdapter + * + * The function attempts to locate file specified by adapter_file_path, read it and create an OrtLoraAdapter + * instance. The adapter_file_path should be a valid path to a file that contains a valid Lora Adapter + * format. The function attempts to validate the format at load time. The file will always be memory mapped, unless + * the platform does not support memory mapping, in which case the file will be read into memory. + * + * \param[in] adapter_file_path adapter file path. + * \param[in] allocator optional pointer to a device allocator. If specified + * data is copied to the device at some point before Run() is invoked. If nullptr, data stays on CPU. + * The data would still be copied to device if required by the model at inference time. + * \param[out] out A pointer to a newly created OrtLoraAdapter instance. Must be released with + * OrtApi::ReleaseLoraAdapter. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.20. + */ + ORT_API2_STATUS(CreateLoraAdapter, const ORTCHAR_T* adapter_file_path, _In_ OrtAllocator* allocator, + _Outptr_ OrtLoraAdapter** out); + + /** \brief Create an OrtLoraAdapter + * + * The function copies the bytes from the array and creates an OrtLoraAdapter instance. + * + * + * \param[in] bytes pointer to a valid Lora Adapter format buffer. + * \param[in] num_bytes length of bytes buffer. + * \param[in] allocator optional pointer to a device allocator. If specified + * data is copied to the device at some point before Run() is invoked. If nullptr, data stays on CPU. + * The data would still be copied to device if required by the model at inference time. + * \param[out] out A pointer to a newly created OrtLoraAdapter instance. Must be released with + * OrtApi::ReleaseLoraAdapter. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.20. + */ + ORT_API2_STATUS(CreateLoraAdapterFromArray, _In_ const void* bytes, size_t num_bytes, _In_ OrtAllocator* allocator, + _Outptr_ OrtLoraAdapter** out); + + /** \brief Release an ::OrtLoraAdapter obtained from OrtApi::CreateLoraAdapter + */ + ORT_CLASS_RELEASE(LoraAdapter); + + /** \brief Add the Lora Adapter to the list of active adapters. + * + * The function adds the Lora Adapter to the list of active adapters. The Lora Adapter must be created with + * OrtApi::CreateLoraAdapter or FromArray. The Lora Adapter will be used by the session to run the model. + * The instance of the OrtRunOptions can then be used to customize the Run() calls. + * More than one OrtLoraAdapter can be active at the same time. Lora Parameters that belong to different + * Lora adapters that will be active at the same time must not overlap. + * This setting does not affect RunWithBinding. + * + * \param[in] options OrtRunOptions instance + * \param[in] adapter OrtLoraAdapter instance + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.20. + */ + ORT_API2_STATUS(RunOptionsAddActiveLoraAdapter, _Inout_ OrtRunOptions* options, _In_ const OrtLoraAdapter* adapter); + + /// @} + /// \name OrtEpDynamicOptions + /// @{ + + /** \brief Set DynamicOptions for EPs (Execution Providers) + * + * Valid options can be found in `include\onnxruntime\core\session\onnxruntime_session_options_config_keys.h` + * Look for `kOrtEpDynamicOptions` + * + * \param[in] sess OrtSession + * \param[in] keys Array of null terminated UTF8 encoded strings of EP dynamic option keys + * \param[in] values Array of null terminated UTF8 encoded string of EP dynamic option values + * \param[in] kv_len Number of elements in the keys and values arrays + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.20. + */ + ORT_API2_STATUS(SetEpDynamicOptions, _Inout_ OrtSession* sess, _In_reads_(kv_len) const char* const* keys, + _In_reads_(kv_len) const char* const* values, _In_ size_t kv_len); + + /// @} + + /** \brief Release an OrtValueInfo instance if it was not added to an OrtGraph. + * \since Version 1.22. + */ + ORT_CLASS_RELEASE(ValueInfo); + + /** \brief Release an OrtNode if it was not added to an OrtGraph. + * \since Version 1.22. + */ + ORT_CLASS_RELEASE(Node); + + /** \brief Release an OrtGraph. + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.22. + */ + ORT_CLASS_RELEASE(Graph); + + /** \brief Release an OrtModel. + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.22. + */ + ORT_CLASS_RELEASE(Model); + + /** \brief Get the value name from an OrtValueInfo instance. + * \param[in] value_info The OrtValueInfo instance. + * \param[out] name The name of the OrtValueInfo + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.22. + */ + ORT_API2_STATUS(GetValueInfoName, _In_ const OrtValueInfo* value_info, _Out_ const char** name); + + /** \brief Get the type information from an OrtValueInfo instance. + * \param[in] value_info The OrtValueInfo instance. + * \param[out] type_info The type info of the OrtValueInfo + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.22. + */ + ORT_API2_STATUS(GetValueInfoTypeInfo, _In_ const OrtValueInfo* value_info, _Outptr_ const OrtTypeInfo** type_info); + + /** \brief Get the Model Editor API instance + * + * Get the Model Editor API instance to create a new model or augment an existing model. + * + * \return Model Editor API struct + * + * \since Version 1.22. + */ + const OrtModelEditorApi*(ORT_API_CALL* GetModelEditorApi)(); + + /** \brief Create an OrtValue for a Tensor that uses pre-existing memory. + * + * ORT will take ownership of the memory and free it using the provided deleter when no longer in use. + * + * \param[in] deleter OrtAllocator instance that will be used to free the memory. + * Only the OrtAllocator:Info and OrtAllocator::Release functions are required. + * The OrtMemoryInfo returned by OrtAllocator::Info must match the location of p_data. + * \param[in] p_data Pointer to the memory that will be used by the Tensor. ORT will take ownership of the memory. + * \param[in] p_data_len Length of the memory in bytes. + * \param[in] shape Dimensions of the Tensor. All values should be > 0. + * \param[in] shape_len Number of dimensions in the shape array. + * \param[in] type Data type of the Tensor. + * \param[out] out Newly created ::OrtValue. Must be freed with OrtApi::ReleaseValue + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateTensorWithDataAndDeleterAsOrtValue, _In_ OrtAllocator* deleter, + _In_ void* p_data, size_t p_data_len, + _In_ const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type, + _Outptr_ OrtValue** out); + + /** \brief sets load cancellation flag to abort session loading process. + * + * \param[in] options instance that was passed to the session at creation time. + * \param[in] cancel setting this to true after model loading process was initiated will + * attempt to cancel the loading process. If cancellation is successful, CreateSession() + * CreateSessionFromArray() or any other session creation API that take session options as an + * argument will return an OrtStatus indicating that session loading was canceled at user request, + * error code ORT_MODEL_LOAD_CANCELED. + * The APIs above would not return any valid Session instance. This is the best case effort and the result + * is not guaranteed. The session may have already been created and initialized + * before the cancellation request was issued. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(SessionOptionsSetLoadCancellationFlag, _Inout_ OrtSessionOptions* options, + _In_ bool cancel); + + /** \brief Get the Compile API instance. + * + * Get the Compile API instance to compile ONNX models. Execution providers that support compilation fuse a subgraph + * into an EPContext node that wraps a provider-specific binary representation of the subgraph. + * For more details about the EPContext design, refer to: + * \htmlonly + * EPContext design document. + * \endhtmlonly + * + * \return Compile API struct instance. + * + * \since Version 1.22. + */ + const OrtCompileApi*(ORT_API_CALL* GetCompileApi)(); + + // + // OrtKeyValuePairs + // + + /** \brief Create an OrtKeyValuePairs instance. + * + * \param[out] out A pointer to a newly created OrtKeyValuePairs instance. + * + * \note Must be released by calling ReleaseKeyValuePairs. + * + * \since Version 1.22. + */ + void(ORT_API_CALL* CreateKeyValuePairs)(_Outptr_ OrtKeyValuePairs** out); + + /** \brief Add a key-value pair to the OrtKeyValuePairs instance. + * + * If a pair with the same key already exists, it is overwritten. + * + * \param[in] kvps OrtKeyValuePairs instance. + * \param[in] key Key to be added. + * \param[in] value Value to be added. + * + * \note The `key` and `value` are copied internally. + * + * \since Version 1.22. + */ + + void(ORT_API_CALL* AddKeyValuePair)(_In_ OrtKeyValuePairs* kvps, _In_ const char* key, _In_ const char* value); + + /** \brief Get the value associated with a key in the OrtKeyValuePairs instance. + * + * \param[in] kvps OrtKeyValuePairs instance. + * \param[in] key Key to be searched. + * + * \return The value associated with the key, or nullptr if the key does not exist. + * + * \since Version 1.22. + */ + const char*(ORT_API_CALL* GetKeyValue)(_In_ const OrtKeyValuePairs* kvps, _In_ const char* key); + + /** \brief Get all the key-value pairs from the OrtKeyValuePairs instance. + * + * \param[in] kvps OrtKeyValuePairs instance. + * \param[out] keys Array of keys from `kvps`. + * \param[out] values Array of values from `kvps`. + * \param[out] num_entries Number of entries in `keys` and `values`. + * + * \since Version 1.22. + */ + void(ORT_API_CALL* GetKeyValuePairs)(_In_ const OrtKeyValuePairs* kvps, + _Outptr_ const char* const** keys, _Outptr_ const char* const** values, + _Out_ size_t* num_entries); + + /** \brief Remove a key-value pair from the OrtKeyValuePairs instance. + * + * \param[in] kvps OrtKeyValuePairs instance. + * \param[in] key Key to be removed. No error if not found. + * + * \since Version 1.22. + */ + void(ORT_API_CALL* RemoveKeyValuePair)(_In_ OrtKeyValuePairs* kvps, _In_ const char* key); + + /** \brief Release an OrtKeyValuePairs instance. + * + * \param[in] input OrtKeyValuePairs instance to be released. + * + * \since Version 1.22. + */ + ORT_CLASS_RELEASE(KeyValuePairs); + + /** \brief Register an execution provider library with ORT. + * + * The library must export 'CreateEpFactories' and 'ReleaseEpFactory' functions. + * See OrtEpApi for more details. + * + * \param[in] env The OrtEnv instance to register the library in. + * \param[in] registration_name The name to register the execution provider library under. + * \param[in] path The path to the execution provider library. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(RegisterExecutionProviderLibrary, _In_ OrtEnv* env, _In_ const char* registration_name, + _In_ const ORTCHAR_T* path); + + /** \brief Unregister an execution provider library with ORT. + * + * ORT will call ReleaseEpFactory for all factories created by the library, and unload the library. + * + * You MUST ensure there are no Session instances using execution providers created by the library + * before calling this function. + * + * \param[in] env The OrtEnv instance to unregister the library from. + * \param[in] registration_name The name the execution provider library was registered under. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(UnregisterExecutionProviderLibrary, _In_ OrtEnv* env, _In_ const char* registration_name); + + /** \brief Get the list of available OrtEpDevice instances. + * + * Each OrtEpDevice instance contains details of the execution provider and the device it will use. + * + * \param[in] env The OrtEnv instance to query. + * \param[out] ep_devices The OrtEpDevice instances that the execution provider will use. + * \param[out] num_ep_devices The number of OrtEpDevice instances returned. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(GetEpDevices, _In_ const OrtEnv* env, + _Outptr_ const OrtEpDevice* const** ep_devices, _Out_ size_t* num_ep_devices); + + /** \brief Append the execution provider that is responsible for the selected OrtEpDevice instances + * to the session options. + * + * \param[in] session_options Session options to add execution provider to. + * \param[in] env Environment that execution providers were registered with. + * \param[in] ep_devices One or more OrtEpDevice instances to create an execution provider for. + * Obtain from GetEpDevices. All OrtEpDevice instances must be from the same execution + * provider. It is only necessary to provide multiple OrtEpDevices if you want to use the + * same execution provider for multiple devices. + * e.g. the EP is capable of running on GPU and NPU. + * \param[in] num_ep_devices Number of OrtEpDevice instances. + * \param[in] ep_option_keys Optional keys to configure the execution provider. + * \param[in] ep_option_vals Optional values to configure the execution provider. + * \param[in] num_ep_options Number of execution provide options to add. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_V2, _In_ OrtSessionOptions* session_options, + _In_ OrtEnv* env, + _In_reads_(num_ep_devices) const OrtEpDevice* const* ep_devices, _In_ size_t num_ep_devices, + _In_reads_(num_op_options) const char* const* ep_option_keys, + _In_reads_(num_op_options) const char* const* ep_option_vals, + size_t num_ep_options); + + /** \brief Set the execution provider selection policy for the session. + * + * Allows users to specify a device selection policy for automatic execution provider (EP) selection. + * If custom selection is required please use SessionOptionsSetEpSelectionPolicyDelegate instead. + * + * \param[in] session_options The OrtSessionOptions instance. + * \param[in] policy The device selection policy to use (see OrtExecutionProviderDevicePolicy). + * + * \since Version 1.22 + */ + ORT_API2_STATUS(SessionOptionsSetEpSelectionPolicy, _In_ OrtSessionOptions* session_options, + _In_ OrtExecutionProviderDevicePolicy policy); + + /** \brief Set the execution provider selection policy delegate for the session. + * + * Allows users to provide a custom device selection policy for automatic execution provider (EP) selection. + * + * \param[in] session_options The OrtSessionOptions instance. + * \param[in] delegate Delegate callback for custom selection. + * \param[in] delegate_state Optional state that will be passed to the delegate callback. nullptr if not required. + * + * \since Version 1.22 + */ + ORT_API2_STATUS(SessionOptionsSetEpSelectionPolicyDelegate, _In_ OrtSessionOptions* session_options, + _In_ EpSelectionDelegate delegate, + _In_opt_ void* delegate_state); + + /** \brief Get the hardware device type. + * + * \param[in] device The OrtHardwareDevice instance to query. + * \return The hardware device type. + * + * \since Version 1.22. + */ + OrtHardwareDeviceType(ORT_API_CALL* HardwareDevice_Type)(_In_ const OrtHardwareDevice* device); + + /** \brief Get the hardware device's vendor identifier. + * + * \param[in] device The OrtHardwareDevice instance to query. + * \return The hardware device vendor identifier. + * + * \since Version 1.22. + */ + uint32_t(ORT_API_CALL* HardwareDevice_VendorId)(_In_ const OrtHardwareDevice* device); + + /** \brief Get the hardware device's vendor name. + * + * \param[in] device The OrtHardwareDevice instance to query. + * \return The hardware device's vendor name. + * + * \since Version 1.22. + */ + const char*(ORT_API_CALL* HardwareDevice_Vendor)(_In_ const OrtHardwareDevice* device); + + /** \brief Get the hardware device's unique identifier. + * + * \param[in] device The OrtHardwareDevice instance to query. + * \return The device id. + * + * \note This is not a unique identifier. It identifies the hardware type when combined with vendor id. + * \since Version 1.22. + */ + uint32_t(ORT_API_CALL* HardwareDevice_DeviceId)(_In_ const OrtHardwareDevice* device); + + /** \brief Get hardware device metadata. + * + * \param[in] device The OrtHardwareDevice instance to query. + * \return An OrtKeyValuePairs instance containing the metadata for the device. + * Note: ORT owns the instance so the user must not call ReleaseKeyValuePairs with it. + * + * \since Version 1.22. + */ + const OrtKeyValuePairs*(ORT_API_CALL* HardwareDevice_Metadata)(_In_ const OrtHardwareDevice* device); + + /** \brief Get the execution provider name. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \return The execution provider name. + * + * \since Version 1.22. + */ + const char*(ORT_API_CALL* EpDevice_EpName)(_In_ const OrtEpDevice* ep_device); + + /** \brief Get the execution provider's vendor name. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \return The execution provider's vendor name. + * + * \since Version 1.22. + */ + const char*(ORT_API_CALL* EpDevice_EpVendor)(_In_ const OrtEpDevice* ep_device); + + /** \brief Get the metadata for the OrtEpDevice. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \return An OrtKeyValuePairs instance containing the metadata for the device. + * + * \since Version 1.22. + */ + const OrtKeyValuePairs*(ORT_API_CALL* EpDevice_EpMetadata)(_In_ const OrtEpDevice* ep_device); + + /** \brief Get the execution provider options for the OrtEpDevice. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \return An OrtKeyValuePairs instance containing the execution provider options for the device. + * + * \since Version 1.22. + */ + const OrtKeyValuePairs*(ORT_API_CALL* EpDevice_EpOptions)(_In_ const OrtEpDevice* ep_device); + + /** \brief Get the OrtHardwareDevice instance for the OrtEpDevice. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \return The OrtHardwareDevice instance for the device. + * + * \since Version 1.22. + */ + const OrtHardwareDevice*(ORT_API_CALL* EpDevice_Device)(_In_ const OrtEpDevice* ep_device); + + /** \brief Get the OrtEpApi instance for implementing an execution provider. + * + * \since Version 1.22. + */ + const OrtEpApi*(ORT_API_CALL* GetEpApi)(); + + /** \brief Compute total size in bytes of the tensor data contained in an OrtValue. + * + * Returns the total number of bytes used to store the tensor data. For numeric tensors, + * this is sizeof(element_type) * total_element_count. OrtValues that are not tensors or + * that are tensors that contain strings will cause an error to be returned. + * + * \param[in] ort_value OrtValue instance containing a tensor + * \param[out] size The total size of the tensor data in bytes + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(GetTensorSizeInBytes, _In_ const OrtValue* ort_value, _Out_ size_t* size); + + /** \brief Calls OrtAllocator::GetStats function + * + * Return a pointer to the OrtKeyValuePairs structure that contains the statistics of the allocator + * and the user should call OrtApi::ReleaseKeyValuePairs. + * + * NOTE: If the allocator does not implement this function, the OrtKeyValuePairs instance will be empty. + * + * \param[in] ort_allocator The allocator to get stats from + * \param[out] out A pointer to the OrtKeyValuePairs instance that contains the stats + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(AllocatorGetStats, _In_ const OrtAllocator* ort_allocator, _Outptr_ OrtKeyValuePairs** out); + + /** \brief Create an ::OrtMemoryInfo + * + * \param[in] name Arbitrary name. + * \param[in] device_type Device type. + * \param[in] vendor_id PCI Vendor ID. Use 0 for a generic allocator (e.g. WebGPU). + * \param[in] device_id Device ID if there are multiple devices of the same type. e.g. 2 GPU devices. + * \param[in] mem_type Memory type. Use OrtDeviceMemoryType_DEFAULT for device memory, and + * OrtDeviceMemoryType_HOST_ACCESSIBLE (if applicable) for memory used to transfer between the + * device and the CPU. Use the device_type and device_id of the GPU/NPU that the memory is also + * accessible to. + * \param[in] alignment Alignment of the memory if required. Pass 0 for default alignment. + * \param[in] allocator_type Allocator type. If OrtAllocatorType::OrtArenaAllocator, the ORT arena will be used. + * Caveat: Support for OrtArenaAllocator is currently limited to usage of internal ORT + * allocators via CreateAllocator/CreateAndRegisterAllocator/CreateAndRegisterAllocatorV2. + * \param[out] out Newly created ::OrtMemoryInfo. Must be freed with OrtApi::ReleaseMemoryInfo + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(CreateMemoryInfo_V2, _In_ const char* name, _In_ enum OrtMemoryInfoDeviceType device_type, + _In_ uint32_t vendor_id, _In_ int32_t device_id, _In_ enum OrtDeviceMemoryType mem_type, + _In_ size_t alignment, enum OrtAllocatorType allocator_type, + _Outptr_ OrtMemoryInfo** out); + + /** \brief Get the device memory type from ::OrtMemoryInfo + * + * \param[in] ptr The OrtMemoryInfo instance to query. + * \return The device memory type. + * + * \since Version 1.23 + */ + ORT_API_T(OrtDeviceMemoryType, MemoryInfoGetDeviceMemType, _In_ const OrtMemoryInfo* ptr); + + /** \brief Get the vendor id from ::OrtMemoryInfo + * + * \param[in] ptr The OrtMemoryInfo instance to query. + * \return The vendor id. + * + * \since Version 1.23 + */ + ORT_API_T(uint32_t, MemoryInfoGetVendorId, _In_ const OrtMemoryInfo* ptr); + + /// \name OrtValueInfo + /// @{ + + /** \brief Get the OrtNode that produces the value represented by the given OrtValueInfo. + * Optionally returns the associated output index. + * + * \param[in] value_info The OrtValueInfo instance. + * \param[out] producer_node Output parameter set to the OrtNode that produces the OrtValueInfo. + * \param[out] producer_output_index Optional output parameter set to the OrtNode instance's output index + * that produces the value. Ignored if set to NULL. + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_GetValueProducer, _In_ const OrtValueInfo* value_info, + _Outptr_ const OrtNode** producer_node, _Out_opt_ size_t* producer_output_index); + + /** \brief Get the number of consumers of a value as a node input. + * + * Only nodes are considered "consumers" by this function. To check if an OrtValueInfo is a graph output, + * call ValueInfo_IsGraphOutput(). + * + * A single OrtNode may use a single value for more than one input (e.g., Mul(x, x)), so the returned + * `num_consumers` may be larger than the number of unique OrtNode instances that consume the value. + * + * \param[in] value_info The OrtValueInfo instance. + * \param[out] num_consumers Output parameter set to the number of consumers of the value. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_GetValueNumConsumers, _In_ const OrtValueInfo* value_info, _Out_ size_t* num_consumers); + + /** \brief Returns information (OrtNode and input index) for all consumer nodes that use the value as an input. + * + * Only nodes are considered "consumers" by this function. + * + * Caller provides 2 pre-allocated arrays that will be filled with the OrtNode and input index values. + * Use ValueInfo_GetValueNumConsumers() to get the number of consumers of the value. + * + * An OrtNode instance may appear multiple times if it uses the given value more than once. + * Example: For a node MulNode(x, x) that consumes the value 'x' twice, the following is returned: + * - nodes: [MulNode, MulNode] + * - input_indices: [0, 1] + * + * \param[in] value_info The OrtValueInfo instance. + * \param[out] nodes Pre-allocated array of size `num_consumers` that is filled with OrtNode instances. + * \param[out] input_indices Pre-allocated array of `num_consumers` elements that is filled + * with input indices. Index is set to -1 for an "implicit" input to a consumer node + * that contains a subgraph (e.g., If, Loop) with nodes that use the value internally. + * \param[in] num_consumers The size of the `consumer_nodes` and `consumer_input_indices` arrays. + * Typical usage sets this to the value of ValueInfo_GetValueNumConsumers(). + * An error status is returned if `num_consumers` is less than the number of actual + * consumers. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_GetValueConsumers, _In_ const OrtValueInfo* value_info, + _Out_writes_all_(num_consumers) const OrtNode** nodes, + _Out_writes_all_(num_consumers) int64_t* input_indices, + _In_ size_t num_consumers); + + /** \brief Get the underlying initializer value, as an OrtValue, from the given OrtValueInfo. + * + * Sets the output parameter to NULL if the given OrtValueInfo does not represent an initializer. + * Does not return an error status in this case. + * + * Supports initializers defined in an outer scope (i.e., a parent graph). + * + * Supports initializers stored in an external file. For external initializers, ORT memory maps + * the initializer data on the first call to this function. If caller needs custom memory mapping, + * use ValueInfo_GetExternalInitializerInfo to get the location of the initializer data. + * + * \param[in] value_info The OrtValueInfo instance. + * \param[out] initializer_value Output parameter set to the initializer value or NULL. Do not cache the OrtValue + * as it is released when the owning OrtGraph is released. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_GetInitializerValue, _In_ const OrtValueInfo* value_info, + _Outptr_ const OrtValue** initializer_value); + + /** \brief Get information about an external initializer (e.g., filepath, file offset, byte size). + * + * Sets the output parameter `info` to NULL if the given OrtValueInfo does not represent an initializer + * with external data. In this case, a NULL status (non-error) is returned. + * + * \param[in] value_info The OrtValueInfo instance. + * \param[out] info Output parameter set to an OrtExternalInitializerInfo instance that can be used to query + * file path, file offset, etc. ORT sets this to NULL if the OrtValueInfo does not represent + * an external initializer. + * Must release with ReleaseExternalInitializerInfo. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_GetExternalInitializerInfo, _In_ const OrtValueInfo* value_info, + _Outptr_result_maybenull_ OrtExternalInitializerInfo** info); + + /** \brief Returns a boolean indicating if the given value is a required graph input. + * + * For ONNX IR version < 4, all graph inputs without a matching initializer are required. + * + * For ONNX IR version >=4, a graph input with a matching initializer is an optional graph input + * with the initializer serving as the default value. + * + * \param[in] value_info The OrtValueInfo instance representing the graph value. + * \param[out] is_required_graph_input Output parameter set to true if the graph value is a required graph input. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_IsRequiredGraphInput, _In_ const OrtValueInfo* value_info, + _Out_ bool* is_required_graph_input); + + /** \brief Returns a boolean indicating if the given value is an optional graph input. + * + * Optional graph inputs were introduced in ONNX IR version 4. For ONNX IR version >=4, a graph input with a + * matching initializer is an optional graph input with the initializer serving as the default value. + * The matching initializer is also known as a non-constant initializer. + * + * \param[in] value_info The OrtValueInfo instance representing the graph value. + * \param[out] is_optional_graph_input Output parameter set to true if the graph value is an optional graph input. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_IsOptionalGraphInput, _In_ const OrtValueInfo* value_info, + _Out_ bool* is_optional_graph_input); + + /** \brief Returns a boolean indicating if the given value is a graph output. + * + * \param[in] value_info The OrtValueInfo instance representing the graph value. + * \param[out] is_graph_output Output parameter set to true if the graph value is a graph output. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_IsGraphOutput, _In_ const OrtValueInfo* value_info, _Out_ bool* is_graph_output); + + /** \brief Returns a boolean indicating if the given value is a constant initializer. + * + * For ONNX IR version < 4, all initializers are constant. + * + * For ONNX IR version >=4, an initializer that serves as the default value for a matching graph input is not a + * constant initializer. + * + * \param[in] value_info The OrtValueInfo instance representing the graph value. + * \param[out] is_constant_initializer Output parameter set to true if the graph value is a constant initializer. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_IsConstantInitializer, _In_ const OrtValueInfo* value_info, + _Out_ bool* is_constant_initializer); + + /** \brief Returns a boolean indicating if the given value is defined in an outer scope. + * + * Certain operator types (e.g., If and Loop) contain nested subgraphs. This function enables + * determining whether a value is defined in a parent node's graph. + * + * \param[in] value_info The OrtValueInfo instance representing the graph value. + * \param[out] is_from_outer_scope Output parameter set to true if the value is defined in an outer + * scope (i.e., a parent graph). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValueInfo_IsFromOuterScope, _In_ const OrtValueInfo* value_info, + _Out_ bool* is_from_outer_scope); + + /// @} + + /// \name OrtGraph + /// @{ + + /** \brief Returns a graph's name. + * + * \param[in] graph The OrtGraph instance. + * \param[out] graph_name Output parameter set to the graph's name. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetName, _In_ const OrtGraph* graph, _Outptr_ const char** graph_name); + + /** \brief Get the filepath to the model from which an OrtGraph is constructed. + * + * \note The model's filepath is empty if the filepath is unknown, such as when the model is loaded from bytes + * via CreateSessionFromArray. + * + * \param[in] graph The OrtGraph instance. + * \param[out] model_path Output parameter set to the model's null-terminated filepath. + * Set to an empty path string if unknown. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetModelPath, _In_ const OrtGraph* graph, _Outptr_ const ORTCHAR_T** model_path); + + /** \brief Returns the ONNX IR version. + * + * \param[in] graph The OrtGraph instance. + * \param[out] onnx_ir_version Output parameter set to the ONNX IR version. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetOnnxIRVersion, _In_ const OrtGraph* graph, _Out_ int64_t* onnx_ir_version); + + /** \brief Returns the number of operator sets that the graph's model uses. + * + * \note An operator set is uniquely identified by the (domain, opset_version) pair. All models must have at + * least one entry that specifies which entry of the ONNX operator set is used. The ONNX domain is represented by + * an empty string. + * + * \param[in] graph The OrtGraph instance. + * \param[out] num_operator_sets Output parameter set to the number of operator sets that the graph's model uses. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNumOperatorSets, _In_ const OrtGraph* graph, _Out_ size_t* num_operator_sets); + + /** \brief Returns the operator sets that the graph's model uses. + * + * \note An operator set is uniquely identified by the (domain, opset_version) pair. All models must have at + * least one entry that specifies which entry of the ONNX operator set is used. The ONNX domain is represented by + * an empty string. + * + * \param[in] graph The OrtGraph instance. + * \param[out] domains Pre-allocated array of `num_operator_sets` elements that is filled with + * null-terminated domain names. + * \param[out] opset_versions Pre-allocated array of `num_operator_sets` elements that is filled with + * the opset version of the corresponding domain in the `domains` array. + * \param[in] num_operator_sets The size of the `domains` and `opset_versions` arrays. + * Typical usage sets this to the result of Graph_GetNumOperatorSets(). + * An error status is returned if `num_operator_sets` is less than the actual number + * of operator sets. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetOperatorSets, _In_ const OrtGraph* graph, + _Out_writes_(num_operator_sets) const char** domains, + _Out_writes_(num_operator_sets) int64_t* opset_versions, _In_ size_t num_operator_sets); + + /** \brief Returns the number of graph inputs. + * + * \note The count includes initializers that are included in the list of graph inputs. + * + * \param[in] graph The OrtGraph instance. + * \param[out] num_inputs Output parameter set to the number of graph inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNumInputs, _In_ const OrtGraph* graph, _Out_ size_t* num_inputs); + + /** \brief Returns the graph's inputs as OrtValueInfo instances. + * + * \note The result includes initializers that are included in the list of graph inputs. + * + * \param[in] graph The OrtGraph instance. + * \param[out] inputs Pre-allocated array of `num_inputs` elements that is filled with the graph's inputs. + * \param[in] num_inputs The size of the `inputs` array. + * Typical usage sets this to the result of Graph_GetNumInputs(). An error status is + * returned if `num_inputs` is less than the number of graph inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetInputs, _In_ const OrtGraph* graph, + _Out_writes_(num_inputs) const OrtValueInfo** inputs, _In_ size_t num_inputs); + + /** \brief Returns the number of graph outputs. + * + * \param[in] graph The OrtGraph instance. + * \param[out] num_outputs Output parameter set to the number of graph outputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNumOutputs, _In_ const OrtGraph* graph, _Out_ size_t* num_outputs); + + /** \brief Returns the graph's outputs as OrtValueInfo instances. + * + * \param[in] graph The OrtGraph instance. + * \param[out] outputs Pre-allocated array of `num_outputs` elements that is filled with the graph's outputs. + * \param[in] num_outputs The size of the `outputs` array. + * Typical usage sets this to the result of Graph_GetNumOutputs(). An error status is + * returned if `num_outputs` is less than the number of graph outputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetOutputs, _In_ const OrtGraph* graph, + _Out_writes_(num_outputs) const OrtValueInfo** outputs, _In_ size_t num_outputs); + + /** \brief Returns the number of graph initializers. + * + * Counts constant and non-constant initializers. + * + * \param[in] graph The OrtGraph instance. + * \param[out] num_initializers Output parameter set to the number of graph initializers. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNumInitializers, _In_ const OrtGraph* graph, _Out_ size_t* num_initializers); + + /** \brief Returns the graph's initializers as OrtValueInfo instances. + * + * Includes constant and non-constant initializers. + * + * For ONNX IR version < 4, all initializers are constant. + * + * For ONNX IR version >= 4, an initializer with a name that matches a graph input is considered a + * non-constant initializer. + * + * Call ValueInfo_GetInitializerValue to get the initializer's data. + * + * \param[in] graph The OrtGraph instance. + * \param[out] initializers Pre-allocated array of `num_outputs` elements that is filled with the initializers. + * \param[in] num_initializers The size of the `initializers` array. Typical usage sets this to the + * result of Graph_GetNumInitializers(). An error status is returned if + * `num_initializers` is less than the number of graph initializers. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetInitializers, _In_ const OrtGraph* graph, + _Out_writes_(num_initializers) const OrtValueInfo** initializers, + _In_ size_t num_initializers); + + /** \brief Returns the number of graph nodes. + * + * \param[in] graph The OrtGraph instance. + * \param[out] num_nodes Output parameter set to the number of graph nodes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNumNodes, _In_ const OrtGraph* graph, _Out_ size_t* num_nodes); + + /** \brief Returns the graph's nodes as OrtNode instances. + * + * The nodes are sorted using a stable topological ordering. Callers are responsible for maintaining their + * own node ordering if a different order is required. + * + * \param[in] graph The OrtGraph instance. + * \param[out] nodes Pre-allocated array of `num_nodes` elements that is filled with the graph's nodes. + * \param[in] num_nodes The size of the `nodes` array. Typical usage sets this to the + * result of Graph_GetNumNodes(). An error status is returned if + * `num_nodes` is less than the number of graph nodes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetNodes, _In_ const OrtGraph* graph, + _Out_writes_(num_nodes) const OrtNode** nodes, _In_ size_t num_nodes); + + /** \brief Get the parent node for the given graph, if any exists. + * + * Certain operator types (e.g., If and Loop) contain nested subgraphs. This function enables + * access to the parent node (e.g., the If and Loop node) from a nested subgraph. + * + * \param[in] graph The OrtGraph instance. + * \param[out] node Output parameter that is set to the graph's parent node. + * Set to NULL if a parent node does not exist (e.g., for a top-level graph). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetParentNode, _In_ const OrtGraph* graph, _Outptr_result_maybenull_ const OrtNode** node); + + /** \brief Returns an OrtGraph that contains a subset of nodes in the source OrtGraph. + * + * \note The lifetime of "dst_graph" is tied to that of "src_graph", as they both internally reference + * the same underlying graph. + * + * \param[in] src_graph The source OrtGraph instance. + * \param[in] nodes A subset of the nodes/OrtNodes in 'graph'. + * \param[in] num_nodes Number of nodes. + * \param[out] dst_graph An OrtGraph created from a given set of nodes. Must be released by calling ReleaseGraph. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetGraphView, _In_ const OrtGraph* src_graph, _In_ const OrtNode** nodes, + _In_ size_t num_nodes, _Outptr_ OrtGraph** dst_graph); + + /// @} + + /// \name OrtNode + /// @{ + + /** \brief Returns a node's identifier. + * + * The node's identifier is only unique in the node's parent graph. Different nested subgraphs + * (e.g., subgraphs contained by If and Loop nodes) may reuse identifiers. + * + * \param[in] node The OrtNode instance. + * \param[out] node_id Output parameter set to the node's identifier. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetId, _In_ const OrtNode* node, _Out_ size_t* node_id); + + /** \brief Returns a node's name. Can be an empty string. + * + * \param[in] node The OrtNode instance. + * \param[out] node_name Output parameter set to the node's name. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetName, _In_ const OrtNode* node, _Outptr_ const char** node_name); + + /** \brief Returns a node's operator type (e.g., "Conv"). + * + * \param[in] node The OrtNode instance. + * \param[out] operator_type Output parameter set to the name of the node's operator type. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetOperatorType, _In_ const OrtNode* node, _Outptr_ const char** operator_type); + + /** \brief Returns a node's domain name. + * + * \param[in] node The OrtNode instance. + * \param[out] domain_name Output parameter set to the node's domain name. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetDomain, _In_ const OrtNode* node, _Outptr_ const char** domain_name); + + /** \brief Get the opset version in which the given node's operator type was first defined. + * + * \param[in] node The OrtNode instance. + * \param[out] since_version The opset version in which the node's operator type was first defined. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetSinceVersion, _In_ const OrtNode* node, _Out_ int* since_version); + + /** \brief Returns the number of node inputs. + * + * \param[in] node The OrtNode instance. + * \param[out] num_inputs Output parameter set to the number of node inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetNumInputs, _In_ const OrtNode* node, _Out_ size_t* num_inputs); + + /** \brief Returns the node's inputs as OrtValueInfo instances. + * + * \param[in] node The OrtNode instance. + * \param[out] inputs Pre-allocated array of `num_inputs` elements that is filled with the node's inputs. + * \param[in] num_inputs The size of the `inputs` array. + * Typical usage sets this to the result of Node_GetNumInputs(). An error status is + * returned if `num_inputs` is less than the number of node inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetInputs, _In_ const OrtNode* node, + _Out_writes_(num_inputs) const OrtValueInfo** inputs, _In_ size_t num_inputs); + + /** \brief Returns the number of node outputs. + * + * \param[in] node The OrtNode instance. + * \param[out] num_outputs Output parameter set to the number of node outputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetNumOutputs, _In_ const OrtNode* node, _Out_ size_t* num_outputs); + + /** \brief Returns the node's outputs as OrtValueInfo instances. + * + * \param[in] node The OrtNode instance. + * \param[out] outputs Pre-allocated array of `num_outputs` elements that is filled with the node's outputs. + * \param[in] num_outputs The size of the `outputs` array. + * Typical usage sets this to the result of Node_GetNumOutputs(). An error status is + * returned if `num_outputs` is less than the number of node outputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetOutputs, _In_ const OrtNode* node, + _Out_writes_(num_outputs) const OrtValueInfo** outputs, _In_ size_t num_outputs); + + /** \brief Returns the number of node implicit inputs. + * + * Certain operator types (e.g., If and Loop) contain nested subgraphs. The internal nodes within the nested subgraphs + * may use values from the outer scope. Those "outer scope" values are considered implicit inputs to the node that + * contains the subgraphs (e.g., the If or Loop node). + * + * \param[in] node The OrtNode instance. + * \param[out] num_implicit_inputs Output parameter set to the number of node implicit inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetNumImplicitInputs, _In_ const OrtNode* node, _Out_ size_t* num_implicit_inputs); + + /** \brief Get the implicit inputs, as OrtValueInfo instances, that are used within the given node's subgraphs. + * + * \note Only certain operator types (e.g., If and Loop) contain nested subgraphs. + * The internal nodes within the nested subgraphs may use values from the outer scope. Those "outer scope" values + * are considered implicit inputs to the node that contains the subgraphs (e.g., the If or Loop node). + * + * \param[in] node The OrtNode instance. + * \param[out] implicit_inputs Pre-allocated array of `num_implicit_inputs` elements that is filled the node's + * implicit inputs. + * \param[in] num_implicit_inputs The size of the `implicit_inputs` array. Typical usage sets this to the result + * of Node_GetNumImplicitInputs(). An error status is returned if + * `num_implicit_inputs` is less than the number of node implicit inputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetImplicitInputs, _In_ const OrtNode* node, + _Out_writes_(num_implicit_inputs) const OrtValueInfo** implicit_inputs, + _In_ size_t num_implicit_inputs); + + /** \brief Returns the number of node attributes. + * + * \param[in] node The OrtNode instance. + * \param[out] num_attributes Output parameter set to the number of node attributes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetNumAttributes, _In_ const OrtNode* node, _Out_ size_t* num_attributes); + + /** \brief Returns a node's attributes as OrtOpAttr instances. + * + * \param[in] node The OrtNode instance. + * \param[out] attributes Pre-allocated array of `num_attributes` elements that is filled with the node's attributes. + * \param[in] num_attributes The size of the `num_attributes` array. + * Typical usage sets this to the result of Node_GetNumAttributes(). An error status is + * returned if `num_attributes` is less than the number of node attributes. + * + * \note ONNX Runtime automatically sets optional (unset) attributes to their default values if the default value + * is a constant expression that does not depend on other tensor/model characteristics. Conv's 'kernel_shape' + * attribute is an example of an optional attribute that does not have a constant default value. This function + * does not provide any unset optional attributes without a constant default value. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetAttributes, _In_ const OrtNode* node, + _Out_writes_(num_attributes) const OrtOpAttr** attributes, _In_ size_t num_attributes); + + /** \brief Gets the OrtNode's attribute as OrtOpAttr by name. + * + * \param[in] node The OrtNode instance. + * \param[in] attribute_name The name of the attribute + * \param[out] attribute Output parameter set to the OrtOpAttr instance if an attribute by the given name exists. + * For an unset optional attribute, `attribute` is set to NULL and a non-error status is + * returned. For an invalid attribute name, `attribute` is set to NULL and an error status with + * code ORT_NOT_FOUND is returned. + * + * \note ONNX Runtime automatically sets optional (unset) attributes to their default values if the default value + * is a constant expression that does not depend on other tensor/model characteristics. Conv's 'kernel_shape' + * attribute is an example of an optional attribute that does not have a constant default value. This function + * does not provide any unset optional attributes without a constant default value. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetAttributeByName, _In_ const OrtNode* node, _In_ const char* attribute_name, + _Outptr_result_maybenull_ const OrtOpAttr** attribute); + + /** \brief Get the OrtNode's 'TENSOR' attribute as an OrtValue. + * + * \param[in] attribute The OrtOpAttr instance. + * \param[out] attr_tensor If successful, contains the 'TENSOR' attribute as a newly created OrtValue. + Must be freed with OrtApi::ReleaseValue. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OpAttr_GetTensorAttributeAsOrtValue, _In_ const OrtOpAttr* attribute, + _Outptr_result_maybenull_ OrtValue** attr_tensor); + + /** \brief Get the attribute type as OrtOpAttrType from an OrtOpAttr. + * + * \param[in] attribute The OrtOpAttr instance. + * \param[out] type Output the attribute type as OrtOpAttrType. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OpAttr_GetType, _In_ const OrtOpAttr* attribute, _Out_ OrtOpAttrType* type); + + /** \brief Get the attribute name from an OrtOpAttr. + * + * \param[in] attribute The OrtOpAttr instance. + * \param[out] name Output parameter set to the attribute's name. The name is a null-terminated string. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OpAttr_GetName, _In_ const OrtOpAttr* attribute, _Outptr_ const char** name); + + /** \brief Returns the number of subgraphs contained by the given node. + * + * \note Only certain operator types (e.g., If and Loop) contain nested subgraphs. + * + * \param[in] node The OrtNode instance. + * \param[out] num_subgraphs Output parameter set to the number of node subgraphs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetNumSubgraphs, _In_ const OrtNode* node, _Out_ size_t* num_subgraphs); + + /** \brief Get the subgraphs, as OrtGraph instances, contained by the given node. + * + * \note Only certain operator types (e.g., If and Loop) contain nested subgraphs. ONNX nodes store subgraphs in + * their attributes, however, this function must be used to obtain subgraphs from an OrtNode. + * + * \param[in] node The OrtNode instance. + * \param[out] subgraphs Pre-allocated array of `num_subgraphs` elements that is filled with the node's subgraphs. + * \param[in] num_subgraphs The size of the `num_subgraphs` array. + * Typical usage sets this to the result of Node_GetNumSubgraphs(). An error status is + * returned if `num_subgraphs` is less than the number of node subgraphs. + * \param[out] attribute_names Optional pre-allocated array of `num_subgraphs` elements that is filled with the + * attribute names that correspond to the subgraphs. Ignored if set to NULL. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetSubgraphs, _In_ const OrtNode* node, + _Out_writes_(num_subgraphs) const OrtGraph** subgraphs, _In_ size_t num_subgraphs, + _Out_writes_opt_(num_subgraphs) const char** attribute_names); + + /** \brief Get the node's parent OrtGraph instance. + * + * Can return NULL if the OrtNode was created without an owning graph. + * + * \param[in] node The OrtNode instance. + * \param[out] graph Output parameter set to the node's OrtGraph. Can be set to NULL + * if the node is not currently contained by a graph. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetGraph, _In_ const OrtNode* node, _Outptr_result_maybenull_ const OrtGraph** graph); + + /** \brief Returns the execution provider name that this node is assigned to run on. + * Returns NULL if the node has not been assigned to any execution provider yet. + * For plugin execution providers, the name is the one returned by OrtEp::GetName. + * + * \param[in] node The OrtNode instance. + * \param[out] out Output execution provider type and can be NULL if node has not been assigned. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Node_GetEpName, _In_ const OrtNode* node, _Outptr_result_maybenull_ const char** out); + + /// @} + + /// \name OrtExternalInitializerInfo + /// @{ + + /** \brief Release an OrtExternalInitializerInfo instance. + * + * \param[in] input OrtExternalInitializerInfo instance to be released. + * + * \since Version 1.23. + */ + ORT_CLASS_RELEASE(ExternalInitializerInfo); + + /** \brief Get the relative path to the file that stores the initializer's data. + * + * \note The path is relative to the filesystem directory where the ONNX model was stored. + * Caller can use Graph_GetModelPath to get the model's full path and construct the absolute path to the + * external initializer file if necessary. + * + * \param[in] info The OrtExternalInitializerInfo instance. + * \return The relative path to the file that stores the initializer's data. Do NOT free this pointer. + * + * \since Version 1.23. + */ + ORT_API_T(const ORTCHAR_T*, ExternalInitializerInfo_GetFilePath, _In_ const OrtExternalInitializerInfo* info); + + /** \brief Get the byte offset within the file where the initializer's data is stored. + * + * \param[in] info The OrtExternalInitializerInfo instance. + * \return The byte offset where the initializer's data is stored within the file. + * + * \since Version 1.23. + */ + ORT_API_T(int64_t, ExternalInitializerInfo_GetFileOffset, _In_ const OrtExternalInitializerInfo* info); + + /** \brief Get the size in bytes of the initializer's data within the file. + * + * \param[in] info The OrtExternalInitializerInfo instance. + * \return The size in bytes of the initializer's data within the file. + * + * \since Version 1.23. + */ + ORT_API_T(size_t, ExternalInitializerInfo_GetByteSize, _In_ const OrtExternalInitializerInfo* info); + + /// @} + + /// \name OrtRunOptions + /// @{ + + /** \brief Get a run configuration entry. + * + * If a run configuration entry with key `config_key` doesn't exist, `config_value` will be set to NULL. + * + * `config_key`s are defined in onnxruntime_run_options_config_keys.h. + * + * \param[in] options The OrtRunOptions instance. + * \param[in] config_key The configuration entry key. A null-terminated string. + * \return The configuration entry value. Either a null-terminated string if the entry was found. nullptr otherwise. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API_T(const char*, GetRunConfigEntry, _In_ const OrtRunOptions* options, + _In_z_ const char* config_key); + + /// @} + + /** \brief Get the OrtMemoryInfo for the device. + * + * \param[in] ep_device The OrtEpDevice instance to query. + * \param[in] memory_type The memory type to return. + * \return A pointer to the OrtMemoryInfo for the device. This may be nullptr if not set. + * If memory_type is OrtDeviceMemoryType_DEFAULT and nullptr is returned the EP uses CPU memory. + * + * \since Version 1.23 + */ + ORT_API_T(const OrtMemoryInfo*, EpDevice_MemoryInfo, _In_ const OrtEpDevice* ep_device, + _In_ OrtDeviceMemoryType memory_type); + + /** \brief Create/replace a shared allocator for the OrtEpDevice in the OrtEnv. + * + * OrtEpDevice maps to the EP factory, and the factory provides the allocator implementation. + * + * Both OrtDeviceMemoryType_DEFAULT and OrtDeviceMemoryType_HOST_ACCESSIBLE are optional for an EP to provide. + * It is EP implementation dependent as to what is available. + * + * If a shared allocator already exists for the OrtEpDevice and OrtDeviceMemoryType, it is replaced. This allows + * changing the shared allocator configuration from the default. e.g. adding an arena. + * + * \param[in] env The OrtEnv instance to create the shared allocator in. + * \param[in] ep_device The OrtEpDevice instance to create the shared allocator for. + * \param[in] mem_type The memory type to use for the shared allocator. + * \param[in] allocator_type The type of allocator to create. Only OrtDeviceAllocator is valid currently. + * \param[in] allocator_options Optional key-value pairs to configure the allocator. If arena based, see + * include/onnxruntime/core/framework/allocator.h for the keys and values that can be + * used. + * \param[out] allocator A pointer to the created shared allocator. Owned by the OrtEnv instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(CreateSharedAllocator, _In_ OrtEnv* env, _In_ const OrtEpDevice* ep_device, + _In_ OrtDeviceMemoryType mem_type, _In_ OrtAllocatorType allocator_type, + _In_opt_ const OrtKeyValuePairs* allocator_options, + _Outptr_opt_ OrtAllocator** allocator); + + /** \brief Get a shared allocator from the OrtEnv. + * + * By default there is a shared allocator created for all OrtEpDevice instances, so if you get the OrtMemoryInfo + * from the OrtEpDevice using EpDevice_MemoryInfo a shared allocator is guaranteed to exist. + * + * This will also match and return custom allocators added with RegisterAllocator. + * + * It is not an error to not find a matching allocator. + * + * \param[in] env The OrtEnv instance to get the shared allocator from. + * \param[in] mem_info The OrtMemoryInfo instance to get the shared allocator for. + * \param[out] allocator A pointer to the shared allocator, or nullptr if no shared allocator exists for + * the given memory info. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(GetSharedAllocator, _In_ OrtEnv* env, _In_ const OrtMemoryInfo* mem_info, + _Outptr_result_maybenull_ OrtAllocator** allocator); + + /** \brief Release a shared allocator from the OrtEnv for the OrtEpDevice and memory type. + * + * This will release the shared allocator for the given OrtEpDevice and memory type. + * If no shared allocator exists, this is a no-op. + * + * \param[in] env The OrtEnv instance to release the shared allocator from. + * \param[in] ep_device The OrtEpDevice instance to release the shared allocator for. + * \param[in] mem_type The memory type of the shared allocator to release. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(ReleaseSharedAllocator, _In_ OrtEnv* env, _In_ const OrtEpDevice* ep_device, + _In_ OrtDeviceMemoryType mem_type); + + /** \brief Get a const pointer to the raw data inside a tensor + * + * Used to read the internal tensor data directly. + * \note The returned pointer is valid until the OrtValue is destroyed. + * + * \param[in] value A tensor type (string tensors are not supported) + * \param[out] out Filled in with a pointer to the internal storage + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(GetTensorData, _In_ const OrtValue* value, _Outptr_ const void** out); + + /** \brief Get Session configuration entries. + * + * \param[in] options The session options. + * \param[out] out A pointer to a newly created OrtKeyValuePairs instance. + * + * An OrtKeyValuePairs instance containing all session configuration entries. + * Note: the user should call OrtApi::ReleaseKeyValuePairs. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(GetSessionOptionsConfigEntries, _In_ const OrtSessionOptions* options, _Outptr_ OrtKeyValuePairs** out); + + /** \brief Get the OrtMemoryInfo for each input of the session. + * + * The memory info can be used to determine where the input tensors are required. + * + * The session must be fully initialized before calling this function as the input locations are not known until + * this has occurred. + * + * \param[in] session The OrtSession instance. + * \param[out] inputs_memory_info Pre-allocated array of size `num_inputs` that will be filled with the + * OrtMemoryInfo* value for each input. + * The order is the same as returned by SessionGetInputName. + * \param[in] num_inputs The number of inputs in the session. Must match SessionGetInputCount. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(SessionGetMemoryInfoForInputs, _In_ const OrtSession* session, + _Out_writes_(num_inputs) const OrtMemoryInfo** inputs_memory_info, + _In_ size_t num_inputs); + + /** \brief Get the OrtMemoryInfo for each output of the session. + * + * The memory info can be used to determine the device the output tensors are produced on. + * The user can pre-allocate an OrtValue using this information or use IOBinding to keep the data on the device. + * ORT will copy the output to CPU otherwise. + * + * The session must be fully initialized before calling this function as the output locations are not known until + * this has occurred. + * + * \param[in] session The OrtSession instance. + * \param[out] outputs_memory_info Pre-allocated array of size `num_outputs` that will be filled with + * OrtMemoryInfo* values for each output. + * The order is the same as returned by SessionGetOutputName. + * \param[in] num_outputs The number of outputs in the session. Must match SessionGetOutputCount. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(SessionGetMemoryInfoForOutputs, _In_ const OrtSession* session, + _Out_writes_(num_outputs) const OrtMemoryInfo** outputs_memory_info, + _In_ size_t num_outputs); + + /** \brief Get the OrtEpDevice (if available) for each input of the session. + * + * An OrtEpDevice will be available if auto EP selection is enabled by calling + * SessionOptionsSetEpSelectionPolicy or SessionOptionsSetEpSelectionPolicyDelegate, + * or if the OrtEpDevice was manually added to the session using SessionOptionsAppendExecutionProvider_V2. + * + * If an OrtEpDevice is not available for the input a nullptr is returned. + * + * The returned OrtEpDevice can be used to create an OrtSyncStream via CreateSyncStreamForEpDevice to asynchronously + * provide input to the inference session Run. + * + * The session must be fully initialized before calling this function as the assigned EPs are not known until + * this has occurred. + * + * \param[in] session The OrtSession instance. + * \param[out] inputs_ep_devices Pre-allocated array of size `num_inputs` that will be filled with + * OrtEpDevice* values for each input. + * The order is the same as returned by SessionGetInputName. + * \param[in] num_inputs The number of inputs in the session. Must match SessionGetInputCount. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(SessionGetEpDeviceForInputs, _In_ const OrtSession* session, + _Out_writes_(num_inputs) const OrtEpDevice** inputs_ep_devices, + _In_ size_t num_inputs); + + /** \brief Create an OrtSyncStream for the given OrtEpDevice. + * + * The OrtSyncStream can be used to enable asynchronous operations. + * e.g. async usage of CopyTensors to provide input to an OrtSession Run call. + * + * An error code of ORT_NOT_IMPLEMENTED will be returned if the EP does not support OrtSyncStream. + * + * \param[in] ep_device The OrtEpDevice instance to create the sync stream for. + * \param[in] stream_options Options for OrtSyncStream creation. May be nullptr. + * \param[out] stream Output parameter set to the created OrtSyncStream instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(CreateSyncStreamForEpDevice, _In_ const OrtEpDevice* ep_device, + _In_opt_ const OrtKeyValuePairs* stream_options, + _Outptr_ OrtSyncStream** stream); + + /** \brief Get the native handle of the sync stream. + * + * This returns the native handle for the stream. e.g. cudaStream_t for CUDA streams. + * + * \param[in] stream The OrtSyncStream instance to get the handle from. + * + * \returns The native handle of the stream. + * + * \since Version 1.23 + */ + ORT_API_T(void*, SyncStream_GetHandle, _In_ OrtSyncStream* stream); + + ORT_CLASS_RELEASE(SyncStream); + + /** \brief Copy OrtValue instances containing Tensors between devices. + * + * The overall copy must be between a single source device and a single destination device. i.e. + * - all src_tensors must have matching OrtMemoryInfo, + * - all dst_tensors must have matching OrtMemoryInfo. + * + * OrtValue instances can be created by: + * - Use GetSharedAllocator to get the shared allocator for the OrtMemoryInfo if you need to allocate memory + * on the device. + * - Use CreateTensorAsOrtValue, CreateTensorWithDataAsOrtValue or CreateTensorWithDataAndDeleterAsOrtValue + * to create an OrtValue containing a tensor depending on whether you have existing data or not, and whether + * you want ORT to free the existing data once it is done with the OrtValue. + * + * \param[in] env The OrtEnv instance to use. The data transfer implementation is provided by an execution provider + * that is registered in this OrtEnv. + * \param[in] src_tensors Array of OrtValue instances containing the source tensors to copy. + * \param[in] dst_tensors Array of OrtValue instances to copy the source tensors to. + * \param[in] stream Optional OrtSyncStream that can be used to perform the copy asynchronously. May be nullptr. + * \param[in] num_tensors The number of tensors to copy. The size of `src_tensors` and `dst_tensors` must match. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23 + */ + ORT_API2_STATUS(CopyTensors, _In_ const OrtEnv* env, + _In_reads_(num_tensors) const OrtValue* const* src_tensors, + _In_reads_(num_tensors) OrtValue* const* dst_tensors, + _In_opt_ OrtSyncStream* stream, + _In_ size_t num_tensors); + + /** \brief Get ::OrtModelMetadata from an ::OrtGraph + * + * \param[in] graph The OrtGraph instance. + * \param[out] out Newly created ::OrtModelMetadata. Must be freed using OrtApi::ReleaseModelMetadata. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Graph_GetModelMetadata, _In_ const OrtGraph* graph, _Outptr_ OrtModelMetadata** out); + + /** \brief Validate a compiled model's compatibility information for one or more EP devices. + * + * \param[in] ep_devices The EP devices to validate against (e.g., from GetEpDevices). + * All devices must belong to the same execution provider. + * \param[in] num_ep_devices The number of EP devices provided. + * \param[in] compatibility_info The compatibility info string produced when the model was compiled. + * \param[out] out_status The resulting compatibility status for the EP devices. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(GetModelCompatibilityForEpDevices, + _In_reads_(num_ep_devices) const OrtEpDevice* const* ep_devices, + _In_ size_t num_ep_devices, + _In_ const char* compatibility_info, + _Out_ OrtCompiledModelCompatibility* out_status); + + /// \name OrtExternalInitializerInfo + /// @{ + + /** \brief Creates an OrtExternalInitializerInfo instance. + * + * \param[in] filepath The relative path to the file that stores the initializer's data. ORT copies this path string. + * \param[in] file_offset The byte offset where the initializer's data is stored within the file. + * \param[in] byte_size The size in bytes of the initializer's data within the file. + * \param[out] out Output parameter set to the new OrtExternalInitializerInfo instance. + * Must be released by calling ReleaseExternalInitializerInfo(). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateExternalInitializerInfo, _In_ const ORTCHAR_T* filepath, _In_ int64_t file_offset, + _In_ size_t byte_size, _Outptr_ OrtExternalInitializerInfo** out); + + /// @} +}; + +/* + * Steps to use a custom op: + * 1 Create an OrtCustomOpDomain with the domain name used by the custom ops + * 2 Create an OrtCustomOp structure for each op and add them to the domain + * 3 Call OrtAddCustomOpDomain to add the custom domain of ops to the session options + */ + +// Specifies some characteristics of inputs/outputs of custom ops: +// Specify if the inputs/outputs are one of: +// 1) Non-optional (input/output must be present in the node) +// 2) Optional (input/output may be absent in the node) +// 3) Variadic: A variadic input or output specifies N (i.e., the minimum arity) or more operands. +// Only the last input or output of a custom op may be marked as variadic. +// The homogeneity of the variadic input or output determines whether all operands must be of the same +// tensor element type. +typedef enum OrtCustomOpInputOutputCharacteristic { + INPUT_OUTPUT_REQUIRED = 0, + INPUT_OUTPUT_OPTIONAL, + INPUT_OUTPUT_VARIADIC, +} OrtCustomOpInputOutputCharacteristic; + +/* + * The OrtCustomOp structure defines a custom op's schema and its kernel callbacks. The callbacks are filled in by + * the implementor of the custom op. + */ +struct OrtCustomOp { + uint32_t version; // Must be initialized to ORT_API_VERSION + + // This callback creates the kernel, which is a user defined + // parameter that is passed to the Kernel* callbacks below. It is + // recommended to use CreateKernelV2 which allows for a safe error + // propagation by returning an OrtStatusPtr. + void*(ORT_API_CALL* CreateKernel)(_In_ const struct OrtCustomOp* op, _In_ const OrtApi* api, + _In_ const OrtKernelInfo* info); + + // Returns the name of the op + const char*(ORT_API_CALL* GetName)(_In_ const struct OrtCustomOp* op); + + // Returns the type of the execution provider, return nullptr to use CPU execution provider + const char*(ORT_API_CALL* GetExecutionProviderType)(_In_ const struct OrtCustomOp* op); + + // Returns the count and types of the input & output tensors + ONNXTensorElementDataType(ORT_API_CALL* GetInputType)(_In_ const struct OrtCustomOp* op, _In_ size_t index); + size_t(ORT_API_CALL* GetInputTypeCount)(_In_ const struct OrtCustomOp* op); + ONNXTensorElementDataType(ORT_API_CALL* GetOutputType)(_In_ const struct OrtCustomOp* op, _In_ size_t index); + size_t(ORT_API_CALL* GetOutputTypeCount)(_In_ const struct OrtCustomOp* op); + + // Perform a computation step. It is recommended to use + // KernelComputeV2 which allows for a safe error propagation by + // returning an OrtStatusPtr. + void(ORT_API_CALL* KernelCompute)(_In_ void* op_kernel, _In_ OrtKernelContext* context); + void(ORT_API_CALL* KernelDestroy)(_In_ void* op_kernel); + + // Returns the characteristics of the input & output tensors + OrtCustomOpInputOutputCharacteristic(ORT_API_CALL* GetInputCharacteristic)(_In_ const struct OrtCustomOp* op, _In_ size_t index); + OrtCustomOpInputOutputCharacteristic(ORT_API_CALL* GetOutputCharacteristic)(_In_ const struct OrtCustomOp* op, _In_ size_t index); + + // Returns the memory type of the input tensors. This API allows the custom op + // to place the inputs on specific devices. By default, it returns + // OrtMemTypeDefault, which means the input is placed on the default device for + // the execution provider. If the inputs need to be with different memory types, + // this function can be overridden to return the specific memory types. + OrtMemType(ORT_API_CALL* GetInputMemoryType)(_In_ const struct OrtCustomOp* op, _In_ size_t index); + + // Returns the minimum number of input arguments expected for the variadic input. + // Applicable only for custom ops that have a variadic input. + int(ORT_API_CALL* GetVariadicInputMinArity)(_In_ const struct OrtCustomOp* op); + + // Returns true (non-zero) if all arguments of a variadic input have to be of the same type (homogeneous), + // and false (zero) otherwise. + // Applicable only for custom ops that have a variadic input. + int(ORT_API_CALL* GetVariadicInputHomogeneity)(_In_ const struct OrtCustomOp* op); + + // Returns the minimum number of output values expected for the variadic output. + // Applicable only for custom ops that have a variadic output. + int(ORT_API_CALL* GetVariadicOutputMinArity)(_In_ const struct OrtCustomOp* op); + + // Returns true (non-zero) if all outputs values of a variadic output have to be of the same type (homogeneous), + // and false (zero) otherwise. + // Applicable only for custom ops that have a variadic output. + int(ORT_API_CALL* GetVariadicOutputHomogeneity)(_In_ const struct OrtCustomOp* op); + + // Create the kernel state which is passed to each compute call. + OrtStatusPtr(ORT_API_CALL* CreateKernelV2)(_In_ const struct OrtCustomOp* op, _In_ const OrtApi* api, + _In_ const OrtKernelInfo* info, + _Out_ void** kernel); + + // Perform the computation step. + OrtStatusPtr(ORT_API_CALL* KernelComputeV2)(_In_ void* op_kernel, _In_ OrtKernelContext* context); + + OrtStatusPtr(ORT_API_CALL* InferOutputShapeFn)(_In_ const struct OrtCustomOp* op, _In_ OrtShapeInferContext*); + + // Get start range + int(ORT_API_CALL* GetStartVersion)(_In_ const struct OrtCustomOp* op); + int(ORT_API_CALL* GetEndVersion)(_In_ const struct OrtCustomOp* op); + + // Get the inplace_map that defines which output can reuse which input + // Callers will provide 2 raw int* and pass in their address, this function will fill these 2 arrays + // when return, output (*output_index)[i] may reuse the input (*input_index[i]). + // The return value is the size of these 2 arrays. + // Callers are responsible to delete these 2 arrays after use by calling OrtCustomOp::ReleaseMayInplace(). + size_t(ORT_API_CALL* GetMayInplace)(_Out_ int** input_index, _Out_ int** output_index); + + // Release the pointer input_index and output_index allocated from GetMayInplace() function. + // If GetMayInplace() is defined, this function MUST be defined as well. + void(ORT_API_CALL* ReleaseMayInplace)(_Frees_ptr_opt_ int* input_index, _Frees_ptr_opt_ int* output_index); + + // Same as GetMayInplace() and ReleaseMayInplace() + size_t(ORT_API_CALL* GetAliasMap)(_Out_ int** input_index, _Out_ int** output_index); + void(ORT_API_CALL* ReleaseAliasMap)(_Frees_ptr_opt_ int* input_index, _Frees_ptr_opt_ int* output_index); +}; + +/** + * ORT Model Editor API + */ + +/** + * \brief The OrtModelEditorApi struct provides functions to create or edit an ONNX model. + * + * See onnxruntime/test/shared_lib/test_model_editor_api.cc for example usage. + * + * \since Version 1.22. + */ +struct OrtModelEditorApi { + // Model building/editing requires a full build. We return nullptr from GetModelEditorApi if this is a minimal + // build, so it doesn't matter if there are no function pointers in this struct as a user will never get an + // OrtModelEditorApi instance. We do however need a dummy field to avoid empty struct warning. +#if defined(ORT_MINIMAL_BUILD) + const bool not_defined_in_this_build; +#else + /** \brief Create an OrtTypeInfo instance for a Tensor. + * + * Create an OrtTypeInfo instance for a Tensor to use as graph inputs/outputs with the Model Editor API. + * + * User can release `tensor_info` after creating the OrtTypeInfo. + * + * \param[in] tensor_info Tensor type and shape information. + * \param[out] type_info TypeInfo instance for the tensor. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateTensorTypeInfo, _In_ const OrtTensorTypeAndShapeInfo* tensor_info, + _Outptr_ OrtTypeInfo** type_info); + + /** \brief Create an OrtTypeInfo instance for a SparseTensor. + * + * Create an OrtTypeInfo instance for a SparseTensor to use as graph inputs/outputs with the Model Editor API. + * + * User can release `tensor_info` after creating the OrtTypeInfo. + * + * \param[in] tensor_info SparseTensor type and shape information. + * \param[out] type_info TypeInfo instance for the tensor. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateSparseTensorTypeInfo, _In_ const OrtTensorTypeAndShapeInfo* tensor_info, + _Outptr_ OrtTypeInfo** type_info); + + /** \brief Create an OrtTypeInfo instance for a Map. + * + * Create an OrtTypeInfo instance for a Map to use as graph inputs/outputs with the Model Editor API. + * + * User can release `map_value_type` after creating the OrtTypeInfo. + * + * \param[in] map_key_type Key type for the map. + * \param[in] map_value_type Value type for the map. + * \param[out] type_info TypeInfo instance for the map. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateMapTypeInfo, ONNXTensorElementDataType map_key_type, _In_ const OrtTypeInfo* map_value_type, + _Outptr_ OrtTypeInfo** type_info); + + /** \brief Create an OrtTypeInfo instance for a Sequence. + * + * Create an OrtTypeInfo instance for a Sequence to use as graph inputs/outputs with the Model Editor API. + * + * User can release `sequence_type` after creating the OrtTypeInfo. + * + * \param[in] sequence_type Sequence type and shape information. + * \param[out] type_info TypeInfo instance for the sequence. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateSequenceTypeInfo, _In_ const OrtTypeInfo* sequence_type, _Outptr_ OrtTypeInfo** type_info); + + /** \brief Create an OrtTypeInfo instance for an Optional. + * + * Create an OrtTypeInfo instance for an Optional to use as graph inputs/outputs with the Model Editor API. + * + * User can release `contained_type` after creating the OrtTypeInfo. + * + * \param[in] contained_type Tensor type and shape information. + * \param[out] type_info TypeInfo instance for the tensor. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateOptionalTypeInfo, _In_ const OrtTypeInfo* contained_type, _Outptr_ OrtTypeInfo** type_info); + + /** \brief Create an OrtValueInfo for use as an OrtGraph input or output. + * + * \param[in] name The name of the input or output. + * \param[in] type_info The type information for the input or output. The provided value is copied. + * \param[out] value_info The OrtValueInfo instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateValueInfo, _In_ const char* name, _In_ const OrtTypeInfo* type_info, + _Outptr_ OrtValueInfo** value_info); + + /** \brief Create an OrtNode to add to an OrtGraph. + * + * Create an OrtNode. + * + * Create attributes with CreateOpAttr. OrtOpAttr instances are copied. + * + * \param[in] operator_name The name of the operator. + * \param[in] domain_name The domain of the operator. Use an empty string for ONNX operators. + * \param[in] node_name The name of the node. + * \param[in] input_names The names of the inputs. + * \param[in] input_names_len The number of input names. + * \param[in] output_names The names of the outputs. + * \param[in] output_names_len The number of output names. + * \param[in] attributes The optional attributes of the node. + * \param[in] attribs_len The number of attributes. May be zero. + * \param[out] node The OrtNode instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateNode, _In_ const char* operator_name, _In_ const char* domain_name, _In_ const char* node_name, + _In_reads_(input_names_len) const char* const* input_names, size_t input_names_len, + _In_reads_(output_names_len) const char* const* output_names, size_t output_names_len, + _In_reads_(attribs_len) _In_opt_ OrtOpAttr** attributes, _In_ size_t attribs_len, + _Outptr_ OrtNode** node); + + /** \brief Create an OrtGraph + * \snippet{doc} snippets.dox OrtStatus Return Value + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateGraph, _Outptr_ OrtGraph** graph); + + /** \brief Set the inputs for the OrtGraph. + * + * Set the graph inputs. This will replace any existing inputs with the new values. + * The OrtGraph takes ownership of the OrtValueInfo instances and you should NOT call ReleaseOrtValueInfo. + * + * \param[in] graph The OrtGraph instance to update. + * \param[in] inputs The input OrtValueInfo instances. + * \param[in] inputs_len The number of input OrtValueInfo instances. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(SetGraphInputs, _Inout_ OrtGraph* graph, + _In_reads_(inputs_len) _In_ OrtValueInfo** inputs, _In_ size_t inputs_len); + + /** \brief Set the outputs for the OrtGraph. + * + * Set the graph outputs. This will replace any existing outputs with the new values. + * The OrtGraph takes ownership of the OrtValueInfo instances provided and you should NOT call ReleaseOrtValueInfo. + * + * \param[in] graph The OrtGraph instance to update. + * \param[in] outputs The output OrtValueInfo instances. + * \param[in] outputs_len The number of output OrtValueInfo instances. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(SetGraphOutputs, _Inout_ OrtGraph* graph, + _In_reads_(outputs_len) _In_ OrtValueInfo** outputs, _In_ size_t outputs_len); + + /** \brief Add an initializer to the OrtGraph + * + * ORT will take ownership of the OrtValue and you should NOT call ReleaseOrtValue. + * + * Two options: + * + * Allocated memory: + * Use CreateTensorAsOrtValue (allocates memory) and populate the tensor with the data. + * Set `data_is_external` to false. + * + * Pre-existing memory: + * Use CreateTensorWithDataAsOrtValue or CreateTensorWithDataAndDeleterAsOrtValue to create an OrtValue + * with a tensor that contains a pointer to the existing data. + * Set `data_is_external` to true. + * + * The pointer must remain valid for the duration of the inference session. + * If using CreateTensorWithDataAsOrtValue you are responsible for freeing the memory after the inference session + * is released. + * If using CreateTensorWithDataAndDeleterAsOrtValue, ORT will free the memory using the provided deleter as + * soon as the OrtValue is no longer in use. + * + * NOTE: A tensor containing pre-existing memory MUST have 128 bytes of data or more. + * For smaller tensors use CreateTensorAsOrtValue. + * + * ONNX shape inferencing does not support external data. An initializer involved in shape inferencing is + * typically small (a single value or limited by the rank of a tensor) and uses less than 128 bytes of + * memory, so this limit acts as a simple catch-all rule to avoid issues. + * e.g. Reshape's `shape`, Clip's `min` and `max`, various ops `axes`. + * + * \param[in] graph The OrtGraph instance to update. + * \param[in] name The value name for the initializer. + * \param[in] tensor The OrtValue instance containing the tensor data. + * \param[in] data_is_external Set to true if the data is external and should not be copied. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(AddInitializerToGraph, _Inout_ OrtGraph* graph, _In_ const char* name, _In_ OrtValue* tensor, + bool data_is_external); + + /** \brief Add an OrtNode to an OrtGraph + * + * Add the node to the graph. The OrtGraph will take ownership of OrtNode and you should NOT call ReleaseOrtNode. + * + * \param[in] graph The OrtGraph instance to update. + * \param[in] node The OrtNode instance to add to the graph. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(AddNodeToGraph, _Inout_ OrtGraph* graph, _In_ OrtNode* node); + + /** \brief Create an OrtModel. + * + * Create an OrtModel. + * + * This can be used to build a new model, or to augment an existing model. + * + * \param[in] domain_names The domain names for the model. + * If augmenting an existing model add additional domains if needed. + * \param[in] opset_versions The opset versions for the model. + * If augmenting an existing model add additional opset versions if needed. + * \param[in] opset_entries_len The number of domain_names and opset_versions entries. + * Domain and opset entries should be 1:1 + * \param[out] model The OrtModel instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateModel, + _In_reads_(opset_entries_len) const char* const* domain_names, + _In_reads_(opset_entries_len) const int* opset_versions, + size_t opset_entries_len, + _Outptr_ OrtModel** model); + + /** \brief Add an OrtGraph to an OrtModel. + * + * Add the graph to a model. This should be called once when creating a new model. + * + * The OrtModel takes ownership of the OrtGraph and you should NOT call ReleaseOrtGraph. + * + * \param[in] model The OrtModel instance to update. + * \param[in] graph The OrtGraph instance to add to the model. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(AddGraphToModel, _Inout_ OrtModel* model, _In_ OrtGraph* graph); + + /** \brief Create an OrtSession using the OrtModel. + * + * Create an inference session using the OrtModel instance. + * The OrtModel should have been populated with an OrtGraph containing nodes and initializers, and SetGraphInputs + * and SetGraphOutputs must have been called. + * This will validate the model, run optimizers, and prepare the session for inferencing. + * + * ReleaseOrtModel must be called to free the OrtModel after session creation. + * + * \param[in] env The OrtEnv instance. + * \param[in] model The OrtModel instance. + * \param[in] options The OrtSessionOptions instance. + * \param[out] out The OrtSession instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateSessionFromModel, _In_ const OrtEnv* env, _In_ const OrtModel* model, + _In_ const OrtSessionOptions* options, _Outptr_ OrtSession** out); + + /** \brief Create an OrtSession to augment an existing model. + * + * Create an OrtSession with an existing model that will be augmented with additional nodes and initializers. + * Nodes can be added before or after the existing nodes in the model. ONNX Runtime will connect the nodes when the + * model is finalized. + * + * To add nodes and initializers to the existing model, first create an OrtModel using CreateModel. + * Add nodes and initializers to the OrtModel using AddNodeToGraph and AddInitializerToGraph. + * Graph inputs/outputs should be updated with SetGraphInputs and SetGraphOutputs as needed to reflect changes made + * by the new nodes. The list of graph inputs/outputs should be for the overall model and not just the new nodes. + * + * Add the new information from the OrtModel to the original model using ApplyModelToSession, and prepare the + * session for inferencing by calling FinalizeModelEditorSession. + * + * \param{in} env The OrtEnv instance. + * \param{in} model_path The path to the existing ONNX model to augment. + * \param{in} options The OrtSessionOptions instance. + * \param{out} out The created OrtSession instance. + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateModelEditorSession, _In_ const OrtEnv* env, _In_ const ORTCHAR_T* model_path, + _In_ const OrtSessionOptions* options, + _Outptr_ OrtSession** out); + + /** \brief Create an OrtSession to augment an existing model. + * + * Create an OrtSession with an existing model that will be augmented with additional nodes and initializers. + * Nodes can be added before or after the existing nodes in the model. ONNX Runtime will connect the nodes when the + * model is finalized. + * + * To add nodes and initializers to the existing model, first create an OrtModel using CreateModel. + * Add nodes and initializers to the OrtModel using AddNodeToGraph and AddInitializerToGraph. + * Graph inputs/outputs should be updated with SetGraphInputs and SetGraphOutputs as needed to reflect changes made + * by the new nodes. The list of graph inputs/outputs should be for the overall model and not just the new nodes. + * + * Add the new information from the OrtModel to the original model using ApplyModelToSession, and prepare the + * session for inferencing by calling FinalizeModelEditorSession. + * + * \param{in} env The OrtEnv instance. + * \param{in} model_data The model data for the existing model to augment. + * \param{in} model_data_length The length of the model data. + * \param{in} options The OrtSessionOptions instance. + * \param{out} out The created OrtSession instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateModelEditorSessionFromArray, _In_ const OrtEnv* env, + _In_ const void* model_data, size_t model_data_length, + _In_ const OrtSessionOptions* options, + _Outptr_ OrtSession** out); + + /** \brief Query the session for the opset version of a domain. + * + * When using the Model Editor API to augment a model, any new nodes must conform to the opset version of the + * original model. To do that the user must be able to discover that opset version. + * Returns an error if the domain is not used in the model. + * + * \param[in] session OrtSession to query + * \param[in] domain Domain to query. The ONNX domain is an empty string. + * \param[out] opset The opset version of the domain. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(SessionGetOpsetForDomain, _In_ const OrtSession* session, _In_ const char* domain, _Out_ int* opset); + + /** \brief Apply changes to augment the ONNX model in a session created using CreateModelEditorSession[FromArray] + * + * Adds new nodes and updates graph inputs/outputs using `model` to augment the original ONNX model in the session. + * All changes will be validated. + * Call FinalizeModelEditorSession to prepare the session for inferencing. + * + * Existing input/outputs will only be updated if the OrtGraph inputs/outputs are set in the OrtModel. + * i.e. you don't need to call SetGraphInputs/SetGraphOutputs if they are unchanged. + * + * ReleaseOrtModel must be called to free the OrtModel after it is applied to the session. + * + * \param[in] session OrtSession to update. Session must have been created using CreateModelEditorSession[FromArray]. + * \param[in] model OrtModel containing new nodes, new initializers, and updated graph input and/or output info. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ApplyModelToModelEditorSession, _Inout_ OrtSession* session, _In_ OrtModel* model); + + /** \brief Finalize the Model Editor session that was created using CreateModelEditorSession[FromArray]. + * + * Finalize the Model Editor session that augmented an ONNX model by adding new nodes. + * This will run optimizers and prepare the session for inferencing. + * + * \param[in] session OrtSession to finalize. Session must have been created using CreateModelEditorSession[FromArray]. + * \param[in] options OrtSessionOptions to use for the session. + * \param[in] prepacked_weights_container Optional OrtPrepackedWeightsContainer to use for the session. + Set to nullptr if not used. + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(FinalizeModelEditorSession, _Inout_ OrtSession* session, _In_ const OrtSessionOptions* options, + _In_opt_ OrtPrepackedWeightsContainer* prepacked_weights_container); +#endif // !defined(ORT_MINIMAL_BUILD) +}; + +/** + * ORT Compile API + */ + +/** \brief Flags representing options to enable when compiling a model. + */ +typedef enum OrtCompileApiFlags { + // Default. Do not enable any additional compilation options. + OrtCompileApiFlags_NONE = 0, + + // Force compilation to return an error (ORT_FAIL) if no nodes were compiled. + // Otherwise, a model with basic optimizations (ORT_ENABLE_BASIC) is still generated by default. + OrtCompileApiFlags_ERROR_IF_NO_NODES_COMPILED = 1 << 0, + + // Force compilation to return an error (ORT_FAIL) if a file with the same filename as the output model exists. + // Otherwise, compilation will automatically overwrite the output file if it exists. + OrtCompileApiFlags_ERROR_IF_OUTPUT_FILE_EXISTS = 1 << 1, +} OrtCompileApiFlags; + +/** + * \brief The OrtCompileApi struct provides functions to compile ONNX models. + * + * Execution providers that support compilation fuse a subgraph into an EPContext node that wraps a provider-specific + * binary representation of the subgraph. + * For more details about the EPContext design, refer to: + * \htmlonly + * EPContext design document. + * \endhtmlonly + * + * Example (error handling not shown): + * OrtStatus* status = NULL; + * OrtCompileApi* compile_api = ort_api->GetCompileApi(); + * OrtModelCompilationOptions* compile_options = NULL; + * + * status = compile_api->CreateModelCompilationOptionsFromSessionOptions(env, session_options, &compile_options); + * status = compile_api->ModelCompilationOptions_SetInputModelPath(compile_options, ORT_TSTR("model.onnx")); + * status = compile_api->ModelCompilationOptions_SetOutputModelPath(compile_options, ORT_TSTR("model.compiled.onnx")); + * status = compile_api->CompileModel(env, compile_options); + * compile_api->ReleaseModelCompilationOptions(compile_options); + * + * \since Version 1.22. + */ +struct OrtCompileApi { + /// \name OrtModelCompilationOptions + /// @{ + ORT_CLASS_RELEASE(ModelCompilationOptions); + + /** \brief Creates an OrtModelCompilationOptions object from an existing OrtSessionOptions object. + * + * An OrtModelCompilationOptions object contains the settings used to generate a compiled ONNX model. + * The OrtSessionOptions object has the execution providers with which the model will be compiled. + * + * ReleaseOrtModelCompilationsOptions must be called to free the OrtModelCompilationOptions after calling + * CompileModel. + * + * \note By default, the GraphOptimizationLevel is set to ORT_DISABLE_ALL. Use + * ModelCompilationOptions_SetGraphOptimizationLevel to enable graph optimizations. + * + * \param[in] env OrtEnv object. + * \param[in] session_options The OrtSessionOptions instance from which to create the OrtModelCompilationOptions. + * \param[out] out The created OrtModelCompilationOptions instance. + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateModelCompilationOptionsFromSessionOptions, _In_ const OrtEnv* env, + _In_ const OrtSessionOptions* session_options, _Outptr_ OrtModelCompilationOptions** out); + + /** \brief Sets the file path to the input ONNX model to compile. + * + * The input model's location (e.g., file path or memory buffer) must be set with either + * ModelCompilationOptions_SetInputModelPath or ModelCompilationOptions_SetInputModelFromBuffer. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] input_model_path Null terminated string of the path (wchar on Windows, char otherwise). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetInputModelPath, _In_ OrtModelCompilationOptions* model_compile_options, + _In_ const ORTCHAR_T* input_model_path); + + /** \brief Sets the buffer that stores the bytes of the loaded ONNX model to compile. + * + * The input model's location (e.g., file path or memory buffer) must be set with either + * ModelCompilationOptions_SetInputModelPath or ModelCompilationOptions_SetInputModelFromBuffer. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] input_model_data Buffer containing the loaded ONNX model bytes. + * \param[in] input_model_data_size The number of bytes in the `input_model_data` buffer. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetInputModelFromBuffer, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ const void* input_model_data, + size_t input_model_data_size); + + /** \brief Sets the file path for the output ONNX model generated by CompileModel. + * + * The output model's location (e.g., file path or memory buffer) can be set with either + * ModelCompilationOptions_SetOutputModelPath or ModelCompilationOptions_SetOutputModelBuffer. + * + * If the output model's location is not set, ONNX Runtime will generate an output file with a path based on + * the input model's file path. Examples: + * /Path/my_model.onnx -> /Path/my_model_ctx.onnx + * /Path/my_model -> /Path/my_model_ctx.onnx + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] output_model_path Null terminated string of the path (wchar on Windows, char otherwise). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetOutputModelPath, _In_ OrtModelCompilationOptions* model_compile_options, + _In_ const ORTCHAR_T* output_model_path); + + /** \brief Optionally sets the file that should store external initializers for the compiled ONNX model. + * If not set, initializers are stored within the model. + * + * Only initializers for nodes that were not compiled are stored in the external initializers file. + * Compiled nodes contain their initializer data within the `ep_cache_context` attribute of EPContext nodes. + * Refer to ModelCompilationOptions_SetEpContextEmbedMode. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] external_initializers_file_path Null terminated string of the path to the file. + * \param[in] external_initializers_size_threshold Initializers larger than this threshold are stored in the file. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetOutputModelExternalInitializersFile, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ const ORTCHAR_T* external_initializers_file_path, + size_t external_initializers_size_threshold); + + /** \brief Configures model compilation to store the output compiled ONNX model in a buffer. + * + * The caller passes an OrtAllocator that ONNX Runtime uses to allocate memory for the buffer. + * + * The output model's location (e.g., file path or memory buffer) can be set with either + * ModelCompilationOptions_SetOutputModelPath or ModelCompilationOptions_SetOutputModelBuffer. + * + * If the output model's location is not set, ONNX Runtime will generate an output file with a path based on + * the input model's file path. Examples: + * /Path/my_model.onnx -> /Path/my_model_ctx.onnx + * /Path/my_model -> /Path/my_model_ctx.onnx + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] allocator The allocator used to allocate the buffer for the compiled model. + * \param[out] output_model_buffer_ptr Pointer to the buffer that stores the compiled model. + * \param[out] output_model_buffer_size_ptr Pointer set to the size of output model in bytes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetOutputModelBuffer, + _In_ OrtModelCompilationOptions* model_compile_options, + _Inout_ OrtAllocator* allocator, + _Outptr_ void** output_model_buffer_ptr, + _Out_ size_t* output_model_buffer_size_ptr); + + /** \brief Enables or disables the embedding of EPContext binary data into the `ep_cache_context` attribute + * of EPContext nodes. Defaults to false. + * + * If enabled, the `ep_cache_context` attribute of EPContext nodes will store the context binary data, which may + * include weights for compiled subgraphs. + * + * If disabled, the `ep_cache_context` attribute of EPContext nodes will contain the path to the file containing the + * context binary data. The path is set by the execution provider creating the EPContext node. + * + * More details relate to EPContext design refers to: + * \htmlonly + * EPContext design document. + * \endhtmlonly + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] embed_ep_context_in_model True to embed EPContext binary data into the EPContext node + * `ep_cache_context` attributes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetEpContextEmbedMode, _In_ OrtModelCompilationOptions* model_compile_options, + bool embed_ep_context_in_model); + + /** \brief Compiles an input ONNX model with the given compilation options. + * + * \param[in] env OrtEnv object. + * \param[in] model_options The compilation options that defines compilation options for a model. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CompileModel, _In_ const OrtEnv* env, _In_ const OrtModelCompilationOptions* model_options); + + /** \brief Sets flags from OrtCompileApiFlags that represent one or more boolean options to enable. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] flags bitwise OR of flags in OrtCompileApiFlags to enable. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetFlags, _In_ OrtModelCompilationOptions* model_compile_options, + uint32_t flags); + + /** Sets information related to EP context binary file. + * + * EP uses this information to decide the location and context binary file name. + * Used while compiling model with input and output in memory buffer + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] output_directory Null terminated string of the path (wchar on Windows, char otherwise). + * \param[in] model_name Null terminated string of the model name (wchar on Windows, char otherwise). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetEpContextBinaryInformation, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ const ORTCHAR_T* output_directory, + _In_ const ORTCHAR_T* model_name); + + /** Set the graph optimization level. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] graph_optimization_level The graph optimization level. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetGraphOptimizationLevel, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ GraphOptimizationLevel graph_optimization_level); + + /** \brief Sets a OrtWriteBufferFunc function that is called by ORT to write out the output model's serialized + * ONNX bytes. + * + * The provided write function may be called repeatedly until then entire output model has been written out. Each call + * to the write function is expected to consume the entire input buffer. + * + * The output model's destination (e.g., file path, memory buffer, or stream) can be set with any of the functions + * that begin with ModelCompilationOptions_SetOutputModel____. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] write_func The OrtWriteBufferFunc function called by ORT when writing out the model. + * \param[in] state Opaque state passed as the first argument to OrtWriteBufferFunc. Can be NULL. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetOutputModelWriteFunc, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ OrtWriteBufferFunc write_func, _In_ void* state); + + /** \brief Sets a OrtGetInitializerLocationFunc function that is called by ORT for every initializer in the generated + * model. Allows implementer to specify whether initializers should be stored within the model or externally. + * + * \param[in] model_compile_options The OrtModelCompilationOptions instance. + * \param[in] get_initializer_location_func The OrtGetInitializerLocationFunc function called by ORT when + * to determine the location of the initializer. + * \param[in] state Opaque state passed as the first argument to OrtGetInitializerLocationFunc. Can be NULL. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ModelCompilationOptions_SetOutputModelGetInitializerLocationFunc, + _In_ OrtModelCompilationOptions* model_compile_options, + _In_ OrtGetInitializerLocationFunc get_initializer_location_func, _In_ void* state); +}; + +/* + * This is the old way to add the CUDA provider to the session, please use SessionOptionsAppendExecutionProvider_CUDA above to access the latest functionality + * This function always exists, but will only succeed if Onnxruntime was built with CUDA support and the CUDA provider shared library exists + * + * \param device_id CUDA device id, starts from zero. + */ +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_CUDA, _In_ OrtSessionOptions* options, int device_id); + +/* + * This is the old way to add the ROCm provider to the session, please use + * SessionOptionsAppendExecutionProvider_ROCM above to access the latest functionality + * This function always exists, but will only succeed if Onnxruntime was built with + * HIP support and the ROCm provider shared library exists + * + * \param device_id HIP device id, starts from zero. + */ +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_ROCM, _In_ OrtSessionOptions* options, int device_id); + +/* + * This is the old way to add the MIGraphX provider to the session, please use + * SessionOptionsAppendExecutionProvider_MIGraphX above to access the latest functionality + * This function always exists, but will only succeed if Onnxruntime was built with + * HIP support and the MIGraphX provider shared library exists + * + * \param device_id HIP device id, starts from zero. + */ +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_MIGraphX, _In_ OrtSessionOptions* options, int device_id); + +/* + * This is the old way to add the oneDNN provider to the session, please use + * SessionOptionsAppendExecutionProvider_oneDNN above to access the latest functionality + * This function always exists, but will only succeed if Onnxruntime was built with + * oneDNN support and the oneDNN provider shared library exists + * + * \param use_arena zero: false. non-zero: true. + */ +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_Dnnl, _In_ OrtSessionOptions* options, int use_arena); + +/* + * This is the old way to add the TensorRT provider to the session, please use SessionOptionsAppendExecutionProvider_TensorRT_V2 above to access the latest functionality + * This function always exists, but will only succeed if Onnxruntime was built with TensorRT support and the TensorRT provider shared library exists + * + * \param device_id CUDA device id, starts from zero. + */ +ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_Tensorrt, _In_ OrtSessionOptions* options, int device_id); + +#ifdef __cplusplus +} +#endif +/// @} + +#include "onnxruntime_ep_c_api.h" diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_api.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_api.h new file mode 100644 index 0000000..879c232 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_api.h @@ -0,0 +1,3224 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +// Summary: The Ort C++ API is a header only wrapper around the Ort C API. +// +// The C++ API simplifies usage by returning values directly instead of error codes, throwing exceptions on errors +// and automatically releasing resources in the destructors. The primary purpose of C++ API is exception safety so +// all the resources follow RAII and do not leak memory. +// +// Each of the C++ wrapper classes holds only a pointer to the C internal object. Treat them like smart pointers. +// To create an empty object, pass 'nullptr' to the constructor (for example, Env e{nullptr};). However, you can't use them +// until you assign an instance that actually holds an underlying object. +// +// For Ort objects only move assignment between objects is allowed, there are no copy constructors. +// Some objects have explicit 'Clone' methods for this purpose. +// +// ConstXXXX types are copyable since they do not own the underlying C object, so you can pass them to functions as arguments +// by value or by reference. ConstXXXX types are restricted to const only interfaces. +// +// UnownedXXXX are similar to ConstXXXX but also allow non-const interfaces. +// +// The lifetime of the corresponding owning object must eclipse the lifetimes of the ConstXXXX/UnownedXXXX types. They exists so you do not +// have to fallback to C types and the API with the usual pitfalls. In general, do not use C API from your C++ code. + +#pragma once +#include "onnxruntime_c_api.h" +#include "onnxruntime_float16.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#ifdef ORT_NO_EXCEPTIONS +#include +#endif + +/** \brief All C++ Onnxruntime APIs are defined inside this namespace + * + */ +namespace Ort { + +/** \brief All C++ methods that can fail will throw an exception of this type + * + * If ORT_NO_EXCEPTIONS is defined, then any error will result in a call to abort() + */ +struct Exception : std::exception { + Exception(const std::string& string, OrtErrorCode code) : message_{string}, code_{code} {} + Exception(std::string&& string, OrtErrorCode code) : message_{std::move(string)}, code_{code} {} + + OrtErrorCode GetOrtErrorCode() const { return code_; } + const char* what() const noexcept override { return message_.c_str(); } + + private: + std::string message_; + OrtErrorCode code_; +}; + +#ifdef ORT_NO_EXCEPTIONS +// The #ifndef is for the very special case where the user of this library wants to define their own way of handling errors. +// NOTE: This header expects control flow to not continue after calling ORT_CXX_API_THROW +#ifndef ORT_CXX_API_THROW +#define ORT_CXX_API_THROW(string, code) \ + do { \ + std::cerr << Ort::Exception(string, code) \ + .what() \ + << std::endl; \ + abort(); \ + } while (false) +#endif +#else +#define ORT_CXX_API_THROW(string, code) \ + throw Ort::Exception(string, code) +#endif + +// This is used internally by the C++ API. This class holds the global variable that points to the OrtApi, +// it's in a template so that we can define a global variable in a header and make +// it transparent to the users of the API. +template +struct Global { + static const OrtApi* api_; +}; + +// If macro ORT_API_MANUAL_INIT is defined, no static initialization will be performed. Instead, user must call InitApi() before using it. +template +#ifdef ORT_API_MANUAL_INIT +const OrtApi* Global::api_{}; +inline void InitApi() noexcept { Global::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); } + +// Used by custom operator libraries that are not linked to onnxruntime. Sets the global API object, which is +// required by C++ APIs. +// +// Example mycustomop.cc: +// +// #define ORT_API_MANUAL_INIT +// #include +// #undef ORT_API_MANUAL_INIT +// +// OrtStatus* ORT_API_CALL RegisterCustomOps(OrtSessionOptions* options, const OrtApiBase* api_base) { +// Ort::InitApi(api_base->GetApi(ORT_API_VERSION)); +// // ... +// } +// +inline void InitApi(const OrtApi* api) noexcept { Global::api_ = api; } +#else +#if defined(_MSC_VER) && !defined(__clang__) +#pragma warning(push) +// "Global initializer calls a non-constexpr function." Therefore you can't use ORT APIs in the other global initializers. +// Please define ORT_API_MANUAL_INIT if it conerns you. +#pragma warning(disable : 26426) +#endif +const OrtApi* Global::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); +#if defined(_MSC_VER) && !defined(__clang__) +#pragma warning(pop) +#endif +#endif + +/// This returns a reference to the ORT C API. +inline const OrtApi& GetApi() noexcept { return *Global::api_; } + +/// +/// This function returns the onnxruntime version string +/// +/// version string major.minor.rev +std::string GetVersionString(); + +/// +/// This function returns the onnxruntime build information: including git branch, +/// git commit id, build type(Debug/Release/RelWithDebInfo) and cmake cpp flags. +/// +/// string +std::string GetBuildInfoString(); + +/// +/// This is a C++ wrapper for OrtApi::GetAvailableProviders() and +/// returns a vector of strings representing the available execution providers. +/// +/// vector of strings +std::vector GetAvailableProviders(); + +/// +/// This returns a reference to the ORT C Model Editor API. Used if building or augmenting a model at runtime. +/// +/// ORT C Model Editor API reference +inline const OrtModelEditorApi& GetModelEditorApi() { + auto* api = GetApi().GetModelEditorApi(); + if (api == nullptr) { + // minimal build + ORT_CXX_API_THROW("Model Editor API is not available in this build", ORT_FAIL); + } + + return *api; +} + +/// +/// This returns a reference to the ORT C Compile API. Used if compiling a model at runtime. +/// +/// ORT C Compile API reference +inline const OrtCompileApi& GetCompileApi() { + auto* api = GetApi().GetCompileApi(); + if (api == nullptr) { + // minimal build + ORT_CXX_API_THROW("Compile API is not available in this build", ORT_FAIL); + } + + return *api; +} + +/// +/// This returns a reference to the ORT C EP API. Used if authoring a plugin execution provider. +/// +/// ORT C EP API reference +inline const OrtEpApi& GetEpApi() { + auto* api = GetApi().GetEpApi(); + if (api == nullptr) { + // minimal build + ORT_CXX_API_THROW("EP API is not available in this build", ORT_FAIL); + } + + return *api; +} + +/** \brief IEEE 754 half-precision floating point data type + * + * \details This struct is used for converting float to float16 and back + * so the user could feed inputs and fetch outputs using these type. + * + * The size of the structure should align with uint16_t and one can freely cast + * uint16_t buffers to/from Ort::Float16_t to feed and retrieve data. + * + * \code{.unparsed} + * // This example demonstrates conversion from float to float16 + * constexpr float values[] = {1.f, 2.f, 3.f, 4.f, 5.f}; + * std::vector fp16_values; + * fp16_values.reserve(std::size(values)); + * std::transform(std::begin(values), std::end(values), std::back_inserter(fp16_values), + * [](float value) { return Ort::Float16_t(value); }); + * + * \endcode + */ +struct Float16_t : onnxruntime_float16::Float16Impl { + private: + /// + /// Constructor from a 16-bit representation of a float16 value + /// No conversion is done here. + /// + /// 16-bit representation + constexpr explicit Float16_t(uint16_t v) noexcept { val = v; } + + public: + using Base = onnxruntime_float16::Float16Impl; + + /// + /// Default constructor + /// + Float16_t() = default; + + /// + /// Explicit conversion to uint16_t representation of float16. + /// + /// uint16_t bit representation of float16 + /// new instance of Float16_t + constexpr static Float16_t FromBits(uint16_t v) noexcept { return Float16_t(v); } + + /// + /// __ctor from float. Float is converted into float16 16-bit representation. + /// + /// float value + explicit Float16_t(float v) noexcept { val = Base::ToUint16Impl(v); } + + /// + /// Converts float16 to float + /// + /// float representation of float16 value + float ToFloat() const noexcept { return Base::ToFloatImpl(); } + + /// + /// Checks if the value is negative + /// + /// true if negative + using Base::IsNegative; + + /// + /// Tests if the value is NaN + /// + /// true if NaN + using Base::IsNaN; + + /// + /// Tests if the value is finite + /// + /// true if finite + using Base::IsFinite; + + /// + /// Tests if the value represents positive infinity. + /// + /// true if positive infinity + using Base::IsPositiveInfinity; + + /// + /// Tests if the value represents negative infinity + /// + /// true if negative infinity + using Base::IsNegativeInfinity; + + /// + /// Tests if the value is either positive or negative infinity. + /// + /// True if absolute value is infinity + using Base::IsInfinity; + + /// + /// Tests if the value is NaN or zero. Useful for comparisons. + /// + /// True if NaN or zero. + using Base::IsNaNOrZero; + + /// + /// Tests if the value is normal (not zero, subnormal, infinite, or NaN). + /// + /// True if so + using Base::IsNormal; + + /// + /// Tests if the value is subnormal (denormal). + /// + /// True if so + using Base::IsSubnormal; + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + using Base::Abs; + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + using Base::Negate; + + /// + /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check + /// for two values by or'ing the private bits together and stripping the sign. They are both zero, + /// and therefore equivalent, if the resulting value is still zero. + /// + /// first value + /// second value + /// True if both arguments represent zero + using Base::AreZero; + + /// + /// User defined conversion operator. Converts Float16_t to float. + /// + explicit operator float() const noexcept { return ToFloat(); } + + using Base::operator==; + using Base::operator!=; + using Base::operator<; +}; + +static_assert(sizeof(Float16_t) == sizeof(uint16_t), "Sizes must match"); + +/** \brief bfloat16 (Brain Floating Point) data type + * + * \details This struct is used for converting float to bfloat16 and back + * so the user could feed inputs and fetch outputs using these type. + * + * The size of the structure should align with uint16_t and one can freely cast + * uint16_t buffers to/from Ort::BFloat16_t to feed and retrieve data. + * + * \code{.unparsed} + * // This example demonstrates conversion from float to float16 + * constexpr float values[] = {1.f, 2.f, 3.f, 4.f, 5.f}; + * std::vector bfp16_values; + * bfp16_values.reserve(std::size(values)); + * std::transform(std::begin(values), std::end(values), std::back_inserter(bfp16_values), + * [](float value) { return Ort::BFloat16_t(value); }); + * + * \endcode + */ +struct BFloat16_t : onnxruntime_float16::BFloat16Impl { + private: + /// + /// Constructor from a uint16_t representation of bfloat16 + /// used in FromBits() to escape overload resolution issue with + /// constructor from float. + /// No conversion is done. + /// + /// 16-bit bfloat16 value + constexpr explicit BFloat16_t(uint16_t v) noexcept { val = v; } + + public: + using Base = onnxruntime_float16::BFloat16Impl; + + BFloat16_t() = default; + + /// + /// Explicit conversion to uint16_t representation of bfloat16. + /// + /// uint16_t bit representation of bfloat16 + /// new instance of BFloat16_t + static constexpr BFloat16_t FromBits(uint16_t v) noexcept { return BFloat16_t(v); } + + /// + /// __ctor from float. Float is converted into bfloat16 16-bit representation. + /// + /// float value + explicit BFloat16_t(float v) noexcept { val = Base::ToUint16Impl(v); } + + /// + /// Converts bfloat16 to float + /// + /// float representation of bfloat16 value + float ToFloat() const noexcept { return Base::ToFloatImpl(); } + + /// + /// Checks if the value is negative + /// + /// true if negative + using Base::IsNegative; + + /// + /// Tests if the value is NaN + /// + /// true if NaN + using Base::IsNaN; + + /// + /// Tests if the value is finite + /// + /// true if finite + using Base::IsFinite; + + /// + /// Tests if the value represents positive infinity. + /// + /// true if positive infinity + using Base::IsPositiveInfinity; + + /// + /// Tests if the value represents negative infinity + /// + /// true if negative infinity + using Base::IsNegativeInfinity; + + /// + /// Tests if the value is either positive or negative infinity. + /// + /// True if absolute value is infinity + using Base::IsInfinity; + + /// + /// Tests if the value is NaN or zero. Useful for comparisons. + /// + /// True if NaN or zero. + using Base::IsNaNOrZero; + + /// + /// Tests if the value is normal (not zero, subnormal, infinite, or NaN). + /// + /// True if so + using Base::IsNormal; + + /// + /// Tests if the value is subnormal (denormal). + /// + /// True if so + using Base::IsSubnormal; + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + using Base::Abs; + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + using Base::Negate; + + /// + /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check + /// for two values by or'ing the private bits together and stripping the sign. They are both zero, + /// and therefore equivalent, if the resulting value is still zero. + /// + /// first value + /// second value + /// True if both arguments represent zero + using Base::AreZero; + + /// + /// User defined conversion operator. Converts BFloat16_t to float. + /// + explicit operator float() const noexcept { return ToFloat(); } + + // We do not have an inherited impl for the below operators + // as the internal class implements them a little differently + bool operator==(const BFloat16_t& rhs) const noexcept; + bool operator!=(const BFloat16_t& rhs) const noexcept { return !(*this == rhs); } + bool operator<(const BFloat16_t& rhs) const noexcept; +}; + +static_assert(sizeof(BFloat16_t) == sizeof(uint16_t), "Sizes must match"); + +/** \brief float8e4m3fn (Float8 Floating Point) data type + * \details It is necessary for type dispatching to make use of C++ API + * The type is implicitly convertible to/from uint8_t. + * See https://onnx.ai/onnx/technical/float8.html for further details. + */ +struct Float8E4M3FN_t { + uint8_t value; + constexpr Float8E4M3FN_t() noexcept : value(0) {} + constexpr Float8E4M3FN_t(uint8_t v) noexcept : value(v) {} + constexpr operator uint8_t() const noexcept { return value; } + // nan values are treated like any other value for operator ==, != + constexpr bool operator==(const Float8E4M3FN_t& rhs) const noexcept { return value == rhs.value; }; + constexpr bool operator!=(const Float8E4M3FN_t& rhs) const noexcept { return value != rhs.value; }; +}; + +static_assert(sizeof(Float8E4M3FN_t) == sizeof(uint8_t), "Sizes must match"); + +/** \brief float8e4m3fnuz (Float8 Floating Point) data type + * \details It is necessary for type dispatching to make use of C++ API + * The type is implicitly convertible to/from uint8_t. + * See https://onnx.ai/onnx/technical/float8.html for further details. + */ +struct Float8E4M3FNUZ_t { + uint8_t value; + constexpr Float8E4M3FNUZ_t() noexcept : value(0) {} + constexpr Float8E4M3FNUZ_t(uint8_t v) noexcept : value(v) {} + constexpr operator uint8_t() const noexcept { return value; } + // nan values are treated like any other value for operator ==, != + constexpr bool operator==(const Float8E4M3FNUZ_t& rhs) const noexcept { return value == rhs.value; }; + constexpr bool operator!=(const Float8E4M3FNUZ_t& rhs) const noexcept { return value != rhs.value; }; +}; + +static_assert(sizeof(Float8E4M3FNUZ_t) == sizeof(uint8_t), "Sizes must match"); + +/** \brief float8e5m2 (Float8 Floating Point) data type + * \details It is necessary for type dispatching to make use of C++ API + * The type is implicitly convertible to/from uint8_t. + * See https://onnx.ai/onnx/technical/float8.html for further details. + */ +struct Float8E5M2_t { + uint8_t value; + constexpr Float8E5M2_t() noexcept : value(0) {} + constexpr Float8E5M2_t(uint8_t v) noexcept : value(v) {} + constexpr operator uint8_t() const noexcept { return value; } + // nan values are treated like any other value for operator ==, != + constexpr bool operator==(const Float8E5M2_t& rhs) const noexcept { return value == rhs.value; }; + constexpr bool operator!=(const Float8E5M2_t& rhs) const noexcept { return value != rhs.value; }; +}; + +static_assert(sizeof(Float8E5M2_t) == sizeof(uint8_t), "Sizes must match"); + +/** \brief float8e5m2fnuz (Float8 Floating Point) data type + * \details It is necessary for type dispatching to make use of C++ API + * The type is implicitly convertible to/from uint8_t. + * See https://onnx.ai/onnx/technical/float8.html for further details. + */ +struct Float8E5M2FNUZ_t { + uint8_t value; + constexpr Float8E5M2FNUZ_t() noexcept : value(0) {} + constexpr Float8E5M2FNUZ_t(uint8_t v) noexcept : value(v) {} + constexpr operator uint8_t() const noexcept { return value; } + // nan values are treated like any other value for operator ==, != + constexpr bool operator==(const Float8E5M2FNUZ_t& rhs) const noexcept { return value == rhs.value; }; + constexpr bool operator!=(const Float8E5M2FNUZ_t& rhs) const noexcept { return value != rhs.value; }; +}; + +static_assert(sizeof(Float8E5M2FNUZ_t) == sizeof(uint8_t), "Sizes must match"); + +namespace detail { +// This is used internally by the C++ API. This macro is to make it easy to generate overloaded methods for all of the various OrtRelease* functions for every Ort* type +// This can't be done in the C API since C doesn't have function overloading. +#define ORT_DEFINE_RELEASE(NAME) \ + inline void OrtRelease(Ort##NAME* ptr) { GetApi().Release##NAME(ptr); } + +#define ORT_DEFINE_RELEASE_FROM_API_STRUCT(NAME, API_GETTER) \ + inline void OrtRelease(Ort##NAME* ptr) { API_GETTER().Release##NAME(ptr); } + +ORT_DEFINE_RELEASE(Allocator); +ORT_DEFINE_RELEASE(ArenaCfg); +ORT_DEFINE_RELEASE(CustomOpDomain); +ORT_DEFINE_RELEASE(Env); +ORT_DEFINE_RELEASE(ExternalInitializerInfo); +ORT_DEFINE_RELEASE(Graph); +ORT_DEFINE_RELEASE(IoBinding); +ORT_DEFINE_RELEASE(KernelInfo); +ORT_DEFINE_RELEASE(KeyValuePairs); +ORT_DEFINE_RELEASE(LoraAdapter); +ORT_DEFINE_RELEASE(MemoryInfo); +ORT_DEFINE_RELEASE(MapTypeInfo); +ORT_DEFINE_RELEASE(Model); +ORT_DEFINE_RELEASE(ModelMetadata); +ORT_DEFINE_RELEASE(Node); +ORT_DEFINE_RELEASE(Op); +ORT_DEFINE_RELEASE(OpAttr); +ORT_DEFINE_RELEASE(PrepackedWeightsContainer); +ORT_DEFINE_RELEASE(RunOptions); +ORT_DEFINE_RELEASE(Session); +ORT_DEFINE_RELEASE(SessionOptions); +ORT_DEFINE_RELEASE(SequenceTypeInfo); +ORT_DEFINE_RELEASE(Status); +ORT_DEFINE_RELEASE(SyncStream); +ORT_DEFINE_RELEASE(TensorTypeAndShapeInfo); +ORT_DEFINE_RELEASE(ThreadingOptions); +ORT_DEFINE_RELEASE(TypeInfo); +ORT_DEFINE_RELEASE(Value); +ORT_DEFINE_RELEASE(ValueInfo); + +ORT_DEFINE_RELEASE_FROM_API_STRUCT(ModelCompilationOptions, GetCompileApi); +ORT_DEFINE_RELEASE_FROM_API_STRUCT(EpDevice, GetEpApi); + +// This is defined explicitly since OrtTensorRTProviderOptionsV2 is not a C API type, +// but the struct has V2 in its name to indicate that it is the second version of the options. +inline void OrtRelease(OrtTensorRTProviderOptionsV2* ptr) { GetApi().ReleaseTensorRTProviderOptions(ptr); } +inline void OrtRelease(OrtCUDAProviderOptionsV2* ptr) { GetApi().ReleaseCUDAProviderOptions(ptr); } + +#undef ORT_DEFINE_RELEASE +#undef ORT_DEFINE_RELEASE_FROM_API_STRUCT + +/** \brief This is a tagging template type. Use it with Base to indicate that the C++ interface object + * has no ownership of the underlying C object. + */ +template +struct Unowned { + using Type = T; +}; + +/** \brief Used internally by the C++ API. C++ wrapper types inherit from this. + * This is a zero cost abstraction to wrap the C API objects and delete them on destruction. + * + * All of the C++ classes + * a) serve as containers for pointers to objects that are created by the underlying C API. + * Their size is just a pointer size, no need to dynamically allocate them. Use them by value. + * b) Each of struct XXXX, XXX instances function as smart pointers to the underlying C API objects. + * they would release objects owned automatically when going out of scope, they are move-only. + * c) ConstXXXX and UnownedXXX structs function as non-owning, copyable containers for the above pointers. + * ConstXXXX allow calling const interfaces only. They give access to objects that are owned by somebody else + * such as Onnxruntime or instances of XXXX classes. + * d) serve convenient interfaces that return C++ objects and further enhance exception and type safety so they can be used + * in C++ code. + * + */ + +/// +/// This is a non-const pointer holder that is move-only. Disposes of the pointer on destruction. +/// +template +struct Base { + using contained_type = T; + + constexpr Base() = default; + constexpr explicit Base(contained_type* p) noexcept : p_{p} {} + ~Base() { + OrtRelease(p_); + } + + Base(const Base&) = delete; + Base& operator=(const Base&) = delete; + + Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; } + Base& operator=(Base&& v) noexcept { + OrtRelease(p_); + p_ = v.release(); + return *this; + } + + constexpr operator contained_type*() const noexcept { return p_; } + constexpr contained_type& operator*() const noexcept { return *p_; } + + /// \brief Relinquishes ownership of the contained C object pointer + /// The underlying object is not destroyed + contained_type* release() { + T* p = p_; + p_ = nullptr; + return p; + } + + protected: + contained_type* p_{}; +}; + +// Undefined. For const types use Base> +template +struct Base; + +/// +/// Covers unowned pointers owned by either the ORT +/// or some other instance of CPP wrappers. +/// Used for ConstXXX and UnownedXXXX types that are copyable. +/// Also convenient to wrap raw OrtXX pointers . +/// +/// +template +struct Base> { + using contained_type = typename Unowned::Type; + + constexpr Base() = default; + constexpr explicit Base(contained_type* p) noexcept : p_{p} {} + + ~Base() = default; + + Base(const Base&) = default; + Base& operator=(const Base&) = default; + + Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; } + Base& operator=(Base&& v) noexcept { + p_ = nullptr; + std::swap(p_, v.p_); + return *this; + } + + constexpr operator contained_type*() const noexcept { return p_; } + constexpr contained_type& operator*() const noexcept { return *p_; } + + protected: + contained_type* p_{}; +}; + +// Light functor to release memory with OrtAllocator +struct AllocatedFree { + OrtAllocator* allocator_; + explicit AllocatedFree(OrtAllocator* allocator) + : allocator_(allocator) {} + void operator()(void* ptr) const { + if (ptr) allocator_->Free(allocator_, ptr); + } +}; + +} // namespace detail + +struct AllocatorWithDefaultOptions; +struct Env; +struct EpDevice; +struct ExternalInitializerInfo; +struct Graph; +struct Model; +struct Node; +struct ModelMetadata; +struct TypeInfo; +struct PrepackedWeightsContainer; +struct Session; +struct SessionOptions; +struct SyncStream; +struct TensorRTProviderOptions; +struct Value; +struct ValueInfo; + +/** \brief unique_ptr typedef used to own strings allocated by OrtAllocators + * and release them at the end of the scope. The lifespan of the given allocator + * must eclipse the lifespan of AllocatedStringPtr instance + */ +using AllocatedStringPtr = std::unique_ptr; + +/** \brief The Status that holds ownership of OrtStatus received from C API + * Use it to safely destroy OrtStatus* returned from the C API. Use appropriate + * constructors to construct an instance of a Status object from exceptions. + */ +struct Status : detail::Base { + Status() = default; // Same as with std::nullptr_t. But can be used in re-sizable containers and represent success. + explicit Status(std::nullptr_t) noexcept {} ///< Create an empty object, must be assigned a valid one to be used + explicit Status(OrtStatus* status) noexcept; ///< Takes ownership of OrtStatus instance returned from the C API. + explicit Status(const Exception&); ///< Creates status instance out of exception + explicit Status(const std::exception&); ///< Creates status instance out of exception + Status(const char* message, OrtErrorCode code); ///< Creates status instance out of null-terminated string message. + std::string GetErrorMessage() const; + OrtErrorCode GetErrorCode() const; + bool IsOK() const noexcept; ///< Returns true if instance represents an OK (non-error) status. +}; + +/** \brief The ThreadingOptions + * + * The ThreadingOptions used for set global threadpools' options of The Env. + */ +struct ThreadingOptions : detail::Base { + /// \brief Wraps OrtApi::CreateThreadingOptions + ThreadingOptions(); + + /// \brief Wraps OrtApi::SetGlobalIntraOpNumThreads + ThreadingOptions& SetGlobalIntraOpNumThreads(int intra_op_num_threads); + + /// \brief Wraps OrtApi::SetGlobalInterOpNumThreads + ThreadingOptions& SetGlobalInterOpNumThreads(int inter_op_num_threads); + + /// \brief Wraps OrtApi::SetGlobalSpinControl + ThreadingOptions& SetGlobalSpinControl(int allow_spinning); + + /// \brief Wraps OrtApi::SetGlobalDenormalAsZero + ThreadingOptions& SetGlobalDenormalAsZero(); + + /// \brief Wraps OrtApi::SetGlobalCustomCreateThreadFn + ThreadingOptions& SetGlobalCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn); + + /// \brief Wraps OrtApi::SetGlobalCustomThreadCreationOptions + ThreadingOptions& SetGlobalCustomThreadCreationOptions(void* ort_custom_thread_creation_options); + + /// \brief Wraps OrtApi::SetGlobalCustomJoinThreadFn + ThreadingOptions& SetGlobalCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn); +}; + +/** \brief The TensorRTOptions (V2) + * + * Used to pass options to TRT EP + */ +struct TensorRTProviderOptions : detail::Base { + TensorRTProviderOptions(std::nullptr_t) {} + /// \brief Wraps OrtApi::CreateTensorRTProviderOptionsV2 + TensorRTProviderOptions(); + ///< Wrapper around OrtApi::UpdateTensorRTProviderOptions + void Update(const std::unordered_map& options); + ///< Wrapper around OrtApi::UpdateTensorRTProviderOptions + void UpdateWithValue(const char* key, void* value); + + ///< Wrapper around OrtApi::GetTensorRTProviderOptionsByName + void* GetOptionByName(const char* name) const; + ///< Wrapper around OrtApi::GetTensorRTProviderOptionsAsString + std::string GetTensorRTProviderOptionsAsString() const; +}; + +/** \brief The CUDAProviderOptions (V2) + * + * Used to pass options to CUDA EP + */ +struct CUDAProviderOptions : detail::Base { + CUDAProviderOptions(std::nullptr_t) {} + /// \brief Wraps OrtApi::CreateCUDAProviderOptions + CUDAProviderOptions(); + ///< Wrapper around OrtApi::UpdateCUDAProviderOptions + void Update(const std::unordered_map& options); + ///< Wrapper around OrtApi::GetCUDAProviderOptionsAsString + std::string GetCUDAProviderOptionsAsString() const; + ///< Wrapper around OrtApi::UpdateCUDAProviderOptionsWithValue + void UpdateWithValue(const char* key, void* value); + ///< Wrapper around OrtApi::GetCUDAProviderOptionsByName + void* GetOptionByName(const char* name) const; +}; + +/** \brief The PrepackedWeightsContainer + * + * Create only and pass to Ort::Session constructor for multiple sessions + * to share pre-packed weights. + */ +struct PrepackedWeightsContainer : detail::Base { + using Base = detail::Base; + ///< No instance is created + explicit PrepackedWeightsContainer(std::nullptr_t) {} + ///< Take ownership of a pointer created by C API + explicit PrepackedWeightsContainer(OrtPrepackedWeightsContainer* p) : Base{p} {} + /// \brief Wraps OrtApi::CreatePrepackedWeightsContainer + PrepackedWeightsContainer(); +}; + +namespace detail { +template +struct ConstExternalInitializerInfoImpl : Base { + using B = Base; + using B::B; + + // Wraps OrtApi::ExternalInitializerInfo_GetFilePath + const std::basic_string GetFilePath() const; + // Wraps OrtApi::ExternalInitializerInfo_GetFileOffset + int64_t GetFileOffset() const; + // Wraps OrtApi::ExternalInitializerInfo_GetByteSize + size_t GetByteSize() const; +}; +} // namespace detail + +// Const object holder that does not own the underlying object +using ConstExternalInitializerInfo = + detail::ConstExternalInitializerInfoImpl>; + +/** \brief Wrapper around ::OrtExternalInitializerInfo + * + */ +struct ExternalInitializerInfo : detail::ConstExternalInitializerInfoImpl { + using Base = detail::ConstExternalInitializerInfoImpl; + using Base::Base; + + explicit ExternalInitializerInfo(std::nullptr_t) {} + explicit ExternalInitializerInfo(OrtExternalInitializerInfo* p) + : detail::ConstExternalInitializerInfoImpl{p} {} + + ConstExternalInitializerInfo GetConst() const { return ConstExternalInitializerInfo{this->p_}; } + + ///< Wraps OrtApi::CreateExternalInitializerInfo + ExternalInitializerInfo(const ORTCHAR_T* filepath, int64_t file_offset, size_t byte_size); + + ///< Wrapper around CreateExternalInitializerInfo that does not throw an exception. + static Status Create(const ORTCHAR_T* filepath, int64_t file_offset, size_t byte_size, + /*out*/ ExternalInitializerInfo& out); +}; + +namespace detail { +template +struct KeyValuePairsImpl : Ort::detail::Base { + using B = Ort::detail::Base; + using B::B; + + const char* GetValue(const char* key) const; + + // get the pairs in unordered_map. needs to copy to std::string so the hash works as expected + std::unordered_map GetKeyValuePairs() const; + // get the pairs in two vectors. entries will be 1:1 between keys and values. avoids copying to std::string + void GetKeyValuePairs(std::vector& keys, std::vector& values) const; +}; +} // namespace detail + +// Const object holder that does not own the underlying object +using ConstKeyValuePairs = detail::KeyValuePairsImpl>; + +/** \brief Wrapper around ::OrtKeyValuePairs */ +struct KeyValuePairs : detail::KeyValuePairsImpl { + explicit KeyValuePairs(std::nullptr_t) {} ///< No instance is created + /// Take ownership of a pointer created by C API + explicit KeyValuePairs(OrtKeyValuePairs* p) : KeyValuePairsImpl{p} {} + + /// \brief Wraps OrtApi::CreateKeyValuePairs + explicit KeyValuePairs(); + + /// \brief Wraps OrtApi::CreateKeyValuePairs and OrtApi::AddKeyValuePair + explicit KeyValuePairs(const std::unordered_map& kv_pairs); + + /// \brief Wraps OrtApi::AddKeyValuePair + void Add(const char* key, const char* value); + + /// \brief Wraps OrtApi::RemoveKeyValuePair + void Remove(const char* key); + + ConstKeyValuePairs GetConst() const { return ConstKeyValuePairs{this->p_}; } +}; + +namespace detail { +template +struct MemoryInfoImpl : Base { + using B = Base; + using B::B; + + std::string GetAllocatorName() const; ///< Wrapper MemoryInfoGetName + OrtAllocatorType GetAllocatorType() const; ///< Wrapper MemoryInfoGetType + int GetDeviceId() const; ///< Wrapper MemoryInfoGetId + OrtMemoryInfoDeviceType GetDeviceType() const; ///< Wrapper MemoryInfoGetDeviceType + OrtMemType GetMemoryType() const; ///< Wrapper MemoryInfoGetMemType + OrtDeviceMemoryType GetDeviceMemoryType() const; ///< Wrapper MemoryInfoGetDeviceMemType + uint32_t GetVendorId() const; ///< Wrapper MemoryInfoGetVendorId + + template + bool operator==(const MemoryInfoImpl& o) const; +}; +} // namespace detail + +// Const object holder that does not own the underlying object +using ConstMemoryInfo = detail::MemoryInfoImpl>; + +/** \brief Wrapper around ::OrtMemoryInfo + * + */ +struct MemoryInfo : detail::MemoryInfoImpl { + static MemoryInfo CreateCpu(OrtAllocatorType type, OrtMemType mem_type1); + explicit MemoryInfo(std::nullptr_t) {} ///< No instance is created + explicit MemoryInfo(OrtMemoryInfo* p) : MemoryInfoImpl{p} {} ///< Take ownership of a pointer created by C API + MemoryInfo(const char* name, OrtAllocatorType type, int id, OrtMemType mem_type); + MemoryInfo(const char* name, OrtMemoryInfoDeviceType device_type, uint32_t vendor_id, uint32_t device_id, + OrtDeviceMemoryType mem_type, size_t alignment, OrtAllocatorType allocator_type); ///< Wrapper around CreateMemoryInfo_V2 + ConstMemoryInfo GetConst() const { return ConstMemoryInfo{this->p_}; } +}; + +/// +/// Represents native memory allocation coming from one of the +/// OrtAllocators registered with OnnxRuntime. +/// Use it to wrap an allocation made by an allocator +/// so it can be automatically released when no longer needed. +/// +struct MemoryAllocation { + MemoryAllocation(OrtAllocator* allocator, void* p, size_t size); + ~MemoryAllocation(); + MemoryAllocation(const MemoryAllocation&) = delete; + MemoryAllocation& operator=(const MemoryAllocation&) = delete; + MemoryAllocation(MemoryAllocation&&) noexcept; + MemoryAllocation& operator=(MemoryAllocation&&) noexcept; + + void* get() { return p_; } + size_t size() const { return size_; } + + private: + OrtAllocator* allocator_; + void* p_; + size_t size_; +}; + +namespace detail { +template +struct AllocatorImpl : Base { + using B = Base; + using B::B; + + void* Alloc(size_t size); + MemoryAllocation GetAllocation(size_t size); + void Free(void* p); + ConstMemoryInfo GetInfo() const; + + /** \brief Function that returns the statistics of the allocator. + * + * \return A pointer to a KeyValuePairs object that will be filled with the allocator statistics. + */ + KeyValuePairs GetStats() const; +}; +} // namespace detail + +/** \brief Wrapper around ::OrtAllocator default instance that is owned by Onnxruntime + * + */ +struct AllocatorWithDefaultOptions : detail::AllocatorImpl> { + explicit AllocatorWithDefaultOptions(std::nullptr_t) {} ///< Convenience to create a class member and then replace with an instance + AllocatorWithDefaultOptions(); +}; + +/** \brief Wrapper around ::OrtAllocator + * + */ + +struct Allocator : detail::AllocatorImpl { + explicit Allocator(std::nullptr_t) {} ///< Convenience to create a class member and then replace with an instance + Allocator(const Session& session, const OrtMemoryInfo*); +}; + +using UnownedAllocator = detail::AllocatorImpl>; + +/** \brief Wrapper around ::OrtSyncStream + * + */ + +namespace detail { +template +struct SyncStreamImpl : Base { + using B = Base; + using B::B; + // For some reason this is not a const method on the stream + void* GetHandle(); ///< Wraps SyncStream_GetHandle +}; +} // namespace detail + +struct SyncStream : detail::SyncStreamImpl { + ///< Create an empty SyncStream object, must be assigned a valid one to be used + explicit SyncStream(std::nullptr_t) {} + ///< Take ownership of a pointer created by C API + explicit SyncStream(OrtSyncStream* p) : SyncStreamImpl{p} {} +}; + +using UnownedSyncStream = detail::SyncStreamImpl>; + +namespace detail { +template +struct HardwareDeviceImpl : Ort::detail::Base { + using B = Ort::detail::Base; + using B::B; + + OrtHardwareDeviceType Type() const; + uint32_t VendorId() const; + uint32_t DeviceId() const; + const char* Vendor() const; + ConstKeyValuePairs Metadata() const; +}; +} // namespace detail + +/** \brief Wrapper around ::OrtHardwareDevice + * \remarks HardwareDevice is always read-only for API users. + */ +using ConstHardwareDevice = detail::HardwareDeviceImpl>; + +namespace detail { +template +struct EpDeviceImpl : Ort::detail::Base { + using B = Ort::detail::Base; + using B::B; + + const char* EpName() const; + const char* EpVendor() const; + ConstKeyValuePairs EpMetadata() const; + ConstKeyValuePairs EpOptions() const; + ConstHardwareDevice Device() const; + ConstMemoryInfo GetMemoryInfo(OrtDeviceMemoryType memory_type) const; ///< Wraps EpDevice_MemoryInfo + SyncStream CreateSyncStream(ConstKeyValuePairs stream_options = {}) const; /// Wraps EpDevice_CreateSyncStream +}; +} // namespace detail + +/** \brief Wrapper around ::OrtEpDevice + * \remarks EpDevice is always read-only for ORT API users. + */ +using ConstEpDevice = detail::EpDeviceImpl>; + +/** \brief Mutable EpDevice that is created by EpApi users. + */ +struct EpDevice : detail::EpDeviceImpl { + explicit EpDevice(std::nullptr_t) {} ///< No instance is created + explicit EpDevice(OrtEpDevice* p) : EpDeviceImpl{p} {} ///< Take ownership of a pointer created by C API + + /// \brief Wraps OrtEpApi::CreateEpDevice + EpDevice(OrtEpFactory& ep_factory, ConstHardwareDevice& hardware_device, + ConstKeyValuePairs ep_metadata = {}, ConstKeyValuePairs ep_options = {}); +}; + +/** \brief Validate a compiled model's compatibility for one or more EP devices. + * + * Throws on error. Returns the resulting compatibility status. + * /// \param ep_devices The EP devices to check compatibility against. + * /// \param compatibility_info The compatibility string from the precompiled model to validate. + */ +OrtCompiledModelCompatibility GetModelCompatibilityForEpDevices( + const std::vector& ep_devices, + const char* compatibility_info); + +/** \brief The Env (Environment) + * + * The Env holds the logging state used by all other objects. + * Note: One Env must be created before using any other Onnxruntime functionality + */ +struct Env : detail::Base { + explicit Env(std::nullptr_t) {} ///< Create an empty Env object, must be assigned a valid one to be used + + /// \brief Wraps OrtApi::CreateEnv + Env(OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); + + /// \brief Wraps OrtApi::CreateEnvWithCustomLogger + Env(OrtLoggingLevel logging_level, const char* logid, OrtLoggingFunction logging_function, void* logger_param); + + /// \brief Wraps OrtApi::CreateEnvWithGlobalThreadPools + Env(const OrtThreadingOptions* tp_options, OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); + + /// \brief Wraps OrtApi::CreateEnvWithCustomLoggerAndGlobalThreadPools + Env(const OrtThreadingOptions* tp_options, OrtLoggingFunction logging_function, void* logger_param, + OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = ""); + + /// \brief C Interop Helper + explicit Env(OrtEnv* p) : Base{p} {} + + Env& EnableTelemetryEvents(); ///< Wraps OrtApi::EnableTelemetryEvents + Env& DisableTelemetryEvents(); ///< Wraps OrtApi::DisableTelemetryEvents + + Env& UpdateEnvWithCustomLogLevel(OrtLoggingLevel log_severity_level); ///< Wraps OrtApi::UpdateEnvWithCustomLogLevel + + Env& CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg); ///< Wraps OrtApi::CreateAndRegisterAllocator + + Env& CreateAndRegisterAllocatorV2(const std::string& provider_type, const OrtMemoryInfo* mem_info, + const std::unordered_map& options, + const OrtArenaCfg* arena_cfg); ///< Wraps OrtApi::CreateAndRegisterAllocatorV2 + + Env& RegisterAllocator(OrtAllocator* allocator); ///< Wraps OrtApi::RegisterAllocator + + Env& UnregisterAllocator(const OrtMemoryInfo* mem_info); ///< Wraps OrtApi::UnregisterAllocator + + UnownedAllocator CreateSharedAllocator(const OrtEpDevice* ep_device, OrtDeviceMemoryType mem_type, + OrtAllocatorType allocator_type, + const OrtKeyValuePairs* allocator_options); ///< Wraps OrtApi::CreateSharedAllocator + + // Result may be nullptr + UnownedAllocator GetSharedAllocator(const OrtMemoryInfo* mem_info); ///< Wraps OrtApi::GetSharedAllocator + + void ReleaseSharedAllocator(const OrtEpDevice* ep_device, + OrtDeviceMemoryType mem_type); ///< Wraps OrtApi::ReleaseSharedAllocator + + Env& RegisterExecutionProviderLibrary(const char* registration_name, const std::basic_string& path); ///< Wraps OrtApi::RegisterExecutionProviderLibrary + Env& UnregisterExecutionProviderLibrary(const char* registration_name); ///< Wraps OrtApi::UnregisterExecutionProviderLibrary + + std::vector GetEpDevices() const; + + Status CopyTensors(const std::vector& src_tensors, + const std::vector& dst_tensors, + OrtSyncStream* stream) const; ///< Wraps OrtApi::CopyTensors +}; + +/** \brief Custom Op Domain + * + */ +struct CustomOpDomain : detail::Base { + using Base = detail::Base; + using Base::Base; + + explicit CustomOpDomain(std::nullptr_t) {} ///< Create an empty CustomOpDomain object, must be assigned a valid one to be used + + /// \brief Wraps OrtApi::CreateCustomOpDomain + explicit CustomOpDomain(const char* domain); + + // This does not take ownership of the op, simply registers it. + void Add(const OrtCustomOp* op); ///< Wraps CustomOpDomain_Add +}; + +/// \brief LoraAdapter holds a set of Lora Parameters loaded from a single file +struct LoraAdapter : detail::Base { + using Base = detail::Base; + using Base::Base; + + explicit LoraAdapter(std::nullptr_t) {} ///< Create an empty LoraAdapter object, must be assigned a valid one to be used + /// \brief Wraps OrtApi::CreateLoraAdapter + /// + /// The function attempts to load the adapter from the specified file + /// \param adapter_path The path to the Lora adapter + /// \param allocator optional pointer to a device allocator. If nullptr, the data stays on CPU. It would still + /// be copied to device if required by the model at inference time. + static LoraAdapter CreateLoraAdapter(const std::basic_string& adapter_path, + OrtAllocator* allocator); + + /// \brief Wraps OrtApi::CreateLoraAdapterFromArray + /// + /// The function attempts to load the adapter from the specified byte array. + /// \param bytes The byte array containing file LoraAdapter format + /// \param num_bytes The number of bytes in the byte array + /// \param allocator optional pointer to a device allocator. If nullptr, the data stays on CPU. It would still + /// be copied to device if required by the model at inference time. + static LoraAdapter CreateLoraAdapterFromArray(const void* bytes, size_t num_bytes, + OrtAllocator* allocator); +}; + +/** \brief RunOptions + * + */ +struct RunOptions : detail::Base { + explicit RunOptions(std::nullptr_t) {} ///< Create an empty RunOptions object, must be assigned a valid one to be used + RunOptions(); ///< Wraps OrtApi::CreateRunOptions + + RunOptions& SetRunLogVerbosityLevel(int); ///< Wraps OrtApi::RunOptionsSetRunLogVerbosityLevel + int GetRunLogVerbosityLevel() const; ///< Wraps OrtApi::RunOptionsGetRunLogVerbosityLevel + + RunOptions& SetRunLogSeverityLevel(int); ///< Wraps OrtApi::RunOptionsSetRunLogSeverityLevel + int GetRunLogSeverityLevel() const; ///< Wraps OrtApi::RunOptionsGetRunLogSeverityLevel + + RunOptions& SetRunTag(const char* run_tag); ///< wraps OrtApi::RunOptionsSetRunTag + const char* GetRunTag() const; ///< Wraps OrtApi::RunOptionsGetRunTag + + RunOptions& AddConfigEntry(const char* config_key, const char* config_value); ///< Wraps OrtApi::AddRunConfigEntry + const char* GetConfigEntry(const char* config_key); ///< Wraps OrtApi::GetRunConfigEntry + + /** \brief Terminates all currently executing Session::Run calls that were made using this RunOptions instance + * + * If a currently executing session needs to be force terminated, this can be called from another thread to force it to fail with an error + * Wraps OrtApi::RunOptionsSetTerminate + */ + RunOptions& SetTerminate(); + + /** \brief Clears the terminate flag so this RunOptions instance can be used in a new Session::Run call without it instantly terminating + * + * Wraps OrtApi::RunOptionsUnsetTerminate + */ + RunOptions& UnsetTerminate(); + + /** \brief Add the LoraAdapter to the list of active adapters. + * The setting does not affect RunWithBinding() calls. + * + * Wraps OrtApi::RunOptionsAddActiveLoraAdapter + * \param adapter The LoraAdapter to be used as the active adapter + */ + RunOptions& AddActiveLoraAdapter(const LoraAdapter& adapter); +}; + +namespace detail { +// Utility function that returns a SessionOption config entry key for a specific custom operator. +// Ex: custom_op.[custom_op_name].[config] +std::string MakeCustomOpConfigEntryKey(const char* custom_op_name, const char* config); +} // namespace detail + +/// +/// Class that represents session configuration entries for one or more custom operators. +/// +/// Example: +/// Ort::CustomOpConfigs op_configs; +/// op_configs.AddConfig("my_custom_op", "device_type", "CPU"); +/// +/// Passed to Ort::SessionOptions::RegisterCustomOpsLibrary. +/// +struct CustomOpConfigs { + CustomOpConfigs() = default; + ~CustomOpConfigs() = default; + CustomOpConfigs(const CustomOpConfigs&) = default; + CustomOpConfigs& operator=(const CustomOpConfigs&) = default; + CustomOpConfigs(CustomOpConfigs&& o) = default; + CustomOpConfigs& operator=(CustomOpConfigs&& o) = default; + + /** \brief Adds a session configuration entry/value for a specific custom operator. + * + * \param custom_op_name The name of the custom operator for which to add a configuration entry. + * Must match the name returned by the CustomOp's GetName() method. + * \param config_key The name of the configuration entry. + * \param config_value The value of the configuration entry. + * \return A reference to this object to enable call chaining. + */ + CustomOpConfigs& AddConfig(const char* custom_op_name, const char* config_key, const char* config_value); + + /** \brief Returns a flattened map of custom operator configuration entries and their values. + * + * The keys has been flattened to include both the custom operator name and the configuration entry key name. + * For example, a prior call to AddConfig("my_op", "key", "value") corresponds to the flattened key/value pair + * {"my_op.key", "value"}. + * + * \return An unordered map of flattened configurations. + */ + const std::unordered_map& GetFlattenedConfigs() const; + + private: + std::unordered_map flat_configs_; +}; + +/** \brief Options object used when creating a new Session object + * + * Wraps ::OrtSessionOptions object and methods + */ + +namespace detail { +// we separate const-only methods because passing const ptr to non-const methods +// is only discovered when inline methods are compiled which is counter-intuitive +template +struct ConstSessionOptionsImpl : Base { + using B = Base; + using B::B; + + SessionOptions Clone() const; ///< Creates and returns a copy of this SessionOptions object. Wraps OrtApi::CloneSessionOptions + + std::string GetConfigEntry(const char* config_key) const; ///< Wraps OrtApi::GetSessionConfigEntry + bool HasConfigEntry(const char* config_key) const; ///< Wraps OrtApi::HasSessionConfigEntry + std::string GetConfigEntryOrDefault(const char* config_key, const std::string& def) const; +}; + +template +struct SessionOptionsImpl : ConstSessionOptionsImpl { + using B = ConstSessionOptionsImpl; + using B::B; + + SessionOptionsImpl& SetIntraOpNumThreads(int intra_op_num_threads); ///< Wraps OrtApi::SetIntraOpNumThreads + SessionOptionsImpl& SetInterOpNumThreads(int inter_op_num_threads); ///< Wraps OrtApi::SetInterOpNumThreads + SessionOptionsImpl& SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level); ///< Wraps OrtApi::SetSessionGraphOptimizationLevel + SessionOptionsImpl& SetDeterministicCompute(bool value); ///< Wraps OrtApi::SetDeterministicCompute + + SessionOptionsImpl& EnableCpuMemArena(); ///< Wraps OrtApi::EnableCpuMemArena + SessionOptionsImpl& DisableCpuMemArena(); ///< Wraps OrtApi::DisableCpuMemArena + + SessionOptionsImpl& SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_file); ///< Wraps OrtApi::SetOptimizedModelFilePath + + SessionOptionsImpl& EnableProfiling(const ORTCHAR_T* profile_file_prefix); ///< Wraps OrtApi::EnableProfiling + SessionOptionsImpl& DisableProfiling(); ///< Wraps OrtApi::DisableProfiling + + SessionOptionsImpl& EnableOrtCustomOps(); ///< Wraps OrtApi::EnableOrtCustomOps + + SessionOptionsImpl& EnableMemPattern(); ///< Wraps OrtApi::EnableMemPattern + SessionOptionsImpl& DisableMemPattern(); ///< Wraps OrtApi::DisableMemPattern + + SessionOptionsImpl& SetExecutionMode(ExecutionMode execution_mode); ///< Wraps OrtApi::SetSessionExecutionMode + + SessionOptionsImpl& SetLoadCancellationFlag(bool value); ///< Wraps OrtApi::SessionOptionsSetLoadCancellationFlag + + SessionOptionsImpl& SetLogId(const char* logid); ///< Wraps OrtApi::SetSessionLogId + SessionOptionsImpl& SetLogSeverityLevel(int level); ///< Wraps OrtApi::SetSessionLogSeverityLevel + + SessionOptionsImpl& Add(OrtCustomOpDomain* custom_op_domain); ///< Wraps OrtApi::AddCustomOpDomain + + SessionOptionsImpl& DisablePerSessionThreads(); ///< Wraps OrtApi::DisablePerSessionThreads + + SessionOptionsImpl& AddConfigEntry(const char* config_key, const char* config_value); ///< Wraps OrtApi::AddSessionConfigEntry + + SessionOptionsImpl& AddInitializer(const char* name, const OrtValue* ort_val); ///< Wraps OrtApi::AddInitializer + SessionOptionsImpl& AddExternalInitializers(const std::vector& names, const std::vector& ort_values); ///< Wraps OrtApi::AddExternalInitializers + SessionOptionsImpl& AddExternalInitializersFromFilesInMemory(const std::vector>& external_initializer_file_names, + const std::vector& external_initializer_file_buffer_array, + const std::vector& external_initializer_file_lengths); ///< Wraps OrtApi::AddExternalInitializersFromFilesInMemory + + SessionOptionsImpl& AppendExecutionProvider_CPU(int use_arena); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CPU + SessionOptionsImpl& AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CUDA + SessionOptionsImpl& AppendExecutionProvider_CUDA_V2(const OrtCUDAProviderOptionsV2& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CUDA_V2 + SessionOptionsImpl& AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_ROCM + SessionOptionsImpl& AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_OpenVINO + ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_OpenVINO_V2 + SessionOptionsImpl& AppendExecutionProvider_OpenVINO_V2(const std::unordered_map& provider_options = {}); + SessionOptionsImpl& AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_TensorRT + SessionOptionsImpl& AppendExecutionProvider_TensorRT_V2(const OrtTensorRTProviderOptionsV2& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_TensorRT + SessionOptionsImpl& AppendExecutionProvider_MIGraphX(const OrtMIGraphXProviderOptions& provider_options); ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_MIGraphX + /// Wraps OrtApi::SessionOptionsAppendExecutionProvider_CANN + SessionOptionsImpl& AppendExecutionProvider_CANN(const OrtCANNProviderOptions& provider_options); + /// Wraps OrtApi::SessionOptionsAppendExecutionProvider_Dnnl + SessionOptionsImpl& AppendExecutionProvider_Dnnl(const OrtDnnlProviderOptions& provider_options); + /// Wraps OrtApi::SessionOptionsAppendExecutionProvider. Currently supports QNN, SNPE and XNNPACK. + SessionOptionsImpl& AppendExecutionProvider(const std::string& provider_name, + const std::unordered_map& provider_options = {}); + + /// Append EPs that have been registered previously with the OrtEnv. + /// Wraps OrtApi::SessionOptionsAppendExecutionProvider_V2 + SessionOptionsImpl& AppendExecutionProvider_V2(Env& env, const std::vector& ep_devices, + const KeyValuePairs& ep_options); + /// Append EPs that have been registered previously with the OrtEnv. + /// Wraps OrtApi::SessionOptionsAppendExecutionProvider_V2 + SessionOptionsImpl& AppendExecutionProvider_V2(Env& env, const std::vector& ep_devices, + const std::unordered_map& ep_options); + + /// Wraps OrtApi::SessionOptionsSetEpSelectionPolicy + SessionOptionsImpl& SetEpSelectionPolicy(OrtExecutionProviderDevicePolicy policy); + + /// Wraps OrtApi::SessionOptionsSetEpSelectionPolicyDelegate + SessionOptionsImpl& SetEpSelectionPolicy(EpSelectionDelegate delegate, void* state = nullptr); + + SessionOptionsImpl& SetCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn); ///< Wraps OrtApi::SessionOptionsSetCustomCreateThreadFn + SessionOptionsImpl& SetCustomThreadCreationOptions(void* ort_custom_thread_creation_options); ///< Wraps OrtApi::SessionOptionsSetCustomThreadCreationOptions + SessionOptionsImpl& SetCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn); ///< Wraps OrtApi::SessionOptionsSetCustomJoinThreadFn + + ///< Registers the custom operator from the specified shared library via OrtApi::RegisterCustomOpsLibrary_V2. + ///< The custom operator configurations are optional. If provided, custom operator configs are set via + ///< OrtApi::AddSessionConfigEntry. + SessionOptionsImpl& RegisterCustomOpsLibrary(const ORTCHAR_T* library_name, const CustomOpConfigs& custom_op_configs = {}); + + SessionOptionsImpl& RegisterCustomOpsUsingFunction(const char* function_name); ///< Wraps OrtApi::RegisterCustomOpsUsingFunction + + ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_VitisAI + SessionOptionsImpl& AppendExecutionProvider_VitisAI(const std::unordered_map& provider_options = {}); +}; +} // namespace detail + +using UnownedSessionOptions = detail::SessionOptionsImpl>; +using ConstSessionOptions = detail::ConstSessionOptionsImpl>; + +/** \brief Wrapper around ::OrtSessionOptions + * + */ +struct SessionOptions : detail::SessionOptionsImpl { + explicit SessionOptions(std::nullptr_t) {} ///< Create an empty SessionOptions object, must be assigned a valid one to be used + SessionOptions(); ///< Wraps OrtApi::CreateSessionOptions + explicit SessionOptions(OrtSessionOptions* p) : SessionOptionsImpl{p} {} ///< Used for interop with the C API + UnownedSessionOptions GetUnowned() const { return UnownedSessionOptions{this->p_}; } + ConstSessionOptions GetConst() const { return ConstSessionOptions{this->p_}; } +}; + +/** \brief Options object used when compiling a model. + * + * Wraps ::OrtModelCompilationOptions object and methods + */ +struct ModelCompilationOptions : detail::Base { + using Base = detail::Base; + using Base::Base; + + explicit ModelCompilationOptions(std::nullptr_t) {} ///< Create an empty ModelCompilationOptions object, must be assigned a valid one to be used. + + ModelCompilationOptions(const Env& env, const SessionOptions& session_options); ///< Wraps OrtApi::CreateModelCompilationOptionsFromSessionOptions + ModelCompilationOptions(const Env& env, ConstSessionOptions session_options); ///< Wraps OrtApi::CreateModelCompilationOptionsFromSessionOptions + + ModelCompilationOptions& SetInputModelPath(const ORTCHAR_T* input_model_path); ///< Wraps OrtApi::ModelCompilationOptions_SetInputModelPath + ModelCompilationOptions& SetInputModelFromBuffer(const void* input_model_data, + size_t input_model_data_size); ///< Wraps OrtApi::ModelCompilationOptions_SetInputModelFromBuffer + ModelCompilationOptions& SetEpContextEmbedMode(bool embed_ep_context_in_model); ///< Wraps OrtApi::ModelCompilationOptions_SetEpContextEmbedMode + ModelCompilationOptions& SetOutputModelPath(const ORTCHAR_T* output_model_path); ///< Wraps OrtApi::ModelCompilationOptions_SetOutputModelPath + ModelCompilationOptions& SetOutputModelExternalInitializersFile(const ORTCHAR_T* file_path, + size_t initializer_size_threshold); ///< Wraps OrtApi::ModelCompilationOptions_SetOutputModelExternalInitializersFile + + ///< Wraps OrtApi::ModelCompilationOptions_SetOutputModelGetInitializerLocationFunc + ModelCompilationOptions& SetOutputModelGetInitializerLocationFunc( + OrtGetInitializerLocationFunc get_initializer_location_func, + void* state); + + ModelCompilationOptions& SetOutputModelBuffer(OrtAllocator* allocator, void** output_model_buffer_ptr, + size_t* output_model_buffer_size_ptr); ///< Wraps OrtApi::ModelCompilationOptions_SetOutputModelBuffer + + ///< Wraps OrtApi::ModelCompilationOptions_SetOutputModelWriteFunc + ModelCompilationOptions& SetOutputModelWriteFunc(OrtWriteBufferFunc write_func, void* state); + + ModelCompilationOptions& SetEpContextBinaryInformation(const ORTCHAR_T* output_directory, + const ORTCHAR_T* model_name); ///< Wraps OrtApi::ModelCompilationOptions_SetEpContextBinaryInformation + ModelCompilationOptions& SetFlags(uint32_t flags); ///< Wraps OrtApi::ModelCompilationOptions_SetFlags + + ModelCompilationOptions& SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level); ///< Wraps OrtApi::ModelCompilationOptions_SetGraphOptimizationLevel +}; + +/** \brief Compiles an input model to generate a model with EPContext nodes that execute EP-specific kernels. Wraps OrtApi::CompileModels. + * + * \param env: ORT environment object. + * \param model_compilation_options: Compilation options for a model. + * \return A Status indicating success or failure. + */ +Status CompileModel(const Env& env, const ModelCompilationOptions& model_compilation_options); + +/** \brief Wrapper around ::OrtModelMetadata + * + */ +struct ModelMetadata : detail::Base { + using Base = detail::Base; + using Base::Base; + + explicit ModelMetadata(std::nullptr_t) {} ///< Create an empty ModelMetadata object, must be assigned a valid one to be used + + /** \brief Returns a copy of the producer name. + * + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetProducerNameAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetProducerName + + /** \brief Returns a copy of the graph name. + * + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetGraphNameAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetGraphName + + /** \brief Returns a copy of the domain name. + * + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetDomainAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetDomain + + /** \brief Returns a copy of the description. + * + * \param allocator to allocate memory for the copy of the string returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetDescriptionAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetDescription + + /** \brief Returns a copy of the graph description. + * + * \param allocator to allocate memory for the copy of the string returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetGraphDescriptionAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetGraphDescription + + /** \brief Returns a vector of copies of the custom metadata keys. + * + * \param allocator to allocate memory for the copy of the string returned + * \return a instance std::vector of smart pointers that would deallocate the buffers when out of scope. + * The OrtAllocator instance must be valid at the point of memory release. + */ + std::vector GetCustomMetadataMapKeysAllocated(OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataGetCustomMetadataMapKeys + + /** \brief Looks up a value by a key in the Custom Metadata map + * + * \param key zero terminated string key to lookup + * \param allocator to allocate memory for the copy of the string returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * maybe nullptr if key is not found. + * + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr LookupCustomMetadataMapAllocated(const char* key, OrtAllocator* allocator) const; ///< Wraps OrtApi::ModelMetadataLookupCustomMetadataMap + + int64_t GetVersion() const; ///< Wraps OrtApi::ModelMetadataGetVersion +}; + +struct IoBinding; + +namespace detail { + +// we separate const-only methods because passing const ptr to non-const methods +// is only discovered when inline methods are compiled which is counter-intuitive +template +struct ConstSessionImpl : Base { + using B = Base; + using B::B; + + size_t GetInputCount() const; ///< Returns the number of model inputs + size_t GetOutputCount() const; ///< Returns the number of model outputs + size_t GetOverridableInitializerCount() const; ///< Returns the number of inputs that have defaults that can be overridden + + std::vector GetInputNames() const; + std::vector GetOutputNames() const; + std::vector GetOverridableInitializerNames() const; + + std::vector GetMemoryInfoForInputs() const; ///< Wrapper for OrtApi::SessionGetMemoryInfoForInputs + std::vector GetMemoryInfoForOutputs() const; ///< Wrapper for OrtApi::SessionGetMemoryInfoForOutputs + std::vector GetEpDeviceForInputs() const; ///< Wrapper for OrtApi::SessionGetEpDeviceForInputs + + /** \brief Returns a copy of input name at the specified index. + * + * \param index must less than the value returned by GetInputCount() + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetInputNameAllocated(size_t index, OrtAllocator* allocator) const; + + /** \brief Returns a copy of output name at then specified index. + * + * \param index must less than the value returned by GetOutputCount() + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetOutputNameAllocated(size_t index, OrtAllocator* allocator) const; + + /** \brief Returns a copy of the overridable initializer name at then specified index. + * + * \param index must less than the value returned by GetOverridableInitializerCount() + * \param allocator to allocate memory for the copy of the name returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr GetOverridableInitializerNameAllocated(size_t index, OrtAllocator* allocator) const; ///< Wraps OrtApi::SessionGetOverridableInitializerName + + uint64_t GetProfilingStartTimeNs() const; ///< Wraps OrtApi::SessionGetProfilingStartTimeNs + ModelMetadata GetModelMetadata() const; ///< Wraps OrtApi::SessionGetModelMetadata + + TypeInfo GetInputTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetInputTypeInfo + TypeInfo GetOutputTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetOutputTypeInfo + TypeInfo GetOverridableInitializerTypeInfo(size_t index) const; ///< Wraps OrtApi::SessionGetOverridableInitializerTypeInfo + + int GetOpset(const std::string& domain) const; ///< Wraps OrtApi::SessionGetOpsetForDomain + + // Will move before checkin if that's the case. + std::vector GetInputs() const; + std::vector GetOutputs() const; +}; + +template +struct SessionImpl : ConstSessionImpl { + using B = ConstSessionImpl; + using B::B; + + /** \brief Run the model returning results in an Ort allocated vector. + * + * Wraps OrtApi::Run + * + * The caller provides a list of inputs and a list of the desired outputs to return. + * + * See the output logs for more information on warnings/errors that occur while processing the model. + * Common errors are.. (TODO) + * + * \param[in] run_options + * \param[in] input_names Array of null terminated strings of length input_count that is the list of input names + * \param[in] input_values Array of Value objects of length input_count that is the list of input values + * \param[in] input_count Number of inputs (the size of the input_names & input_values arrays) + * \param[in] output_names Array of C style strings of length output_count that is the list of output names + * \param[in] output_count Number of outputs (the size of the output_names array) + * \return A std::vector of Value objects that directly maps to the output_names array (eg. output_name[0] is the first entry of the returned vector) + */ + std::vector Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, size_t output_count); + + /** \brief Run the model returning results in user provided outputs + * Same as Run(const RunOptions&, const char* const*, const Value*, size_t,const char* const*, size_t) + */ + void Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, Value* output_values, size_t output_count); + + void Run(const RunOptions& run_options, const IoBinding&); ///< Wraps OrtApi::RunWithBinding + + /** \brief Run the model asynchronously in a thread owned by intra op thread pool + * + * Wraps OrtApi::RunAsync + * + * \param[in] run_options + * \param[in] input_names Array of null terminated UTF8 encoded strings of the input names + * \param[in] input_values Array of Value objects of length input_count + * \param[in] input_count Number of elements in the input_names and inputs arrays + * \param[in] output_names Array of null terminated UTF8 encoded strings of the output names + * \param[out] output_values Array of provided Values to be filled with outputs. + * On calling RunAsync, output_values[i] could either be initialized by a null pointer or a preallocated OrtValue*. + * Later, on invoking the callback, each output_values[i] of null will be filled with an OrtValue* allocated by onnxruntime. + * Then, an OrtValue** pointer will be casted from output_values, and pass to the callback. + * NOTE: it is customer's duty to finally release output_values and each of its member, + * regardless of whether the member (Ort::Value) is allocated by onnxruntime or preallocated by the customer. + * \param[in] output_count Number of elements in the output_names and outputs array + * \param[in] callback Callback function on model run completion + * \param[in] user_data User data that pass back to the callback + */ + void RunAsync(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, Value* output_values, size_t output_count, RunAsyncCallbackFn callback, void* user_data); + + /** \brief End profiling and return a copy of the profiling file name. + * + * \param allocator to allocate memory for the copy of the string returned + * \return a instance of smart pointer that would deallocate the buffer when out of scope. + * The OrtAllocator instances must be valid at the point of memory release. + */ + AllocatedStringPtr EndProfilingAllocated(OrtAllocator* allocator); ///< Wraps OrtApi::SessionEndProfiling + + /** \brief Set DynamicOptions for EPs (Execution Providers) + * + * Wraps OrtApi::SetEpDynamicOptions + * + * Valid options can be found in `include\onnxruntime\core\session\onnxruntime_session_options_config_keys.h` + * Look for `kOrtEpDynamicOptions` + * + * \param[in] keys Array of null terminated UTF8 encoded strings of EP dynamic option keys + * \param[in] values Array of null terminated UTF8 encoded string of EP dynamic option values + * \param[in] kv_len Number of elements in the keys and values arrays + */ + void SetEpDynamicOptions(const char* const* keys, const char* const* values, size_t kv_len); + + void FinalizeModelEditorSession(const Model& model, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container = nullptr); +}; + +} // namespace detail + +using ConstSession = detail::ConstSessionImpl>; +using UnownedSession = detail::SessionImpl>; + +/** \brief Wrapper around ::OrtSession + * + */ +struct Session : detail::SessionImpl { + /// Create an empty Session object, must be assigned a valid one to be used. Wraps OrtApi::CreateSession + explicit Session(std::nullptr_t) {} + explicit Session(OrtSession* p) : SessionImpl{p} {} ///< C API Interop + + Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options); + + /// Wraps OrtApi::CreateSessionWithPrepackedWeightsContainer + Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container); + + /// Wraps OrtApi::CreateSessionFromArray + Session(const Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options); + + /// Wraps OrtApi::CreateSessionFromArrayWithPrepackedWeightsContainer + Session(const Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container); + +#if !defined(ORT_MINIMAL_BUILD) + /// Wraps OrtModelEditorApi::CreateSessionFromModel + Session(const Env& env, const Model& model, const SessionOptions& options); + + /// Wraps OrtModelEditorApi::CreateModelEditorSession + static Session CreateModelEditorSession(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options); + + /// Wraps OrtModelEditorApi::CreateModelEditorSession + static Session CreateModelEditorSession(const Env& env, const void* model_data, size_t model_data_length, + const SessionOptions& options); +#endif // !defined(ORT_MINIMAL_BUILD) + + ConstSession GetConst() const { return ConstSession{this->p_}; } + UnownedSession GetUnowned() const { return UnownedSession{this->p_}; } +}; + +namespace detail { +template +struct TensorTypeAndShapeInfoImpl : Base { + using B = Base; + using B::B; + + ONNXTensorElementDataType GetElementType() const; ///< Wraps OrtApi::GetTensorElementType + size_t GetElementCount() const; ///< Wraps OrtApi::GetTensorShapeElementCount + + size_t GetDimensionsCount() const; ///< Wraps OrtApi::GetDimensionsCount + + /** \deprecated use GetShape() returning std::vector + * [[deprecated]] + * This interface is unsafe to use + */ + [[deprecated("use GetShape()")]] void GetDimensions(int64_t* values, size_t values_count) const; ///< Wraps OrtApi::GetDimensions + + void GetSymbolicDimensions(const char** values, size_t values_count) const; ///< Wraps OrtApi::GetSymbolicDimensions + std::vector GetSymbolicDimensions() const; + + std::vector GetShape() const; ///< Uses GetDimensionsCount & GetDimensions to return a std::vector of the shape +}; + +} // namespace detail + +using ConstTensorTypeAndShapeInfo = detail::TensorTypeAndShapeInfoImpl>; + +/** \brief Wrapper around ::OrtTensorTypeAndShapeInfo + * + */ +struct TensorTypeAndShapeInfo : detail::TensorTypeAndShapeInfoImpl { + using Base = detail::TensorTypeAndShapeInfoImpl; + using Base::Base; + + /// Create an empty TensorTypeAndShapeInfo object, must be assigned a valid one to be used + explicit TensorTypeAndShapeInfo(std::nullptr_t) {} + /// Used for interop with the C API + explicit TensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* p) : TensorTypeAndShapeInfoImpl{p} {} + + // Create a TensorTypeAndShapeInfo object with the specified element type and dimensions + // symbolic_dims are optional, but should be 1:1 with dims. + // The value in symbolic_dims will be used for all entries in dims that are -1. + explicit TensorTypeAndShapeInfo(ONNXTensorElementDataType element_type, + const std::vector& dims, + const std::vector* symbolic_dims = nullptr); + + ConstTensorTypeAndShapeInfo GetConst() const { return ConstTensorTypeAndShapeInfo{this->p_}; } +}; + +namespace detail { +template +struct SequenceTypeInfoImpl : Base { + using B = Base; + using B::B; + TypeInfo GetSequenceElementType() const; ///< Wraps OrtApi::GetSequenceElementType +}; + +} // namespace detail + +using ConstSequenceTypeInfo = detail::SequenceTypeInfoImpl>; + +/** \brief Wrapper around ::OrtSequenceTypeInfo + * + */ +struct SequenceTypeInfo : detail::SequenceTypeInfoImpl { + using Base = detail::SequenceTypeInfoImpl; + using Base::Base; + + explicit SequenceTypeInfo(std::nullptr_t) {} ///< Create an empty SequenceTypeInfo object, must be assigned a valid one to be used + explicit SequenceTypeInfo(OrtSequenceTypeInfo* p) : SequenceTypeInfoImpl{p} {} ///< Used for interop with the C API + ConstSequenceTypeInfo GetConst() const { return ConstSequenceTypeInfo{this->p_}; } +}; + +namespace detail { +template +struct OptionalTypeInfoImpl : Base { + using B = Base; + using B::B; + TypeInfo GetOptionalElementType() const; ///< Wraps OrtApi::CastOptionalTypeToContainedTypeInfo +}; + +} // namespace detail + +// This is always owned by the TypeInfo and can only be obtained from it. +using ConstOptionalTypeInfo = detail::OptionalTypeInfoImpl>; + +namespace detail { +template +struct MapTypeInfoImpl : detail::Base { + using B = Base; + using B::B; + ONNXTensorElementDataType GetMapKeyType() const; ///< Wraps OrtApi::GetMapKeyType + TypeInfo GetMapValueType() const; ///< Wraps OrtApi::GetMapValueType +}; + +} // namespace detail + +using ConstMapTypeInfo = detail::MapTypeInfoImpl>; + +/** \brief Wrapper around ::OrtMapTypeInfo + * + */ +struct MapTypeInfo : detail::MapTypeInfoImpl { + using Base = detail::MapTypeInfoImpl; + using Base::Base; + + explicit MapTypeInfo(std::nullptr_t) {} ///< Create an empty MapTypeInfo object, must be assigned a valid one to be used + explicit MapTypeInfo(OrtMapTypeInfo* p) : MapTypeInfoImpl{p} {} ///< Used for interop with the C API + ConstMapTypeInfo GetConst() const { return ConstMapTypeInfo{this->p_}; } +}; + +namespace detail { +template +struct TypeInfoImpl : detail::Base { + using B = Base; + using B::B; + + ConstTensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const; ///< Wraps OrtApi::CastTypeInfoToTensorInfo + ConstSequenceTypeInfo GetSequenceTypeInfo() const; ///< Wraps OrtApi::CastTypeInfoToSequenceTypeInfo + ConstMapTypeInfo GetMapTypeInfo() const; ///< Wraps OrtApi::CastTypeInfoToMapTypeInfo + ConstOptionalTypeInfo GetOptionalTypeInfo() const; ///< wraps OrtApi::CastTypeInfoToOptionalTypeInfo + + ONNXType GetONNXType() const; +}; +} // namespace detail + +/// +/// Contains a constant, unowned OrtTypeInfo that can be copied and passed around by value. +/// Provides access to const OrtTypeInfo APIs. +/// +using ConstTypeInfo = detail::TypeInfoImpl>; + +/// +/// Type information that may contain either TensorTypeAndShapeInfo or +/// the information about contained sequence or map depending on the ONNXType. +/// +struct TypeInfo : detail::TypeInfoImpl { + using Base = detail::TypeInfoImpl; + using Base::Base; + + /// Create an empty TypeInfo object, must be assigned a valid one to be used + explicit TypeInfo(std::nullptr_t) {} + explicit TypeInfo(OrtTypeInfo* p) : TypeInfoImpl{p} {} ///< C API Interop + +#if !defined(ORT_MINIMAL_BUILD) + static TypeInfo CreateTensorInfo(ConstTensorTypeAndShapeInfo tensor_info); + static TypeInfo CreateSparseTensorInfo(ConstTensorTypeAndShapeInfo sparse_tensor_info); + static TypeInfo CreateSequenceTypeInfo(ConstTypeInfo sequence_type); + static TypeInfo CreateMapTypeInfo(ONNXTensorElementDataType key_type, ConstTypeInfo value_type); + static TypeInfo CreateOptionalTypeInfo(ConstTypeInfo contained_type); +#endif // !defined(ORT_MINIMAL_BUILD) + + ConstTypeInfo GetConst() const { return ConstTypeInfo{this->p_}; } +}; + +namespace detail { +// This structure is used to feed sparse tensor values +// information for use with FillSparseTensor() API +// if the data type for the sparse tensor values is numeric +// use data.p_data, otherwise, use data.str pointer to feed +// values. data.str is an array of const char* that are zero terminated. +// number of strings in the array must match shape size. +// For fully sparse tensors use shape {0} and set p_data/str +// to nullptr. +struct OrtSparseValuesParam { + const int64_t* values_shape; + size_t values_shape_len; + union { + const void* p_data; + const char** str; + } data; +}; + +// Provides a way to pass shape in a single +// argument +struct Shape { + const int64_t* shape; + size_t shape_len; +}; + +template +struct ConstValueImpl : Base { + using B = Base; + using B::B; + + /// + /// Obtains a pointer to a user defined data for experimental purposes + /// + template + void GetOpaqueData(const char* domain, const char* type_name, R&) const; ///< Wraps OrtApi::GetOpaqueValue + + bool IsTensor() const; ///< Returns true if Value is a tensor, false for other types like map/sequence/etc + bool HasValue() const; /// < Return true if OrtValue contains data and returns false if the OrtValue is a None + + size_t GetCount() const; // If a non tensor, returns 2 for map and N for sequence, where N is the number of elements + Value GetValue(int index, OrtAllocator* allocator) const; + + /// + /// This API returns a full length of string data contained within either a tensor or a sparse Tensor. + /// For sparse tensor it returns a full length of stored non-empty strings (values). The API is useful + /// for allocating necessary memory and calling GetStringTensorContent(). + /// + /// total length of UTF-8 encoded bytes contained. No zero terminators counted. + size_t GetStringTensorDataLength() const; + + /// + /// The API copies all of the UTF-8 encoded string data contained within a tensor or a sparse tensor + /// into a supplied buffer. Use GetStringTensorDataLength() to find out the length of the buffer to allocate. + /// The user must also allocate offsets buffer with the number of entries equal to that of the contained + /// strings. + /// + /// Strings are always assumed to be on CPU, no X-device copy. + /// + /// user allocated buffer + /// length in bytes of the allocated buffer + /// a pointer to the offsets user allocated buffer + /// count of offsets, must be equal to the number of strings contained. + /// that can be obtained from the shape of the tensor or from GetSparseTensorValuesTypeAndShapeInfo() + /// for sparse tensors + void GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const; + + /// + /// Returns a const typed pointer to the tensor contained data. + /// No type checking is performed, the caller must ensure the type matches the tensor type. + /// + /// + /// const pointer to data, no copies made + template + const R* GetTensorData() const; ///< Wraps OrtApi::GetTensorData /// + + /// + /// Returns a non-typed pointer to a tensor contained data. + /// + /// const pointer to data, no copies made + const void* GetTensorRawData() const; + + /// + /// The API returns type information for data contained in a tensor. For sparse + /// tensors it returns type information for contained non-zero values. + /// It returns dense shape for sparse tensors. + /// + /// TypeInfo + TypeInfo GetTypeInfo() const; + + /// + /// The API returns type information for data contained in a tensor. For sparse + /// tensors it returns type information for contained non-zero values. + /// It returns dense shape for sparse tensors. + /// + /// TensorTypeAndShapeInfo + TensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const; + + /// + /// This API returns information about the memory allocation used to hold data. + /// + /// Non owning instance of MemoryInfo + ConstMemoryInfo GetTensorMemoryInfo() const; + + /// + /// The API copies UTF-8 encoded bytes for the requested string element + /// contained within a tensor or a sparse tensor into a provided buffer. + /// Use GetStringTensorElementLength() to obtain the length of the buffer to allocate. + /// + /// + /// + /// + void GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const; + + /// + /// Returns string tensor UTF-8 encoded string element. + /// Use of this API is recommended over GetStringTensorElement() that takes void* buffer pointer. + /// + /// + /// std::string + std::string GetStringTensorElement(size_t element_index) const; + + /// + /// The API returns a byte length of UTF-8 encoded string element + /// contained in either a tensor or a spare tensor values. + /// + /// + /// byte length for the specified string element + size_t GetStringTensorElementLength(size_t element_index) const; + + /// + /// Returns the total size of the tensor data in bytes. Throws an exception if the OrtValue + /// does not contain a tensor or if it contains a tensor that contains strings. + /// For numeric tensors, this is sizeof(element_type) * total_element_count. + /// + /// The total size of the tensor data in bytes + size_t GetTensorSizeInBytes() const; ///< Wraps OrtApi::GetTensorSizeInBytes + +#if !defined(DISABLE_SPARSE_TENSORS) + /// + /// The API returns the sparse data format this OrtValue holds in a sparse tensor. + /// If the sparse tensor was not fully constructed, i.e. Use*() or Fill*() API were not used + /// the value returned is ORT_SPARSE_UNDEFINED. + /// + /// Format enum + OrtSparseFormat GetSparseFormat() const; + + /// + /// The API returns type and shape information for stored non-zero values of the + /// sparse tensor. Use GetSparseTensorValues() to obtain values buffer pointer. + /// + /// TensorTypeAndShapeInfo values information + TensorTypeAndShapeInfo GetSparseTensorValuesTypeAndShapeInfo() const; + + /// + /// The API returns type and shape information for the specified indices. Each supported + /// indices have their own enum values even if a give format has more than one kind of indices. + /// Use GetSparseTensorIndicesData() to obtain pointer to indices buffer. + /// + /// enum requested + /// type and shape information + TensorTypeAndShapeInfo GetSparseTensorIndicesTypeShapeInfo(OrtSparseIndicesFormat format) const; + + /// + /// The API retrieves a pointer to the internal indices buffer. The API merely performs + /// a convenience data type casting on the return type pointer. Make sure you are requesting + /// the right type, use GetSparseTensorIndicesTypeShapeInfo(); + /// + /// type to cast to + /// requested indices kind + /// number of indices entries + /// Pinter to the internal sparse tensor buffer containing indices. Do not free this pointer. + template + const R* GetSparseTensorIndicesData(OrtSparseIndicesFormat indices_format, size_t& num_indices) const; + + /// + /// Returns true if the OrtValue contains a sparse tensor + /// + /// + bool IsSparseTensor() const; + + /// + /// The API returns a pointer to an internal buffer of the sparse tensor + /// containing non-zero values. The API merely does casting. Make sure you + /// are requesting the right data type by calling GetSparseTensorValuesTypeAndShapeInfo() + /// first. + /// + /// numeric data types only. Use GetStringTensor*() to retrieve strings. + /// a pointer to the internal values buffer. Do not free this pointer. + template + const R* GetSparseTensorValues() const; + +#endif +}; + +template +struct ValueImpl : ConstValueImpl { + using B = ConstValueImpl; + using B::B; + + /// + /// Returns a non-const typed pointer to an OrtValue/Tensor contained buffer + /// No type checking is performed, the caller must ensure the type matches the tensor type. + /// + /// non-const pointer to data, no copies made + template + R* GetTensorMutableData(); + + /// + /// Returns a non-typed non-const pointer to a tensor contained data. + /// + /// pointer to data, no copies made + void* GetTensorMutableRawData(); + + /// + // Obtain a reference to an element of data at the location specified + /// by the vector of dims. + /// + /// + /// [in] expressed by a vector of dimensions offsets + /// + template + R& At(const std::vector& location); + + /// + /// Set all strings at once in a string tensor + /// + /// [in] An array of strings. Each string in this array must be null terminated. + /// [in] Count of strings in s (Must match the size of \p value's tensor shape) + void FillStringTensor(const char* const* s, size_t s_len); + + /// + /// Set a single string in a string tensor + /// + /// [in] A null terminated UTF-8 encoded string + /// [in] Index of the string in the tensor to set + void FillStringTensorElement(const char* s, size_t index); + + /// + /// Allocate if necessary and obtain a pointer to a UTF-8 + /// encoded string element buffer indexed by the flat element index, + /// of the specified length. + /// + /// This API is for advanced usage. It avoids a need to construct + /// an auxiliary array of string pointers, and allows to write data directly + /// (do not zero terminate). + /// + /// + /// + /// a pointer to a writable buffer + char* GetResizedStringTensorElementBuffer(size_t index, size_t buffer_length); + +#if !defined(DISABLE_SPARSE_TENSORS) + /// + /// Supplies COO format specific indices and marks the contained sparse tensor as being a COO format tensor. + /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user + /// allocated buffers lifespan must eclipse that of the OrtValue. + /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time. + /// + /// pointer to the user allocated buffer with indices. Use nullptr for fully sparse tensors. + /// number of indices entries. Use 0 for fully sparse tensors + void UseCooIndices(int64_t* indices_data, size_t indices_num); + + /// + /// Supplies CSR format specific indices and marks the contained sparse tensor as being a CSR format tensor. + /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user + /// allocated buffers lifespan must eclipse that of the OrtValue. + /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time. + /// + /// pointer to the user allocated buffer with inner indices or nullptr for fully sparse tensors + /// number of csr inner indices or 0 for fully sparse tensors + /// pointer to the user allocated buffer with outer indices or nullptr for fully sparse tensors + /// number of csr outer indices or 0 for fully sparse tensors + void UseCsrIndices(int64_t* inner_data, size_t inner_num, int64_t* outer_data, size_t outer_num); + + /// + /// Supplies BlockSparse format specific indices and marks the contained sparse tensor as being a BlockSparse format tensor. + /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user + /// allocated buffers lifespan must eclipse that of the OrtValue. + /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time. + /// + /// indices shape or a {0} for fully sparse + /// user allocated buffer with indices or nullptr for fully spare tensors + void UseBlockSparseIndices(const Shape& indices_shape, int32_t* indices_data); + + /// + /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API + /// and copy the values and COO indices into it. If data_mem_info specifies that the data is located + /// at difference device than the allocator, a X-device copy will be performed if possible. + /// + /// specified buffer memory description + /// values buffer information. + /// coo indices buffer or nullptr for fully sparse data + /// number of COO indices or 0 for fully sparse data + void FillSparseTensorCoo(const OrtMemoryInfo* data_mem_info, const OrtSparseValuesParam& values_param, + const int64_t* indices_data, size_t indices_num); + + /// + /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API + /// and copy the values and CSR indices into it. If data_mem_info specifies that the data is located + /// at difference device than the allocator, a X-device copy will be performed if possible. + /// + /// specified buffer memory description + /// values buffer information + /// csr inner indices pointer or nullptr for fully sparse tensors + /// number of csr inner indices or 0 for fully sparse tensors + /// pointer to csr indices data or nullptr for fully sparse tensors + /// number of csr outer indices or 0 + void FillSparseTensorCsr(const OrtMemoryInfo* data_mem_info, + const OrtSparseValuesParam& values, + const int64_t* inner_indices_data, size_t inner_indices_num, + const int64_t* outer_indices_data, size_t outer_indices_num); + + /// + /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API + /// and copy the values and BlockSparse indices into it. If data_mem_info specifies that the data is located + /// at difference device than the allocator, a X-device copy will be performed if possible. + /// + /// specified buffer memory description + /// values buffer information + /// indices shape. use {0} for fully sparse tensors + /// pointer to indices data or nullptr for fully sparse tensors + void FillSparseTensorBlockSparse(const OrtMemoryInfo* data_mem_info, + const OrtSparseValuesParam& values, + const Shape& indices_shape, + const int32_t* indices_data); + +#endif +}; + +} // namespace detail + +using ConstValue = detail::ConstValueImpl>; +using UnownedValue = detail::ValueImpl>; + +/** \brief Wrapper around ::OrtValue + * + */ +struct Value : detail::ValueImpl { + using Base = detail::ValueImpl; + using Base::Base; + using OrtSparseValuesParam = detail::OrtSparseValuesParam; + using Shape = detail::Shape; + + Value(std::nullptr_t) {} ///< Create an empty Value object, must be assigned a valid one to be used + Value(Value&&) = default; + Value& operator=(Value&&) = default; + + ConstValue GetConst() const { return ConstValue{this->p_}; } + UnownedValue GetUnowned() const { return UnownedValue{this->p_}; } + + /** \brief Creates a tensor with a user supplied buffer. Wraps OrtApi::CreateTensorWithDataAsOrtValue. + * \tparam T The numeric datatype. This API is not suitable for strings. + * \param info Memory description of where the p_data buffer resides (CPU vs GPU etc). + * \param p_data Pointer to the data buffer. + * \param p_data_element_count The number of elements in the data buffer. + * \param shape Pointer to the tensor shape dimensions. + * \param shape_len The number of tensor shape dimensions. + */ + template + static Value CreateTensor(const OrtMemoryInfo* info, T* p_data, size_t p_data_element_count, + const int64_t* shape, size_t shape_len); + + /** \brief Creates a tensor with a user supplied buffer. Wraps OrtApi::CreateTensorWithDataAsOrtValue. + * + * \param info Memory description of where the p_data buffer resides (CPU vs GPU etc). + * \param p_data Pointer to the data buffer. + * \param p_data_byte_count The number of bytes in the data buffer. + * \param shape Pointer to the tensor shape dimensions. + * \param shape_len The number of tensor shape dimensions. + * \param type The data type. + */ + static Value CreateTensor(const OrtMemoryInfo* info, void* p_data, size_t p_data_byte_count, + const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type); + + /** \brief Creates a tensor with a user supplied buffer. Wraps OrtApi::CreateTensorWithDataAndDeleterAsOrtValue. + * + * \param deleter OrtAllocator that will be used to free the buffer when no longer required. + * \param p_data Pointer to the data buffer. + * \param p_data_byte_count The number of bytes in the data buffer. + * \param shape Pointer to the tensor shape dimensions. + * \param shape_len The number of tensor shape dimensions. + * \param type The data type. + */ + static Value CreateTensor(OrtAllocator* deleter, void* p_data, size_t p_data_byte_count, + const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type); + + /** \brief Creates an OrtValue with a tensor using a supplied OrtAllocator. Wraps OrtApi::CreateTensorAsOrtValue. + * This overload will allocate the buffer for the tensor according to the supplied shape and data type. + * The allocated buffer will be owned by the returned OrtValue and will be freed when the OrtValue is released. + * The input data would need to be copied into the allocated buffer. + * This API is not suitable for strings. + * + * \tparam T The numeric datatype. This API is not suitable for strings. + * \param allocator The allocator to use. + * \param shape Pointer to the tensor shape dimensions. + * \param shape_len The number of tensor shape dimensions. + */ + template + static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len); + + /** \brief Creates an OrtValue with a tensor using the supplied OrtAllocator. + * Wraps OrtApi::CreateTensorAsOrtValue. + * The allocated buffer will be owned by the returned OrtValue and will be freed when the OrtValue is released. + * The input data would need to be copied into the allocated buffer. + * This API is not suitable for strings. + * + * \param allocator The allocator to use. + * \param shape Pointer to the tensor shape dimensions. + * \param shape_len The number of tensor shape dimensions. + * \param type The data type. + */ + static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type); + + /** \brief Creates an OrtValue with a Map Onnx type representation. + * The API would ref-count the supplied OrtValues and they will be released + * when the returned OrtValue is released. The caller may release keys and values after the call + * returns. + * + * \param keys an OrtValue containing a tensor with primitive data type keys. + * \param values an OrtValue that may contain a tensor. Ort currently supports only primitive data type values. + */ + static Value CreateMap(const Value& keys, const Value& values); ///< Wraps OrtApi::CreateValue + + /** \brief Creates an OrtValue with a Sequence Onnx type representation. + * The API would ref-count the supplied OrtValues and they will be released + * when the returned OrtValue is released. The caller may release the values after the call + * returns. + * + * \param values a vector of OrtValues that must have the same Onnx value type. + */ + static Value CreateSequence(const std::vector& values); ///< Wraps OrtApi::CreateValue + + /** \brief Creates an OrtValue wrapping an Opaque type. + * This is used for experimental support of non-tensor types. + * + * \tparam T - the type of the value. + * \param domain - zero terminated utf-8 string. Domain of the type. + * \param type_name - zero terminated utf-8 string. Name of the type. + * \param value - the value to be wrapped. + */ + template + static Value CreateOpaque(const char* domain, const char* type_name, const T& value); ///< Wraps OrtApi::CreateOpaqueValue + +#if !defined(DISABLE_SPARSE_TENSORS) + /// + /// This is a simple forwarding method to the other overload that helps deducing + /// data type enum value from the type of the buffer. + /// + /// numeric datatype. This API is not suitable for strings. + /// Memory description where the user buffers reside (CPU vs GPU etc) + /// pointer to the user supplied buffer, use nullptr for fully sparse tensors + /// a would be dense shape of the tensor + /// non zero values shape. Use a single 0 shape for fully sparse tensors. + /// + template + static Value CreateSparseTensor(const OrtMemoryInfo* info, T* p_data, const Shape& dense_shape, + const Shape& values_shape); + + /// + /// Creates an OrtValue instance containing SparseTensor. This constructs + /// a sparse tensor that makes use of user allocated buffers. It does not make copies + /// of the user provided data and does not modify it. The lifespan of user provided buffers should + /// eclipse the life span of the resulting OrtValue. This call constructs an instance that only contain + /// a pointer to non-zero values. To fully populate the sparse tensor call UseIndices() API below + /// to supply a sparse format specific indices. + /// This API is not suitable for string data. Use CreateSparseTensor() with allocator specified so strings + /// can be properly copied into the allocated buffer. + /// + /// Memory description where the user buffers reside (CPU vs GPU etc) + /// pointer to the user supplied buffer, use nullptr for fully sparse tensors + /// a would be dense shape of the tensor + /// non zero values shape. Use a single 0 shape for fully sparse tensors. + /// data type + /// Ort::Value instance containing SparseTensor + static Value CreateSparseTensor(const OrtMemoryInfo* info, void* p_data, const Shape& dense_shape, + const Shape& values_shape, ONNXTensorElementDataType type); + + /// + /// This is a simple forwarding method to the below CreateSparseTensor. + /// This helps to specify data type enum in terms of C++ data type. + /// Use CreateSparseTensor + /// + /// numeric data type only. String data enum must be specified explicitly. + /// allocator to use + /// a would be dense shape of the tensor + /// Ort::Value + template + static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape); + + /// + /// Creates an instance of OrtValue containing sparse tensor. The created instance has no data. + /// The data must be supplied by on of the FillSparseTensor() methods that take both non-zero values + /// and indices. The data will be copied into a buffer that would be allocated using the supplied allocator. + /// Use this API to create OrtValues that contain sparse tensors with all supported data types including + /// strings. + /// + /// allocator to use. The allocator lifespan must eclipse that of the resulting OrtValue + /// a would be dense shape of the tensor + /// data type + /// an instance of Ort::Value + static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape, ONNXTensorElementDataType type); + +#endif // !defined(DISABLE_SPARSE_TENSORS) +}; + +namespace detail { +namespace binding_utils { +// Bring these out of template +std::vector GetOutputNamesHelper(const OrtIoBinding* binding, OrtAllocator*); +std::vector GetOutputValuesHelper(const OrtIoBinding* binding, OrtAllocator*); +} // namespace binding_utils + +template +struct ConstIoBindingImpl : Base { + using B = Base; + using B::B; + + std::vector GetOutputNames() const; + std::vector GetOutputNames(OrtAllocator*) const; + std::vector GetOutputValues() const; + std::vector GetOutputValues(OrtAllocator*) const; +}; + +template +struct IoBindingImpl : ConstIoBindingImpl { + using B = ConstIoBindingImpl; + using B::B; + + void BindInput(const char* name, const Value&); + void BindOutput(const char* name, const Value&); + void BindOutput(const char* name, const OrtMemoryInfo*); + void ClearBoundInputs(); + void ClearBoundOutputs(); + void SynchronizeInputs(); + void SynchronizeOutputs(); +}; + +} // namespace detail + +using ConstIoBinding = detail::ConstIoBindingImpl>; +using UnownedIoBinding = detail::IoBindingImpl>; + +/** \brief Wrapper around ::OrtIoBinding + * + */ +struct IoBinding : detail::IoBindingImpl { + explicit IoBinding(std::nullptr_t) {} ///< Create an empty object for convenience. Sometimes, we want to initialize members later. + explicit IoBinding(Session& session); + ConstIoBinding GetConst() const { return ConstIoBinding{this->p_}; } + UnownedIoBinding GetUnowned() const { return UnownedIoBinding{this->p_}; } +}; + +/*! \struct Ort::ArenaCfg + * \brief it is a structure that represents the configuration of an arena based allocator + * \details Please see docs/C_API.md for details + */ +struct ArenaCfg : detail::Base { + explicit ArenaCfg(std::nullptr_t) {} ///< Create an empty ArenaCfg object, must be assigned a valid one to be used + /** + * Wraps OrtApi::CreateArenaCfg + * \param max_mem - use 0 to allow ORT to choose the default + * \param arena_extend_strategy - use -1 to allow ORT to choose the default, 0 = kNextPowerOfTwo, 1 = kSameAsRequested + * \param initial_chunk_size_bytes - use -1 to allow ORT to choose the default + * \param max_dead_bytes_per_chunk - use -1 to allow ORT to choose the default + * See docs/C_API.md for details on what the following parameters mean and how to choose these values + */ + ArenaCfg(size_t max_mem, int arena_extend_strategy, int initial_chunk_size_bytes, int max_dead_bytes_per_chunk); + + /** + * Wraps Ort::CreateArenaCfgV2 + * See C API for details on what the following parameters mean and how to choose these values + */ + explicit ArenaCfg(const std::unordered_map& arena_config); +}; + +// +// Custom OPs (only needed to implement custom OPs) +// + +namespace detail { +// Need to define a templated ConstOpAttr with const members +template +struct ConstOpAttrImpl : Base { + using B = detail::Base; + using B::B; + + // Wraps OrtApi::OpAttr_GetName + std::string GetName() const; + // Wraps OrtApi::OpAttr_GetType + OrtOpAttrType GetType() const; + + // Wraps OrtApi::ReadAttr for a single value + // This does not support Tensor Attribute + // Call GetTensorAttributeAsOrtValue() instead. + template + Status GetValue(R& out) const; + + // Wraps OrtApi::ReadAttr for an array of values + template + Status GetValueArray(std::vector& out) const; + // Wraps OrtApi::OpAttr_GetTensorAttributeAsOrtValue + Status GetTensorAttributeAsOrtValue(Value&) const; +}; +} // namespace detail + +using ConstOpAttr = detail::ConstOpAttrImpl>; + +/// +/// This struct provides life time management for custom op attribute +/// +struct OpAttr : detail::ConstOpAttrImpl { + using Base = detail::ConstOpAttrImpl; + using Base::Base; + + OpAttr() = default; // Enable storing it in the container for resize() + explicit OpAttr(std::nullptr_t) {} + OpAttr(const char* name, const void* data, int len, OrtOpAttrType type); + + ConstOpAttr GetConst() const { return ConstOpAttr{this->p_}; } +}; + +/** + * Macro that logs a message using the provided logger. Throws an exception if OrtApi::Logger_LogMessage fails. + * Example: ORT_CXX_LOG(logger, ORT_LOGGING_LEVEL_INFO, "Log a message"); + * + * \param logger The Ort::Logger instance to use. Must be a value or reference. + * \param message_severity The logging severity level of the message. + * \param message A null-terminated UTF-8 message to log. + */ +#define ORT_CXX_LOG(logger, message_severity, message) \ + do { \ + if (message_severity >= logger.GetLoggingSeverityLevel()) { \ + Ort::ThrowOnError(logger.LogMessage(message_severity, ORT_FILE, __LINE__, \ + static_cast(__FUNCTION__), message)); \ + } \ + } while (false) + +/** + * Macro that logs a message using the provided logger. Can be used in noexcept code since errors are silently ignored. + * Example: ORT_CXX_LOG_NOEXCEPT(logger, ORT_LOGGING_LEVEL_INFO, "Log a message"); + * + * \param logger The Ort::Logger instance to use. Must be a value or reference. + * \param message_severity The logging severity level of the message. + * \param message A null-terminated UTF-8 message to log. + */ +#define ORT_CXX_LOG_NOEXCEPT(logger, message_severity, message) \ + do { \ + if (message_severity >= logger.GetLoggingSeverityLevel()) { \ + static_cast(logger.LogMessage(message_severity, ORT_FILE, __LINE__, \ + static_cast(__FUNCTION__), message)); \ + } \ + } while (false) + +/** + * Macro that logs a printf-like formatted message using the provided logger. Throws an exception if + * OrtApi::Logger_LogMessage fails or if a formatting error occurs. + * Example: ORT_CXX_LOGF(logger, ORT_LOGGING_LEVEL_INFO, "Log an int: %d", 12); + * + * \param logger The Ort::Logger instance to use. Must be a value or reference. + * \param message_severity The logging severity level of the message. + * \param format A null-terminated UTF-8 format string forwarded to a printf-like function. + * Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats. + * \param ... Zero or more variadic arguments referenced by the format string. + */ +#define ORT_CXX_LOGF(logger, message_severity, /*format,*/...) \ + do { \ + if (message_severity >= logger.GetLoggingSeverityLevel()) { \ + Ort::ThrowOnError(logger.LogFormattedMessage(message_severity, ORT_FILE, __LINE__, \ + static_cast(__FUNCTION__), __VA_ARGS__)); \ + } \ + } while (false) + +/** + * Macro that logs a printf-like formatted message using the provided logger. Can be used in noexcept code since errors + * are silently ignored. + * Example: ORT_CXX_LOGF_NOEXCEPT(logger, ORT_LOGGING_LEVEL_INFO, "Log an int: %d", 12); + * + * \param logger The Ort::Logger instance to use. Must be a value or reference. + * \param message_severity The logging severity level of the message. + * \param format A null-terminated UTF-8 format string forwarded to a printf-like function. + * Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats. + * \param ... Zero or more variadic arguments referenced by the format string. + */ +#define ORT_CXX_LOGF_NOEXCEPT(logger, message_severity, /*format,*/...) \ + do { \ + if (message_severity >= logger.GetLoggingSeverityLevel()) { \ + static_cast(logger.LogFormattedMessage(message_severity, ORT_FILE, __LINE__, \ + static_cast(__FUNCTION__), __VA_ARGS__)); \ + } \ + } while (false) + +/// +/// This class represents an ONNX Runtime logger that can be used to log information with an +/// associated severity level and source code location (file path, line number, function name). +/// +/// A Logger can be obtained from within custom operators by calling Ort::KernelInfo::GetLogger(). +/// Instances of Ort::Logger are the size of two pointers and can be passed by value. +/// +/// Use the ORT_CXX_LOG macros to ensure the source code location is set properly from the callsite +/// and to take advantage of a cached logging severity level that can bypass calls to the underlying C API. +/// +struct Logger { + /** + * Creates an empty Ort::Logger. Must be initialized from a valid Ort::Logger before use. + */ + Logger() = default; + + /** + * Creates an empty Ort::Logger. Must be initialized from a valid Ort::Logger before use. + */ + explicit Logger(std::nullptr_t) {} + + /** + * Creates a logger from an ::OrtLogger instance. Caches the logger's current severity level by calling + * OrtApi::Logger_GetLoggingSeverityLevel. Throws an exception if OrtApi::Logger_GetLoggingSeverityLevel fails. + * + * \param logger The ::OrtLogger to wrap. + */ + explicit Logger(const OrtLogger* logger); + + ~Logger() = default; + + Logger(const Logger&) = default; + Logger& operator=(const Logger&) = default; + + Logger(Logger&& v) noexcept = default; + Logger& operator=(Logger&& v) noexcept = default; + + /** + * Returns the logger's current severity level from the cached member. + * + * \return The current ::OrtLoggingLevel. + */ + OrtLoggingLevel GetLoggingSeverityLevel() const noexcept; + + /** + * Logs the provided message via OrtApi::Logger_LogMessage. Use the ORT_CXX_LOG or ORT_CXX_LOG_NOEXCEPT + * macros to properly set the source code location and to use the cached severity level to potentially bypass + * calls to the underlying C API. + * + * \param log_severity_level The message's logging severity level. + * \param file_path The filepath of the file in which the message is logged. Usually the value of ORT_FILE. + * \param line_number The file line number in which the message is logged. Usually the value of __LINE__. + * \param func_name The name of the function in which the message is logged. Usually the value of __FUNCTION__. + * \param message The message to log. + * \return A Ort::Status value to indicate error or success. + */ + Status LogMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, int line_number, + const char* func_name, const char* message) const noexcept; + + /** + * Logs a printf-like formatted message via OrtApi::Logger_LogMessage. Use the ORT_CXX_LOGF or ORT_CXX_LOGF_NOEXCEPT + * macros to properly set the source code location and to use the cached severity level to potentially bypass + * calls to the underlying C API. Returns an error status if a formatting error occurs. + * + * \param log_severity_level The message's logging severity level. + * \param file_path The filepath of the file in which the message is logged. Usually the value of ORT_FILE. + * \param line_number The file line number in which the message is logged. Usually the value of __LINE__. + * \param func_name The name of the function in which the message is logged. Usually the value of __FUNCTION__. + * \param format A null-terminated UTF-8 format string forwarded to a printf-like function. + * Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats. + * \param args Zero or more variadic arguments referenced by the format string. + * \return A Ort::Status value to indicate error or success. + */ + template + Status LogFormattedMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, int line_number, + const char* func_name, const char* format, Args&&... args) const noexcept; + + private: + const OrtLogger* logger_{}; + OrtLoggingLevel cached_severity_level_{}; +}; + +/// +/// This class wraps a raw pointer OrtKernelContext* that is being passed +/// to the custom kernel Compute() method. Use it to safely access context +/// attributes, input and output parameters with exception safety guarantees. +/// See usage example in onnxruntime/test/testdata/custom_op_library/custom_op_library.cc +/// +struct KernelContext { + explicit KernelContext(OrtKernelContext* context); + size_t GetInputCount() const; + size_t GetOutputCount() const; + // If input is optional and is not present, the method returns an empty ConstValue + // which can be compared to nullptr. + ConstValue GetInput(size_t index) const; + // If output is optional and is not present, the method returns an empty UnownedValue + // which can be compared to nullptr. + UnownedValue GetOutput(size_t index, const int64_t* dim_values, size_t dim_count) const; + UnownedValue GetOutput(size_t index, const std::vector& dims) const; + void* GetGPUComputeStream() const; + Logger GetLogger() const; + OrtAllocator* GetAllocator(const OrtMemoryInfo& memory_info) const; + OrtKernelContext* GetOrtKernelContext() const { return ctx_; } + void ParallelFor(void (*fn)(void*, size_t), size_t total, size_t num_batch, void* usr_data) const; + + private: + OrtKernelContext* ctx_; +}; + +struct KernelInfo; + +namespace detail { +namespace attr_utils { +void GetAttr(const OrtKernelInfo* p, const char* name, float&); +void GetAttr(const OrtKernelInfo* p, const char* name, int64_t&); +void GetAttr(const OrtKernelInfo* p, const char* name, std::string&); +void GetAttrs(const OrtKernelInfo* p, const char* name, std::vector&); +void GetAttrs(const OrtKernelInfo* p, const char* name, std::vector&); +} // namespace attr_utils + +template +struct KernelInfoImpl : Base { + using B = Base; + using B::B; + + KernelInfo Copy() const; + + template // R is only implemented for float, int64_t, and string + R GetAttribute(const char* name) const { + R val; + attr_utils::GetAttr(this->p_, name, val); + return val; + } + + template // R is only implemented for std::vector, std::vector + std::vector GetAttributes(const char* name) const { + std::vector result; + attr_utils::GetAttrs(this->p_, name, result); + return result; + } + + Value GetTensorAttribute(const char* name, OrtAllocator* allocator) const; + + size_t GetInputCount() const; + size_t GetOutputCount() const; + + std::string GetInputName(size_t index) const; + std::string GetOutputName(size_t index) const; + + TypeInfo GetInputTypeInfo(size_t index) const; + TypeInfo GetOutputTypeInfo(size_t index) const; + + ConstValue GetTensorConstantInput(size_t index, int* is_constant) const; + + std::string GetNodeName() const; + Logger GetLogger() const; +}; + +} // namespace detail + +using ConstKernelInfo = detail::KernelInfoImpl>; + +/// +/// This struct owns the OrtKernInfo* pointer when a copy is made. +/// For convenient wrapping of OrtKernelInfo* passed to kernel constructor +/// and query attributes, warp the pointer with Ort::Unowned instance +/// so it does not destroy the pointer the kernel does not own. +/// +struct KernelInfo : detail::KernelInfoImpl { + using Base = detail::KernelInfoImpl; + using Base::Base; + explicit KernelInfo(std::nullptr_t) {} ///< Create an empty instance to initialize later + explicit KernelInfo(OrtKernelInfo* info); ///< Take ownership of the instance + ConstKernelInfo GetConst() const { return ConstKernelInfo{this->p_}; } +}; + +/// +/// Create and own custom defined operation. +/// +struct Op : detail::Base { + using Base = detail::Base; + using Base::Base; + + explicit Op(std::nullptr_t) {} ///< Create an empty Operator object, must be assigned a valid one to be used + + explicit Op(OrtOp*); ///< Take ownership of the OrtOp + + static Op Create(const OrtKernelInfo* info, const char* op_name, const char* domain, + int version, const char** type_constraint_names, + const ONNXTensorElementDataType* type_constraint_values, + size_t type_constraint_count, + const OpAttr* attr_values, + size_t attr_count, + size_t input_count, size_t output_count); + + void Invoke(const OrtKernelContext* context, + const Value* input_values, + size_t input_count, + Value* output_values, + size_t output_count); + + // For easier refactoring + void Invoke(const OrtKernelContext* context, + const OrtValue* const* input_values, + size_t input_count, + OrtValue* const* output_values, + size_t output_count); +}; + +/// +/// Provide access to per-node attributes and input shapes, so one could compute and set output shapes. +/// +struct ShapeInferContext { + struct SymbolicInteger { + SymbolicInteger(int64_t i) : i_(i), is_int_(true) {}; + SymbolicInteger(const char* s) : s_(s), is_int_(false) {}; + SymbolicInteger(const SymbolicInteger&) = default; + SymbolicInteger(SymbolicInteger&&) = default; + + SymbolicInteger& operator=(const SymbolicInteger&) = default; + SymbolicInteger& operator=(SymbolicInteger&&) = default; + + bool operator==(const SymbolicInteger& dim) const { + if (is_int_ == dim.is_int_) { + if (is_int_) { + return i_ == dim.i_; + } else { + return std::string{s_} == std::string{dim.s_}; + } + } + return false; + } + + bool IsInt() const { return is_int_; } + int64_t AsInt() const { return i_; } + const char* AsSym() const { return s_; } + + static constexpr int INVALID_INT_DIM = -2; + + private: + union { + int64_t i_; + const char* s_; + }; + bool is_int_; + }; + + using Shape = std::vector; + + ShapeInferContext(const OrtApi* ort_api, OrtShapeInferContext* ctx); + + const Shape& GetInputShape(size_t indice) const { return input_shapes_.at(indice); } + + size_t GetInputCount() const { return input_shapes_.size(); } + + Status SetOutputShape(size_t indice, const Shape& shape, ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT); + + int64_t GetAttrInt(const char* attr_name); + + using Ints = std::vector; + Ints GetAttrInts(const char* attr_name); + + float GetAttrFloat(const char* attr_name); + + using Floats = std::vector; + Floats GetAttrFloats(const char* attr_name); + + std::string GetAttrString(const char* attr_name); + + using Strings = std::vector; + Strings GetAttrStrings(const char* attr_name); + + private: + ConstOpAttr GetAttrHdl(const char* attr_name) const; + const OrtApi* ort_api_; + OrtShapeInferContext* ctx_; + std::vector input_shapes_; +}; + +using ShapeInferFn = Ort::Status (*)(Ort::ShapeInferContext&); + +#define MAX_CUSTOM_OP_END_VER (1UL << 31) - 1 + +template +struct CustomOpBase : OrtCustomOp { + CustomOpBase() { + OrtCustomOp::version = ORT_API_VERSION; + OrtCustomOp::GetName = [](const OrtCustomOp* this_) { return static_cast(this_)->GetName(); }; + + OrtCustomOp::GetExecutionProviderType = [](const OrtCustomOp* this_) { return static_cast(this_)->GetExecutionProviderType(); }; + + OrtCustomOp::GetInputTypeCount = [](const OrtCustomOp* this_) { return static_cast(this_)->GetInputTypeCount(); }; + OrtCustomOp::GetInputType = [](const OrtCustomOp* this_, size_t index) { return static_cast(this_)->GetInputType(index); }; + OrtCustomOp::GetInputMemoryType = [](const OrtCustomOp* this_, size_t index) { return static_cast(this_)->GetInputMemoryType(index); }; + + OrtCustomOp::GetOutputTypeCount = [](const OrtCustomOp* this_) { return static_cast(this_)->GetOutputTypeCount(); }; + OrtCustomOp::GetOutputType = [](const OrtCustomOp* this_, size_t index) { return static_cast(this_)->GetOutputType(index); }; + +#if defined(_MSC_VER) && !defined(__clang__) +#pragma warning(push) +#pragma warning(disable : 26409) +#endif + OrtCustomOp::KernelDestroy = [](void* op_kernel) { delete static_cast(op_kernel); }; +#if defined(_MSC_VER) && !defined(__clang__) +#pragma warning(pop) +#endif + OrtCustomOp::GetInputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast(this_)->GetInputCharacteristic(index); }; + OrtCustomOp::GetOutputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast(this_)->GetOutputCharacteristic(index); }; + + OrtCustomOp::GetVariadicInputMinArity = [](const OrtCustomOp* this_) { return static_cast(this_)->GetVariadicInputMinArity(); }; + OrtCustomOp::GetVariadicInputHomogeneity = [](const OrtCustomOp* this_) { return static_cast(static_cast(this_)->GetVariadicInputHomogeneity()); }; + OrtCustomOp::GetVariadicOutputMinArity = [](const OrtCustomOp* this_) { return static_cast(this_)->GetVariadicOutputMinArity(); }; + OrtCustomOp::GetVariadicOutputHomogeneity = [](const OrtCustomOp* this_) { return static_cast(static_cast(this_)->GetVariadicOutputHomogeneity()); }; +#ifdef __cpp_if_constexpr + if constexpr (WithStatus) { +#else + if (WithStatus) { +#endif + OrtCustomOp::CreateKernelV2 = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info, void** op_kernel) -> OrtStatusPtr { + return static_cast(this_)->CreateKernelV2(*api, info, op_kernel); + }; + OrtCustomOp::KernelComputeV2 = [](void* op_kernel, OrtKernelContext* context) -> OrtStatusPtr { + return static_cast(op_kernel)->ComputeV2(context); + }; + } else { + OrtCustomOp::CreateKernelV2 = nullptr; + OrtCustomOp::KernelComputeV2 = nullptr; + + OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info) { return static_cast(this_)->CreateKernel(*api, info); }; + OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) { + static_cast(op_kernel)->Compute(context); + }; + } + + SetShapeInferFn(0); + + OrtCustomOp::GetStartVersion = [](const OrtCustomOp* this_) { + return static_cast(this_)->start_ver_; + }; + + OrtCustomOp::GetEndVersion = [](const OrtCustomOp* this_) { + return static_cast(this_)->end_ver_; + }; + + OrtCustomOp::GetMayInplace = nullptr; + OrtCustomOp::ReleaseMayInplace = nullptr; + OrtCustomOp::GetAliasMap = nullptr; + OrtCustomOp::ReleaseAliasMap = nullptr; + } + + // Default implementation of GetExecutionProviderType that returns nullptr to default to the CPU provider + const char* GetExecutionProviderType() const { return nullptr; } + + // Default implementations of GetInputCharacteristic() and GetOutputCharacteristic() below + // (inputs and outputs are required by default) + OrtCustomOpInputOutputCharacteristic GetInputCharacteristic(size_t /*index*/) const { + return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED; + } + + OrtCustomOpInputOutputCharacteristic GetOutputCharacteristic(size_t /*index*/) const { + return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED; + } + + // Default implementation of GetInputMemoryType() that returns OrtMemTypeDefault + OrtMemType GetInputMemoryType(size_t /*index*/) const { + return OrtMemTypeDefault; + } + + // Default implementation of GetVariadicInputMinArity() returns 1 to specify that a variadic input + // should expect at least 1 argument. + int GetVariadicInputMinArity() const { + return 1; + } + + // Default implementation of GetVariadicInputHomegeneity() returns true to specify that all arguments + // to a variadic input should be of the same type. + bool GetVariadicInputHomogeneity() const { + return true; + } + + // Default implementation of GetVariadicOutputMinArity() returns 1 to specify that a variadic output + // should produce at least 1 output value. + int GetVariadicOutputMinArity() const { + return 1; + } + + // Default implementation of GetVariadicOutputHomegeneity() returns true to specify that all output values + // produced by a variadic output should be of the same type. + bool GetVariadicOutputHomogeneity() const { + return true; + } + + // Declare list of session config entries used by this Custom Op. + // Implement this function in order to get configs from CustomOpBase::GetSessionConfigs(). + // This default implementation returns an empty vector of config entries. + std::vector GetSessionConfigKeys() const { + return std::vector{}; + } + + // Ort::CustomOpBase derived class should provide the following static method with the type/shape inferencing + // implementation if needed: + // static OrtStatusPtr InferOutputShape(Ort::ShapeInferContext& context) + template + decltype(&C::InferOutputShape) SetShapeInferFn(decltype(&C::InferOutputShape)) { + OrtCustomOp::InferOutputShapeFn = [](const OrtCustomOp*, OrtShapeInferContext* ort_ctx) -> OrtStatusPtr { + ShapeInferContext ctx(&GetApi(), ort_ctx); + return C::InferOutputShape(ctx); + }; + return {}; + } + + template + void SetShapeInferFn(...) { + OrtCustomOp::InferOutputShapeFn = {}; + } + + protected: + // Helper function that returns a map of session config entries specified by CustomOpBase::GetSessionConfigKeys. + void GetSessionConfigs(std::unordered_map& out, ConstSessionOptions options) const; + + int start_ver_ = 1; + int end_ver_ = MAX_CUSTOM_OP_END_VER; +}; + +// Forward declaration to resolve circular dependency +// on ConstNode +struct ValueInfoConsumerProducerInfo; + +namespace detail { +template +struct ConstValueInfoImpl : Base { + using B = Base; + using B::B; + + /// < A wrapper around OrtApi::GetValueInfoName + std::string GetName() const; + /// < A wrapper around OrtApi::GetValueInfoTypeInfo + ConstTypeInfo TypeInfo() const; + ///< Wraps OrtApi::ValueInfo_GetProducerNode + ValueInfoConsumerProducerInfo GetProducerNode() const; + /// < A wrapper around OrtApi::ValueInfo_GetValueConsumers + std::vector GetConsumers() const; + /// < A wrapper around OrtApi::ValueInfo_GetInitializerValue + Status GetInitializer(ConstValue& value) const; + /// < A wrapper around OrtApi::ValueInfo_GetExternalInitializerInfo + Status GetExternalInitializerInfo(ExternalInitializerInfo& info) const; + /// < A wrapper around OrtApi::ValueInfo_IsRequiredGraphInput + bool IsRequiredGraphInput() const; + /// < A wrapper around OrtApi::ValueInfo_IsOptionalGraphInput + bool IsOptionalGraphInput() const; + /// < A wrapper around OrtApi::ValueInfo_IsGraphOutput + bool IsGraphOutput() const; + /// < A wrapper around OrtApi::ValueInfo_IsConstantInitializer + bool IsConstantInitializer() const; + /// < A wrapper around OrtApi::ValueInfo_IsFromOuterScope + bool IsFromOuterScope() const; +}; +} // namespace detail + +// Const object holder that does not own the underlying object +using ConstValueInfo = detail::ConstValueInfoImpl>; + +/** \brief Wrapper around ::OrtValueInfo + * + */ +struct ValueInfo : detail::ConstValueInfoImpl { + ValueInfo() = default; // Same thing as with nullptr + explicit ValueInfo(std::nullptr_t) {} ///< No instance is created + /// Take ownership of a pointer created by C API + explicit ValueInfo(OrtValueInfo* p) : ConstValueInfoImpl{p} {} + +#if !defined(ORT_MINIMAL_BUILD) + // Create ValueInfo for a tensor + explicit ValueInfo(const std::string& name, const ConstTypeInfo& type_info); +#endif + ConstValueInfo GetConst() const { return ConstValueInfo{this->p_}; } +}; + +// Forward declaration +struct AttrNameSubgraph; + +namespace detail { +// Forward decl +template +struct ConstGraphImpl; + +template +struct ConstNodeImpl : Base { + using B = Base; + using B::B; + + // GetInputs() const; + // GetOutputs() const; + // GetImplicitInputs() const; + // GetAttributes() const; + // GetSubgraphs() const; + // > GetGraph() const; + // >; + +/** \brief Wrapper around ::OrtNode + * + */ +struct Node : detail::ConstNodeImpl { + Node() = default; // Same thing as with nullptr + explicit Node(std::nullptr_t) {} ///< No instance is created + explicit Node(OrtNode* p) : ConstNodeImpl{p} {} ///< Take ownership of a pointer created by C API + +#if !defined(ORT_MINIMAL_BUILD) + Node(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names); + + /// + /// Wraps CreateNode. Node takes ownership of attributes on success and updates the OpAttr in `attributes` to do so. + /// + Node(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names, + std::vector& attributes); + + private: + static void Init(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names, + std::vector& attributes, + OrtNode*& node); +#endif // !defined(ORT_MINIMAL_BUILD) +}; + +// Return struct for some of ValueInfo APIs. +// Must be declared after ConstNode is available. +struct ValueInfoConsumerProducerInfo { + ConstNode node; + // either producer output or consumer output index + // producer is unsigned only, output can be -1 + int64_t index; +}; + +// Represents a return value for Graph::GetOperatorSets() +struct OperatorSet { + std::string domain; + int64_t version; +}; + +namespace detail { +template +struct ConstGraphImpl : Base { + using B = Base; + using B::B; + + // GetModelPath() const; + // GetOperatorSets() const; + // GetInputs() const; + // GetOutputs() const; + // GetInitializers() const; + // GetNodes() const; + // & nodes) const; + // +struct GraphImpl : ConstGraphImpl { + using B = ConstGraphImpl; + using B::B; + +#if !defined(ORT_MINIMAL_BUILD) + // & inputs); + // & outputs); + // >; + +// Return value for Node API +// Must be declared after ConstGraph +struct AttrNameSubgraph { + std::string attr_name; + ConstGraph sub_graph; +}; + +/** \brief Wrapper around ::OrtGraph + * + */ +struct Graph : detail::GraphImpl { + explicit Graph(std::nullptr_t) {} ///< No instance is created + explicit Graph(OrtGraph* p) : GraphImpl{p} {} ///< Take ownership of a pointer created by C API +#if !defined(ORT_MINIMAL_BUILD) + // +struct ModelImpl : detail::Base { + using B = Ort::detail::Base; + using B::B; + +#if !defined(ORT_MINIMAL_BUILD) + // >; + +/** \brief Wrapper around ::OrtModel + * + */ +struct Model : detail::ModelImpl { + using DomainOpsetPair = std::pair; + + explicit Model(std::nullptr_t) {} ///< No instance is created + explicit Model(OrtModel* p) : ModelImpl{p} {} ///< Take ownership of a pointer created by C API + +#if !defined(ORT_MINIMAL_BUILD) + //< Wraps GetModelEditorApi().CreateModel() + explicit Model(const std::vector& opsets); +#endif +}; +} // namespace Ort +#include "onnxruntime_cxx_inline.h" diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_inline.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_inline.h new file mode 100644 index 0000000..cb6448a --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_cxx_inline.h @@ -0,0 +1,3547 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +// Do not include this file directly. Please include "onnxruntime_cxx_api.h" instead. +// If interested in trying out features of the new experimental C++ API, include "experimental_onnxruntime_cxx_api.h" instead. +// +// These are the inline implementations of the C++ header APIs. They're in this separate file as to not clutter +// the main C++ file with implementation details. + +#include +#include +#include +#include +#include +#include + +// Convert OrtStatus to Ort::Status and return +// instead of throwing +#define ORT_CXX_RETURN_ON_API_FAIL(expression) \ + { \ + auto ort_status = (expression); \ + if (ort_status) { \ + return Ort::Status(ort_status); \ + } \ + } + +#ifdef __cpp_if_constexpr +#define ORT_CXX_IF_CONSTEXPR if constexpr +#else +#define ORT_CXX_IF_CONSTEXPR if +#endif + +namespace Ort { + +namespace detail { +inline void ThrowStatus(const Status& st) { + std::string error_message = st.GetErrorMessage(); + OrtErrorCode error_code = st.GetErrorCode(); + ORT_CXX_API_THROW(std::move(error_message), error_code); +} +} // namespace detail + +inline void ThrowOnError(OrtStatus* ort_status) { + if (ort_status) { + Ort::Status st(ort_status); + detail::ThrowStatus(st); + } +} + +inline void ThrowOnError(const Status& st) { + if (st) { + detail::ThrowStatus(st); + } +} + +inline Status::Status(OrtStatus* status) noexcept : detail::Base{status} { +} + +inline Status::Status(const std::exception& e) { + p_ = GetApi().CreateStatus(ORT_FAIL, e.what()); +} + +inline Status::Status(const Exception& e) { + p_ = GetApi().CreateStatus(e.GetOrtErrorCode(), e.what()); +} + +inline Status::Status(const char* message, OrtErrorCode code) { + p_ = GetApi().CreateStatus(code, message); +} + +inline std::string Status::GetErrorMessage() const { + std::string message(GetApi().GetErrorMessage(p_)); + return message; +} + +inline OrtErrorCode Status::GetErrorCode() const { + return GetApi().GetErrorCode(p_); +} + +inline bool Status::IsOK() const noexcept { + return (p_ == nullptr); +} + +// This template converts a C++ type into it's ONNXTensorElementDataType +template +struct TypeToTensorType; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL; +}; + +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FN; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FNUZ; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2; +}; +template <> +struct TypeToTensorType { + static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2FNUZ; +}; + +inline bool BFloat16_t::operator==(const BFloat16_t& rhs) const noexcept { + if (IsNaN() || rhs.IsNaN()) { + // IEEE defines that NaN is not equal to anything, including itself. + return false; + } + return val == rhs.val; +} + +inline bool BFloat16_t::operator<(const BFloat16_t& rhs) const noexcept { + if (IsNaN() || rhs.IsNaN()) { + // IEEE defines that NaN is unordered with respect to everything, including itself. + return false; + } + + const bool left_is_negative = IsNegative(); + if (left_is_negative != rhs.IsNegative()) { + // When the signs of left and right differ, we know that left is less than right if it is + // the negative value. The exception to this is if both values are zero, in which case IEEE + // says they should be equal, even if the signs differ. + return left_is_negative && !AreZero(*this, rhs); + } + return (val != rhs.val) && ((val < rhs.val) ^ left_is_negative); +} + +inline MemoryAllocation::MemoryAllocation(OrtAllocator* allocator, void* p, size_t size) + : allocator_(allocator), p_(p), size_(size) { +} + +inline MemoryAllocation::~MemoryAllocation() { + if (p_ != nullptr) { + // We do not throw out of destructor + auto ret = GetApi().AllocatorFree(allocator_, p_); + static_cast(ret); + } +} + +inline MemoryAllocation::MemoryAllocation(MemoryAllocation&& o) noexcept : allocator_(nullptr), p_(nullptr), size_(0) { + *this = std::move(o); +} + +inline MemoryAllocation& MemoryAllocation::operator=(MemoryAllocation&& o) noexcept { + OrtAllocator* alloc = nullptr; + void* p = nullptr; + size_t sz = 0; + + // Swap out this + std::swap(alloc, allocator_); + std::swap(p, p_); + std::swap(sz, size_); + + // Swap with incoming + std::swap(allocator_, o.allocator_); + std::swap(p_, o.p_); + std::swap(size_, o.size_); + + // Destroy this instance if needed + MemoryAllocation this_alloc(alloc, p, sz); + return *this; +} + +namespace detail { + +template +inline void* AllocatorImpl::Alloc(size_t size) { + void* out; + ThrowOnError(GetApi().AllocatorAlloc(this->p_, size, &out)); + return out; +} + +template +inline MemoryAllocation AllocatorImpl::GetAllocation(size_t size) { + void* out; + ThrowOnError(GetApi().AllocatorAlloc(this->p_, size, &out)); + MemoryAllocation result(this->p_, out, size); + return result; +} + +template +inline void AllocatorImpl::Free(void* p) { + ThrowOnError(GetApi().AllocatorFree(this->p_, p)); +} + +template +inline ConstMemoryInfo AllocatorImpl::GetInfo() const { + const OrtMemoryInfo* out; + ThrowOnError(GetApi().AllocatorGetInfo(this->p_, &out)); + return ConstMemoryInfo{out}; +} + +template +inline KeyValuePairs AllocatorImpl::GetStats() const { + OrtKeyValuePairs* out; + ThrowOnError(GetApi().AllocatorGetStats(this->p_, &out)); + return KeyValuePairs(out); +} +} // namespace detail + +inline AllocatorWithDefaultOptions::AllocatorWithDefaultOptions() { + ThrowOnError(GetApi().GetAllocatorWithDefaultOptions(&this->p_)); +} + +inline Allocator::Allocator(const Session& sess, const OrtMemoryInfo* mem_info) { + ThrowOnError(GetApi().CreateAllocator(sess, mem_info, &this->p_)); +} + +namespace detail { + +template +inline std::string MemoryInfoImpl::GetAllocatorName() const { + const char* name = nullptr; + ThrowOnError(GetApi().MemoryInfoGetName(this->p_, &name)); + return std::string(name); +} + +template +inline OrtAllocatorType MemoryInfoImpl::GetAllocatorType() const { + OrtAllocatorType type; + ThrowOnError(GetApi().MemoryInfoGetType(this->p_, &type)); + return type; +} + +template +inline int MemoryInfoImpl::GetDeviceId() const { + int id = 0; + ThrowOnError(GetApi().MemoryInfoGetId(this->p_, &id)); + return id; +} + +template +inline OrtMemoryInfoDeviceType MemoryInfoImpl::GetDeviceType() const { + OrtMemoryInfoDeviceType type; + GetApi().MemoryInfoGetDeviceType(this->p_, &type); + return type; +} + +template +inline OrtMemType MemoryInfoImpl::GetMemoryType() const { + OrtMemType type; + ThrowOnError(GetApi().MemoryInfoGetMemType(this->p_, &type)); + return type; +} + +template +inline OrtDeviceMemoryType MemoryInfoImpl::GetDeviceMemoryType() const { + return GetApi().MemoryInfoGetDeviceMemType(this->p_); +} + +template +inline uint32_t MemoryInfoImpl::GetVendorId() const { + return GetApi().MemoryInfoGetVendorId(this->p_); +} + +template +template +inline bool MemoryInfoImpl::operator==(const MemoryInfoImpl& o) const { + int comp_result = 0; + ThrowOnError(Ort::GetApi().CompareMemoryInfo(this->p_, o, &comp_result)); + return comp_result == 0; +} + +} // namespace detail + +inline MemoryInfo MemoryInfo::CreateCpu(OrtAllocatorType type, OrtMemType mem_type) { + OrtMemoryInfo* p; + ThrowOnError(GetApi().CreateCpuMemoryInfo(type, mem_type, &p)); + return MemoryInfo(p); +} + +inline MemoryInfo::MemoryInfo(const char* name, OrtAllocatorType type, int id, OrtMemType mem_type) { + ThrowOnError(GetApi().CreateMemoryInfo(name, type, id, mem_type, &this->p_)); +} + +inline MemoryInfo::MemoryInfo(const char* name, OrtMemoryInfoDeviceType device_type, uint32_t vendor_id, uint32_t device_id, + OrtDeviceMemoryType mem_type, size_t alignment, OrtAllocatorType allocator_type) { + ThrowOnError(GetApi().CreateMemoryInfo_V2(name, device_type, vendor_id, device_id, mem_type, alignment, + allocator_type, &this->p_)); +} + +namespace detail { +template +inline std::vector ConstIoBindingImpl::GetOutputNames() const { + AllocatorWithDefaultOptions allocator; + return binding_utils::GetOutputNamesHelper(this->p_, allocator); +} + +template +inline std::vector ConstIoBindingImpl::GetOutputNames(OrtAllocator* allocator) const { + return binding_utils::GetOutputNamesHelper(this->p_, allocator); +} + +template +inline std::vector ConstIoBindingImpl::GetOutputValues() const { + AllocatorWithDefaultOptions allocator; + return binding_utils::GetOutputValuesHelper(this->p_, allocator); +} + +template +inline std::vector ConstIoBindingImpl::GetOutputValues(OrtAllocator* allocator) const { + return binding_utils::GetOutputValuesHelper(this->p_, allocator); +} + +template +inline void IoBindingImpl::BindInput(const char* name, const Value& value) { + ThrowOnError(GetApi().BindInput(this->p_, name, value)); +} + +template +inline void IoBindingImpl::BindOutput(const char* name, const Value& value) { + ThrowOnError(GetApi().BindOutput(this->p_, name, value)); +} + +template +inline void IoBindingImpl::BindOutput(const char* name, const OrtMemoryInfo* mem_info) { + ThrowOnError(GetApi().BindOutputToDevice(this->p_, name, mem_info)); +} + +template +inline void IoBindingImpl::ClearBoundInputs() { + GetApi().ClearBoundInputs(this->p_); +} + +template +inline void IoBindingImpl::ClearBoundOutputs() { + GetApi().ClearBoundOutputs(this->p_); +} + +template +inline void IoBindingImpl::SynchronizeInputs() { + ThrowOnError(GetApi().SynchronizeBoundInputs(this->p_)); +} + +template +inline void IoBindingImpl::SynchronizeOutputs() { + ThrowOnError(GetApi().SynchronizeBoundOutputs(this->p_)); +} + +namespace binding_utils { +inline std::vector GetOutputNamesHelper(const OrtIoBinding* binding, OrtAllocator* allocator) { + std::vector result; + auto free_fn = detail::AllocatedFree(allocator); + using Ptr = std::unique_ptr; + + char* buffer = nullptr; + size_t* lengths = nullptr; + size_t count = 0; + ThrowOnError(GetApi().GetBoundOutputNames(binding, allocator, &buffer, &lengths, &count)); + + if (count == 0) { + return result; + } + + Ptr buffer_g(buffer, free_fn); + Ptr lengths_g(lengths, free_fn); + + result.reserve(count); + for (size_t i = 0; i < count; ++i) { + auto sz = *lengths; + result.emplace_back(buffer, sz); + buffer += sz; + ++lengths; + } + return result; +} + +inline std::vector GetOutputValuesHelper(const OrtIoBinding* binding, OrtAllocator* allocator) { + std::vector result; + size_t output_count = 0; + + OrtValue** output_buffer = nullptr; + ThrowOnError(GetApi().GetBoundOutputValues(binding, allocator, &output_buffer, &output_count)); + if (output_count == 0) { + return result; + } + + std::unique_ptr buffer_g(output_buffer, AllocatedFree(allocator)); + + result.reserve(output_count); + for (size_t i = 0; i < output_count; ++i) { + result.emplace_back(output_buffer[i]); + } + return result; +} + +} // namespace binding_utils +} // namespace detail + +inline IoBinding::IoBinding(Session& session) { + ThrowOnError(GetApi().CreateIoBinding(session, &this->p_)); +} + +inline ArenaCfg::ArenaCfg(size_t max_mem, int arena_extend_strategy, int initial_chunk_size_bytes, int max_dead_bytes_per_chunk) { + ThrowOnError(GetApi().CreateArenaCfg(max_mem, arena_extend_strategy, initial_chunk_size_bytes, max_dead_bytes_per_chunk, &p_)); +} + +inline ArenaCfg::ArenaCfg(const std::unordered_map& arena_config) { + std::vector keys; + std::vector values; + keys.reserve(arena_config.size()); + values.reserve(arena_config.size()); + for (const auto& kv : arena_config) { + keys.push_back(kv.first.c_str()); + values.push_back(kv.second); + } + ThrowOnError(GetApi().CreateArenaCfgV2(keys.data(), values.data(), arena_config.size(), &p_)); +} + +inline ThreadingOptions::ThreadingOptions() { + ThrowOnError(GetApi().CreateThreadingOptions(&p_)); +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalIntraOpNumThreads(int intra_op_num_threads) { + ThrowOnError(GetApi().SetGlobalIntraOpNumThreads(p_, intra_op_num_threads)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalInterOpNumThreads(int inter_op_num_threads) { + ThrowOnError(GetApi().SetGlobalInterOpNumThreads(p_, inter_op_num_threads)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalSpinControl(int allow_spinning) { + ThrowOnError(GetApi().SetGlobalSpinControl(p_, allow_spinning)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalDenormalAsZero() { + ThrowOnError(GetApi().SetGlobalDenormalAsZero(p_)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn) { + ThrowOnError(GetApi().SetGlobalCustomCreateThreadFn(p_, ort_custom_create_thread_fn)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalCustomThreadCreationOptions(void* ort_custom_thread_creation_options) { + ThrowOnError(GetApi().SetGlobalCustomThreadCreationOptions(p_, ort_custom_thread_creation_options)); + return *this; +} + +inline ThreadingOptions& ThreadingOptions::SetGlobalCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn) { + ThrowOnError(GetApi().SetGlobalCustomJoinThreadFn(p_, ort_custom_join_thread_fn)); + return *this; +} + +inline TensorRTProviderOptions::TensorRTProviderOptions() { + ThrowOnError(GetApi().CreateTensorRTProviderOptions(&this->p_)); +} + +inline void TensorRTProviderOptions::Update(const std::unordered_map& options) { + std::vector keys; + std::vector values; + keys.reserve(options.size()); + values.reserve(options.size()); + for (const auto& kv : options) { + keys.push_back(kv.first.c_str()); + values.push_back(kv.second.c_str()); + } + ThrowOnError(GetApi().UpdateTensorRTProviderOptions(p_, keys.data(), values.data(), options.size())); +} + +inline void TensorRTProviderOptions::UpdateWithValue(const char* key, void* value) { + ThrowOnError(GetApi().UpdateTensorRTProviderOptionsWithValue(p_, key, value)); +} + +inline void* TensorRTProviderOptions::GetOptionByName(const char* name) const { + void* value = nullptr; + ThrowOnError(GetApi().GetTensorRTProviderOptionsByName(p_, name, &value)); + return value; +} + +inline std::string TensorRTProviderOptions::GetTensorRTProviderOptionsAsString() const { + AllocatorWithDefaultOptions allocator; + char* options_str = nullptr; + ThrowOnError(GetApi().GetTensorRTProviderOptionsAsString(p_, allocator, &options_str)); + std::unique_ptr options_str_g(options_str, detail::AllocatedFree(allocator)); + return std::string(options_str); +} + +inline CUDAProviderOptions::CUDAProviderOptions() { + ThrowOnError(GetApi().CreateCUDAProviderOptions(&this->p_)); +} + +inline void CUDAProviderOptions::Update(const std::unordered_map& options) { + std::vector keys; + std::vector values; + keys.reserve(options.size()); + values.reserve(options.size()); + for (const auto& kv : options) { + keys.push_back(kv.first.c_str()); + values.push_back(kv.second.c_str()); + } + ThrowOnError(GetApi().UpdateCUDAProviderOptions(p_, keys.data(), values.data(), options.size())); +} + +inline std::string CUDAProviderOptions::GetCUDAProviderOptionsAsString() const { + AllocatorWithDefaultOptions allocator; + char* options_str = nullptr; + ThrowOnError(GetApi().GetCUDAProviderOptionsAsString(p_, allocator, &options_str)); + std::unique_ptr options_str_g(options_str, detail::AllocatedFree(allocator)); + return std::string(options_str); +} + +inline void CUDAProviderOptions::UpdateWithValue(const char* key, void* value) { + ThrowOnError(GetApi().UpdateCUDAProviderOptionsWithValue(p_, key, value)); +} + +inline void* CUDAProviderOptions::GetOptionByName(const char* name) const { + void* value = nullptr; + ThrowOnError(GetApi().GetCUDAProviderOptionsByName(p_, name, &value)); + return value; +} + +inline PrepackedWeightsContainer::PrepackedWeightsContainer() { + ThrowOnError(GetApi().CreatePrepackedWeightsContainer(&this->p_)); +} + +namespace detail { + +template +inline const std::basic_string ConstExternalInitializerInfoImpl::GetFilePath() const { + return GetApi().ExternalInitializerInfo_GetFilePath(this->p_); +} + +template +inline int64_t ConstExternalInitializerInfoImpl::GetFileOffset() const { + return GetApi().ExternalInitializerInfo_GetFileOffset(this->p_); +} + +template +inline size_t ConstExternalInitializerInfoImpl::GetByteSize() const { + return GetApi().ExternalInitializerInfo_GetByteSize(this->p_); +} +} // namespace detail + +inline ExternalInitializerInfo::ExternalInitializerInfo(const ORTCHAR_T* filepath, int64_t file_offset, + size_t byte_size) { + ThrowOnError(GetApi().CreateExternalInitializerInfo(filepath, file_offset, byte_size, &this->p_)); +} + +inline Status ExternalInitializerInfo::Create(const ORTCHAR_T* filepath, int64_t file_offset, size_t byte_size, + /*out*/ ExternalInitializerInfo& out) { + OrtExternalInitializerInfo* info = nullptr; + OrtStatus* status = GetApi().CreateExternalInitializerInfo(filepath, file_offset, byte_size, &info); + if (status != nullptr) { + return Status{status}; + } + + out = ExternalInitializerInfo(info); + + return Status{nullptr}; +} + +namespace detail { +template +inline const char* KeyValuePairsImpl::GetValue(const char* key) const { + return GetApi().GetKeyValue(this->p_, key); +} + +template +inline std::unordered_map KeyValuePairsImpl::GetKeyValuePairs() const { + std::unordered_map out; + + size_t num_pairs = 0; + const char* const* keys = nullptr; + const char* const* values = nullptr; + GetApi().GetKeyValuePairs(this->p_, &keys, &values, &num_pairs); + if (num_pairs > 0) { + out.reserve(num_pairs); + for (size_t i = 0; i < num_pairs; ++i) { + out.emplace(keys[i], values[i]); + } + } + + return out; +} + +template +inline void KeyValuePairsImpl::GetKeyValuePairs(std::vector& keys, + std::vector& values) const { + keys.clear(); + values.clear(); + + size_t num_pairs = 0; + const char* const* keys_ptr = nullptr; + const char* const* values_ptr = nullptr; + GetApi().GetKeyValuePairs(this->p_, &keys_ptr, &values_ptr, &num_pairs); + if (num_pairs > 0) { + keys.resize(num_pairs); + values.resize(num_pairs); + std::copy(keys_ptr, keys_ptr + num_pairs, keys.begin()); + std::copy(values_ptr, values_ptr + num_pairs, values.begin()); + } +} +} // namespace detail + +inline KeyValuePairs::KeyValuePairs() { + GetApi().CreateKeyValuePairs(&p_); +} + +inline KeyValuePairs::KeyValuePairs(const std::unordered_map& kv_pairs) { + GetApi().CreateKeyValuePairs(&p_); + for (const auto& kv : kv_pairs) { + GetApi().AddKeyValuePair(this->p_, kv.first.c_str(), kv.second.c_str()); + } +} + +inline void KeyValuePairs::Add(const char* key, const char* value) { + GetApi().AddKeyValuePair(this->p_, key, value); +} + +inline void KeyValuePairs::Remove(const char* key) { + GetApi().RemoveKeyValuePair(this->p_, key); +} + +namespace detail { +template +inline void* SyncStreamImpl::GetHandle() { + return GetApi().SyncStream_GetHandle(this->p_); +} +} // namespace detail + +namespace detail { +template +inline OrtHardwareDeviceType HardwareDeviceImpl::Type() const { + return GetApi().HardwareDevice_Type(this->p_); +} + +template +inline uint32_t HardwareDeviceImpl::VendorId() const { + return GetApi().HardwareDevice_VendorId(this->p_); +} + +template +inline uint32_t HardwareDeviceImpl::DeviceId() const { + return GetApi().HardwareDevice_DeviceId(this->p_); +} + +template +inline const char* HardwareDeviceImpl::Vendor() const { + return GetApi().HardwareDevice_Vendor(this->p_); +} + +template +inline ConstKeyValuePairs HardwareDeviceImpl::Metadata() const { + return ConstKeyValuePairs{GetApi().HardwareDevice_Metadata(this->p_)}; +} + +template +inline const char* EpDeviceImpl::EpName() const { + return GetApi().EpDevice_EpName(this->p_); +} + +template +inline const char* EpDeviceImpl::EpVendor() const { + return GetApi().EpDevice_EpVendor(this->p_); +} + +template +inline ConstKeyValuePairs EpDeviceImpl::EpMetadata() const { + return ConstKeyValuePairs(GetApi().EpDevice_EpMetadata(this->p_)); +} + +template +inline ConstKeyValuePairs EpDeviceImpl::EpOptions() const { + return ConstKeyValuePairs(GetApi().EpDevice_EpOptions(this->p_)); +} + +template +inline ConstHardwareDevice EpDeviceImpl::Device() const { + return ConstHardwareDevice(GetApi().EpDevice_Device(this->p_)); +} + +template +inline ConstMemoryInfo EpDeviceImpl::GetMemoryInfo(OrtDeviceMemoryType memory_type) const { + const auto* mem_info = GetApi().EpDevice_MemoryInfo(this->p_, memory_type); + return ConstMemoryInfo{mem_info}; +} + +template +inline SyncStream EpDeviceImpl::CreateSyncStream(ConstKeyValuePairs stream_options) const { + OrtSyncStream* stream = nullptr; + ThrowOnError(GetApi().CreateSyncStreamForEpDevice(this->p_, stream_options, &stream)); + return SyncStream{stream}; +} +} // namespace detail + +inline EpDevice::EpDevice(OrtEpFactory& ep_factory, ConstHardwareDevice& hardware_device, + ConstKeyValuePairs ep_metadata, ConstKeyValuePairs ep_options) { + ThrowOnError(GetEpApi().CreateEpDevice(&ep_factory, hardware_device, ep_metadata, ep_options, &p_)); +} + +inline Env::Env(OrtLoggingLevel logging_level, _In_ const char* logid) { + ThrowOnError(GetApi().CreateEnv(logging_level, logid, &p_)); + if (strcmp(logid, "onnxruntime-node") == 0) { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_NODEJS)); + } else { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_CPLUSPLUS)); + } +} + +inline Env::Env(OrtLoggingLevel logging_level, const char* logid, OrtLoggingFunction logging_function, void* logger_param) { + ThrowOnError(GetApi().CreateEnvWithCustomLogger(logging_function, logger_param, logging_level, logid, &p_)); + if (strcmp(logid, "onnxruntime-node") == 0) { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_NODEJS)); + } else { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_CPLUSPLUS)); + } +} + +inline Env::Env(const OrtThreadingOptions* tp_options, OrtLoggingLevel logging_level, _In_ const char* logid) { + ThrowOnError(GetApi().CreateEnvWithGlobalThreadPools(logging_level, logid, tp_options, &p_)); + if (strcmp(logid, "onnxruntime-node") == 0) { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_NODEJS)); + } else { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_CPLUSPLUS)); + } +} + +inline Env::Env(const OrtThreadingOptions* tp_options, OrtLoggingFunction logging_function, void* logger_param, + OrtLoggingLevel logging_level, _In_ const char* logid) { + ThrowOnError(GetApi().CreateEnvWithCustomLoggerAndGlobalThreadPools(logging_function, logger_param, logging_level, logid, tp_options, &p_)); + if (strcmp(logid, "onnxruntime-node") == 0) { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_NODEJS)); + } else { + ThrowOnError(GetApi().SetLanguageProjection(p_, OrtLanguageProjection::ORT_PROJECTION_CPLUSPLUS)); + } +} + +inline Env& Env::EnableTelemetryEvents() { + ThrowOnError(GetApi().EnableTelemetryEvents(p_)); + return *this; +} + +inline Env& Env::DisableTelemetryEvents() { + ThrowOnError(GetApi().DisableTelemetryEvents(p_)); + return *this; +} + +inline Env& Env::UpdateEnvWithCustomLogLevel(OrtLoggingLevel log_severity_level) { + ThrowOnError(GetApi().UpdateEnvWithCustomLogLevel(p_, log_severity_level)); + return *this; +} + +inline Env& Env::CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg) { + ThrowOnError(GetApi().CreateAndRegisterAllocator(p_, mem_info, arena_cfg)); + return *this; +} + +inline Env& Env::CreateAndRegisterAllocatorV2(const std::string& provider_type, const OrtMemoryInfo* mem_info, const std::unordered_map& options, const OrtArenaCfg* arena_cfg) { + std::vector keys, values; + auto num_entries = options.size(); + if (num_entries > 0) { + keys.reserve(num_entries); + values.reserve(num_entries); + for (const auto& entry : options) { + keys.push_back(entry.first.c_str()); + values.push_back(entry.second.c_str()); + } + } + ThrowOnError(GetApi().CreateAndRegisterAllocatorV2(p_, provider_type.c_str(), mem_info, arena_cfg, keys.data(), values.data(), num_entries)); + return *this; +} + +inline Env& Env::RegisterAllocator(OrtAllocator* allocator) { + ThrowOnError(GetApi().RegisterAllocator(p_, allocator)); + return *this; +} + +inline Env& Env::UnregisterAllocator(const OrtMemoryInfo* mem_info) { + ThrowOnError(GetApi().UnregisterAllocator(p_, mem_info)); + return *this; +} + +inline Env& Env::RegisterExecutionProviderLibrary(const char* registration_name, + const std::basic_string& path) { + ThrowOnError(GetApi().RegisterExecutionProviderLibrary(p_, registration_name, path.c_str())); + return *this; +} + +inline Env& Env::UnregisterExecutionProviderLibrary(const char* registration_name) { + ThrowOnError(GetApi().UnregisterExecutionProviderLibrary(p_, registration_name)); + return *this; +} + +inline std::vector Env::GetEpDevices() const { + size_t num_devices = 0; + const OrtEpDevice* const* device_ptrs = nullptr; + ThrowOnError(GetApi().GetEpDevices(p_, &device_ptrs, &num_devices)); + + std::vector devices; + if (num_devices > 0) { + devices.reserve(num_devices); + for (size_t i = 0; i < num_devices; ++i) { + devices.emplace_back(device_ptrs[i]); + } + } + + return devices; +} + +inline Status Env::CopyTensors(const std::vector& src_tensors, + const std::vector& dst_tensors, + OrtSyncStream* stream) const { + if (src_tensors.size() != dst_tensors.size()) { + return Status("Source and destination tensor vectors must have the same size", ORT_INVALID_ARGUMENT); + } + if (src_tensors.empty()) { + return Status(nullptr); + } + + const OrtValue* const* src_tensors_ptr = reinterpret_cast(src_tensors.data()); + OrtValue* const* dst_tensors_ptr = reinterpret_cast(dst_tensors.data()); + OrtStatus* status = GetApi().CopyTensors(p_, src_tensors_ptr, dst_tensors_ptr, stream, src_tensors.size()); + return Status(status); +} + +inline UnownedAllocator Env::CreateSharedAllocator(const OrtEpDevice* ep_device, OrtDeviceMemoryType mem_type, + OrtAllocatorType allocator_type, + const OrtKeyValuePairs* allocator_options) { + OrtAllocator* p; + ThrowOnError(GetApi().CreateSharedAllocator(p_, ep_device, mem_type, allocator_type, allocator_options, &p)); + return UnownedAllocator{p}; +} + +inline UnownedAllocator Env::GetSharedAllocator(const OrtMemoryInfo* mem_info) { + OrtAllocator* p; + ThrowOnError(GetApi().GetSharedAllocator(p_, mem_info, &p)); + return UnownedAllocator{p}; +} + +inline void Env::ReleaseSharedAllocator(const OrtEpDevice* ep_device, + OrtDeviceMemoryType mem_type) { + ThrowOnError(GetApi().ReleaseSharedAllocator(p_, ep_device, mem_type)); +} + +inline CustomOpDomain::CustomOpDomain(const char* domain) { + ThrowOnError(GetApi().CreateCustomOpDomain(domain, &p_)); +} + +inline void CustomOpDomain::Add(const OrtCustomOp* op) { + ThrowOnError(GetApi().CustomOpDomain_Add(p_, op)); +} + +inline OrtCompiledModelCompatibility GetModelCompatibilityForEpDevices( + const std::vector& ep_devices, + const char* compatibility_info) { + if (ep_devices.empty()) { + ORT_CXX_API_THROW("ep_devices is empty", ORT_INVALID_ARGUMENT); + } + + std::vector ptrs; + ptrs.reserve(ep_devices.size()); + for (const auto& d : ep_devices) ptrs.push_back(d); + + OrtCompiledModelCompatibility status = OrtCompiledModelCompatibility_EP_NOT_APPLICABLE; + ThrowOnError(GetApi().GetModelCompatibilityForEpDevices( + reinterpret_cast(ptrs.data()), + ptrs.size(), + compatibility_info, + &status)); + return status; +} + +inline LoraAdapter LoraAdapter::CreateLoraAdapter(const std::basic_string& adapter_path, + OrtAllocator* allocator) { + OrtLoraAdapter* p; + ThrowOnError(GetApi().CreateLoraAdapter(adapter_path.c_str(), allocator, &p)); + return LoraAdapter{p}; +} + +inline LoraAdapter LoraAdapter::CreateLoraAdapterFromArray(const void* bytes, size_t num_bytes, + OrtAllocator* allocator) { + OrtLoraAdapter* p; + ThrowOnError(GetApi().CreateLoraAdapterFromArray(bytes, num_bytes, allocator, &p)); + return LoraAdapter{p}; +} + +inline RunOptions::RunOptions() { + ThrowOnError(GetApi().CreateRunOptions(&p_)); +} + +inline RunOptions& RunOptions::SetRunLogVerbosityLevel(int level) { + ThrowOnError(GetApi().RunOptionsSetRunLogVerbosityLevel(p_, level)); + return *this; +} + +inline RunOptions& RunOptions::SetRunLogSeverityLevel(int level) { + ThrowOnError(GetApi().RunOptionsSetRunLogSeverityLevel(p_, level)); + return *this; +} + +inline int RunOptions::GetRunLogVerbosityLevel() const { + int out; + ThrowOnError(GetApi().RunOptionsGetRunLogVerbosityLevel(p_, &out)); + return out; +} + +inline int RunOptions::GetRunLogSeverityLevel() const { + int out; + ThrowOnError(GetApi().RunOptionsGetRunLogSeverityLevel(p_, &out)); + return out; +} + +inline RunOptions& RunOptions::SetRunTag(const char* run_tag) { + ThrowOnError(GetApi().RunOptionsSetRunTag(p_, run_tag)); + return *this; +} + +inline const char* RunOptions::GetRunTag() const { + const char* out; + ThrowOnError(GetApi().RunOptionsGetRunTag(p_, &out)); + return out; +} + +inline RunOptions& RunOptions::AddConfigEntry(const char* config_key, const char* config_value) { + ThrowOnError(GetApi().AddRunConfigEntry(p_, config_key, config_value)); + return *this; +} + +inline const char* RunOptions::GetConfigEntry(const char* config_key) { + return GetApi().GetRunConfigEntry(p_, config_key); +} + +inline RunOptions& RunOptions::SetTerminate() { + ThrowOnError(GetApi().RunOptionsSetTerminate(p_)); + return *this; +} + +inline RunOptions& RunOptions::UnsetTerminate() { + ThrowOnError(GetApi().RunOptionsUnsetTerminate(p_)); + return *this; +} + +inline RunOptions& RunOptions::AddActiveLoraAdapter(const LoraAdapter& adapter) { + ThrowOnError(GetApi().RunOptionsAddActiveLoraAdapter(p_, adapter)); + return *this; +} + +inline ModelCompilationOptions::ModelCompilationOptions(const Env& env, const SessionOptions& session_options) { + ThrowOnError(GetCompileApi().CreateModelCompilationOptionsFromSessionOptions(env, session_options, &this->p_)); +} + +inline ModelCompilationOptions::ModelCompilationOptions(const Env& env, ConstSessionOptions session_options) { + ThrowOnError(GetCompileApi().CreateModelCompilationOptionsFromSessionOptions(env, session_options, &this->p_)); +} + +inline Status CompileModel(const Env& env, const ModelCompilationOptions& model_compilation_options) { + return Ort::Status(GetCompileApi().CompileModel(env, model_compilation_options)); +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetInputModelPath( + const ORTCHAR_T* input_model_path) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetInputModelPath(this->p_, input_model_path)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetInputModelFromBuffer( + const void* input_model_data, size_t input_model_data_size) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetInputModelFromBuffer(this->p_, input_model_data, + input_model_data_size)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetOutputModelPath( + const ORTCHAR_T* output_model_path) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetOutputModelPath(this->p_, output_model_path)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetEpContextBinaryInformation( + const ORTCHAR_T* output_directory, const ORTCHAR_T* model_name) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetEpContextBinaryInformation( + this->p_, + output_directory, + model_name)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetOutputModelExternalInitializersFile( + const ORTCHAR_T* file_path, size_t initializer_size_threshold) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetOutputModelExternalInitializersFile( + this->p_, + file_path, + initializer_size_threshold)); + return *this; +} + +inline ModelCompilationOptions& +ModelCompilationOptions::SetOutputModelGetInitializerLocationFunc( + OrtGetInitializerLocationFunc get_initializer_location_func, void* state) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetOutputModelGetInitializerLocationFunc( + this->p_, + get_initializer_location_func, + state)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetOutputModelBuffer( + OrtAllocator* allocator, void** output_model_buffer_ptr, size_t* output_model_buffer_size_ptr) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetOutputModelBuffer(this->p_, allocator, + output_model_buffer_ptr, + output_model_buffer_size_ptr)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetOutputModelWriteFunc(OrtWriteBufferFunc write_func, + void* state) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetOutputModelWriteFunc(this->p_, write_func, state)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetEpContextEmbedMode( + bool embed_ep_context_in_model) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetEpContextEmbedMode( + this->p_, + embed_ep_context_in_model)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetFlags(uint32_t flags) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetFlags(this->p_, flags)); + return *this; +} + +inline ModelCompilationOptions& ModelCompilationOptions::SetGraphOptimizationLevel( + GraphOptimizationLevel graph_optimization_level) { + Ort::ThrowOnError(GetCompileApi().ModelCompilationOptions_SetGraphOptimizationLevel(this->p_, + graph_optimization_level)); + return *this; +} + +namespace detail { + +template +inline Ort::SessionOptions ConstSessionOptionsImpl::Clone() const { + OrtSessionOptions* out; + ThrowOnError(GetApi().CloneSessionOptions(this->p_, &out)); + return SessionOptions{out}; +} + +template +inline std::string ConstSessionOptionsImpl::GetConfigEntry(const char* config_key) const { + size_t size = 0; + // Feed nullptr for the data buffer to query the true size of the string value + Ort::ThrowOnError(GetApi().GetSessionConfigEntry(this->p_, config_key, nullptr, &size)); + + std::string out; + out.resize(size); + Ort::ThrowOnError(GetApi().GetSessionConfigEntry(this->p_, config_key, &out[0], &size)); + out.resize(size - 1); // remove the terminating character '\0' + + return out; +} + +template +inline bool ConstSessionOptionsImpl::HasConfigEntry(const char* config_key) const { + int out = 0; + Ort::ThrowOnError(GetApi().HasSessionConfigEntry(this->p_, config_key, &out)); + return static_cast(out); +} + +template +inline std::string ConstSessionOptionsImpl::GetConfigEntryOrDefault(const char* config_key, + const std::string& def) const { + if (!this->HasConfigEntry(config_key)) { + return def; + } + + return this->GetConfigEntry(config_key); +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetIntraOpNumThreads(int intra_op_num_threads) { + ThrowOnError(GetApi().SetIntraOpNumThreads(this->p_, intra_op_num_threads)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetInterOpNumThreads(int inter_op_num_threads) { + ThrowOnError(GetApi().SetInterOpNumThreads(this->p_, inter_op_num_threads)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level) { + ThrowOnError(GetApi().SetSessionGraphOptimizationLevel(this->p_, graph_optimization_level)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetDeterministicCompute(bool value) { + ThrowOnError(GetApi().SetDeterministicCompute(this->p_, value)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_filepath) { + ThrowOnError(GetApi().SetOptimizedModelFilePath(this->p_, optimized_model_filepath)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::EnableProfiling(const ORTCHAR_T* profile_file_prefix) { + ThrowOnError(GetApi().EnableProfiling(this->p_, profile_file_prefix)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::DisableProfiling() { + ThrowOnError(GetApi().DisableProfiling(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::EnableOrtCustomOps() { + ThrowOnError(GetApi().EnableOrtCustomOps(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::EnableMemPattern() { + ThrowOnError(GetApi().EnableMemPattern(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::DisableMemPattern() { + ThrowOnError(GetApi().DisableMemPattern(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::EnableCpuMemArena() { + ThrowOnError(GetApi().EnableCpuMemArena(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::DisableCpuMemArena() { + ThrowOnError(GetApi().DisableCpuMemArena(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetExecutionMode(ExecutionMode execution_mode) { + ThrowOnError(GetApi().SetSessionExecutionMode(this->p_, execution_mode)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetLoadCancellationFlag(bool value) { + ThrowOnError(GetApi().SessionOptionsSetLoadCancellationFlag(this->p_, value)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetLogId(const char* logid) { + ThrowOnError(GetApi().SetSessionLogId(this->p_, logid)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetLogSeverityLevel(int level) { + ThrowOnError(GetApi().SetSessionLogSeverityLevel(this->p_, level)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::Add(OrtCustomOpDomain* custom_op_domain) { + ThrowOnError(GetApi().AddCustomOpDomain(this->p_, custom_op_domain)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AddConfigEntry(const char* config_key, const char* config_value) { + ThrowOnError(GetApi().AddSessionConfigEntry(this->p_, config_key, config_value)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AddInitializer(const char* name, const OrtValue* ort_val) { + ThrowOnError(GetApi().AddInitializer(this->p_, name, ort_val)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::DisablePerSessionThreads() { + ThrowOnError(GetApi().DisablePerSessionThreads(this->p_)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AddExternalInitializers(const std::vector& names, + const std::vector& ort_values) { + const size_t inputs_num = names.size(); + if (inputs_num != ort_values.size()) { + ORT_CXX_API_THROW("Expecting names and ort_values to have the same length", ORT_INVALID_ARGUMENT); + } + std::vector names_ptr; + std::vector ort_values_ptrs; + names_ptr.reserve(inputs_num); + ort_values_ptrs.reserve(inputs_num); + for (size_t i = 0; i < inputs_num; ++i) { + names_ptr.push_back(names[i].c_str()); + ort_values_ptrs.push_back(ort_values[i]); + } + ThrowOnError(GetApi().AddExternalInitializers(this->p_, names_ptr.data(), ort_values_ptrs.data(), inputs_num)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AddExternalInitializersFromFilesInMemory(const std::vector>& file_names, + const std::vector& buffer_array, + const std::vector& file_lengths) { + const size_t inputs_num = file_names.size(); + if (inputs_num != buffer_array.size()) { + ORT_CXX_API_THROW("Expecting names and buffer_array to have the same length", ORT_INVALID_ARGUMENT); + } + if (inputs_num != file_lengths.size()) { + ORT_CXX_API_THROW("Expecting names and file_lengths to have the same length", ORT_INVALID_ARGUMENT); + } + std::vector names_ptr; + names_ptr.reserve(inputs_num); + for (size_t i = 0; i < inputs_num; ++i) { + names_ptr.push_back(file_names[i].c_str()); + } + ThrowOnError(GetApi().AddExternalInitializersFromFilesInMemory(this->p_, names_ptr.data(), buffer_array.data(), + file_lengths.data(), inputs_num)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_CPU(int use_arena) { + ThrowOnError(OrtSessionOptionsAppendExecutionProvider_CPU(this->p_, use_arena)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_CUDA(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_CUDA_V2(const OrtCUDAProviderOptionsV2& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_CUDA_V2(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_ROCM(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_TensorRT(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_TensorRT_V2(const OrtTensorRTProviderOptionsV2& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_TensorRT_V2(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_MIGraphX(const OrtMIGraphXProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_MIGraphX(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_CANN(const OrtCANNProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_CANN(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_Dnnl(const OrtDnnlProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_Dnnl(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider( + const std::string& provider_name, + const std::unordered_map& provider_options) { + auto num_entries = provider_options.size(); + std::vector keys, values; + if (num_entries > 0) { + keys.reserve(num_entries); + values.reserve(num_entries); + + for (const auto& entry : provider_options) { + keys.push_back(entry.first.c_str()); + values.push_back(entry.second.c_str()); + } + } + + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider(this->p_, provider_name.c_str(), + keys.data(), values.data(), num_entries)); + + return *this; +} + +namespace { +template +void SessionOptionsAppendEP(detail::SessionOptionsImpl& session_options, + Env& env, const std::vector& ep_devices, + const std::vector& ep_options_keys, + const std::vector& ep_options_values) { + std::vector ep_devices_ptrs; + ep_devices_ptrs.reserve(ep_devices.size()); + for (const auto& ep_device : ep_devices) { + ep_devices_ptrs.push_back(ep_device); + } + + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_V2( + session_options, env, ep_devices_ptrs.data(), ep_devices_ptrs.size(), + ep_options_keys.data(), ep_options_values.data(), ep_options_keys.size())); +} +} // namespace + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_V2( + Env& env, const std::vector& ep_devices, const KeyValuePairs& ep_options) { + std::vector ep_options_keys, ep_options_values; + ep_options.GetKeyValuePairs(ep_options_keys, ep_options_values); + + SessionOptionsAppendEP(*this, env, ep_devices, ep_options_keys, ep_options_values); + + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_V2( + Env& env, const std::vector& ep_devices, + const std::unordered_map& ep_options) { + std::vector ep_options_keys, ep_options_values; + ep_options_keys.reserve(ep_options.size()); + ep_options_values.reserve(ep_options.size()); + + for (const auto& [key, value] : ep_options) { + ep_options_keys.push_back(key.c_str()); + ep_options_values.push_back(value.c_str()); + } + + SessionOptionsAppendEP(*this, env, ep_devices, ep_options_keys, ep_options_values); + + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetEpSelectionPolicy(OrtExecutionProviderDevicePolicy policy) { + ThrowOnError(GetApi().SessionOptionsSetEpSelectionPolicy(this->p_, policy)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetEpSelectionPolicy(EpSelectionDelegate delegate, void* state) { + ThrowOnError(GetApi().SessionOptionsSetEpSelectionPolicyDelegate(this->p_, delegate, state)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn) { + ThrowOnError(GetApi().SessionOptionsSetCustomCreateThreadFn(this->p_, ort_custom_create_thread_fn)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetCustomThreadCreationOptions(void* ort_custom_thread_creation_options) { + ThrowOnError(GetApi().SessionOptionsSetCustomThreadCreationOptions(this->p_, ort_custom_thread_creation_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::SetCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn) { + ThrowOnError(GetApi().SessionOptionsSetCustomJoinThreadFn(this->p_, ort_custom_join_thread_fn)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options) { + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_OpenVINO(this->p_, &provider_options)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_OpenVINO_V2(const std::unordered_map& provider_options) { + auto num_entries = provider_options.size(); + std::vector keys, values; + if (num_entries > 0) { + keys.reserve(num_entries); + values.reserve(num_entries); + + for (const auto& entry : provider_options) { + keys.push_back(entry.first.c_str()); + values.push_back(entry.second.c_str()); + } + } + + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_OpenVINO_V2(this->p_, + keys.data(), values.data(), num_entries)); + + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::AppendExecutionProvider_VitisAI(const std::unordered_map& provider_options) { + auto num_entries = provider_options.size(); + std::vector keys, values; + if (num_entries > 0) { + keys.reserve(num_entries); + values.reserve(num_entries); + + for (const auto& entry : provider_options) { + keys.push_back(entry.first.c_str()); + values.push_back(entry.second.c_str()); + } + } + + ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_VitisAI(this->p_, keys.data(), values.data(), num_entries)); + + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::RegisterCustomOpsLibrary(const ORTCHAR_T* library_name, + const CustomOpConfigs& custom_op_configs) { + // Add custom op config entries before registering the custom op library. Otherwise, the config entries _may_ be ignored by + // the custom op library. + for (const auto& config_iter : custom_op_configs.GetFlattenedConfigs()) { + AddConfigEntry(config_iter.first.c_str(), config_iter.second.c_str()); + } + + ThrowOnError(GetApi().RegisterCustomOpsLibrary_V2(this->p_, library_name)); + return *this; +} + +template +inline SessionOptionsImpl& SessionOptionsImpl::RegisterCustomOpsUsingFunction(const char* registration_function_name) { + ThrowOnError(GetApi().RegisterCustomOpsUsingFunction(this->p_, registration_function_name)); + return *this; +} + +/// Session +template +inline size_t ConstSessionImpl::GetInputCount() const { + size_t out; + ThrowOnError(GetApi().SessionGetInputCount(this->p_, &out)); + return out; +} + +template +inline size_t ConstSessionImpl::GetOutputCount() const { + size_t out; + ThrowOnError(GetApi().SessionGetOutputCount(this->p_, &out)); + return out; +} + +template +inline size_t ConstSessionImpl::GetOverridableInitializerCount() const { + size_t out; + ThrowOnError(GetApi().SessionGetOverridableInitializerCount(this->p_, &out)); + return out; +} + +template +inline std::vector ConstSessionImpl::GetInputNames() const { + AllocatorWithDefaultOptions allocator; + + auto num_inputs = GetInputCount(); + std::vector input_names; + input_names.reserve(num_inputs); + + for (size_t i = 0; i < num_inputs; ++i) { + char* name; + ThrowOnError(GetApi().SessionGetInputName(this->p_, i, allocator, &name)); + input_names.emplace_back(name); + allocator.Free(name); + } + + return input_names; +} + +template +inline std::vector ConstSessionImpl::GetOutputNames() const { + AllocatorWithDefaultOptions allocator; + + auto num_inputs = GetOutputCount(); + std::vector output_names; + output_names.reserve(num_inputs); + + for (size_t i = 0; i < num_inputs; ++i) { + char* name; + ThrowOnError(GetApi().SessionGetOutputName(this->p_, i, allocator, &name)); + output_names.emplace_back(name); + allocator.Free(name); + } + + return output_names; +} + +template +inline std::vector ConstSessionImpl::GetOverridableInitializerNames() const { + AllocatorWithDefaultOptions allocator; + + auto num_initializers = GetOverridableInitializerCount(); + std::vector initializer_names; + initializer_names.reserve(num_initializers); + + for (size_t i = 0; i < num_initializers; ++i) { + char* name; + ThrowOnError(GetApi().SessionGetOverridableInitializerName(this->p_, i, allocator, &name)); + initializer_names.emplace_back(name); + } + + return initializer_names; +} + +template +inline std::vector ConstSessionImpl::GetMemoryInfoForInputs() const { + static_assert(sizeof(ConstMemoryInfo) == sizeof(OrtMemoryInfo*), + "ConstMemoryInfo must be compatible with OrtMemoryInfo*"); + + auto num_inputs = GetInputCount(); + std::vector mem_infos; + if (num_inputs > 0) { + mem_infos.resize(num_inputs); + + ThrowOnError(GetApi().SessionGetMemoryInfoForInputs(this->p_, + reinterpret_cast(mem_infos.data()), + num_inputs)); + } + + return mem_infos; +} + +template +inline std::vector ConstSessionImpl::GetMemoryInfoForOutputs() const { + static_assert(sizeof(ConstMemoryInfo) == sizeof(OrtMemoryInfo*), + "ConstMemoryInfo must be compatible with OrtMemoryInfo*"); + + auto num_outputs = GetOutputCount(); + std::vector mem_infos; + if (num_outputs > 0) { + mem_infos.resize(num_outputs); + + ThrowOnError(GetApi().SessionGetMemoryInfoForOutputs(this->p_, + reinterpret_cast(mem_infos.data()), + num_outputs)); + } + return mem_infos; +} + +template +inline AllocatedStringPtr ConstSessionImpl::GetInputNameAllocated(size_t index, OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().SessionGetInputName(this->p_, index, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +template +inline AllocatedStringPtr ConstSessionImpl::GetOutputNameAllocated(size_t index, OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().SessionGetOutputName(this->p_, index, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +template +inline AllocatedStringPtr ConstSessionImpl::GetOverridableInitializerNameAllocated(size_t index, OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().SessionGetOverridableInitializerName(this->p_, index, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +template +inline std::vector ConstSessionImpl::GetEpDeviceForInputs() const { + auto num_inputs = GetInputCount(); + std::vector input_devices; + if (num_inputs > 0) { + input_devices.resize(num_inputs); + ThrowOnError(GetApi().SessionGetEpDeviceForInputs(this->p_, + reinterpret_cast(input_devices.data()), + num_inputs)); + } + return input_devices; +} + +template +inline uint64_t ConstSessionImpl::GetProfilingStartTimeNs() const { + uint64_t out; + ThrowOnError(GetApi().SessionGetProfilingStartTimeNs(this->p_, &out)); + return out; +} + +template +inline ModelMetadata ConstSessionImpl::GetModelMetadata() const { + OrtModelMetadata* out; + ThrowOnError(GetApi().SessionGetModelMetadata(this->p_, &out)); + return ModelMetadata{out}; +} + +template +inline TypeInfo ConstSessionImpl::GetInputTypeInfo(size_t index) const { + OrtTypeInfo* out; + ThrowOnError(GetApi().SessionGetInputTypeInfo(this->p_, index, &out)); + return TypeInfo{out}; +} + +template +inline TypeInfo ConstSessionImpl::GetOutputTypeInfo(size_t index) const { + OrtTypeInfo* out; + ThrowOnError(GetApi().SessionGetOutputTypeInfo(this->p_, index, &out)); + return TypeInfo{out}; +} + +template +inline TypeInfo ConstSessionImpl::GetOverridableInitializerTypeInfo(size_t index) const { + OrtTypeInfo* out; + ThrowOnError(GetApi().SessionGetOverridableInitializerTypeInfo(this->p_, index, &out)); + return TypeInfo{out}; +} + +#if !defined(ORT_MINIMAL_BUILD) +template +inline int ConstSessionImpl::GetOpset(const std::string& domain) const { + int opset; + ThrowOnError(GetModelEditorApi().SessionGetOpsetForDomain(this->p_, domain.c_str(), &opset)); + return opset; +} +#endif // !defined(ORT_MINIMAL_BUILD) + +template +std::vector ConstSessionImpl::GetInputs() const { + const std::vector input_names = GetInputNames(); + + std::vector inputs; + inputs.reserve(input_names.size()); + + for (size_t i = 0; i < input_names.size(); ++i) { + auto type_info = GetInputTypeInfo(i); + inputs.emplace_back(ValueInfo{input_names[i], type_info.GetConst()}); + } + + return inputs; +} + +template +std::vector ConstSessionImpl::GetOutputs() const { + const std::vector output_names = GetOutputNames(); + + std::vector outputs; + outputs.reserve(output_names.size()); + + for (size_t i = 0; i < output_names.size(); ++i) { + auto type_info = GetOutputTypeInfo(i); + outputs.emplace_back(ValueInfo{output_names[i], type_info.GetConst()}); + } + + return outputs; +} + +template +inline std::vector SessionImpl::Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, size_t output_count) { + std::vector output_values; + output_values.reserve(output_count); + for (size_t i = 0; i < output_count; i++) + output_values.emplace_back(nullptr); + Run(run_options, input_names, input_values, input_count, output_names, output_values.data(), output_count); + return output_values; +} + +template +inline void SessionImpl::Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, Value* output_values, size_t output_count) { + static_assert(sizeof(Value) == sizeof(OrtValue*), "Value is really just an array of OrtValue* in memory, so we can reinterpret_cast safely"); + auto ort_input_values = reinterpret_cast(input_values); + auto ort_output_values = reinterpret_cast(output_values); + ThrowOnError(GetApi().Run(this->p_, run_options, input_names, ort_input_values, input_count, output_names, output_count, ort_output_values)); +} + +template +inline void SessionImpl::Run(const RunOptions& run_options, const IoBinding& io_binding) { + ThrowOnError(GetApi().RunWithBinding(this->p_, run_options, io_binding)); +} + +template +inline void SessionImpl::RunAsync(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count, + const char* const* output_names, Value* output_values, size_t output_count, RunAsyncCallbackFn callback, void* user_data) { + auto ort_input_values = reinterpret_cast(input_values); + auto ort_output_values = reinterpret_cast(output_values); + ThrowOnError(GetApi().RunAsync(this->p_, run_options, input_names, + ort_input_values, input_count, output_names, output_count, + ort_output_values, callback, user_data)); +} + +template +inline AllocatedStringPtr SessionImpl::EndProfilingAllocated(OrtAllocator* allocator) { + char* out = nullptr; + ThrowOnError(GetApi().SessionEndProfiling(this->p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +template +inline void SessionImpl::SetEpDynamicOptions(const char* const* keys, const char* const* values, size_t kv_len) { + ThrowOnError(GetApi().SetEpDynamicOptions(this->p_, keys, values, kv_len)); +} + +#if !defined(ORT_MINIMAL_BUILD) +template +inline void SessionImpl::FinalizeModelEditorSession(const Model& model, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container) { + ThrowOnError(GetModelEditorApi().ApplyModelToModelEditorSession(this->p_, model)); + ThrowOnError(GetModelEditorApi().FinalizeModelEditorSession(this->p_, options, prepacked_weights_container)); +} +#endif // #if !defined(ORT_MINIMAL_BUILD) + +} // namespace detail + +inline SessionOptions::SessionOptions() { + ThrowOnError(GetApi().CreateSessionOptions(&this->p_)); +} + +/// CustomOpConfigs +inline std::string detail::MakeCustomOpConfigEntryKey(const char* custom_op_name, const char* config) { + std::string config_key = "custom_op."; + + config_key += custom_op_name; + config_key += "."; + config_key += config; + + return config_key; +} + +inline CustomOpConfigs& CustomOpConfigs::AddConfig(const char* custom_op_name, const char* config_key, const char* config_value) { + const std::string full_flat_key = detail::MakeCustomOpConfigEntryKey(custom_op_name, config_key); + flat_configs_[full_flat_key] = config_value; + return *this; +} + +inline const std::unordered_map& CustomOpConfigs::GetFlattenedConfigs() const { + return flat_configs_; +} + +inline Session::Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options) { + ThrowOnError(GetApi().CreateSession(env, model_path, options, &this->p_)); +} + +inline Session::Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container) { + ThrowOnError(GetApi().CreateSessionWithPrepackedWeightsContainer(env, model_path, options, prepacked_weights_container, &this->p_)); +} + +inline Session::Session(const Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options) { + ThrowOnError(GetApi().CreateSessionFromArray(env, model_data, model_data_length, options, &this->p_)); +} + +inline Session::Session(const Env& env, const void* model_data, size_t model_data_length, + const SessionOptions& options, OrtPrepackedWeightsContainer* prepacked_weights_container) { + ThrowOnError(GetApi().CreateSessionFromArrayWithPrepackedWeightsContainer(env, model_data, model_data_length, options, + prepacked_weights_container, &this->p_)); +} + +#if !defined(ORT_MINIMAL_BUILD) +inline Session::Session(const Env& env, const Model& model, const SessionOptions& options) { + ThrowOnError(GetModelEditorApi().CreateSessionFromModel(env, model, options, &this->p_)); +} + +// static +inline Session Session::CreateModelEditorSession(const Env& env, const ORTCHAR_T* model_path, + const SessionOptions& options) { + OrtSession* session = nullptr; + ThrowOnError(GetModelEditorApi().CreateModelEditorSession(env, model_path, options, &session)); + return Session(session); +} + +// static +inline Session Session::CreateModelEditorSession(const Env& env, const void* model_data, size_t model_data_length, + const SessionOptions& options) { + OrtSession* session = nullptr; + ThrowOnError(GetModelEditorApi().CreateModelEditorSessionFromArray(env, model_data, model_data_length, options, + &session)); + return Session(session); +} + +void FinalizeModelEditorSession(const Model& model, const SessionOptions& options, + OrtPrepackedWeightsContainer* prepacked_weights_container); +#endif // #if !defined(ORT_MINIMAL_BUILD) + +inline AllocatedStringPtr ModelMetadata::GetProducerNameAllocated(OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataGetProducerName(p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline AllocatedStringPtr ModelMetadata::GetGraphNameAllocated(OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataGetGraphName(p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline AllocatedStringPtr ModelMetadata::GetDomainAllocated(OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataGetDomain(p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline AllocatedStringPtr Ort::ModelMetadata::GetDescriptionAllocated(OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataGetDescription(p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline AllocatedStringPtr ModelMetadata::GetGraphDescriptionAllocated(OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataGetGraphDescription(p_, allocator, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline AllocatedStringPtr ModelMetadata::LookupCustomMetadataMapAllocated(const char* key, OrtAllocator* allocator) const { + char* out; + ThrowOnError(GetApi().ModelMetadataLookupCustomMetadataMap(p_, allocator, key, &out)); + return AllocatedStringPtr(out, detail::AllocatedFree(allocator)); +} + +inline std::vector ModelMetadata::GetCustomMetadataMapKeysAllocated(OrtAllocator* allocator) const { + auto deletor = detail::AllocatedFree(allocator); + std::vector result; + + char** out = nullptr; + int64_t num_keys = 0; + ThrowOnError(GetApi().ModelMetadataGetCustomMetadataMapKeys(p_, allocator, &out, &num_keys)); + if (num_keys <= 0) { + return result; + } + + // array of pointers will be freed + std::unique_ptr array_guard(out, deletor); + // reserve may throw + auto strings_deletor = [&deletor, num_keys](char** out) { for(int64_t i = 0; i < num_keys; ++i) deletor(out[i]); }; + std::unique_ptr strings_guard(out, strings_deletor); + result.reserve(static_cast(num_keys)); + strings_guard.release(); + for (int64_t i = 0; i < num_keys; ++i) { + result.push_back(AllocatedStringPtr(out[i], deletor)); + } + + return result; +} + +inline int64_t ModelMetadata::GetVersion() const { + int64_t out; + ThrowOnError(GetApi().ModelMetadataGetVersion(p_, &out)); + return out; +} + +inline TensorTypeAndShapeInfo::TensorTypeAndShapeInfo(ONNXTensorElementDataType element_type, + const std::vector& dims, + const std::vector* symbolic_dims) { + ThrowOnError(GetApi().CreateTensorTypeAndShapeInfo(&p_)); + ThrowOnError(GetApi().SetTensorElementType(p_, element_type)); + ThrowOnError(GetApi().SetDimensions(p_, dims.data(), dims.size())); + + if (symbolic_dims) { + std::vector symbolic_dims_cstr; + symbolic_dims_cstr.reserve(symbolic_dims->size()); + std::transform(symbolic_dims->begin(), symbolic_dims->end(), std::back_inserter(symbolic_dims_cstr), + [](const std::string& s) { return s.c_str(); }); + ThrowOnError(GetApi().SetSymbolicDimensions(p_, symbolic_dims_cstr.data(), symbolic_dims_cstr.size())); + } +} + +#if !defined(ORT_MINIMAL_BUILD) +// static +inline TypeInfo TypeInfo::CreateTensorInfo(ConstTensorTypeAndShapeInfo tensor_type_and_shape_info) { + OrtTypeInfo* output = nullptr; + ThrowOnError(GetModelEditorApi().CreateTensorTypeInfo(tensor_type_and_shape_info, &output)); + return TypeInfo{output}; +} + +// static +inline TypeInfo TypeInfo::CreateSparseTensorInfo(ConstTensorTypeAndShapeInfo sparse_tensor_type_and_shape_info) { + OrtTypeInfo* output = nullptr; + ThrowOnError(GetModelEditorApi().CreateSparseTensorTypeInfo(sparse_tensor_type_and_shape_info, &output)); + return TypeInfo{output}; +} + +// static +inline TypeInfo TypeInfo::CreateSequenceTypeInfo(ConstTypeInfo sequence_type) { + OrtTypeInfo* output; + ThrowOnError(GetModelEditorApi().CreateSequenceTypeInfo(sequence_type, &output)); + return TypeInfo{output}; +} + +// static +inline TypeInfo TypeInfo::CreateMapTypeInfo(ONNXTensorElementDataType key_type, ConstTypeInfo value_type) { + OrtTypeInfo* output; + ThrowOnError(GetModelEditorApi().CreateMapTypeInfo(key_type, value_type, &output)); + return TypeInfo{output}; +} + +// static +inline TypeInfo TypeInfo::CreateOptionalTypeInfo(ConstTypeInfo contained_type) { + OrtTypeInfo* output; + ThrowOnError(GetModelEditorApi().CreateOptionalTypeInfo(contained_type, &output)); + return TypeInfo{output}; +} +#endif // #if !defined(ORT_MINIMAL_BUILD) + +namespace detail { + +template +inline ONNXTensorElementDataType TensorTypeAndShapeInfoImpl::GetElementType() const { + ONNXTensorElementDataType out; + ThrowOnError(GetApi().GetTensorElementType(this->p_, &out)); + return out; +} + +template +inline size_t TensorTypeAndShapeInfoImpl::GetElementCount() const { + size_t out; + ThrowOnError(GetApi().GetTensorShapeElementCount(this->p_, &out)); + return static_cast(out); +} + +template +inline size_t TensorTypeAndShapeInfoImpl::GetDimensionsCount() const { + size_t out; + ThrowOnError(GetApi().GetDimensionsCount(this->p_, &out)); + return out; +} + +template +inline void TensorTypeAndShapeInfoImpl::GetDimensions(int64_t* values, size_t values_count) const { + ThrowOnError(GetApi().GetDimensions(this->p_, values, values_count)); +} + +template +inline void TensorTypeAndShapeInfoImpl::GetSymbolicDimensions(const char** values, size_t values_count) const { + ThrowOnError(GetApi().GetSymbolicDimensions(this->p_, values, values_count)); +} + +template +inline std::vector TensorTypeAndShapeInfoImpl::GetSymbolicDimensions() const { + std::vector out(GetDimensionsCount(), nullptr); + ThrowOnError(GetApi().GetSymbolicDimensions(this->p_, out.data(), out.size())); + return out; +} + +template +inline std::vector TensorTypeAndShapeInfoImpl::GetShape() const { + std::vector out(GetDimensionsCount(), -1); + ThrowOnError(GetApi().GetDimensions(this->p_, out.data(), out.size())); + return out; +} + +template +inline ConstTensorTypeAndShapeInfo TypeInfoImpl::GetTensorTypeAndShapeInfo() const { + const OrtTensorTypeAndShapeInfo* out; + ThrowOnError(GetApi().CastTypeInfoToTensorInfo(this->p_, &out)); + return ConstTensorTypeAndShapeInfo{out}; +} + +template +inline ConstSequenceTypeInfo TypeInfoImpl::GetSequenceTypeInfo() const { + const OrtSequenceTypeInfo* out; + ThrowOnError(GetApi().CastTypeInfoToSequenceTypeInfo(this->p_, &out)); + return ConstSequenceTypeInfo{out}; +} + +template +inline ConstMapTypeInfo TypeInfoImpl::GetMapTypeInfo() const { + const OrtMapTypeInfo* out; + ThrowOnError(GetApi().CastTypeInfoToMapTypeInfo(this->p_, &out)); + return ConstMapTypeInfo{out}; +} + +template +inline ONNXType TypeInfoImpl::GetONNXType() const { + ONNXType out; + ThrowOnError(GetApi().GetOnnxTypeFromTypeInfo(this->p_, &out)); + return out; +} + +template +inline TypeInfo SequenceTypeInfoImpl::GetSequenceElementType() const { + OrtTypeInfo* output; + ThrowOnError(GetApi().GetSequenceElementType(this->p_, &output)); + return TypeInfo{output}; +} + +template +inline TypeInfo OptionalTypeInfoImpl::GetOptionalElementType() const { + OrtTypeInfo* info; + ThrowOnError(GetApi().GetOptionalContainedTypeInfo(this->p_, &info)); + return TypeInfo{info}; +} + +template +inline ONNXTensorElementDataType MapTypeInfoImpl::GetMapKeyType() const { + ONNXTensorElementDataType out; + ThrowOnError(GetApi().GetMapKeyType(this->p_, &out)); + return out; +} + +template +inline TypeInfo MapTypeInfoImpl::GetMapValueType() const { + OrtTypeInfo* output; + ThrowOnError(GetApi().GetMapValueType(this->p_, &output)); + return TypeInfo{output}; +} + +template +inline ConstOptionalTypeInfo TypeInfoImpl::GetOptionalTypeInfo() const { + const OrtOptionalTypeInfo* info; + ThrowOnError(GetApi().CastTypeInfoToOptionalTypeInfo(this->p_, &info)); + return ConstOptionalTypeInfo{info}; +} + +} // namespace detail + +namespace detail { + +template +template +inline void ConstValueImpl::GetOpaqueData(const char* domain, const char* type_name, R& out) const { + ThrowOnError(GetApi().GetOpaqueValue(domain, type_name, this->p_, &out, sizeof(R))); +} + +template +inline bool ConstValueImpl::IsTensor() const { + int out; + ThrowOnError(GetApi().IsTensor(this->p_, &out)); + return out != 0; +} + +template +inline bool ConstValueImpl::HasValue() const { + int out; + ThrowOnError(GetApi().HasValue(this->p_, &out)); + return out != 0; +} + +template +inline size_t ConstValueImpl::GetCount() const { + size_t out; + ThrowOnError(GetApi().GetValueCount(this->p_, &out)); + return out; +} + +template +inline Value ConstValueImpl::GetValue(int index, OrtAllocator* allocator) const { + OrtValue* out; + ThrowOnError(GetApi().GetValue(this->p_, index, allocator, &out)); + return Value{out}; +} + +template +inline size_t ConstValueImpl::GetStringTensorDataLength() const { + size_t out; + ThrowOnError(GetApi().GetStringTensorDataLength(this->p_, &out)); + return out; +} + +template +inline size_t ConstValueImpl::GetStringTensorElementLength(size_t element_index) const { + size_t out; + ThrowOnError(GetApi().GetStringTensorElementLength(this->p_, element_index, &out)); + return out; +} + +template +inline size_t ConstValueImpl::GetTensorSizeInBytes() const { + size_t out; + ThrowOnError(GetApi().GetTensorSizeInBytes(this->p_, &out)); + return out; +} + +template +template +inline const R* ConstValueImpl::GetTensorData() const { + const R* out; + ThrowOnError(GetApi().GetTensorData(this->p_, reinterpret_cast(&out))); + return out; +} + +template +inline const void* ConstValueImpl::GetTensorRawData() const { + const void* out; + ThrowOnError(GetApi().GetTensorData(this->p_, &out)); + return out; +} + +template +inline TypeInfo ConstValueImpl::GetTypeInfo() const { + OrtTypeInfo* output; + ThrowOnError(GetApi().GetTypeInfo(this->p_, &output)); + return TypeInfo{output}; +} + +template +inline TensorTypeAndShapeInfo ConstValueImpl::GetTensorTypeAndShapeInfo() const { + OrtTensorTypeAndShapeInfo* output; + ThrowOnError(GetApi().GetTensorTypeAndShape(this->p_, &output)); + return TensorTypeAndShapeInfo{output}; +} + +template +inline ConstMemoryInfo ConstValueImpl::GetTensorMemoryInfo() const { + const OrtMemoryInfo* mem_info; + ThrowOnError(GetApi().GetTensorMemoryInfo(this->p_, &mem_info)); + return ConstMemoryInfo(mem_info); +} + +template +inline void ConstValueImpl::GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const { + ThrowOnError(GetApi().GetStringTensorElement(this->p_, buffer_length, element_index, buffer)); +} + +template +inline std::string ConstValueImpl::GetStringTensorElement(size_t element_index) const { + size_t buffer_length; + ThrowOnError(GetApi().GetStringTensorElementLength(this->p_, element_index, &buffer_length)); + + std::string s; + s.resize(buffer_length); + ThrowOnError(GetApi().GetStringTensorElement(this->p_, buffer_length, element_index, &s[0])); + return s; +} + +template +inline void ConstValueImpl::GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const { + ThrowOnError(GetApi().GetStringTensorContent(this->p_, buffer, buffer_length, offsets, offsets_count)); +} + +#if !defined(DISABLE_SPARSE_TENSORS) +template +inline OrtSparseFormat ConstValueImpl::GetSparseFormat() const { + OrtSparseFormat format; + ThrowOnError(GetApi().GetSparseTensorFormat(this->p_, &format)); + return format; +} + +template +inline TensorTypeAndShapeInfo ConstValueImpl::GetSparseTensorValuesTypeAndShapeInfo() const { + OrtTensorTypeAndShapeInfo* output; + ThrowOnError(GetApi().GetSparseTensorValuesTypeAndShape(this->p_, &output)); + return TensorTypeAndShapeInfo{output}; +} + +template +inline TensorTypeAndShapeInfo ConstValueImpl::GetSparseTensorIndicesTypeShapeInfo(OrtSparseIndicesFormat indices_format) const { + OrtTensorTypeAndShapeInfo* output; + ThrowOnError(GetApi().GetSparseTensorIndicesTypeShape(this->p_, indices_format, &output)); + return TensorTypeAndShapeInfo{output}; +} + +template +template +inline const R* ConstValueImpl::GetSparseTensorIndicesData(OrtSparseIndicesFormat indices_format, size_t& num_indices) const { + const void* out; + ThrowOnError(GetApi().GetSparseTensorIndices(this->p_, indices_format, &num_indices, &out)); + return reinterpret_cast(out); +} + +template +inline bool ConstValueImpl::IsSparseTensor() const { + int out; + ThrowOnError(GetApi().IsSparseTensor(this->p_, &out)); + return out != 0; +} + +template +template +inline const R* ConstValueImpl::GetSparseTensorValues() const { + const void* out; + ThrowOnError(GetApi().GetSparseTensorValues(this->p_, &out)); + return reinterpret_cast(out); +} + +#endif + +template +void ValueImpl::FillStringTensor(const char* const* s, size_t s_len) { + ThrowOnError(GetApi().FillStringTensor(this->p_, s, s_len)); +} + +template +void ValueImpl::FillStringTensorElement(const char* s, size_t index) { + ThrowOnError(GetApi().FillStringTensorElement(this->p_, s, index)); +} + +template +inline char* ValueImpl::GetResizedStringTensorElementBuffer(size_t index, size_t buffer_length) { + char* result; + ThrowOnError(GetApi().GetResizedStringTensorElementBuffer(this->p_, index, buffer_length, &result)); + return result; +} + +template +void* ValueImpl::GetTensorMutableRawData() { + void* out; + ThrowOnError(GetApi().GetTensorMutableData(this->p_, &out)); + return out; +} + +template +template +R* ValueImpl::GetTensorMutableData() { + R* out; + ThrowOnError(GetApi().GetTensorMutableData(this->p_, (void**)&out)); + return out; +} + +template +template +R& ValueImpl::At(const std::vector& location) { + static_assert(!std::is_same::value, "this api does not support std::string"); + R* out; + ThrowOnError(GetApi().TensorAt(this->p_, location.data(), location.size(), (void**)&out)); + return *out; +} + +#if !defined(DISABLE_SPARSE_TENSORS) +template +void ValueImpl::UseCooIndices(int64_t* indices_data, size_t indices_num) { + ThrowOnError(GetApi().UseCooIndices(this->p_, indices_data, indices_num)); +} + +template +void ValueImpl::UseCsrIndices(int64_t* inner_data, size_t inner_num, int64_t* outer_data, size_t outer_num) { + ThrowOnError(GetApi().UseCsrIndices(this->p_, inner_data, inner_num, outer_data, outer_num)); +} + +template +void ValueImpl::UseBlockSparseIndices(const Shape& indices_shape, int32_t* indices_data) { + ThrowOnError(GetApi().UseBlockSparseIndices(this->p_, indices_shape.shape, indices_shape.shape_len, indices_data)); +} + +template +void ValueImpl::FillSparseTensorCoo(const OrtMemoryInfo* mem_info, const OrtSparseValuesParam& values_param, + const int64_t* indices_data, size_t indices_num) { + ThrowOnError(GetApi().FillSparseTensorCoo(this->p_, mem_info, values_param.values_shape, + values_param.values_shape_len, values_param.data.p_data, + indices_data, indices_num)); +} + +template +void ValueImpl::FillSparseTensorCsr(const OrtMemoryInfo* data_mem_info, + const OrtSparseValuesParam& values, + const int64_t* inner_indices_data, size_t inner_indices_num, + const int64_t* outer_indices_data, size_t outer_indices_num) { + ThrowOnError(GetApi().FillSparseTensorCsr(this->p_, data_mem_info, values.values_shape, values.values_shape_len, values.data.p_data, + inner_indices_data, inner_indices_num, + outer_indices_data, outer_indices_num)); +} + +template +void ValueImpl::FillSparseTensorBlockSparse(const OrtMemoryInfo* data_mem_info, + const OrtSparseValuesParam& values, + const Shape& indices_shape, + const int32_t* indices_data) { + ThrowOnError(GetApi().FillSparseTensorBlockSparse(this->p_, data_mem_info, values.values_shape, values.values_shape_len, values.data.p_data, + indices_shape.shape, indices_shape.shape_len, + indices_data)); +} + +#endif // !defined(DISABLE_SPARSE_TENSORS) + +} // namespace detail + +template +inline Value Value::CreateTensor(const OrtMemoryInfo* info, T* p_data, size_t p_data_element_count, + const int64_t* shape, size_t shape_len) { + return CreateTensor(info, p_data, p_data_element_count * sizeof(T), shape, shape_len, TypeToTensorType::type); +} + +inline Value Value::CreateTensor(const OrtMemoryInfo* info, void* p_data, size_t p_data_byte_count, + const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type) { + OrtValue* out; + ThrowOnError(GetApi().CreateTensorWithDataAsOrtValue(info, p_data, p_data_byte_count, shape, shape_len, type, &out)); + return Value{out}; +} + +inline Value Value::CreateTensor(OrtAllocator* deleter, void* p_data, size_t p_data_byte_count, + const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type) { + OrtValue* out; + ThrowOnError(GetApi().CreateTensorWithDataAndDeleterAsOrtValue(deleter, p_data, p_data_byte_count, + shape, shape_len, type, &out)); + return Value{out}; +} + +template +inline Value Value::CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len) { + return CreateTensor(allocator, shape, shape_len, TypeToTensorType::type); +} + +inline Value Value::CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len, + ONNXTensorElementDataType type) { + OrtValue* out; + ThrowOnError(GetApi().CreateTensorAsOrtValue(allocator, shape, shape_len, type, &out)); + return Value{out}; +} + +#if !defined(DISABLE_SPARSE_TENSORS) + +template +inline Value Value::CreateSparseTensor(const OrtMemoryInfo* info, T* p_data, const Shape& dense_shape, + const Shape& values_shape) { + return CreateSparseTensor(info, p_data, dense_shape, values_shape, TypeToTensorType::type); +} + +inline Value Value::CreateSparseTensor(const OrtMemoryInfo* info, void* p_data, const Shape& dense_shape, + const Shape& values_shape, ONNXTensorElementDataType type) { + OrtValue* out; + ThrowOnError(GetApi().CreateSparseTensorWithValuesAsOrtValue(info, p_data, dense_shape.shape, dense_shape.shape_len, + values_shape.shape, values_shape.shape_len, type, + &out)); + return Value{out}; +} + +template +inline Value Value::CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape) { + return CreateSparseTensor(allocator, dense_shape, TypeToTensorType::type); +} + +inline Value Value::CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape, + ONNXTensorElementDataType type) { + OrtValue* out; + ThrowOnError(GetApi().CreateSparseTensorAsOrtValue(allocator, dense_shape.shape, dense_shape.shape_len, type, &out)); + return Value{out}; +} +#endif // !defined(DISABLE_SPARSE_TENSORS) + +inline Value Value::CreateMap(const Value& keys, const Value& values) { + OrtValue* out; + const OrtValue* inputs[2] = {keys, values}; + ThrowOnError(GetApi().CreateValue(inputs, 2, ONNX_TYPE_MAP, &out)); + return Value{out}; +} + +inline Value Value::CreateSequence(const std::vector& values) { + OrtValue* out; + std::vector values_ort{values.data(), values.data() + values.size()}; + ThrowOnError(GetApi().CreateValue(values_ort.data(), values_ort.size(), ONNX_TYPE_SEQUENCE, &out)); + return Value{out}; +} + +template +inline Value Value::CreateOpaque(const char* domain, const char* type_name, const T& data_container) { + OrtValue* out; + ThrowOnError(GetApi().CreateOpaqueValue(domain, type_name, &data_container, sizeof(T), &out)); + return Value{out}; +} + +// +// Custom OP Inlines +// +inline Logger::Logger(const OrtLogger* logger) : logger_(logger) { + Ort::ThrowOnError(GetApi().Logger_GetLoggingSeverityLevel(this->logger_, &this->cached_severity_level_)); +} + +inline OrtLoggingLevel Logger::GetLoggingSeverityLevel() const noexcept { + return cached_severity_level_; +} + +inline Status Logger::LogMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, int line_number, + const char* func_name, const char* message) const noexcept { + OrtStatus* status = GetApi().Logger_LogMessage(logger_, log_severity_level, message, file_path, line_number, + func_name); + return Status{status}; +} + +// Disable warnings about the format string not being a literal (-Wformat-nonliteral and -Wformat-security) +// for gcc and clang. The alternative is to use actual C-style variadic parameters and apply +// __attribute__(format(printf...)), which does not work with variadic templates. +#if defined(__GNUC__) +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wformat-nonliteral" +#pragma GCC diagnostic ignored "-Wformat-security" +#elif defined(__clang__) +#pragma clang diagnostic push +#pragma clang diagnostic ignored "-Wformat-nonliteral" +#pragma clang diagnostic ignored "-Wformat-security" +#endif +template +inline Status Logger::LogFormattedMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, + int line_number, const char* func_name, const char* format, + Args&&... args) const noexcept { + int msg_len = std::snprintf(nullptr, 0U, format, std::forward(args)...); + + if (msg_len < 0) { // Formatting error + return Status("Failed to log message due to formatting error", OrtErrorCode::ORT_FAIL); + } + + OrtStatus* status = nullptr; + const size_t buffer_size = static_cast(msg_len) + 1U; + + constexpr size_t kStackBufferSize = 1024; + + if (buffer_size < kStackBufferSize) { + char buffer[kStackBufferSize]; + snprintf(buffer, kStackBufferSize, format, std::forward(args)...); + status = GetApi().Logger_LogMessage(logger_, log_severity_level, buffer, file_path, line_number, func_name); + } else { + // std::make_unique is only supported starting at C++14. +#if (__cplusplus >= 201402L) || (_MSC_VER >= 1900) + auto buffer = std::make_unique(buffer_size); +#else + std::unique_ptr buffer(new char[buffer_size]); +#endif + std::snprintf(buffer.get(), buffer_size, format, std::forward(args)...); + status = GetApi().Logger_LogMessage(logger_, log_severity_level, buffer.get(), file_path, line_number, func_name); + } + + return Status{status}; +} +// Re-enable -Wformat-nonliteral and -Wformat-security +#if defined(__GNUC__) +#pragma GCC diagnostic pop +#elif defined(__clang__) +#pragma clang diagnostic pop +#endif + +inline KernelContext::KernelContext(OrtKernelContext* context) : ctx_(context) { +} + +inline size_t KernelContext::GetInputCount() const { + size_t out = 0; + Ort::ThrowOnError(GetApi().KernelContext_GetInputCount(ctx_, &out)); + return out; +} + +inline size_t KernelContext::GetOutputCount() const { + size_t out = 0; + Ort::ThrowOnError(GetApi().KernelContext_GetOutputCount(ctx_, &out)); + return out; +} + +inline ConstValue KernelContext::GetInput(size_t index) const { + const OrtValue* out = nullptr; + Ort::ThrowOnError(GetApi().KernelContext_GetInput(ctx_, index, &out)); + return ConstValue{out}; +} + +inline UnownedValue KernelContext::GetOutput(size_t index, const int64_t* dim_values, size_t dim_count) const { + OrtValue* out = nullptr; + Ort::ThrowOnError(GetApi().KernelContext_GetOutput(ctx_, index, dim_values, dim_count, &out)); + return UnownedValue(out); +} + +inline UnownedValue KernelContext::GetOutput(size_t index, const std::vector& dims) const { + OrtValue* out = nullptr; + Ort::ThrowOnError(GetApi().KernelContext_GetOutput(ctx_, index, dims.data(), dims.size(), &out)); + return UnownedValue(out); +} + +inline void* KernelContext::GetGPUComputeStream() const { + void* out = nullptr; + Ort::ThrowOnError(GetApi().KernelContext_GetGPUComputeStream(ctx_, &out)); + return out; +} + +inline OrtAllocator* KernelContext::GetAllocator(const OrtMemoryInfo& memory_info) const { + OrtAllocator* out = nullptr; + Ort::ThrowOnError(GetApi().KernelContext_GetAllocator(ctx_, &memory_info, &out)); + return out; +} + +inline Logger KernelContext::GetLogger() const { + const OrtLogger* out = nullptr; + ThrowOnError(GetApi().KernelContext_GetLogger(this->ctx_, &out)); + return Logger{out}; +} + +inline void KernelContext::ParallelFor(void (*fn)(void*, size_t), size_t total, size_t num_batch, void* usr_data) const { + ThrowOnError(GetApi().KernelContext_ParallelFor(ctx_, fn, total, num_batch, usr_data)); +} + +namespace detail { + +template +constexpr OrtOpAttrType TypeToAttrType(); + +template <> +inline constexpr OrtOpAttrType TypeToAttrType() { + return OrtOpAttrType::ORT_OP_ATTR_INT; +} + +template <> +inline constexpr OrtOpAttrType TypeToAttrType() { + return OrtOpAttrType::ORT_OP_ATTR_FLOAT; +} + +template +inline constexpr OrtOpAttrType TypeToAttrsType(); + +template <> +inline constexpr OrtOpAttrType TypeToAttrsType() { + return OrtOpAttrType::ORT_OP_ATTR_INTS; +} + +template <> +inline constexpr OrtOpAttrType TypeToAttrsType() { + return OrtOpAttrType::ORT_OP_ATTR_FLOATS; +} + +inline Status CheckAttrType(const OrtOpAttr* attr, OrtOpAttrType requested_type) { + OrtOpAttrType type; + Ort::Status status(GetApi().OpAttr_GetType(attr, &type)); + if (!status.IsOK()) return status; + if (requested_type != type) { + std::string msg = "Attribute type mismatch: expected " + std::to_string(requested_type) + + ", but got " + std::to_string(type); + return Ort::Status(msg.c_str(), OrtErrorCode::ORT_INVALID_ARGUMENT); + } + return Ort::Status{}; +} + +inline size_t GetDataSize(const OrtOpAttr* attr, OrtOpAttrType attr_type) { + size_t result{}; + // Ignore the status here because we check the data type so the error should only be about + // the size + [[maybe_unused]] Status status{GetApi().ReadOpAttr(attr, attr_type, nullptr, 0, &result)}; + return result; +} + +template +Ort::Status GetNumericValue(const OrtOpAttr* attr, T& out) { + static_assert(std::is_arithmetic::value, "T must be an arithmetic type"); + size_t size{}; + return Ort::Status{GetApi().ReadOpAttr(attr, TypeToAttrType(), &out, sizeof(out), &size)}; +} + +template +struct GetValueImpl { + static Status GetValue(const OrtOpAttr* attr, T& out) { + return GetNumericValue(attr, out); + } + static Status GetValues(const OrtOpAttr* attr, std::vector& out) { + // Api deficiency when it comes to value arrays. It is not possible + // to tell if the error is due to the type mismatch or the size + // so we check the type first, and then ignore the status of the size check + constexpr auto deduced_type = TypeToAttrsType(); + auto status = CheckAttrType(attr, deduced_type); + if (!status.IsOK()) return status; + auto size = GetDataSize(attr, deduced_type); + std::vector result; + if (size > 0) { + result.resize(size / sizeof(T)); + status = Status{GetApi().ReadOpAttr( + attr, deduced_type, result.data(), size, &size)}; + if (!status.IsOK()) return status; + } + out.swap(result); + return status; + } +}; + +// Create GetValueImpl specializations for std::string +template <> +struct GetValueImpl { + static Status GetValue(const OrtOpAttr* attr, std::string& out) { + // Api deficiency when it comes to value arrays. It is not possible + // to tell if the error is due to the type mismatch or the size + // so we check the type first, and then ignore the status of the size check + auto status = CheckAttrType(attr, OrtOpAttrType::ORT_OP_ATTR_STRING); + if (!status.IsOK()) return status; + auto size = GetDataSize(attr, OrtOpAttrType::ORT_OP_ATTR_STRING); + std::string result; + if (size > 0) { + result.resize(size); + // some compilers in use do not support std::string::data() non-const + auto* buffer = &result[0]; + status = Status{GetApi().ReadOpAttr( + attr, OrtOpAttrType::ORT_OP_ATTR_STRING, buffer, size, &size)}; + if (!status.IsOK()) return status; + } + out.swap(result); + return status; + } + static Status GetValues(const OrtOpAttr* attr, std::vector& out) { + auto status = CheckAttrType(attr, OrtOpAttrType::ORT_OP_ATTR_STRINGS); + if (!status.IsOK()) return status; + + std::vector result; + size_t total_buffer_size = GetDataSize(attr, OrtOpAttrType::ORT_OP_ATTR_STRINGS); + if (total_buffer_size > 0) { + // Create a temporary buffer to hold the string data + std::vector buffer(total_buffer_size); + status = Status{GetApi().ReadOpAttr(attr, OrtOpAttrType::ORT_OP_ATTR_STRINGS, buffer.data(), + total_buffer_size, &total_buffer_size)}; + if (!status.IsOK()) return status; + + const char* data = buffer.data(); + const char* end = data + total_buffer_size; + while (data < end) { + result.emplace_back(data); + data += result.back().size() + 1; // Move past the null terminator + } + } + out.swap(result); + return status; + } +}; + +template +template +inline Status ConstOpAttrImpl::GetValue(R& out) const { + return GetValueImpl::GetValue(this->p_, out); +} + +template +template +inline Status ConstOpAttrImpl::GetValueArray(std::vector& out) const { + return GetValueImpl::GetValues(this->p_, out); +} + +template +inline Status ConstOpAttrImpl::GetTensorAttributeAsOrtValue(Value& out) const { + OrtValue* tensor_value = nullptr; + auto status = Status(GetApi().OpAttr_GetTensorAttributeAsOrtValue(this->p_, &tensor_value)); + if (!status.IsOK()) return status; + out = Value{tensor_value}; + return status; +} + +template +inline std::string ConstOpAttrImpl::GetName() const { + const char* name = nullptr; + ThrowOnError(GetApi().OpAttr_GetName(this->p_, &name)); + if (name != nullptr) { + return name; + } + return {}; +} + +template +inline OrtOpAttrType ConstOpAttrImpl::GetType() const { + OrtOpAttrType type; + ThrowOnError(GetApi().OpAttr_GetType(this->p_, &type)); + return type; +} +} // namespace detail + +inline OpAttr::OpAttr(const char* name, const void* data, int len, OrtOpAttrType type) { + Ort::ThrowOnError(GetApi().CreateOpAttr(name, data, len, type, &p_)); +} + +namespace detail { +template +inline KernelInfo KernelInfoImpl::Copy() const { + OrtKernelInfo* info_copy = nullptr; + Ort::ThrowOnError(GetApi().CopyKernelInfo(this->p_, &info_copy)); + return KernelInfo{info_copy}; +} + +template +inline size_t KernelInfoImpl::GetInputCount() const { + size_t out = 0; + ThrowOnError(GetApi().KernelInfo_GetInputCount(this->p_, &out)); + return out; +} + +template +inline size_t KernelInfoImpl::GetOutputCount() const { + size_t out = 0; + ThrowOnError(GetApi().KernelInfo_GetOutputCount(this->p_, &out)); + return out; +} + +template +inline std::string KernelInfoImpl::GetInputName(size_t index) const { + size_t size = 0; + + // Feed nullptr for the data buffer to query the true size of the string value + Ort::ThrowOnError(GetApi().KernelInfo_GetInputName(this->p_, index, nullptr, &size)); + + std::string out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfo_GetInputName(this->p_, index, &out[0], &size)); + out.resize(size - 1); // remove the terminating character '\0' + + return out; +} + +template +inline std::string KernelInfoImpl::GetOutputName(size_t index) const { + size_t size = 0; + + // Feed nullptr for the data buffer to query the true size of the string value + Ort::ThrowOnError(GetApi().KernelInfo_GetOutputName(this->p_, index, nullptr, &size)); + + std::string out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfo_GetOutputName(this->p_, index, &out[0], &size)); + out.resize(size - 1); // remove the terminating character '\0' + + return out; +} + +template +inline TypeInfo KernelInfoImpl::GetInputTypeInfo(size_t index) const { + OrtTypeInfo* out = nullptr; + ThrowOnError(GetApi().KernelInfo_GetInputTypeInfo(this->p_, index, &out)); + return TypeInfo{out}; +} + +template +inline TypeInfo KernelInfoImpl::GetOutputTypeInfo(size_t index) const { + OrtTypeInfo* out = nullptr; + ThrowOnError(GetApi().KernelInfo_GetOutputTypeInfo(this->p_, index, &out)); + return TypeInfo{out}; +} + +template +inline Value KernelInfoImpl::GetTensorAttribute(const char* name, OrtAllocator* allocator) const { + OrtValue* out = nullptr; + ThrowOnError(GetApi().KernelInfoGetAttribute_tensor(this->p_, name, allocator, &out)); + return Value{out}; +} + +template +inline ConstValue KernelInfoImpl::GetTensorConstantInput(size_t index, int* is_constant) const { + const OrtValue* out = nullptr; + ThrowOnError(GetApi().KernelInfoGetConstantInput_tensor(this->p_, index, is_constant, &out)); + return ConstValue{out}; +} + +template +inline std::string KernelInfoImpl::GetNodeName() const { + size_t size = 0; + + // Feed nullptr for the data buffer to query the true size of the string value + Ort::ThrowOnError(GetApi().KernelInfo_GetNodeName(this->p_, nullptr, &size)); + + std::string out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfo_GetNodeName(this->p_, &out[0], &size)); + out.resize(size - 1); // remove the terminating character '\0' + + return out; +} + +template +inline Logger KernelInfoImpl::GetLogger() const { + const OrtLogger* out = nullptr; + ThrowOnError(GetApi().KernelInfo_GetLogger(this->p_, &out)); + return Logger{out}; +} + +inline void attr_utils::GetAttr(const OrtKernelInfo* p, const char* name, float& out) { + Ort::ThrowOnError(GetApi().KernelInfoGetAttribute_float(p, name, &out)); +} + +inline void attr_utils::GetAttr(const OrtKernelInfo* p, const char* name, int64_t& out) { + Ort::ThrowOnError(GetApi().KernelInfoGetAttribute_int64(p, name, &out)); +} + +inline void attr_utils::GetAttr(const OrtKernelInfo* p, const char* name, std::string& result) { + size_t size = 0; + // Feed nullptr for the data buffer to query the true size of the string attribute + Ort::ThrowOnError(GetApi().KernelInfoGetAttribute_string(p, name, nullptr, &size)); + + std::string out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfoGetAttribute_string(p, name, &out[0], &size)); + out.resize(size - 1); // remove the terminating character '\0' + out.swap(result); +} + +inline void attr_utils::GetAttrs(const OrtKernelInfo* p, const char* name, std::vector& result) { + size_t size = 0; + // Feed nullptr for the data buffer to query the true size of the attribute + Ort::ThrowOnError(GetApi().KernelInfoGetAttributeArray_float(p, name, nullptr, &size)); + + std::vector out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfoGetAttributeArray_float(p, name, out.data(), &size)); + out.swap(result); +} + +inline void attr_utils::GetAttrs(const OrtKernelInfo* p, const char* name, std::vector& result) { + size_t size = 0; + + // Feed nullptr for the data buffer to query the true size of the attribute + Ort::ThrowOnError(GetApi().KernelInfoGetAttributeArray_int64(p, name, nullptr, &size)); + + std::vector out; + out.resize(size); + Ort::ThrowOnError(GetApi().KernelInfoGetAttributeArray_int64(p, name, out.data(), &size)); + out.swap(result); +} +} // namespace detail + +inline KernelInfo::KernelInfo(OrtKernelInfo* info) : detail::KernelInfoImpl{info} {} + +inline Op::Op(OrtOp* p) : detail::Base(p) {} + +inline Op Op::Create(const OrtKernelInfo* info, const char* op_name, const char* domain, int version, + const char** type_constraint_names, + const ONNXTensorElementDataType* type_constraint_values, + size_t type_constraint_count, + const OpAttr* attr_values, size_t attr_count, + size_t input_count, size_t output_count) { + static_assert(sizeof(OpAttr) == sizeof(OrtOpAttr*), + "OpAttr's is expected to be just an array of OrtOpAttr in memory so we can reinterpret safely"); + auto attr_input_values = reinterpret_cast(attr_values); + OrtOp* op; + Ort::ThrowOnError(GetApi().CreateOp(info, op_name, domain, version, type_constraint_names, type_constraint_values, + static_cast(type_constraint_count), + attr_input_values, + static_cast(attr_count), + static_cast(input_count), + static_cast(output_count), &op)); + return Op{op}; +} + +inline void Op::Invoke(const OrtKernelContext* context, + const Value* input_values, + size_t input_count, + Value* output_values, + size_t output_count) { + static_assert(sizeof(Value) == sizeof(OrtValue*), + "Value is really just an array of OrtValue* in memory, so we can reinterpret_cast safely"); + auto ort_input_values = reinterpret_cast(input_values); + auto ort_output_values = reinterpret_cast(output_values); + Ort::ThrowOnError(GetApi().InvokeOp(context, p_, ort_input_values, static_cast(input_count), + ort_output_values, static_cast(output_count))); +} + +inline void Op::Invoke(const OrtKernelContext* context, + const OrtValue* const* input_values, + size_t input_count, + OrtValue* const* output_values, + size_t output_count) { + Ort::ThrowOnError(GetApi().InvokeOp(context, p_, input_values, static_cast(input_count), + output_values, static_cast(output_count))); +} + +inline std::string GetVersionString() { + return OrtGetApiBase()->GetVersionString(); +} + +inline std::string GetBuildInfoString() { + return GetApi().GetBuildInfoString(); +} + +inline std::vector GetAvailableProviders() { + char** providers; + int len; + + auto release_fn = [&len](char** providers) { + // This should always return nullptr. + ThrowOnError(GetApi().ReleaseAvailableProviders(providers, len)); + }; + + ThrowOnError(GetApi().GetAvailableProviders(&providers, &len)); + std::unique_ptr guard(providers, release_fn); + std::vector available_providers; + available_providers.reserve(static_cast(len)); + for (int i = 0; i < len; ++i) { + available_providers.emplace_back(providers[i]); + } + return available_providers; +} + +template +void CustomOpBase::GetSessionConfigs(std::unordered_map& out, + ConstSessionOptions options) const { + const TOp* derived = static_cast(this); + std::vector keys = derived->GetSessionConfigKeys(); + + out.reserve(keys.size()); + + std::string config_entry_key = detail::MakeCustomOpConfigEntryKey(derived->GetName(), ""); + const size_t prefix_size = config_entry_key.length(); + + for (const auto& key : keys) { + config_entry_key.resize(prefix_size); + config_entry_key.append(key); + out[key] = options.GetConfigEntryOrDefault(config_entry_key.c_str(), ""); + } +} + +inline ShapeInferContext::ShapeInferContext(const OrtApi* ort_api, + OrtShapeInferContext* ctx) : ort_api_(ort_api), ctx_(ctx) { + size_t input_count = 0; + Ort::ThrowOnError(ort_api_->ShapeInferContext_GetInputCount(ctx_, &input_count)); + for (size_t ith_input = 0; ith_input < input_count; ++ith_input) { + OrtTensorTypeAndShapeInfo* info{}; + Ort::ThrowOnError(ort_api_->ShapeInferContext_GetInputTypeShape(ctx, ith_input, &info)); + TensorTypeAndShapeInfo type_shape_info(info); + auto integer_shape = type_shape_info.GetShape(); + std::vector symbolic_shape(integer_shape.size(), {}); + if (!integer_shape.empty()) { + type_shape_info.GetSymbolicDimensions(&symbolic_shape[0], integer_shape.size()); + } + Shape shape; + for (size_t ith = 0; ith < integer_shape.size(); ++ith) { + if (symbolic_shape[ith] && std::string{symbolic_shape[ith]}.size() > 0) { + shape.emplace_back(symbolic_shape[ith]); + } else { + shape.emplace_back(integer_shape[ith]); + } + } + input_shapes_.push_back(std::move(shape)); + type_shape_info.release(); + } +} + +inline Status ShapeInferContext::SetOutputShape(size_t indice, const Shape& shape, ONNXTensorElementDataType type) { + OrtTensorTypeAndShapeInfo* info = {}; + ORT_CXX_RETURN_ON_API_FAIL(ort_api_->CreateTensorTypeAndShapeInfo(&info)); + ORT_CXX_RETURN_ON_API_FAIL(ort_api_->SetTensorElementType(info, type)); + + using InfoPtr = std::unique_ptr>; + + InfoPtr info_ptr(info, [this](OrtTensorTypeAndShapeInfo* obj) { + ort_api_->ReleaseTensorTypeAndShapeInfo(obj); + }); + + std::vector integer_dims; + std::vector symbolic_dims; + + for (const auto dim : shape) { + if (dim.IsInt()) { + integer_dims.push_back(dim.AsInt()); + symbolic_dims.push_back(""); + } else { + if (!dim.AsSym() || std::string{dim.AsSym()}.empty()) { + ORT_CXX_API_THROW("Symbolic dim must not be an empty string", ORT_INVALID_ARGUMENT); + } + integer_dims.push_back(SymbolicInteger::INVALID_INT_DIM); + symbolic_dims.push_back(dim.AsSym()); + } + } + + ORT_CXX_RETURN_ON_API_FAIL(ort_api_->SetDimensions(info, integer_dims.data(), integer_dims.size())); + ORT_CXX_RETURN_ON_API_FAIL(ort_api_->SetSymbolicDimensions(info, symbolic_dims.data(), symbolic_dims.size())); + ORT_CXX_RETURN_ON_API_FAIL(ort_api_->ShapeInferContext_SetOutputTypeShape(ctx_, indice, info)); + return Status{nullptr}; +} + +inline int64_t ShapeInferContext::GetAttrInt(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + int64_t value; + Status status = attr.GetValue(value); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting int attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return value; +} + +inline ShapeInferContext::Ints ShapeInferContext::GetAttrInts(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + ShapeInferContext::Ints result; + auto status = attr.GetValueArray(result); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting ints attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return result; +} + +inline float ShapeInferContext::GetAttrFloat(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + float value; + Status status = attr.GetValue(value); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting float attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return value; +} + +inline ShapeInferContext::Floats ShapeInferContext::GetAttrFloats(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + ShapeInferContext::Floats result; + auto status = attr.GetValueArray(result); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting floats attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return result; +} + +inline std::string ShapeInferContext::GetAttrString(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + std::string value; + Status status = attr.GetValue(value); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting string attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return value; +} + +inline ShapeInferContext::Strings ShapeInferContext::GetAttrStrings(const char* attr_name) { + auto attr = GetAttrHdl(attr_name); + ShapeInferContext::Strings result; + auto status = attr.GetValueArray(result); + if (!status.IsOK()) { + ORT_CXX_API_THROW("Getting strings attribute failed: " + status.GetErrorMessage(), status.GetErrorCode()); + } + return result; +} + +inline ConstOpAttr ShapeInferContext::GetAttrHdl(const char* attr_name) const { + const OrtOpAttr* attr_hdl = {}; + Ort::ThrowOnError(ort_api_->ShapeInferContext_GetAttribute(ctx_, attr_name, &attr_hdl)); + return ConstOpAttr{attr_hdl}; +} + +namespace detail { +inline std::vector StringsToCharPtrs(const std::vector& strings) { + std::vector ptrs; + ptrs.reserve(strings.size()); + std::transform(strings.begin(), strings.end(), std::back_inserter(ptrs), + [](const std::string& s) { return s.c_str(); }); + + return ptrs; +} +} // namespace detail + +namespace detail { +template +inline size_t ConstNodeImpl::GetId() const { + size_t id; + ThrowOnError(GetApi().Node_GetId(this->p_, &id)); + return id; +} + +template +inline std::string ConstNodeImpl::GetName() const { + const char* name; + ThrowOnError(GetApi().Node_GetName(this->p_, &name)); + return std::string(name); +} + +template +inline std::string ConstNodeImpl::GetOperatorType() const { + const char* type; + ThrowOnError(GetApi().Node_GetOperatorType(this->p_, &type)); + return std::string(type); +} + +template +inline std::string ConstNodeImpl::GetDomain() const { + const char* domain; + ThrowOnError(GetApi().Node_GetDomain(this->p_, &domain)); + return std::string(domain); +} + +template +inline int ConstNodeImpl::GetSinceVersion() const { + int since_version; + ThrowOnError(GetApi().Node_GetSinceVersion(this->p_, &since_version)); + return since_version; +} + +template +inline std::vector ConstNodeImpl::GetInputs() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Node_GetNumInputs(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Node_GetInputs(this->p_, reinterpret_cast(result.data()), num_vi)); + } + return result; +} + +template +inline std::vector ConstNodeImpl::GetOutputs() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Node_GetNumOutputs(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Node_GetOutputs(this->p_, reinterpret_cast(result.data()), num_vi)); + } + return result; +} + +template +inline std::vector ConstNodeImpl::GetImplicitInputs() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Node_GetNumImplicitInputs(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Node_GetImplicitInputs(this->p_, reinterpret_cast(result.data()), + num_vi)); + } + return result; +} + +template +inline std::vector ConstNodeImpl::GetAttributes() const { + static_assert(sizeof(const OrtOpAttr*) == sizeof(ConstOpAttr), "Must be the same size"); + size_t num_attrs; + ThrowOnError(GetApi().Node_GetNumAttributes(this->p_, &num_attrs)); + std::vector attrs; + if (num_attrs > 0) { + attrs.resize(num_attrs); + ThrowOnError(GetApi().Node_GetAttributes(this->p_, reinterpret_cast(attrs.data()), num_attrs)); + } + return attrs; +} + +template +inline Status ConstNodeImpl::GetAttributeByName(const std::string& name, ConstOpAttr& out) const { + const OrtOpAttr* attr = nullptr; + auto status = Status(GetApi().Node_GetAttributeByName(this->p_, name.c_str(), &attr)); + out = ConstOpAttr{attr}; + return status; +} + +template +inline std::vector ConstNodeImpl::GetSubgraphs() const { + size_t num_graphs; + ThrowOnError(GetApi().Node_GetNumSubgraphs(this->p_, &num_graphs)); + std::vector result; + if (num_graphs > 0) { + std::vector sub_graphs(num_graphs); + std::vector attr_names(num_graphs); + ThrowOnError(GetApi().Node_GetSubgraphs(this->p_, sub_graphs.data(), num_graphs, attr_names.data())); + result.reserve(num_graphs); + for (size_t i = 0; i < num_graphs; ++i) { + result.push_back({std::string(attr_names[i]), ConstGraph{sub_graphs[i]}}); + } + } + return result; +} + +template +inline ConstGraph ConstNodeImpl::GetGraph() const { + const OrtGraph* graph; + ThrowOnError(GetApi().Node_GetGraph(this->p_, &graph)); + return ConstGraph{graph}; +} + +template +inline std::string ConstNodeImpl::GetEpName() const { + const char* name; + ThrowOnError(GetApi().Node_GetEpName(this->p_, &name)); + return std::string(name); +} + +} // namespace detail + +#if !defined(ORT_MINIMAL_BUILD) +// static +inline void Node::Init(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names, + std::vector& attributes, + OrtNode*& node) { + auto inputs = detail::StringsToCharPtrs(input_names); + auto outputs = detail::StringsToCharPtrs(output_names); + + std::vector attributes_ptrs; + attributes_ptrs.reserve(attributes.size()); + std::transform(attributes.begin(), attributes.end(), std::back_inserter(attributes_ptrs), + [](OpAttr& attr) -> OrtOpAttr* { return attr; }); + + ThrowOnError(GetModelEditorApi().CreateNode(operator_name.c_str(), operator_domain.c_str(), node_name.c_str(), + inputs.data(), inputs.size(), + outputs.data(), outputs.size(), + attributes_ptrs.data(), attributes_ptrs.size(), + &node)); + + // Node now owns the attributes + std::for_each(attributes.begin(), attributes.end(), [](OpAttr& attr) { attr.release(); }); +} + +inline Node::Node(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names, + std::vector& attributes) { + Init(operator_name, operator_domain, node_name, input_names, output_names, attributes, p_); +} + +inline Node::Node(const std::string& operator_name, const std::string& operator_domain, + const std::string& node_name, + const std::vector& input_names, + const std::vector& output_names) { + std::vector empty_attributes; + Init(operator_name, operator_domain, node_name, input_names, output_names, empty_attributes, p_); +} +inline ValueInfo::ValueInfo(const std::string& name, const ConstTypeInfo& type_info) { + ThrowOnError(GetModelEditorApi().CreateValueInfo(name.c_str(), type_info, &p_)); +} +#endif // !defined(ORT_MINIMAL_BUILD) + +namespace detail { +template +inline std::string ConstValueInfoImpl::GetName() const { + const char* p = nullptr; + ThrowOnError(GetApi().GetValueInfoName(this->p_, &p)); + return std::string(p); +} + +template +inline ConstTypeInfo ConstValueInfoImpl::TypeInfo() const { + const OrtTypeInfo* type_info = nullptr; + ThrowOnError(GetApi().GetValueInfoTypeInfo(this->p_, &type_info)); + return ConstTypeInfo{type_info}; +} + +template +inline ValueInfoConsumerProducerInfo ConstValueInfoImpl::GetProducerNode() const { + ValueInfoConsumerProducerInfo info; + const OrtNode* producer; + size_t index; + ThrowOnError(GetApi().ValueInfo_GetValueProducer(this->p_, &producer, &index)); + info.node = ConstNode(producer); + info.index = static_cast(index); + return info; +} + +template +inline std::vector ConstValueInfoImpl::GetConsumers() const { + size_t num = 0; + ThrowOnError(GetApi().ValueInfo_GetValueNumConsumers(this->p_, &num)); + std::vector out; + if (num > 0) { + std::vector nodes(num); + std::vector indices(num); + ThrowOnError(GetApi().ValueInfo_GetValueConsumers(this->p_, nodes.data(), indices.data(), num)); + out.reserve(num); + for (size_t i = 0; i < num; ++i) { + out.push_back({ConstNode{nodes[i]}, indices[i]}); + } + } + return out; +} + +template +inline Status ConstValueInfoImpl::GetInitializer(ConstValue& value) const { + const OrtValue* out = nullptr; + auto status = Status(GetApi().ValueInfo_GetInitializerValue(this->p_, &out)); + if (!status.IsOK()) return status; + value = ConstValue{out}; + return status; +} + +template +inline Status ConstValueInfoImpl::GetExternalInitializerInfo(ExternalInitializerInfo& info) const { + OrtExternalInitializerInfo* out = nullptr; + auto status = Status(GetApi().ValueInfo_GetExternalInitializerInfo(this->p_, &out)); + if (!status.IsOK()) return status; + info = ExternalInitializerInfo{out}; + return status; +} + +template +inline bool ConstValueInfoImpl::IsRequiredGraphInput() const { + bool out = false; + ThrowOnError(GetApi().ValueInfo_IsRequiredGraphInput(this->p_, &out)); + return out; +} + +template +inline bool ConstValueInfoImpl::IsOptionalGraphInput() const { + bool out = false; + ThrowOnError(GetApi().ValueInfo_IsOptionalGraphInput(this->p_, &out)); + return out; +} + +template +inline bool ConstValueInfoImpl::IsGraphOutput() const { + bool out = false; + ThrowOnError(GetApi().ValueInfo_IsGraphOutput(this->p_, &out)); + return out; +} + +template +inline bool ConstValueInfoImpl::IsConstantInitializer() const { + bool out = false; + ThrowOnError(GetApi().ValueInfo_IsConstantInitializer(this->p_, &out)); + return out; +} + +template +inline bool ConstValueInfoImpl::IsFromOuterScope() const { + bool out = false; + ThrowOnError(GetApi().ValueInfo_IsFromOuterScope(this->p_, &out)); + return out; +} + +template +inline ModelMetadata ConstGraphImpl::GetModelMetadata() const { + OrtModelMetadata* out; + ThrowOnError(GetApi().Graph_GetModelMetadata(this->p_, &out)); + return ModelMetadata{out}; +} + +template +inline std::string ConstGraphImpl::GetName() const { + const char* name; + ThrowOnError(GetApi().Graph_GetName(this->p_, &name)); + return std::string(name); +} + +template +inline std::basic_string ConstGraphImpl::GetModelPath() const { + const ORTCHAR_T* path; + ThrowOnError(GetApi().Graph_GetModelPath(this->p_, &path)); + return std::basic_string(path); +} + +template +inline int64_t ConstGraphImpl::GetOnnxIRVersion() const { + int64_t version; + ThrowOnError(GetApi().Graph_GetOnnxIRVersion(this->p_, &version)); + return version; +} + +template +inline std::vector ConstGraphImpl::GetOperatorSets() const { + size_t num_opsets; + ThrowOnError(GetApi().Graph_GetNumOperatorSets(this->p_, &num_opsets)); + std::vector result; + if (num_opsets > 0) { + std::vector domains; + std::vector versions; + domains.resize(num_opsets); + versions.resize(num_opsets); + ThrowOnError(GetApi().Graph_GetOperatorSets(this->p_, domains.data(), versions.data(), num_opsets)); + result.reserve(num_opsets); + for (size_t i = 0; i < num_opsets; ++i) { + result.push_back({domains[i], versions[i]}); + } + } + return result; +} + +template +inline std::vector ConstGraphImpl::GetInputs() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Graph_GetNumInputs(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Graph_GetInputs(this->p_, reinterpret_cast(result.data()), num_vi)); + } + return result; +} + +template +inline std::vector ConstGraphImpl::GetOutputs() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Graph_GetNumOutputs(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Graph_GetOutputs(this->p_, reinterpret_cast(result.data()), num_vi)); + } + return result; +} + +template +inline std::vector ConstGraphImpl::GetInitializers() const { + static_assert(sizeof(const OrtValueInfo*) == sizeof(ConstValueInfo)); + size_t num_vi; + ThrowOnError(GetApi().Graph_GetNumInitializers(this->p_, &num_vi)); + std::vector result; + if (num_vi > 0) { + result.resize(num_vi); + ThrowOnError(GetApi().Graph_GetInitializers(this->p_, reinterpret_cast(result.data()), + num_vi)); + } + return result; +} + +template +inline std::vector ConstGraphImpl::GetNodes() const { + static_assert(sizeof(const OrtNode*) == sizeof(ConstNode)); + size_t num_nodes; + ThrowOnError(GetApi().Graph_GetNumNodes(this->p_, &num_nodes)); + std::vector result; + if (num_nodes > 0) { + result.resize(num_nodes); + ThrowOnError(GetApi().Graph_GetNodes(this->p_, reinterpret_cast(result.data()), num_nodes)); + } + return result; +} + +template +inline ConstNode ConstGraphImpl::GetParentNode() const { + const OrtNode* parent; + ThrowOnError(GetApi().Graph_GetParentNode(this->p_, &parent)); + return ConstNode{parent}; +} + +template +inline Graph ConstGraphImpl::GetGraphView(const std::vector& nodes) const { + OrtGraph* graph_viewer; + std::vector inputs_ptrs; + inputs_ptrs.reserve(nodes.size()); + std::transform(nodes.begin(), nodes.end(), std::back_inserter(inputs_ptrs), + [](ConstNode n) -> const OrtNode* { return n; }); + ThrowOnError(GetApi().Graph_GetGraphView(this->p_, inputs_ptrs.data(), + nodes.size(), &graph_viewer)); + return Graph{graph_viewer}; +} + +#if !defined(ORT_MINIMAL_BUILD) +template +inline void GraphImpl::SetInputs(std::vector& inputs) { + std::vector inputs_ptrs; + inputs_ptrs.reserve(inputs.size()); + std::transform(inputs.begin(), inputs.end(), std::back_inserter(inputs_ptrs), + [](ValueInfo& vi) -> OrtValueInfo* { return vi; }); + + ThrowOnError(GetModelEditorApi().SetGraphInputs(this->p_, inputs_ptrs.data(), inputs_ptrs.size())); + + // Graph now owns the inputs + std::for_each(inputs.begin(), inputs.end(), [](ValueInfo& vi) { vi.release(); }); +} + +template +inline void GraphImpl::SetOutputs(std::vector& outputs) { + std::vector outputs_ptrs; + outputs_ptrs.reserve(outputs.size()); + std::transform(outputs.begin(), outputs.end(), std::back_inserter(outputs_ptrs), + [](ValueInfo& vi) -> OrtValueInfo* { return vi; }); + + ThrowOnError(GetModelEditorApi().SetGraphOutputs(this->p_, outputs_ptrs.data(), outputs_ptrs.size())); + + // Graph now owns the outputs + std::for_each(outputs.begin(), outputs.end(), [](ValueInfo& vi) { vi.release(); }); +} + +template +inline void GraphImpl::AddInitializer(const std::string& name, Value& initializer, bool data_is_external) { + // Graph takes ownership of `initializer` + // On error the ownership is not transferred. + ThrowOnError(GetModelEditorApi().AddInitializerToGraph(this->p_, name.c_str(), initializer, data_is_external)); + initializer.release(); +} + +template +inline void GraphImpl::AddNode(Node& node) { + // Graph takes ownership of `node` + ThrowOnError(GetModelEditorApi().AddNodeToGraph(this->p_, node.release())); +} + +template +inline void ModelImpl::AddGraph(Graph& graph) { + // Model takes ownership of `graph` + ThrowOnError(GetModelEditorApi().AddGraphToModel(this->p_, graph.release())); +} +#endif // !defined(ORT_MINIMAL_BUILD) + +} // namespace detail + +#if !defined(ORT_MINIMAL_BUILD) +inline Graph::Graph() { + ThrowOnError(GetModelEditorApi().CreateGraph(&p_)); +} + +inline Model::Model(const std::vector& opsets) { + std::vector domains; + std::vector versions; + domains.reserve(opsets.size()); + versions.reserve(opsets.size()); + + for (const auto& pair : opsets) { + domains.push_back(pair.first.c_str()); + versions.push_back(pair.second); + } + + ThrowOnError(GetModelEditorApi().CreateModel(domains.data(), versions.data(), opsets.size(), &p_)); +} +#endif + +} // namespace Ort diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_c_api.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_c_api.h new file mode 100644 index 0000000..975f6b4 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_c_api.h @@ -0,0 +1,988 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +// Do not include this file directly. Please include "onnxruntime_c_api.h" instead. + +#ifdef __cplusplus +extern "C" { +#endif + +ORT_RUNTIME_CLASS(Ep); +ORT_RUNTIME_CLASS(EpFactory); +ORT_RUNTIME_CLASS(EpGraphSupportInfo); +ORT_RUNTIME_CLASS(MemoryDevice); // opaque class to wrap onnxruntime::OrtDevice +ORT_RUNTIME_CLASS(NodeComputeContext); + +ORT_RUNTIME_CLASS(DataTransferImpl); +ORT_RUNTIME_CLASS(SyncNotificationImpl); +ORT_RUNTIME_CLASS(SyncStreamImpl); + +// struct that an EP implements for IDataTransfer to copy between devices it uses and CPU +struct OrtDataTransferImpl { + uint32_t ort_version_supported; ///< Must be initialized to ORT_API_VERSION + + /** \brief Release the OrtDataTransferImpl instance. + * + * This is called by ORT when the OrtDataTransferImpl instance is no longer needed. + * The implementation should release any resources held by the instance. + * + * \param[in] this_ptr Pointer to the OrtDataTransferImpl instance. + * + * \since Version 1.23. + */ + ORT_API_T(void, Release, _In_ OrtDataTransferImpl* this_ptr); + + /** \brief Check if the implementation can copy between the source and destination memory devices. + * + * \param[in] this_ptr Pointer to the OrtDataTransferImpl instance. + * \param[in] src_memory_device Source OrtMemoryDevice to copy from. + * \param[in] dst_memory_device Destination OrtMemoryDevice to copy to. + * \return True if the implementation can copy between the devices. + * + * \since Version 1.23. + */ + ORT_API_T(bool, CanCopy, _In_ const OrtDataTransferImpl* this_ptr, + _In_ const OrtMemoryDevice* src_memory_device, _In_ const OrtMemoryDevice* dst_memory_device); + + /** \brief Copy tensors from src_tensors to dst_tensors using the provided streams. + * + * The implementation can use the provided streams to perform asynchronous copies if supported. + * If a stream is not available, the copy is performed synchronously. + * + * \param[in] this_ptr Pointer to the OrtDataTransferImpl instance. + * \param[in] src_tensors Array of source OrtValue pointers to copy from. + * \param[in] dst_tensors Array of destination OrtValue pointers to copy to. + * \param[in] streams Array of OrtSyncStream pointers for the copy operations, if the execution provider is stream + * aware. nullptr if it is not. + * \param[in] num_tensors Number of tensors to copy. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CopyTensors, _In_ OrtDataTransferImpl* this_ptr, + _In_reads_(num_tensors) const OrtValue** src_tensors, + _In_reads_(num_tensors) OrtValue** dst_tensors, + _In_reads_(num_tensors) OrtSyncStream** streams, + _In_ size_t num_tensors); +}; + +/** \brief Struct that an EP implements for Stream Notifications. + * + * \since Version 1.23. + */ +struct OrtSyncNotificationImpl { + uint32_t ort_version_supported; ///< Must be initialized to ORT_API_VERSION + + /** \brief Release the OrtSyncNotificationImpl instance. + * + * This is called by ORT when the OrtSyncNotificationImpl instance is no longer needed. + * The implementation should release any resources held by the instance. + * + * \param[in] this_ptr Pointer to the OrtSyncNotificationImpl instance. + * + * \since Version 1.23. + */ + ORT_API_T(void, Release, _In_ OrtSyncNotificationImpl* this_ptr); + + /** \brief Called by ORT to activate the notification. + * + * \param[in] this_ptr Pointer to the OrtSyncNotificationImpl instance. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Activate, _In_ OrtSyncNotificationImpl* this_ptr); + + /** \brief Wait for a device to device operation to complete. + * + * \param[in] this_ptr Pointer to the OrtSyncNotificationImpl instance. + * \param[in] stream The OrtSyncStream instance that will wait on this notification to be activated. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(WaitOnDevice, _In_ OrtSyncNotificationImpl* this_ptr, _In_ OrtSyncStream* consumer_stream); + + /** \brief Wait for a device to host operation to complete. + * + * \param[in] this_ptr Pointer to the OrtSyncNotificationImpl instance. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(WaitOnHost, _In_ OrtSyncNotificationImpl* this_ptr); +}; + +/** \brief Struct that an EP implements if it wishes to implement Stream support. + * + * This struct provides the overrides for onnxruntime::Stream's virtual methods. + * + * \since Version 1.23. + */ +struct OrtSyncStreamImpl { + uint32_t ort_version_supported; ///< Must be initialized to ORT_API_VERSION + + /** \brief Release the OrtSyncStreamImpl instance. + * + * This is called by ORT when the OrtSyncStreamImpl instance is no longer needed. + * The implementation should release any resources held by the instance. + * + * \param[in] this_ptr Pointer to the OrtSyncStreamImpl instance. + * + * \since Version 1.23. + */ + ORT_API_T(void, Release, _In_ OrtSyncStreamImpl* this_ptr); + + /** \brief Get the handle of the stream. + * + * This returns the native handle for the stream. e.g. cudaStream_t for CUDA streams. + * + * \param[in] this_ptr Pointer to the OrtSyncStreamImpl instance. + * \return The handle of the stream. + * + * \since Version 1.23. + */ + ORT_API_T(void*, GetHandle, _In_ OrtSyncStreamImpl* this_ptr); + + /** \brief Create an OrtSyncNotificationImpl for the OrtSyncStreamImpl instance. + * + * \param[in] this_ptr Pointer to the OrtSyncStreamImpl instance + * \param[out] notification The new OrtSyncNotificationImpl instance. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateNotification, _In_ OrtSyncStreamImpl* this_ptr, + _Outptr_ OrtSyncNotificationImpl** notification); + + /** \brief Flush the stream. + * + * This is called by ORT to flush the stream, ensuring that all operations submitted to the stream are completed. + * + * \param[in] this_ptr Pointer to the OrtSyncStreamImpl instance. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Flush, _In_ OrtSyncStreamImpl* this_ptr); + + /** \brief Notify the stream that a session run has ended. + * + * This is called by ORT to notify the stream that a session run has ended, allowing the stream to perform any + * necessary cleanup or finalization. + * + * \param[in] this_ptr Pointer to the OrtSyncStreamImpl instance. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OnSessionRunEnd, _In_ OrtSyncStreamImpl* this_ptr); +}; + +struct OrtNodeFusionOptions; +typedef struct OrtNodeFusionOptions OrtNodeFusionOptions; + +struct OrtNodeComputeInfo; +typedef struct OrtNodeComputeInfo OrtNodeComputeInfo; + +/** + * \brief The OrtNodeFusionOptions struct specifies options for fusing nodes supported by an execution provider. + * + * Refer to OrtEpApi::EpGraphSupportInfo_AddNodesToFuse. + * + * \since Version 1.23. + */ +struct OrtNodeFusionOptions { + /** \brief The ONNX Runtime version the OrtNodeFusionOptions was compiled with. + * + * Implementation should set to ORT_API_VERSION. + * ORT will use this to ensure it does not use members that were not available when the EP library was compiled. + * + * \since Version 1.23. + */ + uint32_t ort_version_supported; + + /** \brief If set to true, specify that the execution provider does not require ONNX Runtime to provide constant + * initializers as inputs to the fused node during model inference. This is used when the execution + * provider saves a copy of constant initializers, and allows ONNX Runtime to release constant initializers that + * are not used by any execution provider. + * + * If not specified, defaults to false. That is, ONNX Runtime provides constant initializers as inputs to + * the fused node by default. + * + * \since Version 1.23. + */ + bool drop_constant_initializers; + + // const OrtNode* fused_node_schema; +}; + +/** + * \brief The OrtNodeComputeInfo struct provides functions that an OrtEp implements to specify the compute + * function for a compiled OrtGraph instance. + * \since Version 1.23. + */ +struct OrtNodeComputeInfo { + /** \brief The ONNX Runtime version the OrtNodeComputeInfo was compiled with. + * + * Implementation should set to ORT_API_VERSION. + * ORT will use this to ensure it does not call functions that were not available when the EP library was compiled. + * + * \since Version 1.23. + */ + uint32_t ort_version_supported; + + /** \brief Creates an opaque compute state object that is then passed to the Compute() function during inference. + * \param[in] this_ptr The OrtNodeComputeInfo instance. + * \param[in] compute_context OrtNodeComputeContext instance that contains compiled/fused node's name and host + * memory allocation functions. Can optionally be used to build the compute state. + * \param[out] compute_state Output parameter that is assigned the opaque computation state. ONNX Runtime calls + * ReleaseState() (after calling Compute()) to allow the implementer to release the + * compute state. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + OrtStatus*(ORT_API_CALL* CreateState)(_In_ OrtNodeComputeInfo* this_ptr, + _In_ OrtNodeComputeContext* compute_context, + _Outptr_ void** compute_state); + + /** \brief Computation function called to execute the fused node compiled by an OrtEp instance. + * \param[in] this_ptr The OrtNodeComputeInfo instance. + * \param[in] compute_state The opaque computation state returned by CreateState(). + * \param[in] kernel_context The OrtKernelContext instance used to access inputs/outputs. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + OrtStatus*(ORT_API_CALL* Compute)(_In_ OrtNodeComputeInfo* this_ptr, _In_ void* compute_state, + _In_ OrtKernelContext* kernel_context); + + /** \brief Releases the compute state returned by CreateState(). + * \param[in] this_ptr The OrtNodeComputeInfo instance. + * \param[inout] compute_state The opaque compute state returned by CreateState(). + * + * \since Version 1.23. + */ + void(ORT_API_CALL* ReleaseState)(_In_ OrtNodeComputeInfo* this_ptr, _Frees_ptr_opt_ void* compute_state); +}; + +struct OrtEpApi { + /** \brief Create an OrtEpDevice for the EP and an OrtHardwareDevice. + * \param[in] ep_factory Execution provider factory that is creating the instance. + * \param[in] hardware_device Hardware device that the EP can utilize. + * \param[in] ep_metadata Optional OrtKeyValuePairs instance for execution provider metadata that may be used + * during execution provider selection and passed to CreateEp. + * ep_device will copy this instance and the user should call ReleaseKeyValuePairs. + * \param[in] ep_options Optional OrtKeyValuePairs instance for execution provider options that will be added + * to the Session configuration options if the execution provider is selected. + * ep_device will copy this instance and the user should call ReleaseKeyValuePairs. + * \param ep_device OrtExecutionDevice that is created. + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateEpDevice, _In_ OrtEpFactory* ep_factory, + _In_ const OrtHardwareDevice* hardware_device, + _In_opt_ const OrtKeyValuePairs* ep_metadata, + _In_opt_ const OrtKeyValuePairs* ep_options, + _Out_ OrtEpDevice** ep_device); + + ORT_CLASS_RELEASE(EpDevice); + + /** \brief Specify nodes that are supported by an OrtEp and should be fused into one node. + * + * Because the nodes will be fused into one "fused node", there must not exist an unsupported node in + * a path between two of the provided nodes. Otherwise, the graph will become invalid. + * + * This function can be called multiple times. A subsequent call to this function will force the next set of + * nodes to be fused into a different node. + * + * \param[in] graph_support_info OrtEpGraphSupportInfo instance to which to add the supported nodes. + * \param[in] nodes Array of nodes supported by the EP that should be fused/compiled. + * \param[in] num_nodes The number of supported nodes. + * \param[in] node_fusion_options Optional node fusion options. Ignored if set to NULL. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(EpGraphSupportInfo_AddNodesToFuse, _In_ OrtEpGraphSupportInfo* graph_support_info, + _In_reads_(num_nodes) const OrtNode* const* nodes, _In_ size_t num_nodes, + _In_opt_ const OrtNodeFusionOptions* node_fusion_options); + + /** \brief Specify a node that is supported by an OrtEp and should be run with a registered EP kernel. + * + * \param[in] graph_support_info OrtEpGraphSupportInfo instance to which to add the supported node. + * \param[in] node The supported OrtNode instance. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(EpGraphSupportInfo_AddSingleNode, _In_ OrtEpGraphSupportInfo* graph_support_info, + _In_ const OrtNode* node); + + /** \brief Query a OrtNodeComputeContext for the name of the node that encapsulates the compiled/fused node. + * + * Used in OrtNodeComputeInfo::CreateComputeState(). + * + * \param[in] context The OrtNodeComputeContext instance to query. + * \return The node's name. + * + * \note Returned string is owned by ORT and valid only while OrtNodeComputeInfo::CreateComputeState() is called. + * + * \since Version 1.23. + */ + ORT_API_T(const char*, NodeComputeContext_NodeName, _In_ const OrtNodeComputeContext* context); + + /** \brief Register an allocator with the OrtEpDevice. + * + * This allows an EP to provide OrtMemoryInfo for DEFAULT and HOST_ACCESSIBLE memory type as needed. + * The registered values will be used in calls to OrtEpFactory::CreateAllocator to ensure the required allocator/s + * are available for EP usage. + * + * Multiple calls for the same entry type will replace a previous entry. + * + * Available entries: + * - OrtDeviceAllocator with type of OrtDeviceMemoryType_DEFAULT + * - OrtDeviceAllocator with type of OrtDeviceMemoryType_HOST_ACCESSIBLE + * - OrtReadOnlyAllocator with type of OrtDeviceMemoryType_DEFAULT + * - if provided this allocator will only be used to copy initializers to the device the EP uses. + * ORT will use the OrtDeviceAllocator if not provided. + * + * \param[in] ep_device The OrtEpDevice instance to register the OrtMemoryInfo with. + * \param[in] allocator_memory_info The OrtMemoryInfo information for the allocator. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(EpDevice_AddAllocatorInfo, _In_ OrtEpDevice* ep_device, + _In_ const OrtMemoryInfo* allocator_memory_info); + + /** \brief Get the OrtMemoryDevice from an OrtMemoryInfo instance. + * + * This is required for OrtDataTransferImpl (which implements onnxruntime::IDataTransfer) where the OrtMemoryDevice + * is used in the CanCopy and CopyTensors functions. + * + * \param[in] memory_info The OrtMemoryInfo instance to get the memory device from. + * \return The OrtMemoryDevice associated with the OrtMemoryInfo instance. + * + * \since Version 1.23. + */ + ORT_API_T(const OrtMemoryDevice*, MemoryInfo_GetMemoryDevice, _In_ const OrtMemoryInfo* memory_info); + + /** \brief Get the OrtMemoryDevice from an OrtValue instance if it contains a Tensor. + * + * \param[in] value The OrtValue instance to get the memory device from. + * \return Memory device if OrtValue contains a Tensor, nullptr otherwise. + * + * \since Version 1.23. + */ + ORT_API_T(const OrtMemoryDevice*, Value_GetMemoryDevice, _In_ const OrtValue* value); + + /** \brief Compare two OrtMemoryDevice instances for equality. + * + * This is used to check if two memory devices are the same. + * Used to implement DataTransferImpl::CanCopy. + * + * \param[in] a The first OrtMemoryDevice instance to compare. + * \param[in] b The second OrtMemoryDevice instance to compare. + * \return True if the two OrtMemoryDevice instances are equal, false otherwise. + * + * \since Version 1.23. + */ + ORT_API_T(bool, MemoryDevice_AreEqual, _In_ const OrtMemoryDevice* a, _In_ const OrtMemoryDevice* b); + + /** \brief Get the OrtMemoryInfoDeviceType value from an OrtMemoryDevice instance. + * + * \param[in] memory_device OrtMemoryDevice instance. + * \return The OrtMemoryInfoDeviceType value. + * + * \since Version 1.23. + */ + ORT_API_T(OrtMemoryInfoDeviceType, MemoryDevice_GetDeviceType, _In_ const OrtMemoryDevice* memory_device); + + /** \brief Get the OrtDeviceMemoryType value from an OrtMemoryDevice instance. + * + * \param[in] memory_device OrtMemoryDevice instance. + * \return The OrtDeviceMemoryType value. + * + * \since Version 1.23. + */ + ORT_API_T(OrtDeviceMemoryType, MemoryDevice_GetMemoryType, _In_ const OrtMemoryDevice* memory_device); + + /** \brief Get the vendor ID from an OrtMemoryDevice instance. + * + * The vendor ID is used to identify the vendor of the device, and is typically set to the PCI vendor ID. + * + * If the device is not vendor specific (e.g. CPU memory) the vendor ID is set to 0. + * + * \param[in] memory_device OrtMemoryDevice instance. + * \return The vendor ID value. + * + * \since Version 1.23. + */ + ORT_API_T(uint32_t, MemoryDevice_GetVendorId, _In_ const OrtMemoryDevice* memory_device); + + /** \brief Get the device ID from an OrtMemoryDevice instance. + * + * \param[in] memory_device OrtMemoryDevice instance. + * \return The device ID. + * + * \since Version 1.23. + */ + ORT_API_T(uint32_t, MemoryDevice_GetDeviceId, _In_ const OrtMemoryDevice* memory_device); + + /** \brief Get the OrtSyncStreamImpl associated with an OrtSyncStream instance. + * + * This allows an the plugin library to connect its OrtSyncStreamImpl instance with an OrtSyncStream if needed. + * + * \param[in] stream The OrtSyncStream instance to find an OrtSyncStreamImpl for. + * \return The associated OrtSyncStreamImpl if found. nullptr otherwise. + * + * \since Version 1.23. + * + * \remarks There should always be an OrtSyncStreamImpl associated with an OrtSyncStream instance that the EP gets. + */ + ORT_API_T(const OrtSyncStreamImpl*, SyncStream_GetImpl, _In_ const OrtSyncStream* stream); + + /** \brief Get the current sync ID for a stream. + * + * \param[in] stream The OrtSyncStream to get the sync ID for. + * \return Current sync ID. + * + * \since Version 1.23. + */ + ORT_API_T(uint64_t, SyncStream_GetSyncId, _In_ const OrtSyncStream* stream); + + /** \brief Get the sync ID for the last time the consumer_stream waited on the producer_stream. + * + * When two streams are synchronized, the sync id represents the event used in that synchronization. + * + * \param[in] producer_stream The OrtSyncStream that produced the data. + * \param[in] consumer_stream The OrtSyncStream that waited on the producer_stream. + * \return ID for last sync. 0 if no sync has occurred between the two streams. + * + * \since Version 1.23. + */ + ORT_API_T(uint64_t, GetSyncIdForLastWaitOnSyncStream, + _In_ const OrtSyncStream* producer_stream, _In_ const OrtSyncStream* consumer_stream); +}; + +/** + * \brief The data layout type. + * + * EPs may specify a preferred data layout type. ORT's default layout type is OrtEpDataLayout_NCHW, or + * OrtEpDataLayout_Default. + * + * \since Version 1.23. + */ +typedef enum OrtEpDataLayout { + OrtEpDataLayout_NCHW = 0, + OrtEpDataLayout_NHWC, + + OrtEpDataLayout_Default = OrtEpDataLayout_NCHW, +} OrtEpDataLayout; + +/** + * \brief The OrtEp struct provides functions to implement for an execution provider. + * \since Version 1.22. + */ +struct OrtEp { + /** \brief The ONNX Runtime version the execution provider was compiled with. + * + * Implementation should set to ORT_API_VERSION. + * ORT will use this to ensure it does not call functions that were not available when the library was compiled. + * + * \since Version 1.22. + */ + uint32_t ort_version_supported; + + /** \brief Get the execution provider name. + * + * The returned string should be a null-terminated, UTF-8 encoded string. ORT will copy it. + * + * \param[in] this_ptr The OrtEp instance. + * \return The execution provider name. + * + * \since Version 1.22. + */ + ORT_API_T(const char*, GetName, _In_ const OrtEp* this_ptr); + + /** \brief Get information about the nodes supported by the OrtEp instance. + * + * IMPORTANT: This is not the final version of this API function. This is currently experimental but will + * be stabilized by the ONNX Runtime 1.23 release. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] graph The OrtGraph instance for which to populate node support. The OrtGraph could be a nested subgraph + * contained by a node (e.g., an If or Loop node). ONNX Runtime calls this function separately + * for each nested subgraph. + * \param[inout] graph_support_info OrtEpGraphSupportInfo instance that the implementer must fill out in order to + * specify the supported nodes. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(GetCapability, _In_ OrtEp* this_ptr, _In_ const OrtGraph* graph, + _Inout_ OrtEpGraphSupportInfo* graph_support_info); + + /** \brief Compile OrtGraph instances assigned to the OrtEp. Implementer must set a OrtNodeComputeInfo instance + * for each OrtGraph in order to define its computation function. + * + * If the session is configured to generate a pre-compiled model, the execution provider must return EPContext nodes, + * as OrtNode instances, that ONNX Runtime uses to create a pre-compiled model, known as an "EPContext model". + * An EPContext model contains EPContext nodes. Each EPContext node encapsulates the pre-compiled binary data for a + * OrtGraph compiled for a specific execution provider. For more details about the EPContext design, refer to: + * \htmlonly + * EPContext design document. + * \endhtmlonly + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] graphs Array of `count` OrtGraph instances to compile. Each graph contains only the nodes for + * which the execution provider indicated support. Nested subgraphs contained by a + * node, such as an If or Loop, have separate OrtGraph instances. + * \param[in] fused_nodes Array of `count` fused nodes that will replace the compiled graphs. + * Each fused node is an OrtNode initialized with the intended fused node name and + * input/output information. + * \param[in] count The number of OrtGraph instances to compile. + * \param[out] node_compute_infos Array of `count` OrtNodeComputeInfo instances that define each OrtGraph instance's + * computation function. The implementer allocates the OrtNodeComputeInfo instances. + * ORT calls ReleaseNodeComputeInfos() to release multiple instances in a batch. + * \param[out] ep_context_nodes Output array of `count` OrtNode instances, each representing an EPContext + * node for a compiled OrtGraph. The execution provider must use + * OrtModelEditorApi::CreateNode to create the OrtNode instances. ONNX Runtime takes + * ownership of the OrtNode instances, so the execution provider must NOT call + * OrtApi::ReleaseNode. Should be ignored if the session is not configured to generate an + * EPContext model. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \note Do NOT cache the provided OrtGraph instances in any of the OrtNodeComputeInfo functions because the + * graphs are only valid for the duration of the call to Compile. Any graph/node/input/output + * names that are needed by the OrtNodeComputeInfo functions must be copied and stored by the OrtEp. + * + * \since Version 1.23. + */ + ORT_API2_STATUS(Compile, _In_ OrtEp* this_ptr, _In_ const OrtGraph** graphs, + _In_ const OrtNode** fused_nodes, _In_ size_t count, + _Out_writes_all_(count) OrtNodeComputeInfo** node_compute_infos, + _Out_writes_(count) OrtNode** ep_context_nodes); + + /** \brief Release OrtNodeComputeInfo instances. + * + * \param[in] this_ptr The OrtEp instance. + * \param[inout] node_compute_infos The OrtNodeComputeInfo instances to release. + * \param[in] num_node_compute_infos The number of OrtNodeComputeInfo instances. + * + * \since Version 1.23. + */ + ORT_API_T(void, ReleaseNodeComputeInfos, _In_ OrtEp* this_ptr, + OrtNodeComputeInfo** node_compute_infos, + _In_ size_t num_node_compute_infos); + + /** \brief Get the EP's preferred data layout. + * + * \note Implementation of this function is optional. + * If not implemented, ORT will assume that this EP prefers the data layout `OrtEpDataLayout::NCHW`. + * + * \param[in] this_ptr The OrtEp instance. + * \param[out] preferred_data_layout The EP's preferred data layout. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(GetPreferredDataLayout, _In_ OrtEp* this_ptr, _Out_ OrtEpDataLayout* preferred_data_layout); + + /** \brief Given an op with domain `domain` and type `op_type`, determine whether an associated node's data layout + * should be converted to `target_data_layout`. + * If the EP prefers a non-default data layout (see `GetPreferredDataLayout()`), this function will be called + * during layout transformation with `target_data_layout` set to the EP's preferred data layout. + * + * \note Implementation of this function is optional. + * If an EP prefers a non-default data layout, it may implement this to customize the specific op data layout + * preferences at a finer granularity. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] domain The op domain. An empty string means the ONNX domain. + * \param[in] op_type The op type. + * \param[in] target_data_layout The target data layout. + * \param[out] should_convert Whether the associated node's data layout should be converted to `target_data_layout`. + * If greater than 0, convert. + * If 0, don't convert. + * Otherwise, if less than 0, leave the decision to ORT. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ShouldConvertDataLayoutForOp, _In_ OrtEp* this_ptr, + _In_z_ const char* domain, _In_z_ const char* op_type, + _In_ OrtEpDataLayout target_data_layout, + _Outptr_ int* should_convert); + + /** \brief Set dynamic options on this EP. + * + * Dynamic options can be set by the user at any time after session creation with `OrtApi::SetEpDynamicOptions()`. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] option_keys The dynamic option keys. + * \param[in] option_values The dynamic option values. + * \param[in] num_options The number of dynamic options. + * + * \note Implementation of this function is optional. + * An EP should only implement this if it needs to handle any dynamic options. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(SetDynamicOptions, _In_ OrtEp* this_ptr, + _In_reads_(num_options) const char* const* option_keys, + _In_reads_(num_options) const char* const* option_values, + _In_ size_t num_options); + + /** \brief Called by ORT to notify the EP of the start of a run. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] run_options The run options for this run. + * + * \note Implementation of this function is optional. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OnRunStart, _In_ OrtEp* this_ptr, _In_ const OrtRunOptions* run_options); + + /** \brief Called by ORT to notify the EP of the end of a run. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] run_options The run options for this run. + * \param[in] sync_stream Whether any associated stream should be synchronized during this call. + * Only applicable if there is such a stream. + * + * \note Implementation of this function is optional. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(OnRunEnd, _In_ OrtEp* this_ptr, _In_ const OrtRunOptions* run_options, _In_ bool sync_stream); + + /** \brief Create an OrtAllocator for the given OrtMemoryInfo for an OrtSession. + * + * The OrtMemoryInfo instance will match one of the values set in the OrtEpDevice using EpDevice_AddAllocatorInfo. + * Any allocator specific options should be read from the session options. + * + * If nullptr OrtEpFactory::CreateAllocator will be used. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] memory_info The OrtMemoryInfo to create the allocator for. May be nullptr. + * \param[out] allocator The created OrtAllocator instance. Set to nullptr if the default CPU allocator is used. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateAllocator, _In_ OrtEp* this_ptr, + _In_ const OrtMemoryInfo* memory_info, + _Outptr_result_maybenull_ OrtAllocator** allocator); + + /** \brief Create a synchronization stream for the given memory device for an OrtSession. + * + * This is used to create a synchronization stream for the execution provider and is used to synchronize + * operations on the device during model execution. + * Any stream specific options should be read from the session options. + * + * If nullptr OrtEpFactory::CreateSyncStreamForDevice will be used. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] memory_device The OrtMemoryDevice to create the synchronization stream for. + * \param[out] stream The created OrtSyncStreamImpl instance. nullptr if the execution provider is not stream aware. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateSyncStreamForDevice, _In_ OrtEp* this_ptr, + _In_ const OrtMemoryDevice* memory_device, + _Outptr_ OrtSyncStreamImpl** stream); + + /** \brief Get a string with details about the EP stack used to produce a compiled model. + * + * This function gets a compatibility information string that contains details about the execution provider + * used to compile a given model. This string can later be used with ValidateCompiledModelCompatibilityInfo + * to determine if a compiled model is compatible with the EP. + * + * The returned string should be a null-terminated, UTF-8 encoded string. ORT will copy it. + * + * \param[in] this_ptr The OrtEp instance. + * \param[in] graph The OrtGraph instance for which to generate compatibility information. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API_T(const char*, GetCompiledModelCompatibilityInfo, _In_ OrtEp* this_ptr, + _In_ const OrtGraph* graph); +}; + +/** \brief The function signature that ORT will call to create OrtEpFactory instances. + * + * This must be available in a function called 'CreateEpFactories' in the execution provider library. + * + * \param[in] registered_name The name the execution library is registered with by RegisterExecutionProviderLibrary + * \param[in] ort_api_base The OrtApiBase instance that is used by the factory to get the OrtApi instance for the + * version of ORT that the library was compiled against. + * \param[in] default_logger The default ORT logger that can be used for logging outside of an inference session. + * \param[in,out] factories The implementation should create and add OrtEpFactory instances to this + * pre-allocated array. + * i.e. usage is `factories[0] = new MyEpFactory();` + * \param[in] max_factories The maximum number of OrtEpFactory instances that can be added to `factories`. + * Current default is to allow 4 factories. This can be increased in the future if needed. + * \param[out] num_factories The number of OrtEpFactory instances created by the factory and added to `factories`. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ +typedef OrtStatus* (*CreateEpApiFactoriesFn)(_In_ const char* registered_name, _In_ const OrtApiBase* ort_api_base, + _In_ const OrtLogger* default_logger, + _Inout_ OrtEpFactory** factories, _In_ size_t max_factories, + _Out_ size_t* num_factories); + +/** \brief The function signature that ORT will call to release an OrtEpFactory instance. + * + * This must be available in a function called 'ReleaseEpFactory' in the execution provider library. + * + * \param[in] factory The OrtEpFactory instance to release. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ +typedef OrtStatus* (*ReleaseEpApiFactoryFn)(_In_ OrtEpFactory* factory); + +/** + * \brief The OrtEpFactory provides functions to create and manage execution providers. + * \since Version 1.22. + */ +struct OrtEpFactory { + /** \brief The ONNX Runtime version the execution provider was compiled with. + * + * Implementation should set to ORT_API_VERSION. + * ORT will use this to ensure it does not call functions that were not available when the library was compiled. + * + * \since Version 1.22. + */ + uint32_t ort_version_supported; + + /** \brief Get the name of the execution provider that the factory creates. + * + * The returned string should be a null-terminated, UTF-8 encoded string. ORT will copy it. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \return The name of the execution provider the factory creates. + * + * \since Version 1.22. + */ + ORT_API_T(const char*, GetName, const OrtEpFactory* this_ptr); + + /** \brief Get the name of vendor who owns the execution provider that the factory creates. + * + * The returned string should be a null-terminated, UTF-8 encoded string. ORT will copy it. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \return vendor The vendor name of the execution provider the factory creates. + * + * \since Version 1.22. + */ + ORT_API_T(const char*, GetVendor, const OrtEpFactory* this_ptr); // return EP vendor + + /** \brief Get information from the execution provider about OrtHardwareDevice support. + * + * \param[in] this_ptr The OrtEpFactory instance. + * Non-const as the factory is passed through to the CreateEp call via the OrtEpDevice. + * \param[in] devices The OrtHardwareDevice instances that are available. + * \param[in] num_devices The number of OrtHardwareDevice instances. + * \param[out] ep_devices OrtEpDevice instances for each OrtHardwareDevice that the EP can use. + * The implementation should call OrtEpApi::CreateEpDevice to create, and add the OrtEpDevice + * instances to this pre-allocated array. ORT will take ownership of the values returned. + * i.e. usage is `ep_devices[0] = ;` + * \param[in] max_ep_devices The maximum number of OrtEpDevices that can be added to ep_devices. + * Current default is 8. This can be increased if needed. + * \param[out] num_ep_devices The number of EP devices added to ep_devices. + * \return true if the factory can create an execution provider that uses `device`. + * + * \since Version 1.22. + */ + ORT_API2_STATUS(GetSupportedDevices, _In_ OrtEpFactory* this_ptr, + _In_reads_(num_devices) const OrtHardwareDevice* const* devices, + _In_ size_t num_devices, + _Inout_ OrtEpDevice** ep_devices, + _In_ size_t max_ep_devices, + _Out_ size_t* num_ep_devices); + + /** \brief Function to create an OrtEp instance for use in a Session. + * + * ORT will call ReleaseEp to release the instance when it is no longer needed. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] devices The OrtHardwareDevice instances that the execution provider was selected to use. + * May be a subset of the OrtHardwareDevice instances that the execution provider's factory + * set as supported in the call to OrtEpFactory::GetSupportedDevices. + * \param[in] ep_metadata_pairs Execution provider metadata that was provided to OrtEpApi::CreateEpDevice, for each + * device. + * \param[in] num_devices The number of devices the execution provider was selected for. + * \param[in] session_options The OrtSessionOptions instance that contains the configuration options for the + * session. This will include ep_options from GetSupportedDevices as well as any + * user provided overrides. + * Execution provider options will have been added with a prefix of 'ep.[ep name].'. + * The OrtSessionOptions instance will NOT be valid after this call and should not be + * stored for later use. + * \param[in] logger The OrtLogger instance for the session that the execution provider should use for logging. + * \param[out] ep The OrtEp instance created by the factory. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.22. + */ + ORT_API2_STATUS(CreateEp, _In_ OrtEpFactory* this_ptr, + _In_reads_(num_devices) const OrtHardwareDevice* const* devices, + _In_reads_(num_devices) const OrtKeyValuePairs* const* ep_metadata_pairs, + _In_ size_t num_devices, + _In_ const OrtSessionOptions* session_options, + _In_ const OrtLogger* logger, _Outptr_ OrtEp** ep); + + /** \brief Release the OrtEp instance. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] ep The OrtEp instance to release. + * + * \since Version 1.22. + */ + ORT_API_T(void, ReleaseEp, OrtEpFactory* this_ptr, struct OrtEp* ep); + + /** \brief Get the vendor id who owns the execution provider that the factory creates. + * + * This is typically the PCI vendor ID. See https://pcisig.com/membership/member-companies + * + * \param[in] this_ptr The OrtEpFactory instance. + * \return vendor_id The vendor ID of the execution provider the factory creates. + * + * \since Version 1.23. + */ + ORT_API_T(uint32_t, GetVendorId, const OrtEpFactory* this_ptr); + + /** \brief Get the version of the execution provider that the factory creates. + * + * The version string should adhere to the Semantic Versioning 2.0 specification + * (https://github.com/semver/semver/blob/v2.0.0/semver.md). + * + * The returned string should be a null-terminated, UTF-8 encoded string. ORT will copy it. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \return The execution provider version string. + * + * \since Version 1.23. + */ + ORT_API_T(const char*, GetVersion, _In_ const OrtEpFactory* this_ptr); + + /** \brief Validate the compatibility of a compiled model with the execution provider factory for one or more devices. + * + * Given a compatibility info string produced during model compilation, the EP factory should determine whether the + * compiled model is compatible with the EP factory when targeting the provided hardware devices. All devices provided + * must belong to the same execution provider instance that this factory creates. + * + * The EP factory implementation should consider the set of devices (e.g., multi-adapter or multi-GPU scenarios) when + * evaluating compatibility and set `model_compatibility` accordingly. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] devices Array of OrtHardwareDevice pointers that the EP would run on. All must map to this EP. + * \param[in] num_devices Number of entries in `devices`. + * \param[in] compatibility_info The compatibility information string produced when the model was compiled. + * \param[out] model_compatibility OrtCompiledModelCompatibility value describing the compatibility of the model with the EP. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(ValidateCompiledModelCompatibilityInfo, _In_ OrtEpFactory* this_ptr, + _In_reads_(num_devices) const OrtHardwareDevice* const* devices, + _In_ size_t num_devices, + _In_ const char* compatibility_info, + _Out_ OrtCompiledModelCompatibility* model_compatibility); + + /** \brief Create an OrtAllocator that can be shared across sessions for the given OrtMemoryInfo. + * + * The factory that creates the EP is responsible for providing the allocators required by the EP. + * The OrtMemoryInfo instance will match one of the values set in the OrtEpDevice using EpDevice_AddAllocatorInfo. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] memory_info The OrtMemoryInfo to create the allocator for. May be nullptr. + * \param[in] allocator_options Optional key-value pairs for allocator options, can be nullptr. + * \param[out] allocator The created OrtAllocator instance. Set to nullptr if the default CPU allocator is used. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateAllocator, _In_ OrtEpFactory* this_ptr, + _In_ const OrtMemoryInfo* memory_info, + _In_opt_ const OrtKeyValuePairs* allocator_options, + _Outptr_result_maybenull_ OrtAllocator** allocator); + + /** \brief Release an OrtAllocator created by the factory. + * + * \since Version 1.23. + */ + ORT_API_T(void, ReleaseAllocator, _In_ OrtEpFactory* this_ptr, _In_ OrtAllocator* allocator); + + /** \brief Create an OrtDataTransferImpl instance for the factory. + * + * This is used to create an IDataTransfer implementation that can be used to copy data between devices + * that the execution provider supports. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[out] data_transfer The created OrtDataTransferImpl instance. Set to nullptr if not required. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateDataTransfer, _In_ OrtEpFactory* this_ptr, + _Outptr_result_maybenull_ OrtDataTransferImpl** data_transfer); + + /** \brief Check if execution providers created by the factory are stream aware. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \return True if the factory creates execution providers that are stream aware and it implements CreateSyncStreamForDevice. + * + * \since Version 1.23. + */ + ORT_API_T(bool, IsStreamAware, _In_ const OrtEpFactory* this_ptr); + + /** \brief Create a synchronization stream for the given memory device. + * + * This is used to create a synchronization stream for the memory device that can be used for operations outside of + * a session. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] memory_device The OrtMemoryDevice to create the synchronization stream for. + * \param[in] stream_options Options for stream creation. May be nullptr. + * \param[out] stream The created OrtSyncStreamImpl instance. nullptr if the execution provider is not stream aware. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.23. + */ + ORT_API2_STATUS(CreateSyncStreamForDevice, _In_ OrtEpFactory* this_ptr, + _In_ const OrtMemoryDevice* memory_device, + _In_opt_ const OrtKeyValuePairs* stream_options, + _Outptr_ OrtSyncStreamImpl** stream); +}; + +#ifdef __cplusplus +} +#endif diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_device_ep_metadata_keys.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_device_ep_metadata_keys.h new file mode 100644 index 0000000..bbd6a43 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_ep_device_ep_metadata_keys.h @@ -0,0 +1,18 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +// This file contains well-known keys for OrtEpDevice EP metadata entries. +// It does NOT specify all available metadata keys. + +// Key for the execution provider version string. This should be available for all plugin EPs. +static const char* const kOrtEpDevice_EpMetadataKey_Version = "version"; + +// Prefix for execution provider compatibility information stored in model metadata. +// Used when generating EP context models to store compatibility strings for each EP. +// Full key format: "ep_compatibility_info." +static const char* const kOrtModelMetadata_EpCompatibilityInfoPrefix = "ep_compatibility_info."; + +// Key for the execution provider library path (for dynamically loaded EPs) +static const char* const kOrtEpDevice_EpMetadataKey_LibraryPath = "library_path"; diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_float16.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_float16.h new file mode 100644 index 0000000..408d3cc --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_float16.h @@ -0,0 +1,535 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include +#include +#include +#include + +namespace onnxruntime_float16 { + +namespace detail { + +enum class endian { +#if defined(_WIN32) + little = 0, + big = 1, + native = little, +#elif defined(__GNUC__) || defined(__clang__) + little = __ORDER_LITTLE_ENDIAN__, + big = __ORDER_BIG_ENDIAN__, + native = __BYTE_ORDER__, +#else +#error onnxruntime_float16::detail::endian is not implemented in this environment. +#endif +}; + +static_assert( + endian::native == endian::little || endian::native == endian::big, + "Only little-endian or big-endian native byte orders are supported."); + +} // namespace detail + +/// +/// Shared implementation between public and internal classes. CRTP pattern. +/// +template +struct Float16Impl { + protected: + /// + /// Converts from float to uint16_t float16 representation + /// + /// + /// + constexpr static uint16_t ToUint16Impl(float v) noexcept; + + /// + /// Converts float16 to float + /// + /// float representation of float16 value + float ToFloatImpl() const noexcept; + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + uint16_t AbsImpl() const noexcept { + return static_cast(val & ~kSignMask); + } + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + uint16_t NegateImpl() const noexcept { + return IsNaN() ? val : static_cast(val ^ kSignMask); + } + + public: + // uint16_t special values + static constexpr uint16_t kSignMask = 0x8000U; + static constexpr uint16_t kBiasedExponentMask = 0x7C00U; + static constexpr uint16_t kPositiveInfinityBits = 0x7C00U; + static constexpr uint16_t kNegativeInfinityBits = 0xFC00U; + static constexpr uint16_t kPositiveQNaNBits = 0x7E00U; + static constexpr uint16_t kNegativeQNaNBits = 0xFE00U; + static constexpr uint16_t kMaxValueBits = 0x7BFFU; // Largest normal number + static constexpr uint16_t kOneBits = 0x3C00U; + static constexpr uint16_t kMinusOneBits = 0xBC00U; + + uint16_t val{0}; + + Float16Impl() = default; + + /// + /// Checks if the value is negative + /// + /// true if negative + bool IsNegative() const noexcept { + return static_cast(val) < 0; + } + + /// + /// Tests if the value is NaN + /// + /// true if NaN + bool IsNaN() const noexcept { + return AbsImpl() > kPositiveInfinityBits; + } + + /// + /// Tests if the value is finite + /// + /// true if finite + bool IsFinite() const noexcept { + return AbsImpl() < kPositiveInfinityBits; + } + + /// + /// Tests if the value represents positive infinity. + /// + /// true if positive infinity + bool IsPositiveInfinity() const noexcept { + return val == kPositiveInfinityBits; + } + + /// + /// Tests if the value represents negative infinity + /// + /// true if negative infinity + bool IsNegativeInfinity() const noexcept { + return val == kNegativeInfinityBits; + } + + /// + /// Tests if the value is either positive or negative infinity. + /// + /// True if absolute value is infinity + bool IsInfinity() const noexcept { + return AbsImpl() == kPositiveInfinityBits; + } + + /// + /// Tests if the value is NaN or zero. Useful for comparisons. + /// + /// True if NaN or zero. + bool IsNaNOrZero() const noexcept { + auto abs = AbsImpl(); + return (abs == 0 || abs > kPositiveInfinityBits); + } + + /// + /// Tests if the value is normal (not zero, subnormal, infinite, or NaN). + /// + /// True if so + bool IsNormal() const noexcept { + auto abs = AbsImpl(); + return (abs < kPositiveInfinityBits) // is finite + && (abs != 0) // is not zero + && ((abs & kBiasedExponentMask) != 0); // is not subnormal (has a non-zero exponent) + } + + /// + /// Tests if the value is subnormal (denormal). + /// + /// True if so + bool IsSubnormal() const noexcept { + auto abs = AbsImpl(); + return (abs < kPositiveInfinityBits) // is finite + && (abs != 0) // is not zero + && ((abs & kBiasedExponentMask) == 0); // is subnormal (has a zero exponent) + } + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + Derived Abs() const noexcept { return Derived::FromBits(AbsImpl()); } + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + Derived Negate() const noexcept { return Derived::FromBits(NegateImpl()); } + + /// + /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check + /// for two values by or'ing the private bits together and stripping the sign. They are both zero, + /// and therefore equivalent, if the resulting value is still zero. + /// + /// first value + /// second value + /// True if both arguments represent zero + static bool AreZero(const Float16Impl& lhs, const Float16Impl& rhs) noexcept { + return static_cast((lhs.val | rhs.val) & ~kSignMask) == 0; + } + + bool operator==(const Float16Impl& rhs) const noexcept { + if (IsNaN() || rhs.IsNaN()) { + // IEEE defines that NaN is not equal to anything, including itself. + return false; + } + return val == rhs.val; + } + + bool operator!=(const Float16Impl& rhs) const noexcept { return !(*this == rhs); } + + bool operator<(const Float16Impl& rhs) const noexcept { + if (IsNaN() || rhs.IsNaN()) { + // IEEE defines that NaN is unordered with respect to everything, including itself. + return false; + } + + const bool left_is_negative = IsNegative(); + if (left_is_negative != rhs.IsNegative()) { + // When the signs of left and right differ, we know that left is less than right if it is + // the negative value. The exception to this is if both values are zero, in which case IEEE + // says they should be equal, even if the signs differ. + return left_is_negative && !AreZero(*this, rhs); + } + return (val != rhs.val) && ((val < rhs.val) ^ left_is_negative); + } +}; + +// The following Float16_t conversions are based on the code from +// Eigen library. + +// The conversion routines are Copyright (c) Fabian Giesen, 2016. +// The original license follows: +// +// Copyright (c) Fabian Giesen, 2016 +// All rights reserved. +// Redistribution and use in source and binary forms, with or without +// modification, are permitted. +// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +namespace detail { +union float32_bits { + unsigned int u; + float f; +}; +} // namespace detail + +template +inline constexpr uint16_t Float16Impl::ToUint16Impl(float v) noexcept { + detail::float32_bits f{}; + f.f = v; + + constexpr detail::float32_bits f32infty = {255 << 23}; + constexpr detail::float32_bits f16max = {(127 + 16) << 23}; + constexpr detail::float32_bits denorm_magic = {((127 - 15) + (23 - 10) + 1) << 23}; + constexpr unsigned int sign_mask = 0x80000000u; + uint16_t val = static_cast(0x0u); + + unsigned int sign = f.u & sign_mask; + f.u ^= sign; + + // NOTE all the integer compares in this function can be safely + // compiled into signed compares since all operands are below + // 0x80000000. Important if you want fast straight SSE2 code + // (since there's no unsigned PCMPGTD). + + if (f.u >= f16max.u) { // result is Inf or NaN (all exponent bits set) + val = (f.u > f32infty.u) ? 0x7e00 : 0x7c00; // NaN->qNaN and Inf->Inf + } else { // (De)normalized number or zero + if (f.u < (113 << 23)) { // resulting FP16 is subnormal or zero + // use a magic value to align our 10 mantissa bits at the bottom of + // the float. as long as FP addition is round-to-nearest-even this + // just works. + f.f += denorm_magic.f; + + // and one integer subtract of the bias later, we have our final float! + val = static_cast(f.u - denorm_magic.u); + } else { + unsigned int mant_odd = (f.u >> 13) & 1; // resulting mantissa is odd + + // update exponent, rounding bias part 1 + // Equivalent to `f.u += ((unsigned int)(15 - 127) << 23) + 0xfff`, but + // without arithmetic overflow. + f.u += 0xc8000fffU; + // rounding bias part 2 + f.u += mant_odd; + // take the bits! + val = static_cast(f.u >> 13); + } + } + + val |= static_cast(sign >> 16); + return val; +} + +template +inline float Float16Impl::ToFloatImpl() const noexcept { + constexpr detail::float32_bits magic = {113 << 23}; + constexpr unsigned int shifted_exp = 0x7c00 << 13; // exponent mask after shift + detail::float32_bits o{}; + + o.u = (val & 0x7fff) << 13; // exponent/mantissa bits + unsigned int exp = shifted_exp & o.u; // just the exponent + o.u += (127 - 15) << 23; // exponent adjust + + // handle exponent special cases + if (exp == shifted_exp) { // Inf/NaN? + o.u += (128 - 16) << 23; // extra exp adjust + } else if (exp == 0) { // Zero/Denormal? + o.u += 1 << 23; // extra exp adjust + o.f -= magic.f; // re-normalize + } + + // Attempt to workaround the Internal Compiler Error on ARM64 + // for bitwise | operator, including std::bitset +#if (defined _MSC_VER) && (defined _M_ARM || defined _M_ARM64 || defined _M_ARM64EC) + if (IsNegative()) { + return -o.f; + } +#else + // original code: + o.u |= (val & 0x8000U) << 16U; // sign bit +#endif + return o.f; +} + +/// Shared implementation between public and internal classes. CRTP pattern. +template +struct BFloat16Impl { + protected: + /// + /// Converts from float to uint16_t float16 representation + /// + /// + /// + static uint16_t ToUint16Impl(float v) noexcept; + + /// + /// Converts bfloat16 to float + /// + /// float representation of bfloat16 value + float ToFloatImpl() const noexcept; + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + uint16_t AbsImpl() const noexcept { + return static_cast(val & ~kSignMask); + } + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + uint16_t NegateImpl() const noexcept { + return IsNaN() ? val : static_cast(val ^ kSignMask); + } + + public: + // uint16_t special values + static constexpr uint16_t kSignMask = 0x8000U; + static constexpr uint16_t kBiasedExponentMask = 0x7F80U; + static constexpr uint16_t kPositiveInfinityBits = 0x7F80U; + static constexpr uint16_t kNegativeInfinityBits = 0xFF80U; + static constexpr uint16_t kPositiveQNaNBits = 0x7FC1U; + static constexpr uint16_t kNegativeQNaNBits = 0xFFC1U; + static constexpr uint16_t kMaxValueBits = 0x7F7FU; + static constexpr uint16_t kRoundToNearest = 0x7FFFU; + static constexpr uint16_t kOneBits = 0x3F80U; + static constexpr uint16_t kMinusOneBits = 0xBF80U; + + uint16_t val{0}; + + BFloat16Impl() = default; + + /// + /// Checks if the value is negative + /// + /// true if negative + bool IsNegative() const noexcept { + return static_cast(val) < 0; + } + + /// + /// Tests if the value is NaN + /// + /// true if NaN + bool IsNaN() const noexcept { + return AbsImpl() > kPositiveInfinityBits; + } + + /// + /// Tests if the value is finite + /// + /// true if finite + bool IsFinite() const noexcept { + return AbsImpl() < kPositiveInfinityBits; + } + + /// + /// Tests if the value represents positive infinity. + /// + /// true if positive infinity + bool IsPositiveInfinity() const noexcept { + return val == kPositiveInfinityBits; + } + + /// + /// Tests if the value represents negative infinity + /// + /// true if negative infinity + bool IsNegativeInfinity() const noexcept { + return val == kNegativeInfinityBits; + } + + /// + /// Tests if the value is either positive or negative infinity. + /// + /// True if absolute value is infinity + bool IsInfinity() const noexcept { + return AbsImpl() == kPositiveInfinityBits; + } + + /// + /// Tests if the value is NaN or zero. Useful for comparisons. + /// + /// True if NaN or zero. + bool IsNaNOrZero() const noexcept { + auto abs = AbsImpl(); + return (abs == 0 || abs > kPositiveInfinityBits); + } + + /// + /// Tests if the value is normal (not zero, subnormal, infinite, or NaN). + /// + /// True if so + bool IsNormal() const noexcept { + auto abs = AbsImpl(); + return (abs < kPositiveInfinityBits) // is finite + && (abs != 0) // is not zero + && ((abs & kBiasedExponentMask) != 0); // is not subnormal (has a non-zero exponent) + } + + /// + /// Tests if the value is subnormal (denormal). + /// + /// True if so + bool IsSubnormal() const noexcept { + auto abs = AbsImpl(); + return (abs < kPositiveInfinityBits) // is finite + && (abs != 0) // is not zero + && ((abs & kBiasedExponentMask) == 0); // is subnormal (has a zero exponent) + } + + /// + /// Creates an instance that represents absolute value. + /// + /// Absolute value + Derived Abs() const noexcept { return Derived::FromBits(AbsImpl()); } + + /// + /// Creates a new instance with the sign flipped. + /// + /// Flipped sign instance + Derived Negate() const noexcept { return Derived::FromBits(NegateImpl()); } + + /// + /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check + /// for two values by or'ing the private bits together and stripping the sign. They are both zero, + /// and therefore equivalent, if the resulting value is still zero. + /// + /// first value + /// second value + /// True if both arguments represent zero + static bool AreZero(const BFloat16Impl& lhs, const BFloat16Impl& rhs) noexcept { + // IEEE defines that positive and negative zero are equal, this gives us a quick equality check + // for two values by or'ing the private bits together and stripping the sign. They are both zero, + // and therefore equivalent, if the resulting value is still zero. + return static_cast((lhs.val | rhs.val) & ~kSignMask) == 0; + } +}; + +template +inline uint16_t BFloat16Impl::ToUint16Impl(float v) noexcept { + uint16_t result; + if (std::isnan(v)) { + result = kPositiveQNaNBits; + } else { + auto get_msb_half = [](float fl) { + uint16_t result; +#ifdef __cpp_if_constexpr + if constexpr (detail::endian::native == detail::endian::little) { +#else + if (detail::endian::native == detail::endian::little) { +#endif + std::memcpy(&result, reinterpret_cast(&fl) + sizeof(uint16_t), sizeof(uint16_t)); + } else { + std::memcpy(&result, &fl, sizeof(uint16_t)); + } + return result; + }; + + uint16_t upper_bits = get_msb_half(v); + union { + uint32_t U32; + float F32; + }; + F32 = v; + U32 += (upper_bits & 1) + kRoundToNearest; + result = get_msb_half(F32); + } + return result; +} + +template +inline float BFloat16Impl::ToFloatImpl() const noexcept { + if (IsNaN()) { + return std::numeric_limits::quiet_NaN(); + } + float result; + char* const first = reinterpret_cast(&result); + char* const second = first + sizeof(uint16_t); +#ifdef __cpp_if_constexpr + if constexpr (detail::endian::native == detail::endian::little) { +#else + if (detail::endian::native == detail::endian::little) { +#endif + std::memset(first, 0, sizeof(uint16_t)); + std::memcpy(second, &val, sizeof(uint16_t)); + } else { + std::memcpy(first, &val, sizeof(uint16_t)); + std::memset(second, 0, sizeof(uint16_t)); + } + return result; +} + +} // namespace onnxruntime_float16 diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_lite_custom_op.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_lite_custom_op.h new file mode 100644 index 0000000..5002e16 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_lite_custom_op.h @@ -0,0 +1,1119 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +// Summary +// The header has APIs to save custom op authors the trouble of defining schemas, +// which will be inferred by functions' signature, as long as their argument list has types supported here. +// Input could be: +// 1. Tensor of onnx data types. +// 2. Span of onnx data types. +// 3. Scalar of onnx data types. +// A input could be optional if indicated as std::optional<...>. +// For an output, it must be a tensor of onnx data types. +// Further, the header also has utility for a simple custom struct, where resources could be kept, to be registered as a custom op. +// For concrete examples, please search keyword "LiteCustomOpTest" under "/onnxruntime/test/". +// Note - all APIs in this header are ABI. + +#pragma once +#include "onnxruntime_cxx_api.h" +#include +#include +#include +#include + +namespace Ort { +namespace Custom { + +class ArgBase { + public: + ArgBase(OrtKernelContext* ctx, + size_t indice, + bool is_input) : ctx_(ctx), indice_(indice), is_input_(is_input) {} + virtual ~ArgBase() {}; + + protected: + struct KernelContext ctx_; + size_t indice_; + bool is_input_; +}; + +using ArgPtr = std::unique_ptr; +using ArgPtrs = std::vector; + +class TensorBase : public ArgBase { + public: + TensorBase(OrtKernelContext* ctx, + size_t indice, + bool is_input) : ArgBase(ctx, indice, is_input) {} + + operator bool() const { + return shape_.has_value(); + } + + const std::vector& Shape() const { + if (!shape_.has_value()) { + ORT_CXX_API_THROW("tensor shape is not yet initialized", OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + return shape_.value(); + } + + ONNXTensorElementDataType Type() const { + return type_; + } + + int64_t NumberOfElement() const { + if (shape_.has_value()) { + return std::accumulate(shape_->begin(), shape_->end(), 1LL, std::multiplies()); + } else { + return 0; + } + } + + std::string Shape2Str() const { + if (shape_.has_value()) { + std::string shape_str; + for (const auto& dim : *shape_) { + shape_str.append(std::to_string(dim)); + shape_str.append(", "); + } + return shape_str; + } else { + return "empty"; + } + } + + bool IsCpuTensor() const { + return strcmp("Cpu", mem_type_) == 0; + } + + virtual const void* DataRaw() const = 0; + virtual size_t SizeInBytes() const = 0; + + protected: + std::optional> shape_; + ONNXTensorElementDataType type_ = ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED; + const char* mem_type_ = "Cpu"; +}; + +template +struct Span { + const T* data_ = {}; + size_t size_ = {}; + void Assign(const T* data, size_t size) { + data_ = data; + size_ = size; + } + size_t size() const { return size_; } + T operator[](size_t indice) const { + return data_[indice]; + } + const T* data() const { return data_; } +}; + +template +class Tensor : public TensorBase { + public: + using TT = typename std::remove_reference::type; + Tensor(OrtKernelContext* ctx, size_t indice, bool is_input) : TensorBase(ctx, indice, is_input) { + if (is_input_) { + if (indice >= ctx_.GetInputCount()) { + ORT_CXX_API_THROW("invalid indice for Ort::Custom::Tensor", OrtErrorCode::ORT_INVALID_ARGUMENT); + } + const_value_ = ctx_.GetInput(indice); + auto type_shape_info = const_value_.GetTensorTypeAndShapeInfo(); + shape_ = type_shape_info.GetShape(); + } + } + const TT* Data() const { + return reinterpret_cast(const_value_.GetTensorRawData()); + } + TT* Allocate(const std::vector& shape) { + shape_ = shape; + if (!data_) { + shape_ = shape; + data_ = ctx_.GetOutput(indice_, shape).template GetTensorMutableData(); + } + return data_; + } + static TT GetT() { return (TT)0; } + const Span& AsSpan() { + if (!shape_.has_value() || shape_->size() != 1) { + ORT_CXX_API_THROW("invalid shape while trying to get a span out of Ort::Custom::Tensor", + OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + span_.Assign(Data(), static_cast((*shape_)[0])); + return span_; + } + const T& AsScalar() { + if (!shape_.has_value() || shape_->size() != 1 || (*shape_)[0] != 1) { + ORT_CXX_API_THROW("invalid shape while trying to get a scalar from Ort::Custom::Tensor", + OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + return *Data(); + } + const void* DataRaw() const override { + return reinterpret_cast(Data()); + } + + size_t SizeInBytes() const override { + return sizeof(TT) * static_cast(NumberOfElement()); + } + + private: + ConstValue const_value_; // for input + TT* data_{}; // for output + Span span_; +}; + +template <> +class Tensor : public TensorBase { + public: + using strings = std::vector; + + Tensor(OrtKernelContext* ctx, size_t indice, bool is_input) : TensorBase(ctx, indice, is_input) { + if (is_input_) { + if (indice >= ctx_.GetInputCount()) { + ORT_CXX_API_THROW("invalid indice for Ort::Custom::Tensor", OrtErrorCode::ORT_INVALID_ARGUMENT); + } + auto const_value = ctx_.GetInput(indice); + auto type_shape_info = const_value.GetTensorTypeAndShapeInfo(); + shape_ = type_shape_info.GetShape(); + auto num_chars = const_value.GetStringTensorDataLength(); + // note - there will be copy ... + auto num_strings = static_cast(NumberOfElement()); + if (num_strings) { + std::vector chars(num_chars + 1, '\0'); + std::vector offsets(num_strings); + const_value.GetStringTensorContent(static_cast(chars.data()), num_chars, offsets.data(), offsets.size()); + auto upper_bound = num_strings - 1; + input_strings_.resize(num_strings); + for (size_t i = upper_bound;; --i) { + if (i < upper_bound) { + chars[offsets[i + 1]] = '\0'; + } + input_strings_[i] = chars.data() + offsets[i]; + if (0 == i) { + break; + } + } + } + } + } + const strings& Data() const { + return input_strings_; + } + const void* DataRaw() const override { + if (input_strings_.size() != 1) { + ORT_CXX_API_THROW("DataRaw() only applies to string scalar", ORT_RUNTIME_EXCEPTION); + } + return reinterpret_cast(input_strings_[0].c_str()); + } + size_t SizeInBytes() const override { + if (input_strings_.size() != 1) { + ORT_CXX_API_THROW("SizeInBytes() only applies to string scalar", ORT_RUNTIME_EXCEPTION); + } + return input_strings_[0].size(); + } + void SetStringOutput(const strings& ss, const std::vector& dims) { + shape_ = dims; + std::vector raw; + for (const auto& s : ss) { + raw.push_back(s.data()); + } + auto output = ctx_.GetOutput(indice_, dims.data(), dims.size()); + // note - there will be copy ... + output.FillStringTensor(raw.data(), raw.size()); + } + const Span& AsSpan() { + ORT_CXX_API_THROW("span for TensorT of string not implemented", OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + const std::string& AsScalar() { + if (input_strings_.size() != 1) { + ORT_CXX_API_THROW("invalid shape while trying to get a scalar string from Ort::Custom::Tensor", + OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + return input_strings_[0]; + } + + private: + std::vector input_strings_; // for input +}; + +template <> +class Tensor : public TensorBase { + public: + using strings = std::vector; + using string_views = std::vector; + + Tensor(OrtKernelContext* ctx, size_t indice, bool is_input) : TensorBase(ctx, indice, is_input) { + if (is_input_) { + if (indice >= ctx_.GetInputCount()) { + ORT_CXX_API_THROW("invalid indice for Ort::Custom::Tensor", OrtErrorCode::ORT_INVALID_ARGUMENT); + } + auto const_value = ctx_.GetInput(indice); + auto type_shape_info = const_value.GetTensorTypeAndShapeInfo(); + shape_ = type_shape_info.GetShape(); + auto num_chars = const_value.GetStringTensorDataLength(); + chars_.resize(num_chars + 1, '\0'); + auto num_strings = static_cast(NumberOfElement()); + if (num_strings) { + std::vector offsets(num_strings); + const_value.GetStringTensorContent(static_cast(chars_.data()), num_chars, offsets.data(), offsets.size()); + offsets.push_back(num_chars); + for (size_t i = 0; i < num_strings; ++i) { + input_string_views_.emplace_back(chars_.data() + offsets[i], offsets[i + 1] - offsets[i]); + } + } + } + } + const string_views& Data() const { + return input_string_views_; + } + const void* DataRaw() const override { + if (input_string_views_.size() != 1) { + ORT_CXX_API_THROW("DataRaw() only applies to string scalar", ORT_RUNTIME_EXCEPTION); + } + return reinterpret_cast(input_string_views_[0].data()); + } + size_t SizeInBytes() const override { + if (input_string_views_.size() != 1) { + ORT_CXX_API_THROW("SizeInBytes() only applies to string scalar", ORT_RUNTIME_EXCEPTION); + } + return input_string_views_[0].size(); + } + void SetStringOutput(const strings& ss, const std::vector& dims) { + shape_ = dims; + std::vector raw; + for (const auto& s : ss) { + raw.push_back(s.data()); + } + auto output = ctx_.GetOutput(indice_, dims.data(), dims.size()); + // note - there will be copy ... + output.FillStringTensor(raw.data(), raw.size()); + } + const Span& AsSpan() { + ORT_CXX_API_THROW("span for TensorT of string view not implemented", OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + std::string_view AsScalar() { + if (input_string_views_.size() != 1) { + ORT_CXX_API_THROW("invalid shape while trying to get a scalar string view from Ort::Custom::Tensor", + OrtErrorCode::ORT_RUNTIME_EXCEPTION); + } + return input_string_views_[0]; + } + + private: + std::vector chars_; // for input + std::vector input_string_views_; // for input +}; + +using TensorPtr = std::unique_ptr; +using TensorPtrs = std::vector; + +struct TensorArray : public ArgBase { + TensorArray(OrtKernelContext* ctx, + size_t start_indice, + bool is_input) : ArgBase(ctx, + start_indice, + is_input) { + if (is_input) { + auto input_count = ctx_.GetInputCount(); + for (size_t ith_input = start_indice; ith_input < input_count; ++ith_input) { + auto const_value = ctx_.GetInput(start_indice); + auto type_shape_info = const_value.GetTensorTypeAndShapeInfo(); + auto type = type_shape_info.GetElementType(); + TensorPtr tensor; + switch (type) { + case ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64: + tensor = std::make_unique>(ctx, ith_input, true); + break; + case ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING: + tensor = std::make_unique>(ctx, ith_input, true); + break; + default: + ORT_CXX_API_THROW("unknown input type", ORT_RUNTIME_EXCEPTION); + break; + } + tensors_.emplace_back(tensor.release()); + } // for + } + } + template + T* AllocateOutput(size_t ith_output, const std::vector& shape) { + // ith_output is the indice of output relative to the tensor array + // indice_ + ith_output is the indice relative to context + auto tensor = std::make_unique>(ctx_.GetOrtKernelContext(), indice_ + ith_output, false); + auto raw_output = tensor.get()->Allocate(shape); + tensors_.emplace_back(tensor.release()); + return raw_output; + } + Tensor& AllocateStringTensor(size_t ith_output) { + // ith_output is the indice of output relative to the tensor array + // indice_ + ith_output is the indice relative to context + auto tensor = std::make_unique>(ctx_.GetOrtKernelContext(), indice_ + ith_output, false); + Tensor& output = *tensor; + tensors_.emplace_back(tensor.release()); + return output; + } + size_t Size() const { + return tensors_.size(); + } + const TensorPtr& operator[](size_t ith_input) const { + // ith_input is the indice of output relative to the tensor array + return tensors_.at(ith_input); + } + + private: + TensorPtrs tensors_; +}; + +using Variadic = TensorArray; + +/* +Note: +OrtLiteCustomOp inherits from OrtCustomOp to bridge tween a custom func/struct and ort core. +The lifetime of an OrtLiteCustomOp instance is managed by customer code, not ort, so: +1. DO NOT cast OrtLiteCustomOp to OrtCustomOp and release since there is no virtual destructor in the hierarchy. +2. OrtLiteCustomFunc and OrtLiteCustomStruct, as two sub-structs, can be released in form of OrtLiteCustomOp since all members are kept in the OrtLiteCustomOp, + hence memory could still be recycled properly. +Further, OrtCustomOp is a c struct bearing no v-table, so offspring structs are by design to be of zero virtual functions to maintain cast safety. +*/ +struct OrtLiteCustomOp : public OrtCustomOp { + using ConstOptionalFloatTensor = std::optional&>; + using OptionalFloatTensor = std::optional>; + + // CreateTuple + template + static typename std::enable_if>::type + CreateTuple(OrtKernelContext*, ArgPtrs&, size_t, size_t, const std::string&) { + return std::make_tuple(); + } + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + std::tuple current = std::tuple{context}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + std::tuple current = std::tuple{*context}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + +#ifdef ORT_CUDA_CTX + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + thread_local CudaContext cuda_context; + cuda_context.Init(*context); + std::tuple current = std::tuple{cuda_context}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } +#endif + +#ifdef ORT_ROCM_CTX + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + thread_local RocmContext rocm_context; + rocm_context.Init(*context); + std::tuple current = std::tuple{rocm_context}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } +#endif + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + args.push_back(std::make_unique(context, ith_input, true)); + std::tuple current = std::tuple{reinterpret_cast(args.back().get())}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + args.push_back(std::make_unique(context, ith_input, true)); + std::tuple current = std::tuple{reinterpret_cast(*args.back().get())}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + args.push_back(std::make_unique(context, ith_output, false)); + std::tuple current = std::tuple{reinterpret_cast(args.back().get())}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + + template + static typename std::enable_if::value, std::tuple>::type + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { + args.push_back(std::make_unique(context, ith_output, false)); + std::tuple current = std::tuple{reinterpret_cast(*args.back().get())}; + auto next = CreateTuple(context, args, num_input, num_output, ep); + return std::tuple_cat(current, next); + } + +#define CREATE_TUPLE_INPUT(data_type) \ + template \ + static typename std::enable_if*>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast(args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if&>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast(*args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if*>>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if (ith_input < num_input) { \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast*>(args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } else { \ + std::tuple current = std::tuple{}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + } \ + template \ + static typename std::enable_if*>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if ("CPUExecutionProvider" != ep) { \ + ORT_CXX_API_THROW("span input could only be applied to CPU EP", OrtErrorCode::ORT_RUNTIME_EXCEPTION); \ + } \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{&reinterpret_cast*>(args.back().get())->AsSpan()}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if&>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if ("CPUExecutionProvider" != ep) { \ + ORT_CXX_API_THROW("span input could only be applied to CPU EP", OrtErrorCode::ORT_RUNTIME_EXCEPTION); \ + } \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast*>(args.back().get())->AsSpan()}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if*>>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if (ith_input < num_input) { \ + if ("CPUExecutionProvider" != ep) { \ + ORT_CXX_API_THROW("span input could only be applied to CPU EP", OrtErrorCode::ORT_RUNTIME_EXCEPTION); \ + } \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{&reinterpret_cast*>(args.back().get())->AsSpan()}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } else { \ + std::tuple current = std::tuple{}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + } \ + template \ + static typename std::enable_if::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if ("CPUExecutionProvider" != ep) { \ + ORT_CXX_API_THROW("scalar input could only be applied to CPU EP", OrtErrorCode::ORT_RUNTIME_EXCEPTION); \ + } \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast*>(args.back().get())->AsScalar()}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if (ith_input < num_input) { \ + if ("CPUExecutionProvider" != ep) { \ + ORT_CXX_API_THROW("scalar input could only be applied to CPU EP", OrtErrorCode::ORT_RUNTIME_EXCEPTION); \ + } \ + args.push_back(std::make_unique>(context, ith_input, true)); \ + std::tuple current = std::tuple{reinterpret_cast*>(args.back().get())->AsScalar()}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } else { \ + std::tuple current = std::tuple{}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + } +#define CREATE_TUPLE_OUTPUT(data_type) \ + template \ + static typename std::enable_if*>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + args.push_back(std::make_unique>(context, ith_output, false)); \ + std::tuple current = std::tuple{reinterpret_cast(args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if&>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + args.push_back(std::make_unique>(context, ith_output, false)); \ + std::tuple current = std::tuple{reinterpret_cast(*args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + template \ + static typename std::enable_if*>>::value, std::tuple>::type \ + CreateTuple(OrtKernelContext* context, ArgPtrs& args, size_t num_input, size_t num_output, const std::string& ep) { \ + if (ith_output < num_output) { \ + args.push_back(std::make_unique>(context, ith_output, false)); \ + std::tuple current = std::tuple{reinterpret_cast*>(args.back().get())}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } else { \ + std::tuple current = std::tuple{}; \ + auto next = CreateTuple(context, args, num_input, num_output, ep); \ + return std::tuple_cat(current, next); \ + } \ + } +#define CREATE_TUPLE(data_type) \ + CREATE_TUPLE_INPUT(data_type) \ + CREATE_TUPLE_OUTPUT(data_type) + + CREATE_TUPLE(bool) + CREATE_TUPLE(float) + CREATE_TUPLE(Ort::Float16_t) + CREATE_TUPLE(Ort::BFloat16_t) + CREATE_TUPLE(double) + CREATE_TUPLE(int8_t) + CREATE_TUPLE(int16_t) + CREATE_TUPLE(int32_t) + CREATE_TUPLE(int64_t) + CREATE_TUPLE(uint8_t) + CREATE_TUPLE(uint16_t) + CREATE_TUPLE(uint32_t) + CREATE_TUPLE(uint64_t) + CREATE_TUPLE(std::string) + CREATE_TUPLE_INPUT(std::string_view) + CREATE_TUPLE(Ort::Float8E4M3FN_t) + CREATE_TUPLE(Ort::Float8E4M3FNUZ_t) + CREATE_TUPLE(Ort::Float8E5M2_t) + CREATE_TUPLE(Ort::Float8E5M2FNUZ_t) + + // ParseArgs ... + template + static typename std::enable_if<0 == sizeof...(Ts)>::type + ParseArgs(std::vector&, std::vector&) { + } + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + ParseArgs(input_types, output_types); + } + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + ParseArgs(input_types, output_types); + } + +#ifdef ORT_CUDA_CTX + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + ParseArgs(input_types, output_types); + } +#endif + +#ifdef ORT_ROCM_CTX + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + ParseArgs(input_types, output_types); + } +#endif + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + input_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED); + ParseArgs(input_types, output_types); + } + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + input_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED); + ParseArgs(input_types, output_types); + } + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + output_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED); + ParseArgs(input_types, output_types); + } + + template + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type + ParseArgs(std::vector& input_types, std::vector& output_types) { + output_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED); + ParseArgs(input_types, output_types); + } + +#define PARSE_INPUT_BASE(pack_type, onnx_type) \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + input_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same>::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + input_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same>::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + input_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } + +#define PARSE_INPUT(data_type, onnx_type) \ + PARSE_INPUT_BASE(const Custom::Tensor*, onnx_type) \ + PARSE_INPUT_BASE(const Custom::Tensor&, onnx_type) \ + PARSE_INPUT_BASE(const Custom::Span*, onnx_type) \ + PARSE_INPUT_BASE(const Custom::Span&, onnx_type) \ + PARSE_INPUT_BASE(data_type, onnx_type) + +#define PARSE_OUTPUT(data_type, onnx_type) \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same*>::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + output_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same&>::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + output_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } \ + template \ + static typename std::enable_if<0 <= sizeof...(Ts) && std::is_same*>>::value>::type \ + ParseArgs(std::vector& input_types, std::vector& output_types) { \ + output_types.push_back(onnx_type); \ + ParseArgs(input_types, output_types); \ + } + +#define PARSE_ARGS(data_type, onnx_type) \ + PARSE_INPUT(data_type, onnx_type) \ + PARSE_OUTPUT(data_type, onnx_type) + + PARSE_ARGS(bool, ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL) + PARSE_ARGS(float, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + PARSE_ARGS(Ort::Float16_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16) + PARSE_ARGS(Ort::BFloat16_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16) + PARSE_ARGS(double, ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE) + PARSE_ARGS(int8_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8) + PARSE_ARGS(int16_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16) + PARSE_ARGS(int32_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32) + PARSE_ARGS(int64_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64) + PARSE_ARGS(uint8_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8) + PARSE_ARGS(uint16_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16) + PARSE_ARGS(uint32_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32) + PARSE_ARGS(uint64_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64) + PARSE_ARGS(std::string, ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING) + PARSE_ARGS(std::string_view, ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING) // todo - remove string_view output + PARSE_ARGS(Ort::Float8E4M3FN_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FN) + PARSE_ARGS(Ort::Float8E4M3FNUZ_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FNUZ) + PARSE_ARGS(Ort::Float8E5M2_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2) + PARSE_ARGS(Ort::Float8E5M2FNUZ_t, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2FNUZ) + + OrtLiteCustomOp(const char* op_name, + const char* execution_provider, + ShapeInferFn shape_infer_fn, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) : op_name_(op_name), + execution_provider_(execution_provider), + shape_infer_fn_(shape_infer_fn), + start_ver_(start_ver), + end_ver_(end_ver) { + OrtCustomOp::version = ORT_API_VERSION; + + OrtCustomOp::GetName = [](const OrtCustomOp* op) { return static_cast(op)->op_name_.c_str(); }; + OrtCustomOp::GetExecutionProviderType = [](const OrtCustomOp* op) { return ((OrtLiteCustomOp*)op)->execution_provider_.c_str(); }; + OrtCustomOp::GetInputMemoryType = [](const OrtCustomOp*, size_t) { return OrtMemTypeDefault; }; + + OrtCustomOp::GetInputTypeCount = [](const OrtCustomOp* op) { + auto self = reinterpret_cast(op); + return self->input_types_.size(); + }; + + OrtCustomOp::GetInputType = [](const OrtCustomOp* op, size_t indice) { + auto self = reinterpret_cast(op); + return self->input_types_[indice]; + }; + + OrtCustomOp::GetOutputTypeCount = [](const OrtCustomOp* op) { + auto self = reinterpret_cast(op); + return self->output_types_.size(); + }; + + OrtCustomOp::GetOutputType = [](const OrtCustomOp* op, size_t indice) { + auto self = reinterpret_cast(op); + return self->output_types_[indice]; + }; + + OrtCustomOp::GetInputCharacteristic = [](const OrtCustomOp* op, size_t indice) { + auto self = reinterpret_cast(op); + return self->input_types_[indice] == ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED ? INPUT_OUTPUT_VARIADIC : INPUT_OUTPUT_OPTIONAL; + }; + + OrtCustomOp::GetOutputCharacteristic = [](const OrtCustomOp* op, size_t indice) { + auto self = reinterpret_cast(op); + return self->output_types_[indice] == ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED ? INPUT_OUTPUT_VARIADIC : INPUT_OUTPUT_OPTIONAL; + }; + + OrtCustomOp::GetVariadicInputMinArity = [](const OrtCustomOp*) { + return 1; + }; + + OrtCustomOp::GetVariadicInputHomogeneity = [](const OrtCustomOp*) { + return 0; + }; + + OrtCustomOp::GetVariadicOutputMinArity = [](const OrtCustomOp*) { + return 1; + }; + + OrtCustomOp::GetVariadicOutputHomogeneity = [](const OrtCustomOp*) { + return 0; + }; + + OrtCustomOp::GetVariadicInputMinArity = [](const OrtCustomOp*) { return 0; }; + OrtCustomOp::GetVariadicInputHomogeneity = [](const OrtCustomOp*) { return 0; }; + OrtCustomOp::GetVariadicOutputMinArity = [](const OrtCustomOp*) { return 0; }; + OrtCustomOp::GetVariadicOutputHomogeneity = [](const OrtCustomOp*) { return 0; }; + + OrtCustomOp::CreateKernelV2 = {}; + OrtCustomOp::KernelComputeV2 = {}; + OrtCustomOp::KernelCompute = {}; + + OrtCustomOp::InferOutputShapeFn = {}; + + OrtCustomOp::GetStartVersion = [](const OrtCustomOp* op) { + auto self = reinterpret_cast(op); + return self->start_ver_; + }; + + OrtCustomOp::GetEndVersion = [](const OrtCustomOp* op) { + auto self = reinterpret_cast(op); + return self->end_ver_; + }; + + OrtCustomOp::GetMayInplace = {}; + OrtCustomOp::ReleaseMayInplace = {}; + OrtCustomOp::GetAliasMap = {}; + OrtCustomOp::ReleaseAliasMap = {}; + } + + const std::string op_name_; + const std::string execution_provider_; + + std::vector input_types_; + std::vector output_types_; + + ShapeInferFn shape_infer_fn_ = {}; + + int start_ver_ = 1; + int end_ver_ = MAX_CUSTOM_OP_END_VER; + + void* compute_fn_ = {}; + void* compute_fn_return_status_ = {}; +}; + +//////////////////////////// OrtLiteCustomFunc //////////////////////////////// +// The struct is to implement function-as-op. +// E.g. a function might be defined as: +// void Filter(const Ort::Custom::Tensor& floats_in, Ort::Custom::Tensor& floats_out) { ... } +// It could be registered this way: +// Ort::CustomOpDomain v2_domain{"v2"}; +// std::unique_ptr fil_op_ptr{Ort::Custom::CreateLiteCustomOp("Filter", "CPUExecutionProvider", Filter)}; +// v2_domain.Add(fil_op_ptr.get()); +// session_options.Add(v2_domain); +// For the complete example, please search keyword "LiteCustomOpTest" under "/onnxruntime/test/". +template +struct OrtLiteCustomFunc : public OrtLiteCustomOp { + using ComputeFn = void (*)(Args...); + using ComputeFnReturnStatus = Status (*)(Args...); + using MyType = OrtLiteCustomFunc; + + struct Kernel { + size_t num_input_{}; + size_t num_output_{}; + ComputeFn compute_fn_{}; + ComputeFnReturnStatus compute_fn_return_status_{}; + std::string ep_{}; + }; + + OrtLiteCustomFunc(const char* op_name, + const char* execution_provider, + ComputeFn compute_fn, + ShapeInferFn shape_infer_fn = {}, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) : OrtLiteCustomOp(op_name, execution_provider, shape_infer_fn, start_ver, end_ver) { + compute_fn_ = reinterpret_cast(compute_fn); + ParseArgs(input_types_, output_types_); + + OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) { + auto kernel = reinterpret_cast(op_kernel); + std::vector args; + auto t = CreateTuple<0, 0, Args...>(context, args, kernel->num_input_, kernel->num_output_, kernel->ep_); + std::apply([kernel](Args const&... t_args) { kernel->compute_fn_(t_args...); }, t); + }; + + OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* ort_api, const OrtKernelInfo* info) { + auto kernel = std::make_unique(); + auto me = static_cast(this_); + kernel->compute_fn_ = reinterpret_cast(me->compute_fn_); + Ort::ThrowOnError(ort_api->KernelInfo_GetInputCount(info, &kernel->num_input_)); + Ort::ThrowOnError(ort_api->KernelInfo_GetOutputCount(info, &kernel->num_output_)); + auto self = static_cast(this_); + kernel->ep_ = self->execution_provider_; + return reinterpret_cast(kernel.release()); + }; + + OrtCustomOp::KernelDestroy = [](void* op_kernel) { + delete reinterpret_cast(op_kernel); + }; + + if (shape_infer_fn_) { + OrtCustomOp::InferOutputShapeFn = [](const OrtCustomOp* op, OrtShapeInferContext* ort_ctx) -> OrtStatusPtr { + auto shape_info_fn = static_cast(op)->shape_infer_fn_; + ShapeInferContext ctx(&GetApi(), ort_ctx); + return shape_info_fn(ctx); + }; + } + } + + OrtLiteCustomFunc(const char* op_name, + const char* execution_provider, + ComputeFnReturnStatus compute_fn_return_status, + ShapeInferFn shape_infer_fn = {}, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) : OrtLiteCustomOp(op_name, execution_provider, shape_infer_fn, start_ver, end_ver) { + compute_fn_return_status_ = reinterpret_cast(compute_fn_return_status); + ParseArgs(input_types_, output_types_); + + OrtCustomOp::KernelComputeV2 = [](void* op_kernel, OrtKernelContext* context) -> OrtStatusPtr { + auto kernel = reinterpret_cast(op_kernel); + std::vector args; + auto t = CreateTuple<0, 0, Args...>(context, args, kernel->num_input_, kernel->num_output_, kernel->ep_); + return std::apply([kernel](Args const&... t_args) { Status status = kernel->compute_fn_return_status_(t_args...); return status.release(); }, t); + }; + + OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* ort_api, const OrtKernelInfo* info) { + auto kernel = std::make_unique(); + auto me = static_cast(this_); + kernel->compute_fn_return_status_ = reinterpret_cast(me->compute_fn_return_status_); + Ort::ThrowOnError(ort_api->KernelInfo_GetInputCount(info, &kernel->num_input_)); + Ort::ThrowOnError(ort_api->KernelInfo_GetOutputCount(info, &kernel->num_output_)); + auto self = static_cast(this_); + kernel->ep_ = self->execution_provider_; + return reinterpret_cast(kernel.release()); + }; + + OrtCustomOp::KernelDestroy = [](void* op_kernel) { + delete reinterpret_cast(op_kernel); + }; + + if (shape_infer_fn_) { + OrtCustomOp::InferOutputShapeFn = [](const OrtCustomOp* op, OrtShapeInferContext* ort_ctx) -> OrtStatusPtr { + auto shape_info_fn = static_cast(op)->shape_infer_fn_; + ShapeInferContext ctx(&GetApi(), ort_ctx); + return shape_info_fn(ctx); + }; + } + } +}; // struct OrtLiteCustomFunc + +/////////////////////////// OrtLiteCustomStruct /////////////////////////// +// The struct is to implement struct-as-op. +// E.g. a struct might be defined as: +// struct Merge { +// Merge(const OrtApi* ort_api, const OrtKernelInfo* info) {...} +// void Compute(const Ort::Custom::Tensor& strings_in, +// std::string_view string_in, +// Ort::Custom::Tensor* strings_out) {...} +// bool reverse_ = false; +// }; +// It could be registered this way: +// Ort::CustomOpDomain v2_domain{"v2"}; +// std::unique_ptr mrg_op_ptr{Ort::Custom::CreateLiteCustomOp("Merge", "CPUExecutionProvider")}; +// v2_domain.Add(mrg_op_ptr.get()); +// session_options.Add(v2_domain); +// For the complete example, please search keyword "LiteCustomOpTest" under "/onnxruntime/test/". +template +struct OrtLiteCustomStruct : public OrtLiteCustomOp { + template + using CustomComputeFn = void (CustomOp::*)(Args...); + + template + using CustomComputeFnReturnStatus = Status (CustomOp::*)(Args...); + + using MyType = OrtLiteCustomStruct; + + struct Kernel { + size_t num_input_{}; + size_t num_output_{}; + std::unique_ptr custom_op_; + std::string ep_{}; + }; + + OrtLiteCustomStruct(const char* op_name, + const char* execution_provider, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) : OrtLiteCustomOp(op_name, execution_provider, {}, start_ver, end_ver) { + SetCompute(&CustomOp::Compute); + + OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* ort_api, const OrtKernelInfo* info) { + auto kernel = std::make_unique(); + Ort::ThrowOnError(ort_api->KernelInfo_GetInputCount(info, &kernel->num_input_)); + Ort::ThrowOnError(ort_api->KernelInfo_GetOutputCount(info, &kernel->num_output_)); + kernel->custom_op_ = std::make_unique(ort_api, info); + auto self = static_cast(this_); + kernel->ep_ = self->execution_provider_; + return reinterpret_cast(kernel.release()); + }; + + OrtCustomOp::KernelDestroy = [](void* op_kernel) { + delete reinterpret_cast(op_kernel); + }; + + SetShapeInfer(0); + } + + template + void SetCompute(CustomComputeFn) { + ParseArgs(input_types_, output_types_); + OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) { + auto kernel = reinterpret_cast(op_kernel); + ArgPtrs args; + auto t = CreateTuple<0, 0, Args...>(context, args, kernel->num_input_, kernel->num_output_, kernel->ep_); + std::apply([kernel](Args const&... t_args) { kernel->custom_op_->Compute(t_args...); }, t); + }; + } + + template + void SetCompute(CustomComputeFnReturnStatus) { + ParseArgs(input_types_, output_types_); + OrtCustomOp::KernelComputeV2 = [](void* op_kernel, OrtKernelContext* context) -> OrtStatusPtr { + auto kernel = reinterpret_cast(op_kernel); + ArgPtrs args; + auto t = CreateTuple<0, 0, Args...>(context, args, kernel->num_input_, kernel->num_output_, kernel->ep_); + return std::apply([kernel](Args const&... t_args) { Status status = kernel->custom_op_->Compute(t_args...); return status.release(); }, t); + }; + } + + template + decltype(&C::InferOutputShape) SetShapeInfer(decltype(&C::InferOutputShape)) { + OrtCustomOp::InferOutputShapeFn = [](const OrtCustomOp*, OrtShapeInferContext* ort_ctx) -> OrtStatusPtr { + ShapeInferContext ctx(&GetApi(), ort_ctx); + return C::InferOutputShape(ctx); + }; + return {}; + } + + template + void SetShapeInfer(...) { + OrtCustomOp::InferOutputShapeFn = {}; + } +}; // struct OrtLiteCustomStruct + +/////////////////////////// CreateLiteCustomOp //////////////////////////// + +template +OrtLiteCustomOp* CreateLiteCustomOp(const char* op_name, + const char* execution_provider, + void (*custom_compute_fn)(Args...), + Status (*shape_infer_fn)(ShapeInferContext&) = {}, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) { + using LiteOp = OrtLiteCustomFunc; + return std::make_unique(op_name, execution_provider, custom_compute_fn, shape_infer_fn, start_ver, end_ver).release(); +} + +template +OrtLiteCustomOp* CreateLiteCustomOp(const char* op_name, + const char* execution_provider, + Status (*custom_compute_fn_v2)(Args...), + Status (*shape_infer_fn)(ShapeInferContext&) = {}, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) { + using LiteOp = OrtLiteCustomFunc; + return std::make_unique(op_name, execution_provider, custom_compute_fn_v2, shape_infer_fn, start_ver, end_ver).release(); +} + +template +OrtLiteCustomOp* CreateLiteCustomOp(const char* op_name, + const char* execution_provider, + int start_ver = 1, + int end_ver = MAX_CUSTOM_OP_END_VER) { + using LiteOp = OrtLiteCustomStruct; + return std::make_unique(op_name, execution_provider, start_ver, end_ver).release(); +} + +} // namespace Custom +} // namespace Ort diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_run_options_config_keys.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_run_options_config_keys.h new file mode 100644 index 0000000..f40ea65 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_run_options_config_keys.h @@ -0,0 +1,54 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +/* + * This file defines RunOptions Config Keys and format of the Config Values. + * + * The Naming Convention for a RunOptions Config Key, + * "[Area][.[SubArea1].[SubArea2]...].[Keyname]" + * Such as "ep.cuda.use_arena" + * The Config Key cannot be empty + * The maximum length of the Config Key is 128 + * + * The string format of a RunOptions Config Value is defined individually for each Config. + * The maximum length of the Config Value is 1024 + */ + +// Key for enabling shrinkages of user listed device memory arenas. +// Expects a list of semi-colon separated key value pairs separated by colon in the following format: +// "device_0:device_id_0;device_1:device_id_1" +// No white-spaces allowed in the provided list string. +// Currently, the only supported devices are : "cpu", "gpu" (case sensitive). +// If "cpu" is included in the list, DisableCpuMemArena() API must not be called (i.e.) arena for cpu should be enabled. +// Example usage: "cpu:0;gpu:0" (or) "gpu:0" +// By default, the value for this key is empty (i.e.) no memory arenas are shrunk +static const char* const kOrtRunOptionsConfigEnableMemoryArenaShrinkage = "memory.enable_memory_arena_shrinkage"; + +// Set to '1' to not synchronize execution providers with CPU at the end of session run. +// Per default it will be set to '0' +// Taking CUDA EP as an example, it omit triggering cudaStreamSynchronize on the compute stream. +static const char* const kOrtRunOptionsConfigDisableSynchronizeExecutionProviders = "disable_synchronize_execution_providers"; + +// Set HTP performance mode for QNN HTP backend before session run. +// options for HTP performance mode: "burst", "balanced", "default", "high_performance", +// "high_power_saver", "low_balanced", "extreme_power_saver", "low_power_saver", "power_saver", +// "sustained_high_performance". Default to "default". +static const char* const kOrtRunOptionsConfigQnnPerfMode = "qnn.htp_perf_mode"; + +// Set HTP performance mode for QNN HTP backend post session run. +static const char* const kOrtRunOptionsConfigQnnPerfModePostRun = "qnn.htp_perf_mode_post_run"; + +// Set RPC control latency for QNN HTP backend +static const char* const kOrtRunOptionsConfigQnnRpcControlLatency = "qnn.rpc_control_latency"; + +// Set QNN Lora Config File for apply Lora in QNN context binary +static const char* const kOrtRunOptionsConfigQnnLoraConfig = "qnn.lora_config"; + +// Set graph annotation id for CUDA EP. Use with enable_cuda_graph=true. +// The value should be an integer. If the value is not set, the default value is 0 and +// ORT session only captures one cuda graph before another capture is requested. +// If the value is set to -1, cuda graph capture/replay is disabled in that run. +// User are not expected to set the value to 0 as it is reserved for internal use. +static const char* const kOrtRunOptionsConfigCudaGraphAnnotation = "gpu_graph_id"; diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_session_options_config_keys.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_session_options_config_keys.h new file mode 100644 index 0000000..64a434e --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/onnxruntime_session_options_config_keys.h @@ -0,0 +1,417 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +/* + * This file defines SessionOptions Config Keys and format of the Config Values. + * + * The Naming Convention for a SessionOptions Config Key, + * "[Area][.[SubArea1].[SubArea2]...].[Keyname]" + * Such as "ep.cuda.use_arena" + * The Config Key cannot be empty + * The maximum length of the Config Key is 1024 + * + * The string format of a SessionOptions Config Value is defined individually for each Config. + * The maximum length of the Config Value is 2048 + */ + +// Key for disable PrePacking, +// If the config value is set to "1" then the prepacking is disabled, otherwise prepacking is enabled (default value) +static const char* const kOrtSessionOptionsConfigDisablePrepacking = "session.disable_prepacking"; + +// A value of "1" means allocators registered in the env will be used. "0" means the allocators created in the session +// will be used. Use this to override the usage of env allocators on a per session level. +static const char* const kOrtSessionOptionsConfigUseEnvAllocators = "session.use_env_allocators"; + +// Set to 'ORT' (case sensitive) to load an ORT format model. +// If unset, model type will default to ONNX unless inferred from filename ('.ort' == ORT format) or bytes to be ORT +static const char* const kOrtSessionOptionsConfigLoadModelFormat = "session.load_model_format"; + +// Set to 'ORT' (case sensitive) to save optimized model in ORT format when SessionOptions.optimized_model_path is set. +// If unset, format will default to ONNX unless optimized_model_filepath ends in '.ort'. +static const char* const kOrtSessionOptionsConfigSaveModelFormat = "session.save_model_format"; + +// If a value is "1", flush-to-zero and denormal-as-zero are applied. The default is "0". +// When multiple sessions are created, a main thread doesn't override changes from succeeding session options, +// but threads in session thread pools follow option changes. +// When ORT runs with OpenMP, the same rule is applied, i.e. the first session option to flush-to-zero and +// denormal-as-zero is only applied to global OpenMP thread pool, which doesn't support per-session thread pool. +// Note that an alternative way not using this option at runtime is to train and export a model without denormals +// and that's recommended because turning this option on may hurt model accuracy. +static const char* const kOrtSessionOptionsConfigSetDenormalAsZero = "session.set_denormal_as_zero"; + +// It controls to run quantization model in QDQ (QuantizelinearDeQuantizelinear) format or not. +// "0": enable. ORT does fusion logic for QDQ format. +// "1": disable. ORT doesn't do fusion logic for QDQ format. +// Its default value is "0" unless the DirectML execution provider is registered, in which case it defaults to "1". +static const char* const kOrtSessionOptionsDisableQuantQDQ = "session.disable_quant_qdq"; + +// It controls whether to enable Double QDQ remover and Identical Children Consolidation +// "0": not to disable. ORT does remove the middle 2 Nodes from a Q->(QD->Q)->QD pairs +// "1": disable. ORT doesn't remove the middle 2 Nodes from a Q->(QD->Q)->QD pairs +// Its default value is "0" +static const char* const kOrtSessionOptionsDisableDoubleQDQRemover = "session.disable_double_qdq_remover"; + +// If set to "1", enables the removal of QuantizeLinear/DequantizeLinear node pairs once all QDQ handling has been +// completed. e.g. If after all QDQ handling has completed and we have -> FloatOp -> Q -> DQ -> FloatOp -> the +// Q -> DQ could potentially be removed. This will provide a performance benefit by avoiding going from float to +// 8-bit and back to float, but could impact accuracy. The impact on accuracy will be model specific and depend on +// other factors like whether the model was created using Quantization Aware Training or Post Training Quantization. +// As such, it's best to test to determine if enabling this works well for your scenario. +// The default value is "0" +// Available since version 1.11. +static const char* const kOrtSessionOptionsEnableQuantQDQCleanup = "session.enable_quant_qdq_cleanup"; + +// Enable or disable gelu approximation in graph optimization. "0": disable; "1": enable. The default is "0". +// GeluApproximation has side effects which may change the inference results. It is disabled by default due to this. +static const char* const kOrtSessionOptionsEnableGeluApproximation = "optimization.enable_gelu_approximation"; + +// Enable or disable Cast chain elimination in graph optimization. "0": disable; "1": enable. The default is "0". +// CastElimination with chain elimination has side effects which may change the inference results. It is disabled by default due to this. +static const char* const kOrtSessionOptionsEnableCastChainElimination = "optimization.enable_cast_chain_elimination"; + +// This setting controls whether to enable AheadOfTime function inlining. +// AOT function inlining examines the graph and attempts to inline as many locally defined functions in the model +// as possible with the help of enabled execution providers. +// This can reduce the number of function calls and improve performance because it is done before +// Level1 optimizers and constant folding. However, under some circumstances, when the EPs are not available, +// one can disable the AOT inlining, produce an optimized model and postpone AOT until run time. +// "0": enable; "1": disable. +// Its default value is "0". +static const char* const kOrtSessionOptionsDisableAheadOfTimeFunctionInlining = "session.disable_aot_function_inlining"; + +#ifdef ENABLE_TRAINING +// Specifies a path of the file containing a list of memory optimization configurations. +// The value should be a string indicating the file path of the config file. +// The content of the config file is a JSON struct like this: +// [ +// "Gelu+Cast+:1:0", +// "Dropout+:1:1" +// ] +// Taking the example of "Gelu+Cast+:1:0", +// > "Gelu+Cast+" is the subgraph string, a valid "subgraph string" should be one subgraph representation +// output by ORT graph transformations. +// > "1" is "optimization strategy", valid values: 0 - disabled, 1 - recompute. +// > "0" is "number of subgraph to apply" which is used to control how many subgraphs to apply optimization, +// to avoid "oversaving" the memory. +static const char* const kOrtSessionOptionsMemoryOptimizerApplyConfig = "optimization.memory_optimizer_config"; + +// Specifies the config for detecting subgraphs for memory footprint reduction. +// The value should be a string contains int separated using commas. The default value is "0:0". +static const char* const kOrtSessionOptionsMemoryOptimizerProbeConfig = "optimization.enable_memory_probe_recompute_config"; +#endif + +// This setting if set should contain a comma separated list of optimizers names that should be disabled. +// Optimizers may take time to execute and affect model loading time. If you feel that a specific optimizer +// does not provider runtime benefits, but affects your model loading time you may disable it using this config +// entry. This option is not enabled in ORT_MINIMAL_BUILD build. +// A list of optimizes is available in onnxruntime/core/optimizer/graph_transformer_utils.cc +// +// Default is an empty string which means no optimizers are disabled. +static const char* const kOrtSessionOptionsDisableSpecifiedOptimizers = "optimization.disable_specified_optimizers"; + +// It controls whether to run graph optimizations in loop or not. +// +// "0": disable. Graph Optimization Loop is disabled. +// ``` +// Level 2 --> Level 3 --> InsertCastTransforms --> Level 4 +// ^ | +// | "No Loop" | +// | | +// X xxxxxxxxxxx X +// ``` +// "1": enable. Graph Optimization Loop is enabled, such that, if optimizations at Level 4 are applied then +// the loop will check for any other valid optimization that can happen. +// ``` +// Level 2 --> Level 3 --> InsertCastTransforms --> Level 4 +// ^ | +// | "Loop only depending on Level 4" | +// | | +// --------------------------------------------------- +// ``` +// "2": enable. Graph Optimization Loop is enabled, such that, if optimizations at Level 2 or above are applied then +// The loop will check for any other valid optimization that can happen. +// ``` +// Level 2 --> Level 3 --> InsertCastTransforms --> Level 4 +// ^ | +// | "Loop" | +// | | +// --------------------------------------------------- +// ``` +// Default value is set to "1". +static const char* const kOrtSessionOptionsGraphOptimizationsLoopLevel = "session.graph_optimizations_loop_level"; + +// Enable or disable using device allocator for allocating initialized tensor memory. "1": enable; "0": disable. The default is "0". +// Using device allocators means the memory allocation is made using malloc/new. +static const char* const kOrtSessionOptionsUseDeviceAllocatorForInitializers = "session.use_device_allocator_for_initializers"; + +// Configure whether to allow the inter_op/intra_op threads spinning a number of times before blocking +// "0": thread will block if found no job to run +// "1": thread will spin a number of times before blocking +// The default is "0" when ORT is built with "ORT_CLIENT_PACKAGE_BUILD" and "1" otherwise. +// Thread spinning is disabled by default for client/on-device workloads to reduce cpu utilization and improve power efficiency. +static const char* const kOrtSessionOptionsConfigAllowInterOpSpinning = "session.inter_op.allow_spinning"; +static const char* const kOrtSessionOptionsConfigAllowIntraOpSpinning = "session.intra_op.allow_spinning"; + +// Key for using model bytes directly for ORT format +// If a session is created using an input byte array contains the ORT format model data, +// By default we will copy the model bytes at the time of session creation to ensure the model bytes +// buffer is valid. +// Setting this option to "1" will disable copy the model bytes, and use the model bytes directly. The caller +// has to guarantee that the model bytes are valid until the ORT session using the model bytes is destroyed. +static const char* const kOrtSessionOptionsConfigUseORTModelBytesDirectly = "session.use_ort_model_bytes_directly"; + +/// +/// Key for using the ORT format model flatbuffer bytes directly for initializers. +/// This avoids copying the bytes and reduces peak memory usage during model loading and initialization. +/// Requires `session.use_ort_model_bytes_directly` to be true. +/// If set, the flatbuffer bytes provided when creating the InferenceSession MUST remain valid for the entire +/// duration of the InferenceSession. +/// +static const char* const kOrtSessionOptionsConfigUseORTModelBytesForInitializers = + "session.use_ort_model_bytes_for_initializers"; + +// This should only be specified when exporting an ORT format model for use on a different platform. +// If the ORT format model will be used on ARM platforms set to "1". For other platforms set to "0" +// Available since version 1.11. +static const char* const kOrtSessionOptionsQDQIsInt8Allowed = "session.qdqisint8allowed"; + +// x64 SSE4.1/AVX2/AVX512(with no VNNI) has overflow problem with quantizied matrix multiplication with U8S8. +// To avoid this we need to use slower U8U8 matrix multiplication instead. This option, if +// turned on, use slower U8U8 matrix multiplications. Only effective with AVX2 or AVX512 +// platforms. +static const char* const kOrtSessionOptionsAvx2PrecisionMode = "session.x64quantprecision"; + +// Specifies how minimal build graph optimizations are handled in a full build. +// These optimizations are at the extended level or higher. +// Possible values and their effects are: +// "save": Save runtime optimizations when saving an ORT format model. +// "apply": Only apply optimizations available in a minimal build. +// ""/: Apply optimizations available in a full build. +// Available since version 1.11. +static const char* const kOrtSessionOptionsConfigMinimalBuildOptimizations = + "optimization.minimal_build_optimizations"; + +// Note: The options specific to an EP should be specified prior to appending that EP to the session options object in +// order for them to take effect. + +// Specifies a list of stop op types. Nodes of a type in the stop op types and nodes downstream from them will not be +// run by the NNAPI EP. +// The value should be a ","-delimited list of op types. For example, "Add,Sub". +// If not specified, the default set of stop ops is used. To specify an empty stop ops types list and disable stop op +// exclusion, set the value to "". +static const char* const kOrtSessionOptionsConfigNnapiEpPartitioningStopOps = "ep.nnapi.partitioning_stop_ops"; + +// Enabling dynamic block-sizing for multithreading. +// With a positive value, thread pool will split a task of N iterations to blocks of size starting from: +// N / (num_of_threads * dynamic_block_base) +// As execution progresses, the size will decrease according to the diminishing residual of N, +// meaning the task will be distributed in smaller granularity for better parallelism. +// For some models, it helps to reduce the variance of E2E inference latency and boost performance. +// The feature will not function by default, specify any positive integer, e.g. "4", to enable it. +// Available since version 1.11. +static const char* const kOrtSessionOptionsConfigDynamicBlockBase = "session.dynamic_block_base"; + +// This option allows to decrease CPU usage between infrequent +// requests and forces any TP threads spinning stop immediately when the last of +// concurrent Run() call returns. +// Spinning is restarted on the next Run() call. +// Applies only to internal thread-pools +static const char* const kOrtSessionOptionsConfigForceSpinningStop = "session.force_spinning_stop"; + +// "1": all inconsistencies encountered during shape and type inference +// will result in failures. +// "0": in some cases warnings will be logged but processing will continue. The default. +// May be useful to expose bugs in models. +static const char* const kOrtSessionOptionsConfigStrictShapeTypeInference = "session.strict_shape_type_inference"; + +// "1": every model using a more recent opset than the latest released one will fail +// "0": the model may or may not work if onnxruntime cannot find an implementation, this option +// is used for development purpose. +static const char* const kOrtSessionOptionsConfigStrictAllowReleasedOpsetsOnly = "session.allow_released_opsets_only"; + +// The file saves configuration for partitioning node among logic streams +static const char* const kNodePartitionConfigFile = "session.node_partition_config_file"; + +// This Option allows setting affinities for intra op threads. +// Affinity string follows format: +// logical_processor_id,logical_processor_id;logical_processor_id,logical_processor_id +// Semicolon isolates configurations among threads, while comma split processors where ith thread expected to attach to. +// e.g.1,2,3;4,5 +// specifies affinities for two threads, with the 1st thread attach to the 1st, 2nd, and 3rd processor, and 2nd thread to the 4th and 5th. +// To ease the configuration, an "interval" is also allowed: +// e.g. 1-8;8-16;17-24 +// orders that the 1st thread runs on first eight processors, 2nd thread runs on next eight processors, and so forth. +// Note: +// 1. Once set, the number of thread affinities must equal to intra_op_num_threads - 1, since ort does not set affinity on the main thread which +// is started and managed by the calling app; +// 2. For windows, ort will infer the group id from a logical processor id, for example, assuming there are two groups with each has 64 logical processors, +// an id of 64 will be inferred as the last processor of the 1st group, while 65 will be interpreted as the 1st processor of the second group. +// Hence 64-65 is an invalid configuration, because a windows thread cannot be attached to processors across group boundary. +static const char* const kOrtSessionOptionsConfigIntraOpThreadAffinities = "session.intra_op_thread_affinities"; + +// This option will dump out the model to assist debugging any issues with layout transformation, +// and is primarily intended for developer usage. It is only relevant if an execution provider that requests +// NHWC layout is enabled such as NNAPI, XNNPACK or QNN. +// +// Default is off. Set to "1" to enable. +// +// If modified by layout transformation the model will be dumped after these steps: +// 1) insertion of the layout transformation Transpose nodes +// 2) after those are optimized using the transpose optimizer, +// 3) after the L1 transformers are applied to the updated graph. +// The model will be saved to filename post_layout_transform_step_.onnx. +static const char* const kDebugLayoutTransformation = "session.debug_layout_transformation"; + +// Graph nodes that are not supported by the execution providers (EPs) explicitly added to the session are +// assigned (i.e., "fallback") to the CPU EP by default. +// +// This option allows the user to disable the fallback of unsupported graph nodes to the CPU EP. +// If this option is set to "1", session creation will fail if the execution providers other than the CPU EP cannot +// fully support all of the nodes in the graph. +// +// It is invalid to set this option and explicitly add the CPU EP to the session. In this case, session creation +// will also fail with an error. +// +// Option values: +// - "0": CPU EP fallback is not disabled. [DEFAULT] +// - "1": CPU EP fallback is disabled. +static const char* const kOrtSessionOptionsDisableCPUEPFallback = "session.disable_cpu_ep_fallback"; + +// Use this config when serializing a large model after optimization to specify an external initializers file +static const char* const kOrtSessionOptionsOptimizedModelExternalInitializersFileName = + "session.optimized_model_external_initializers_file_name"; + +// Use this config to control the minimum size of the initializer when externalizing it during serialization +static const char* const kOrtSessionOptionsOptimizedModelExternalInitializersMinSizeInBytes = + "session.optimized_model_external_initializers_min_size_in_bytes"; + +// When loading model from memory buffer and the model has external initializers +// Use this config to set the external data file folder path +// All external data files should be in the same folder +static const char* const kOrtSessionOptionsModelExternalInitializersFileFolderPath = + "session.model_external_initializers_file_folder_path"; + +// Use this config when saving pre-packed constant initializers to an external data file. +// This allows you to memory map pre-packed initializers on model load and leave it to +// to the OS the amount of memory consumed by the pre-packed initializers. Otherwise, +// pre-packed data resides on the heap. +// +// - "0": Default is not save pre-packed initializers to a data file. +// - "1": Save pre-packed constant initializers to an external data file. +// Sample usage: sess_options.add_session_config_entry(kOrtSessionOptionsSavePrePackedConstantInitializers, "1") +static const char* const kOrtSessionOptionsSavePrePackedConstantInitializers = + "session.save_external_prepacked_constant_initializers"; + +// Use this config when you want to collect memory stats for each node in the graph. +// The file format is a CSV file with the following columns: +// The file will be created if it does not exist, and will be overwritten if it does. +// +// The content of the file can be used to estimate memory requirements at run time including +// the temporary allocations. This operation is preferably done on a CPU device, as the model may exceed +// device memory limits in constrained environments. When enabling this option, it is important to disable +// memory patterns, as they tend to allocate large blocks to avoid fragmentation and accommodate needs of multiple +// kernels. Memory patterns may make it difficult to allocate on a device with limited memory. +// +// The collected stats then can be used to partition the graph among the devices in a way that only the +// required memory is allocated on each device. +// +// node_name, initializers_memory, dynamic_outputs_sizes, temp_allocations_size +// +// - "full path to file": there is not a default for this option. If the file can not be opened for writing, an error will be returned. +static const char* const kOrtSessionOptionsCollectNodeMemoryStatsToFile = "session.collect_node_memory_stats_to_file"; + +/// This is a composite CSV setting formatted as "memory limit in kb,file name for collected stats" +/// "limit > 0": enables Capacity Aware Partitioning for Cuda EP. `limit` is optional and when absent +/// the provider may attempt to figure out the memory available automatically. +/// The setting with no limit is expected to look like: ",file name for collected stats" +/// The EP will place nodes on device "file name" : +/// this file is expected to be found at the same folder with the model. The file contains +/// pre-recorded stats collected when running with kOrtSessionOptionsCollectNodeMemoryStatsToFile enforce (see above) +static const char* const kOrtSessionOptionsResourceCudaPartitioningSettings = + "session.resource_cuda_partitioning_settings"; + +// Enable EP context feature to dump the partitioned graph which includes the EP context into Onnx file. +// The dumped Onnx model with EP context can be used for future inference to avoid the EP graph partitioning/compile overhead. +// "0": disable. (default) +// "1": enable. +static const char* const kOrtSessionOptionEpContextEnable = "ep.context_enable"; + +// Specify the file path for the Onnx model which has EP context. +// Default to original_file_name_ctx.onnx if not specified +// Folder is not a valid option +static const char* const kOrtSessionOptionEpContextFilePath = "ep.context_file_path"; + +// Flag to specify whether to dump the EP context into the Onnx model. +// "0": dump the EP context into separate file, keep the file name in the Onnx model. (default). +// "1": dump the EP context into the Onnx model. +static const char* const kOrtSessionOptionEpContextEmbedMode = "ep.context_embed_mode"; + +// Specify the EPContext node name prefix to make it unique +// in case user need to merge/connect multiple EPContext nodes in one model +static const char* const kOrtSessionOptionEpContextNodeNamePrefix = "ep.context_node_name_prefix"; + +// Share EP related resources across sessions +static const char* const kOrtSessionOptionShareEpContexts = "ep.share_ep_contexts"; + +// Stop to share EP related resources across sessions from then on +static const char* const kOrtSessionOptionStopShareEpContexts = "ep.stop_share_ep_contexts"; + +// Used only for context model generation. +// This configuration is used when some nodes are partitioned on the CPU EP and those nodes have external initializers. +// When generating the EP context model, the new model should not rely on the old external data file used by the source ONNX model. +// Use this setting when dumping the EP context model with an external initializers file. +// If specified, all initializers will be placed inside the external data file. +// Otherwise, all initializers will be embedded inside the generated ONNX file. +// By default, this option is not set, meaning all initializers will be included within the ONNX file. +static const char* const kOrtSessionOptionsEpContextModelExternalInitializersFileName = + "ep.context_model_external_initializers_file_name"; + +// Gemm fastmath mode provides fp32 gemm acceleration with bfloat16 based matmul. +// Option values: +// - "0": Gemm FastMath mode is not enabled. [DEFAULT] +// - "1": Gemm FastMath mode is enabled. +static const char* const kOrtSessionOptionsMlasGemmFastMathArm64Bfloat16 = "mlas.enable_gemm_fastmath_arm64_bfloat16"; + +// When converting DQ + MatMul -> MatMulNBits, the accuracy level of the MatMulNBits is controlled by this option. +// Refer to MatMulNBits op schema for more details. +// If not provided, default is 4. +static const char* const kOrtSessionOptionsQDQMatMulNBitsAccuracyLevel = "session.qdq_matmulnbits_accuracy_level"; + +// THIS OPTION IS NOT A REGULAR SESSION OPTION SINCE IT CAN BE MODIFIED AT ANY TIME +// Meant to be used with SetEpDynamicOptions +// Specify the type of workload for this session. +// "Default": OS determines the scheduling priority and processor performance to service this workload. [Default] +// "Efficient": OS treats this workload is efficiency oriented with low scheduling priority and efficient processor performance. +static const char* const kOrtEpDynamicOptionsWorkloadType = "ep.dynamic.workload_type"; + +// Disables model compilation during session initialization. +// +// If this option is set to "1", inference session creation will fail with error code ORT_MODEL_REQUIRES_COMPILATION +// if compilation is required to run the model on any Execution Provider added to the session. +// Only the following kinds of models are valid when this option is set to "1": +// - Pre-compiled models that have EPContext nodes for the compiling Execution Providers in the session. +// - Non-compiled models that run only on non-compiling Execution Providers, like CPU EP. +// +// See \href https://onnxruntime.ai/docs/execution-providers/EP-Context-Design.html for details about +// compiled models with EPContext nodes. +// +// Option values: +// - "0": EP compile is not disabled. [DEFAULT] +// - "1": EP compile is disabled. +static const char* const kOrtSessionOptionsDisableModelCompile = "session.disable_model_compile"; + +// Controls behavior when compiled model compatibility is SUPPORTED_PREFER_RECOMPILATION. +// "0": Allow execution with suboptimal performance. [DEFAULT] +// "1": Fail session creation to require recompilation for optimal performance. +// Note: UNSUPPORTED models always fail regardless of this setting. +static const char* const kOrtSessionOptionsFailOnSuboptimalCompiledModel = + "session.fail_on_suboptimal_compiled_model"; + +// THIS OPTION IS NOT A REGULAR SESSION OPTION SINCE IT CAN BE MODIFIED AT ANY TIME +// Meant to be used with SetEpDynamicOptions +// options for HTP performance mode: "burst", "balanced", "default", "high_performance", +// "high_power_saver", "low_balanced", "extreme_power_saver", "low_power_saver", "power_saver", +// "sustained_high_performance". Default to "default". +static const char* const kOrtEpDynamicOptionsQnnHtpPerformanceMode = "ep.dynamic.qnn_htp_performance_mode"; diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/provider_options.h b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/provider_options.h new file mode 100644 index 0000000..aab13e8 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/include/provider_options.h @@ -0,0 +1,18 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include +#include +#include + +namespace onnxruntime { + +// data types for execution provider options + +using ProviderOptions = std::unordered_map; +using ProviderOptionsVector = std::vector; +using ProviderOptionsMap = std::unordered_map; + +} // namespace onnxruntime diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfig.cmake b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfig.cmake new file mode 100644 index 0000000..7d52998 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfig.cmake @@ -0,0 +1,26 @@ + +####### Expanded from @PACKAGE_INIT@ by configure_package_config_file() ####### +####### Any changes to this file will be overwritten by the next CMake run #### +####### The input file was PROJECT_CONFIG_FILE ######## + +get_filename_component(PACKAGE_PREFIX_DIR "${CMAKE_CURRENT_LIST_DIR}/../../../" ABSOLUTE) + +macro(set_and_check _var _file) + set(${_var} "${_file}") + if(NOT EXISTS "${_file}") + message(FATAL_ERROR "File or directory ${_file} referenced by variable ${_var} does not exist !") + endif() +endmacro() + +macro(check_required_components _NAME) + foreach(comp ${${_NAME}_FIND_COMPONENTS}) + if(NOT ${_NAME}_${comp}_FOUND) + if(${_NAME}_FIND_REQUIRED_${comp}) + set(${_NAME}_FOUND FALSE) + endif() + endif() + endforeach() +endmacro() + +#################################################################################### +include("${CMAKE_CURRENT_LIST_DIR}/onnxruntimeTargets.cmake") diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfigVersion.cmake b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfigVersion.cmake new file mode 100644 index 0000000..fb66f4b --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeConfigVersion.cmake @@ -0,0 +1,65 @@ +# This is a basic version file for the Config-mode of find_package(). +# It is used by write_basic_package_version_file() as input file for configure_file() +# to create a version-file which can be installed along a config.cmake file. +# +# The created file sets PACKAGE_VERSION_EXACT if the current version string and +# the requested version string are exactly the same and it sets +# PACKAGE_VERSION_COMPATIBLE if the current version is >= requested version, +# but only if the requested major version is the same as the current one. +# The variable CVF_VERSION must be set before calling configure_file(). + + +set(PACKAGE_VERSION "1.23.2") + +if(PACKAGE_VERSION VERSION_LESS PACKAGE_FIND_VERSION) + set(PACKAGE_VERSION_COMPATIBLE FALSE) +else() + + if("1.23.2" MATCHES "^([0-9]+)\\.") + set(CVF_VERSION_MAJOR "${CMAKE_MATCH_1}") + if(NOT CVF_VERSION_MAJOR VERSION_EQUAL 0) + string(REGEX REPLACE "^0+" "" CVF_VERSION_MAJOR "${CVF_VERSION_MAJOR}") + endif() + else() + set(CVF_VERSION_MAJOR "1.23.2") + endif() + + if(PACKAGE_FIND_VERSION_RANGE) + # both endpoints of the range must have the expected major version + math (EXPR CVF_VERSION_MAJOR_NEXT "${CVF_VERSION_MAJOR} + 1") + if (NOT PACKAGE_FIND_VERSION_MIN_MAJOR STREQUAL CVF_VERSION_MAJOR + OR ((PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "INCLUDE" AND NOT PACKAGE_FIND_VERSION_MAX_MAJOR STREQUAL CVF_VERSION_MAJOR) + OR (PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "EXCLUDE" AND NOT PACKAGE_FIND_VERSION_MAX VERSION_LESS_EQUAL CVF_VERSION_MAJOR_NEXT))) + set(PACKAGE_VERSION_COMPATIBLE FALSE) + elseif(PACKAGE_FIND_VERSION_MIN_MAJOR STREQUAL CVF_VERSION_MAJOR + AND ((PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "INCLUDE" AND PACKAGE_VERSION VERSION_LESS_EQUAL PACKAGE_FIND_VERSION_MAX) + OR (PACKAGE_FIND_VERSION_RANGE_MAX STREQUAL "EXCLUDE" AND PACKAGE_VERSION VERSION_LESS PACKAGE_FIND_VERSION_MAX))) + set(PACKAGE_VERSION_COMPATIBLE TRUE) + else() + set(PACKAGE_VERSION_COMPATIBLE FALSE) + endif() + else() + if(PACKAGE_FIND_VERSION_MAJOR STREQUAL CVF_VERSION_MAJOR) + set(PACKAGE_VERSION_COMPATIBLE TRUE) + else() + set(PACKAGE_VERSION_COMPATIBLE FALSE) + endif() + + if(PACKAGE_FIND_VERSION STREQUAL PACKAGE_VERSION) + set(PACKAGE_VERSION_EXACT TRUE) + endif() + endif() +endif() + + +# if the installed or the using project don't have CMAKE_SIZEOF_VOID_P set, ignore it: +if("${CMAKE_SIZEOF_VOID_P}" STREQUAL "" OR "8" STREQUAL "") + return() +endif() + +# check that the installed version has the same 32/64bit-ness as the one which is currently searching: +if(NOT CMAKE_SIZEOF_VOID_P STREQUAL "8") + math(EXPR installedBits "8 * 8") + set(PACKAGE_VERSION "${PACKAGE_VERSION} (${installedBits}bit)") + set(PACKAGE_VERSION_UNSUITABLE TRUE) +endif() diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets-release.cmake b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets-release.cmake new file mode 100644 index 0000000..6c8522c --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets-release.cmake @@ -0,0 +1,19 @@ +#---------------------------------------------------------------- +# Generated CMake target import file for configuration "Release". +#---------------------------------------------------------------- + +# Commands may need to know the format version. +set(CMAKE_IMPORT_FILE_VERSION 1) + +# Import target "onnxruntime::onnxruntime" for configuration "Release" +set_property(TARGET onnxruntime::onnxruntime APPEND PROPERTY IMPORTED_CONFIGURATIONS RELEASE) +set_target_properties(onnxruntime::onnxruntime PROPERTIES + IMPORTED_LOCATION_RELEASE "${_IMPORT_PREFIX}/lib64/libonnxruntime.so.1.23.2" + IMPORTED_SONAME_RELEASE "libonnxruntime.so.1" + ) + +list(APPEND _cmake_import_check_targets onnxruntime::onnxruntime ) +list(APPEND _cmake_import_check_files_for_onnxruntime::onnxruntime "${_IMPORT_PREFIX}/lib64/libonnxruntime.so.1.23.2" ) + +# Commands beyond this point should not need to know the version. +set(CMAKE_IMPORT_FILE_VERSION) diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets.cmake b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets.cmake new file mode 100644 index 0000000..3a373d0 --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/cmake/onnxruntime/onnxruntimeTargets.cmake @@ -0,0 +1,106 @@ +# Generated by CMake + +if("${CMAKE_MAJOR_VERSION}.${CMAKE_MINOR_VERSION}" LESS 2.8) + message(FATAL_ERROR "CMake >= 2.8.3 required") +endif() +if(CMAKE_VERSION VERSION_LESS "2.8.3") + message(FATAL_ERROR "CMake >= 2.8.3 required") +endif() +cmake_policy(PUSH) +cmake_policy(VERSION 2.8.3...3.29) +#---------------------------------------------------------------- +# Generated CMake target import file. +#---------------------------------------------------------------- + +# Commands may need to know the format version. +set(CMAKE_IMPORT_FILE_VERSION 1) + +# Protect against multiple inclusion, which would fail when already imported targets are added once more. +set(_cmake_targets_defined "") +set(_cmake_targets_not_defined "") +set(_cmake_expected_targets "") +foreach(_cmake_expected_target IN ITEMS onnxruntime::onnxruntime) + list(APPEND _cmake_expected_targets "${_cmake_expected_target}") + if(TARGET "${_cmake_expected_target}") + list(APPEND _cmake_targets_defined "${_cmake_expected_target}") + else() + list(APPEND _cmake_targets_not_defined "${_cmake_expected_target}") + endif() +endforeach() +unset(_cmake_expected_target) +if(_cmake_targets_defined STREQUAL _cmake_expected_targets) + unset(_cmake_targets_defined) + unset(_cmake_targets_not_defined) + unset(_cmake_expected_targets) + unset(CMAKE_IMPORT_FILE_VERSION) + cmake_policy(POP) + return() +endif() +if(NOT _cmake_targets_defined STREQUAL "") + string(REPLACE ";" ", " _cmake_targets_defined_text "${_cmake_targets_defined}") + string(REPLACE ";" ", " _cmake_targets_not_defined_text "${_cmake_targets_not_defined}") + message(FATAL_ERROR "Some (but not all) targets in this export set were already defined.\nTargets Defined: ${_cmake_targets_defined_text}\nTargets not yet defined: ${_cmake_targets_not_defined_text}\n") +endif() +unset(_cmake_targets_defined) +unset(_cmake_targets_not_defined) +unset(_cmake_expected_targets) + + +# Compute the installation prefix relative to this file. +get_filename_component(_IMPORT_PREFIX "${CMAKE_CURRENT_LIST_FILE}" PATH) +get_filename_component(_IMPORT_PREFIX "${_IMPORT_PREFIX}" PATH) +get_filename_component(_IMPORT_PREFIX "${_IMPORT_PREFIX}" PATH) +get_filename_component(_IMPORT_PREFIX "${_IMPORT_PREFIX}" PATH) +if(_IMPORT_PREFIX STREQUAL "/") + set(_IMPORT_PREFIX "") +endif() + +# Create imported target onnxruntime::onnxruntime +add_library(onnxruntime::onnxruntime SHARED IMPORTED) + +set_target_properties(onnxruntime::onnxruntime PROPERTIES + INTERFACE_INCLUDE_DIRECTORIES "${_IMPORT_PREFIX}/include/onnxruntime" +) + +# Load information for each installed configuration. +file(GLOB _cmake_config_files "${CMAKE_CURRENT_LIST_DIR}/onnxruntimeTargets-*.cmake") +foreach(_cmake_config_file IN LISTS _cmake_config_files) + include("${_cmake_config_file}") +endforeach() +unset(_cmake_config_file) +unset(_cmake_config_files) + +# Cleanup temporary variables. +set(_IMPORT_PREFIX) + +# Loop over all imported files and verify that they actually exist +foreach(_cmake_target IN LISTS _cmake_import_check_targets) + if(CMAKE_VERSION VERSION_LESS "3.28" + OR NOT DEFINED _cmake_import_check_xcframework_for_${_cmake_target} + OR NOT IS_DIRECTORY "${_cmake_import_check_xcframework_for_${_cmake_target}}") + foreach(_cmake_file IN LISTS "_cmake_import_check_files_for_${_cmake_target}") + if(NOT EXISTS "${_cmake_file}") + message(FATAL_ERROR "The imported target \"${_cmake_target}\" references the file + \"${_cmake_file}\" +but this file does not exist. Possible reasons include: +* The file was deleted, renamed, or moved to another location. +* An install or uninstall procedure did not complete successfully. +* The installation package was faulty and contained + \"${CMAKE_CURRENT_LIST_FILE}\" +but not all the files it references. +") + endif() + endforeach() + endif() + unset(_cmake_file) + unset("_cmake_import_check_files_for_${_cmake_target}") +endforeach() +unset(_cmake_target) +unset(_cmake_import_check_targets) + +# This file does not depend on other imported targets which have +# been exported from the same project but in a separate export set. + +# Commands beyond this point should not need to know the version. +set(CMAKE_IMPORT_FILE_VERSION) +cmake_policy(POP) diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1 b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1 new file mode 120000 index 0000000..a7c97da --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1 @@ -0,0 +1 @@ +libonnxruntime.so.1.23.2 \ No newline at end of file diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1.23.2 b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1.23.2 new file mode 100755 index 0000000..64ef20a Binary files /dev/null and b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/libonnxruntime.so.1.23.2 differ diff --git a/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/pkgconfig/libonnxruntime.pc b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/pkgconfig/libonnxruntime.pc new file mode 100644 index 0000000..b68eb1c --- /dev/null +++ b/prebuilt_libs/onnxruntime-linux-x64-1.23.2/lib/pkgconfig/libonnxruntime.pc @@ -0,0 +1,13 @@ +prefix=/usr/local +bindir=${prefix}/bin +mandir=${prefix}/share/man +docdir=${prefix}/share/doc/onnxruntime +libdir=${prefix}/lib64 +includedir=${prefix}/include/onnxruntime + +Name: onnxruntime +Description: ONNX runtime +URL: https://github.com/microsoft/onnxruntime +Version: 1.23.2 +Libs: -L${libdir} -lonnxruntime +Cflags: -I${includedir} diff --git a/src/main/java/com/bonus/sdk/YoloSdk.java b/src/main/java/com/bonus/sdk/YoloSdk.java index a2a644b..9d74a7f 100644 --- a/src/main/java/com/bonus/sdk/YoloSdk.java +++ b/src/main/java/com/bonus/sdk/YoloSdk.java @@ -1,5 +1,4 @@ -// -package com.bonus.sdk; +package com.bonus.sdk; // import java.awt.image.BufferedImage; import java.awt.image.DataBufferByte; @@ -11,11 +10,9 @@ import java.util.Set; public class YoloSdk implements AutoCloseable { - private long nativeHandle; // + private long nativeHandle; private static final Set loadedLibraries = new HashSet<>(); - /** - * */ static { try { loadSdkLibrary(); @@ -27,45 +24,56 @@ public class YoloSdk implements AutoCloseable { private static void loadSdkLibrary() throws IOException { String osName = System.getProperty("os.name").toLowerCase(); String osArch = System.getProperty("os.arch").toLowerCase(); - String libPathInJar, sdkLibName; - String[] dependencyLibs = {}; // + String libPathInJar; + String sdkLibName; + String[] dependencyLibs = {}; if (osName.contains("win") && osArch.contains("64")) { + libPathInJar = "/lib/win-x64/"; dependencyLibs = new String[]{ - "onnxruntime.dll", - "abseil_dll.dll", - "libprotobuf.dll", - "zlib1.dll", - "opencv_core4.dll", - "opencv_imgproc4.dll", - "opencv_dnn4.dll" - }; + "onnxruntime.dll", + "abseil_dll.dll", + "libprotobuf.dll", + "zlib1.dll", + "opencv_core4.dll", + "opencv_imgproc4.dll", + "opencv_dnn4.dll" + + }; + sdkLibName = "my_yolo_sdk.dll"; + } else if ((osName.contains("nix") || osName.contains("nux")) && osArch.contains("64")) { + libPathInJar = "/lib/linux-x86_64/"; - // - // + + dependencyLibs = new String[]{ + "libonnxruntime.so.1.23.2", + "libopencv_core.so.4.6.0", + "libopencv_imgproc.so.4.6.0", + "libopencv_dnn.so.4.6.0" + }; + sdkLibName = "libmy_yolo_sdk.so"; + } else { throw new UnsupportedOperationException("Unsupported OS/Arch: " + osName + "/" + osArch); } - // 1. for (String lib : dependencyLibs) { loadLibraryFromJar(libPathInJar + lib); } - // 2. + loadLibraryFromJar(libPathInJar + sdkLibName); } - /** - * */ + private static void loadLibraryFromJar(String path) throws IOException { String libName = new File(path).getName(); if (loadedLibraries.contains(libName)) { - return; // + return; } try (InputStream in = YoloSdk.class.getResourceAsStream(path)) { @@ -82,7 +90,6 @@ public class YoloSdk implements AutoCloseable { } } - // --- private native long nativeInit(String modelPath, int inputWidth, int inputHeight); private native void nativeRelease(long handle); private native Detection[] nativePredict( @@ -117,8 +124,6 @@ public class YoloSdk implements AutoCloseable { } } - /** - * */ private byte[] getBgrBytes(BufferedImage image) { if (image.getType() == BufferedImage.TYPE_3BYTE_BGR) { return ((DataBufferByte) image.getRaster().getDataBuffer()).getData();