diff options
| author | Stanislaw Halik <sthalik@misaki.pl> | 2021-08-29 02:27:01 +0200 |
|---|---|---|
| committer | Stanislaw Halik <sthalik@misaki.pl> | 2021-08-29 02:47:55 +0200 |
| commit | aa284ed32b6058dd664ba5abd84e1d3f21b71598 (patch) | |
| tree | be42a20bcfe1d5170704ed190dc1adf8ae258876 /onnxruntime-1.8.1 | |
| parent | 3181a9f6c85c93bed2cfa3f0ab217cada438bcb1 (diff) | |
add onnxruntime
Diffstat (limited to 'onnxruntime-1.8.1')
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/cpu_provider_factory.h | 19 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/cuda_provider_factory.h | 61 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/onnxruntime_c_api.h | 1439 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_api.h | 650 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_inline.h | 1038 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/onnxruntime_run_options_config_keys.h | 27 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/onnxruntime_session_options_config_keys.h | 62 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/build/native/include/provider_options.h | 18 | ||||
| -rw-r--r-- | onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.dll | bin | 0 -> 5936008 bytes | |||
| -rw-r--r-- | onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.lib | bin | 0 -> 2146 bytes |
10 files changed, 3314 insertions, 0 deletions
diff --git a/onnxruntime-1.8.1/build/native/include/cpu_provider_factory.h b/onnxruntime-1.8.1/build/native/include/cpu_provider_factory.h new file mode 100644 index 0000000..3aa39ca --- /dev/null +++ b/onnxruntime-1.8.1/build/native/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/onnxruntime-1.8.1/build/native/include/cuda_provider_factory.h b/onnxruntime-1.8.1/build/native/include/cuda_provider_factory.h new file mode 100644 index 0000000..d4bd90b --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/cuda_provider_factory.h @@ -0,0 +1,61 @@ +// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "onnxruntime_c_api.h"
+
+#ifdef __cplusplus
+#include "core/framework/provider_options.h"
+
+namespace onnxruntime {
+class IAllocator;
+class IDataTransfer;
+struct IExecutionProviderFactory;
+struct CUDAExecutionProviderInfo;
+enum class ArenaExtendStrategy : int32_t;
+struct CUDAExecutionProviderExternalAllocatorInfo;
+
+namespace cuda {
+class INcclService;
+}
+
+} // namespace onnxruntime
+
+struct ProviderInfo_CUDA {
+ virtual OrtStatus* SetCurrentGpuDeviceId(_In_ int device_id) = 0;
+ virtual OrtStatus* GetCurrentGpuDeviceId(_In_ int* device_id) = 0;
+
+ virtual std::unique_ptr<onnxruntime::IAllocator> CreateCUDAAllocator(int16_t device_id, const char* name) = 0;
+ virtual std::unique_ptr<onnxruntime::IAllocator> CreateCUDAPinnedAllocator(int16_t device_id, const char* name) = 0;
+ virtual std::unique_ptr<onnxruntime::IDataTransfer> CreateGPUDataTransfer(void* stream) = 0;
+
+ virtual void cuda__Impl_Cast(void* stream, const int64_t* input_data, int32_t* output_data, size_t count) = 0;
+ virtual void cuda__Impl_Cast(void* stream, const int32_t* input_data, int64_t* output_data, size_t count) = 0;
+
+ virtual bool CudaCall_false(int retCode, const char* exprString, const char* libName, int successCode, const char* msg) = 0;
+ virtual bool CudaCall_true(int retCode, const char* exprString, const char* libName, int successCode, const char* msg) = 0;
+
+ virtual void CopyGpuToCpu(void* dst_ptr, const void* src_ptr, const size_t size, const OrtMemoryInfo& dst_location, const OrtMemoryInfo& src_location) = 0;
+ virtual void cudaMemcpy_HostToDevice(void* dst, const void* src, size_t count) = 0;
+ virtual void cudaMemcpy_DeviceToHost(void* dst, const void* src, size_t count) = 0;
+ virtual int cudaGetDeviceCount() = 0;
+ virtual void CUDAExecutionProviderInfo__FromProviderOptions(const onnxruntime::ProviderOptions& options, onnxruntime::CUDAExecutionProviderInfo& info) = 0;
+
+#if defined(USE_CUDA) && defined(ORT_USE_NCCL) && defined(USE_NCCL_P2P)
+ virtual onnxruntime::cuda::INcclService& GetINcclService() = 0;
+#endif
+
+ virtual std::shared_ptr<onnxruntime::IExecutionProviderFactory> CreateExecutionProviderFactory(const onnxruntime::CUDAExecutionProviderInfo& info) = 0;
+ virtual std::shared_ptr<onnxruntime::IAllocator> CreateCudaAllocator(int16_t device_id, size_t gpu_mem_limit, onnxruntime::ArenaExtendStrategy arena_extend_strategy, onnxruntime::CUDAExecutionProviderExternalAllocatorInfo& external_allocator_info, OrtArenaCfg* default_memory_arena_cfg) = 0;
+};
+
+extern "C" {
+#endif
+
+/**
+ * \param device_id cuda device id, starts from zero.
+ */
+ORT_API_STATUS(OrtSessionOptionsAppendExecutionProvider_CUDA, _In_ OrtSessionOptions* options, int device_id);
+
+#ifdef __cplusplus
+}
+#endif
diff --git a/onnxruntime-1.8.1/build/native/include/onnxruntime_c_api.h b/onnxruntime-1.8.1/build/native/include/onnxruntime_c_api.h new file mode 100644 index 0000000..0ed4e67 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/onnxruntime_c_api.h @@ -0,0 +1,1439 @@ +// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+
+// This value is used in structures passed to ORT so that a newer version of ORT will still work with them
+#define ORT_API_VERSION 8
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// SAL2 Definitions
+#ifndef _WIN32
+#define _In_
+#define _In_z_
+#define _In_opt_
+#define _In_opt_z_
+#define _Out_
+#define _Outptr_
+#define _Out_opt_
+#define _Inout_
+#define _Inout_opt_
+#define _Frees_ptr_opt_
+#define _Ret_maybenull_
+#define _Ret_notnull_
+#define _Check_return_
+#define _Outptr_result_maybenull_
+#define _In_reads_(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 <specstrings.h>
+#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
+
+#ifndef ORT_TSTR
+#ifdef _WIN32
+#define ORT_TSTR(X) L##X
+#else
+#define ORT_TSTR(X) X
+#endif
+#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
+
+// 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
+} 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,
+} ONNXType;
+
+typedef enum OrtLoggingLevel {
+ ORT_LOGGING_LEVEL_VERBOSE,
+ ORT_LOGGING_LEVEL_INFO,
+ ORT_LOGGING_LEVEL_WARNING,
+ ORT_LOGGING_LEVEL_ERROR,
+ ORT_LOGGING_LEVEL_FATAL,
+} 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,
+} OrtErrorCode;
+
+#define ORT_RUNTIME_CLASS(X) \
+ struct Ort##X; \
+ typedef struct Ort##X Ort##X;
+
+// 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(SessionOptions);
+ORT_RUNTIME_CLASS(CustomOpDomain);
+ORT_RUNTIME_CLASS(MapTypeInfo);
+ORT_RUNTIME_CLASS(SequenceTypeInfo);
+ORT_RUNTIME_CLASS(ModelMetadata);
+ORT_RUNTIME_CLASS(ThreadPoolParams);
+ORT_RUNTIME_CLASS(ThreadingOptions);
+ORT_RUNTIME_CLASS(ArenaCfg);
+ORT_RUNTIME_CLASS(PrepackedWeightsContainer);
+
+#ifdef _WIN32
+typedef _Return_type_success_(return == 0) OrtStatus* OrtStatusPtr;
+#else
+typedef OrtStatus* OrtStatusPtr;
+#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_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)
+
+// When passing in an allocator to any ORT 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; // Initialize to ORT_API_VERSION
+ void*(ORT_API_CALL* Alloc)(struct OrtAllocator* this_, size_t size);
+ void(ORT_API_CALL* Free)(struct OrtAllocator* this_, void* p);
+ const struct OrtMemoryInfo*(ORT_API_CALL* Info)(const struct OrtAllocator* this_);
+} OrtAllocator;
+
+typedef void(ORT_API_CALL* OrtLoggingFunction)(
+ void* param, OrtLoggingLevel severity, const char* category, const char* logid, const char* code_location,
+ const char* message);
+
+// Graph optimization level.
+// Refer to https://www.onnxruntime.ai/docs/resources/graph-optimizations.html
+// for an in-depth understanding of Graph Optimizations in ORT
+typedef enum GraphOptimizationLevel {
+ ORT_DISABLE_ALL = 0,
+ ORT_ENABLE_BASIC = 1,
+ ORT_ENABLE_EXTENDED = 2,
+ ORT_ENABLE_ALL = 99
+} GraphOptimizationLevel;
+
+typedef enum ExecutionMode {
+ ORT_SEQUENTIAL = 0,
+ ORT_PARALLEL = 1,
+} ExecutionMode;
+
+// Set the language projection, default is C, which means it will classify the language not in the list to C also.
+typedef enum OrtLanguageProjection {
+ ORT_PROJECTION_C = 0, // default
+ 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 {
+ Invalid = -1,
+ OrtDeviceAllocator = 0,
+ OrtArenaAllocator = 1
+} OrtAllocatorType;
+
+/**
+ * memory types for allocator, exec 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 {
+ OrtMemTypeCPUInput = -2, // Any CPU memory used by non-CPU execution provider
+ OrtMemTypeCPUOutput = -1, // CPU accessible memory outputted by non-CPU execution provider, i.e. CUDA_PINNED
+ OrtMemTypeCPU = OrtMemTypeCPUOutput, // temporary CPU accessible memory allocated by non-CPU execution provider, i.e. CUDA_PINNED
+ OrtMemTypeDefault = 0, // the default allocator for execution provider
+} OrtMemType;
+
+typedef enum OrtCudnnConvAlgoSearch {
+ EXHAUSTIVE, // expensive exhaustive benchmarking using cudnnFindConvolutionForwardAlgorithmEx
+ HEURISTIC, // lightweight heuristic based search using cudnnGetConvolutionForwardAlgorithm_v7
+ DEFAULT, // default algorithm using CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM
+} OrtCudnnConvAlgoSearch;
+
+/// <summary>
+/// Options for the CUDA provider that are passed to SessionOptionsAppendExecutionProvider_CUDA
+/// </summary>
+typedef struct OrtCUDAProviderOptions {
+ int device_id; // cuda device with id=0 as default device.
+ OrtCudnnConvAlgoSearch cudnn_conv_algo_search; // cudnn conv algo search option
+
+ size_t gpu_mem_limit; // default cuda memory limitation to maximum finite value of size_t.
+ // (will be overridden by "max_mem" value used while creating `arena_cfg` if `arena_cfg` is provided)
+
+ int arena_extend_strategy; // default area extend strategy to KNextPowerOfTwo.
+ // (will be overridden by "arena_extend_strategy" value used while creating `arena_cfg` if `arena_cfg` is provided)
+
+ int do_copy_in_default_stream;
+ int has_user_compute_stream;
+ void* user_compute_stream;
+ OrtArenaCfg* default_memory_arena_cfg;
+} OrtCUDAProviderOptions;
+
+/// <summary>
+/// Options for the ROCM provider that are passed to SessionOptionsAppendExecutionProvider_ROCM
+/// </summary>
+typedef struct OrtROCMProviderOptions {
+ int device_id; // hip device with id=0 as default device.
+ int miopen_conv_exhaustive_search; // miopen conv algo exhaustive search option
+ size_t gpu_mem_limit; // default hip memory limitation to maximum finite value of size_t.
+ int arena_extend_strategy; // default area extend strategy to KNextPowerOfTwo.
+} OrtROCMProviderOptions;
+
+/// <summary>
+/// Options for the TensorRT provider that are passed to SessionOptionsAppendExecutionProvider_TensorRT
+/// </summary>
+typedef struct OrtTensorRTProviderOptions {
+ int device_id; // cuda device id.
+ 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
+} OrtTensorRTProviderOptions;
+
+/// <summary>
+/// Options for the OpenVINO provider that are passed to SessionOptionsAppendExecutionProvider_OpenVINO
+/// </summary>
+typedef struct OrtOpenVINOProviderOptions {
+#ifdef __cplusplus
+ OrtOpenVINOProviderOptions() : device_type{}, enable_vpu_fast_compile{}, device_id{}, num_of_threads{}, use_compiled_network{}, blob_dump_path{} {}
+#endif
+ const char* device_type; // CPU_FP32, GPU_FP32, GPU_FP16, MYRIAD_FP16, VAD-M_FP16 or VAD-F_FP32
+ unsigned char enable_vpu_fast_compile; // 0 = false, nonzero = true
+ const char* device_id;
+ size_t num_of_threads; // 0 uses default number of threads
+ unsigned char use_compiled_network; // 0 = false, nonzero = true
+ const char* blob_dump_path; // path is set to empty by default
+} OrtOpenVINOProviderOptions;
+
+struct OrtApi;
+typedef struct OrtApi OrtApi;
+
+struct OrtApiBase {
+ const OrtApi*(ORT_API_CALL* GetApi)(uint32_t version)NO_EXCEPTION; // Pass in ORT_API_VERSION
+ // nullptr will be returned if the version is unsupported, for example when using a runtime older than this header file
+
+ const char*(ORT_API_CALL* GetVersionString)(void)NO_EXCEPTION;
+};
+typedef struct OrtApiBase OrtApiBase;
+
+ORT_EXPORT const OrtApiBase* ORT_API_CALL OrtGetApiBase(void) NO_EXCEPTION;
+
+struct OrtApi {
+ /**
+* \param msg A null-terminated string. Its content will be copied into the newly created OrtStatus
+*/
+ OrtStatus*(ORT_API_CALL* CreateStatus)(OrtErrorCode code, _In_ const char* msg)NO_EXCEPTION ORT_ALL_ARGS_NONNULL;
+
+ OrtErrorCode(ORT_API_CALL* GetErrorCode)(_In_ const OrtStatus* status) NO_EXCEPTION ORT_ALL_ARGS_NONNULL;
+
+ /**
+ * \param status must not be NULL
+ * \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;
+
+ /**
+ * \param out Should be freed by `ReleaseEnv` after use
+ */
+ ORT_API2_STATUS(CreateEnv, OrtLoggingLevel logging_level, _In_ const char* logid, _Outptr_ OrtEnv** out);
+
+ /**
+ * \param out Should be freed by `ReleaseEnv` after use
+ */
+ ORT_API2_STATUS(CreateEnvWithCustomLogger, OrtLoggingFunction logging_function, _In_opt_ void* logger_param,
+ OrtLoggingLevel logging_level, _In_ const char* logid, _Outptr_ OrtEnv** out);
+
+ // Platform telemetry events are on by default since they are lightweight. You can manually turn them off.
+ ORT_API2_STATUS(EnableTelemetryEvents, _In_ const OrtEnv* env);
+ ORT_API2_STATUS(DisableTelemetryEvents, _In_ const OrtEnv* env);
+
+ // 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);
+
+ 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);
+
+ ORT_API2_STATUS(Run, _Inout_ OrtSession* sess, _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_names1, size_t output_names_len,
+ _Inout_updates_all_(output_names_len) OrtValue** output);
+
+ /**
+ * \return A pointer of the newly created object. The pointer should be freed by ReleaseSessionOptions after use
+ */
+ ORT_API2_STATUS(CreateSessionOptions, _Outptr_ OrtSessionOptions** options);
+
+ // Set filepath to save optimized model after graph level transformations.
+ ORT_API2_STATUS(SetOptimizedModelFilePath, _Inout_ OrtSessionOptions* options,
+ _In_ const ORTCHAR_T* optimized_model_filepath);
+
+ // create a copy of an existing OrtSessionOptions
+ ORT_API2_STATUS(CloneSessionOptions, _In_ const OrtSessionOptions* in_options,
+ _Outptr_ OrtSessionOptions** out_options);
+
+ // 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.
+ ORT_API2_STATUS(SetSessionExecutionMode, _Inout_ OrtSessionOptions* options, ExecutionMode execution_mode);
+
+ // Enable profiling for this session.
+ ORT_API2_STATUS(EnableProfiling, _Inout_ OrtSessionOptions* options, _In_ const ORTCHAR_T* profile_file_prefix);
+ ORT_API2_STATUS(DisableProfiling, _Inout_ OrtSessionOptions* options);
+
+ // 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 SequentialExecution enabled.
+ ORT_API2_STATUS(EnableMemPattern, _Inout_ OrtSessionOptions* options);
+ ORT_API2_STATUS(DisableMemPattern, _Inout_ OrtSessionOptions* options);
+
+ // Enable the memory arena on CPU
+ // Arena may pre-allocate memory for future usage.
+ // set this option to false if you don't want it.
+ ORT_API2_STATUS(EnableCpuMemArena, _Inout_ OrtSessionOptions* options);
+ ORT_API2_STATUS(DisableCpuMemArena, _Inout_ OrtSessionOptions* options);
+
+ // < logger id to use for session output
+ ORT_API2_STATUS(SetSessionLogId, _Inout_ OrtSessionOptions* options, const char* logid);
+
+ // < applies to session load, initialization, etc
+ ORT_API2_STATUS(SetSessionLogVerbosityLevel, _Inout_ OrtSessionOptions* options, int session_log_verbosity_level);
+ ORT_API2_STATUS(SetSessionLogSeverityLevel, _Inout_ OrtSessionOptions* options, int session_log_severity_level);
+
+ ORT_API2_STATUS(SetSessionGraphOptimizationLevel, _Inout_ OrtSessionOptions* options,
+ GraphOptimizationLevel graph_optimization_level);
+
+ // Sets the number of threads used to parallelize the execution within nodes
+ // A value of 0 means ORT will pick a default
+ // Note: If you've built ORT with OpenMP, this API 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.
+ ORT_API2_STATUS(SetIntraOpNumThreads, _Inout_ OrtSessionOptions* options, int intra_op_num_threads);
+
+ // Sets the number of threads used to parallelize the execution of the graph (across nodes)
+ // If sequential execution is enabled this value is ignored
+ // A value of 0 means ORT will pick a default
+ ORT_API2_STATUS(SetInterOpNumThreads, _Inout_ OrtSessionOptions* options, int inter_op_num_threads);
+
+ /*
+ Create a custom op domain. After all sessions using it are released, call ReleaseCustomOpDomain
+ */
+ ORT_API2_STATUS(CreateCustomOpDomain, _In_ const char* domain, _Outptr_ OrtCustomOpDomain** out);
+
+ /*
+ * Add custom ops to the OrtCustomOpDomain
+ * Note: The OrtCustomOp* pointer must remain valid until the OrtCustomOpDomain using it is released
+ */
+ ORT_API2_STATUS(CustomOpDomain_Add, _Inout_ OrtCustomOpDomain* custom_op_domain, _In_ const OrtCustomOp* op);
+
+ /*
+ * Add a custom op domain to the OrtSessionOptions
+ * Note: The OrtCustomOpDomain* must not be deleted until the sessions using it are released
+ */
+ ORT_API2_STATUS(AddCustomOpDomain, _Inout_ OrtSessionOptions* options, _In_ OrtCustomOpDomain* custom_op_domain);
+
+ /*
+ * Loads a DLL 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.
+ */
+ ORT_API2_STATUS(RegisterCustomOpsLibrary, _Inout_ OrtSessionOptions* options, _In_ const char* library_path,
+ void** library_handle);
+
+ /**
+ * 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.
+ */
+
+ ORT_API2_STATUS(SessionGetInputCount, _In_ const OrtSession* sess, _Out_ size_t* out);
+ ORT_API2_STATUS(SessionGetOutputCount, _In_ const OrtSession* sess, _Out_ size_t* out);
+ ORT_API2_STATUS(SessionGetOverridableInitializerCount, _In_ const OrtSession* sess, _Out_ size_t* out);
+
+ /**
+ * \param out should be freed by ReleaseTypeInfo after use
+ */
+ ORT_API2_STATUS(SessionGetInputTypeInfo, _In_ const OrtSession* sess, size_t index, _Outptr_ OrtTypeInfo** type_info);
+
+ /**
+ * \param out should be freed by ReleaseTypeInfo after use
+ */
+ ORT_API2_STATUS(SessionGetOutputTypeInfo, _In_ const OrtSession* sess, size_t index,
+ _Outptr_ OrtTypeInfo** type_info);
+
+ /**
+ * \param out should be freed by ReleaseTypeInfo after use
+ */
+ ORT_API2_STATUS(SessionGetOverridableInitializerTypeInfo, _In_ const OrtSession* sess, size_t index,
+ _Outptr_ OrtTypeInfo** type_info);
+
+ /**
+ * \param value is set to a null terminated UTF-8 encoded string allocated using 'allocator'.
+ * The caller is responsible for freeing it.
+ */
+ ORT_API2_STATUS(SessionGetInputName, _In_ const OrtSession* sess, size_t index, _Inout_ OrtAllocator* allocator,
+ _Outptr_ char** value);
+ ORT_API2_STATUS(SessionGetOutputName, _In_ const OrtSession* sess, size_t index, _Inout_ OrtAllocator* allocator,
+ _Outptr_ char** value);
+ ORT_API2_STATUS(SessionGetOverridableInitializerName, _In_ const OrtSession* sess, size_t index,
+ _Inout_ OrtAllocator* allocator, _Outptr_ char** value);
+
+ /**
+ * \return A pointer to the newly created object. The pointer should be freed by ReleaseRunOptions after use
+ */
+ ORT_API2_STATUS(CreateRunOptions, _Outptr_ OrtRunOptions** out);
+
+ ORT_API2_STATUS(RunOptionsSetRunLogVerbosityLevel, _Inout_ OrtRunOptions* options, int value);
+ ORT_API2_STATUS(RunOptionsSetRunLogSeverityLevel, _Inout_ OrtRunOptions* options, int value);
+ ORT_API2_STATUS(RunOptionsSetRunTag, _Inout_ OrtRunOptions*, _In_ const char* run_tag);
+
+ ORT_API2_STATUS(RunOptionsGetRunLogVerbosityLevel, _In_ const OrtRunOptions* options, _Out_ int* out);
+ ORT_API2_STATUS(RunOptionsGetRunLogSeverityLevel, _In_ const OrtRunOptions* options, _Out_ int* out);
+ ORT_API2_STATUS(RunOptionsGetRunTag, _In_ const OrtRunOptions*, _Out_ const char** out);
+
+ // Set a flag so that ALL incomplete OrtRun calls that are using this instance of OrtRunOptions
+ // will exit as soon as possible.
+ ORT_API2_STATUS(RunOptionsSetTerminate, _Inout_ OrtRunOptions* options);
+ // Unset the terminate flag to enable this OrtRunOptions instance being used in new OrtRun calls.
+ ORT_API2_STATUS(RunOptionsUnsetTerminate, _Inout_ OrtRunOptions* options);
+
+ /**
+ * Create a tensor from an allocator. ReleaseValue will also release the buffer inside the output value
+ * \param out Should be freed by calling ReleaseValue
+ * \param type must be one of TENSOR_ELEMENT_DATA_TYPE_xxxx
+ */
+ ORT_API2_STATUS(CreateTensorAsOrtValue, _Inout_ OrtAllocator* allocator, _In_ const int64_t* shape, size_t shape_len,
+ ONNXTensorElementDataType type, _Outptr_ OrtValue** out);
+
+ /**
+ * 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.
+ * \param out Should be freed by calling ReleaseValue
+ */
+ 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);
+
+ /**
+ * \Sets *out to 1 iff an OrtValue is a tensor, 0 otherwise
+ */
+ ORT_API2_STATUS(IsTensor, _In_ const OrtValue* value, _Out_ int* out);
+
+ // This function doesn't work with string tensor
+ // this is a no-copy method whose pointer is only valid until the backing OrtValue is free'd.
+ ORT_API2_STATUS(GetTensorMutableData, _Inout_ OrtValue* value, _Outptr_ void** out);
+
+ /**
+ * \param value A tensor created from OrtCreateTensor... function.
+ * \param s each A string array. Each string in this array must be null terminated.
+ * \param s_len length of s
+ */
+ ORT_API2_STATUS(FillStringTensor, _Inout_ OrtValue* value, _In_ const char* const* s, size_t s_len);
+
+ /**
+ * \param value A tensor created from OrtCreateTensor... function.
+ * \param len total data length, not including the trailing '\0' chars.
+ */
+ ORT_API2_STATUS(GetStringTensorDataLength, _In_ const OrtValue* value, _Out_ size_t* len);
+
+ /**
+ * \param s string contents. Each string is NOT null-terminated.
+ * \param value A tensor created from OrtCreateTensor... function.
+ * \param s_len total data length, get it from OrtGetStringTensorDataLength
+ */
+ 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);
+
+ /**
+ * Don't free the 'out' value
+ */
+ ORT_API2_STATUS(CastTypeInfoToTensorInfo, _In_ const OrtTypeInfo*,
+ _Outptr_result_maybenull_ const OrtTensorTypeAndShapeInfo** out);
+
+ /**
+ * Return OnnxType from OrtTypeInfo
+ */
+ ORT_API2_STATUS(GetOnnxTypeFromTypeInfo, _In_ const OrtTypeInfo*, _Out_ enum ONNXType* out);
+
+ /**
+ * The 'out' value should be released by calling ReleaseTensorTypeAndShapeInfo
+ */
+ ORT_API2_STATUS(CreateTensorTypeAndShapeInfo, _Outptr_ OrtTensorTypeAndShapeInfo** out);
+
+ ORT_API2_STATUS(SetTensorElementType, _Inout_ OrtTensorTypeAndShapeInfo*, enum ONNXTensorElementDataType type);
+
+ /**
+ * \param info Created from CreateTensorTypeAndShapeInfo() function
+ * \param dim_values An array with length of `dim_count`. Its elements can contain negative values.
+ * \param dim_count length of dim_values
+ */
+ ORT_API2_STATUS(SetDimensions, OrtTensorTypeAndShapeInfo* info, _In_ const int64_t* dim_values, size_t dim_count);
+
+ ORT_API2_STATUS(GetTensorElementType, _In_ const OrtTensorTypeAndShapeInfo*,
+ _Out_ enum ONNXTensorElementDataType* out);
+ ORT_API2_STATUS(GetDimensionsCount, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ size_t* out);
+ ORT_API2_STATUS(GetDimensions, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ int64_t* dim_values,
+ size_t dim_values_length);
+ ORT_API2_STATUS(GetSymbolicDimensions, _In_ const OrtTensorTypeAndShapeInfo* info,
+ _Out_writes_all_(dim_params_length) const char* dim_params[], size_t dim_params_length);
+
+ /**
+ * Return the number of elements specified by the tensor shape.
+ * Return a negative value if unknown (i.e., any dimension is negative.)
+ * e.g.
+ * [] -> 1
+ * [1,3,4] -> 12
+ * [2,0,4] -> 0
+ * [-1,3,4] -> -1
+ */
+ ORT_API2_STATUS(GetTensorShapeElementCount, _In_ const OrtTensorTypeAndShapeInfo* info, _Out_ size_t* out);
+
+ /**
+ * \param out Should be freed by ReleaseTensorTypeAndShapeInfo after use
+ */
+ ORT_API2_STATUS(GetTensorTypeAndShape, _In_ const OrtValue* value, _Outptr_ OrtTensorTypeAndShapeInfo** out);
+
+ /**
+ * Get the type information of an OrtValue
+ * \param value
+ * \param out The returned value should be freed by ReleaseTypeInfo after use
+ */
+ ORT_API2_STATUS(GetTypeInfo, _In_ const OrtValue* value, _Outptr_result_maybenull_ OrtTypeInfo** out);
+
+ ORT_API2_STATUS(GetValueType, _In_ const OrtValue* value, _Out_ enum ONNXType* out);
+
+ ORT_API2_STATUS(CreateMemoryInfo, _In_ const char* name1, enum OrtAllocatorType type, int id1,
+ enum OrtMemType mem_type1, _Outptr_ OrtMemoryInfo** out);
+
+ /**
+ * Convenience function for special case of CreateMemoryInfo, for the CPU allocator. Uses name = "Cpu" and id = 0.
+ */
+ ORT_API2_STATUS(CreateCpuMemoryInfo, enum OrtAllocatorType type, enum OrtMemType mem_type1,
+ _Outptr_ OrtMemoryInfo** out);
+
+ /**
+ * Test if two memory info are equal
+ * \Sets 'out' to 0 if equal, -1 if not equal
+ */
+ ORT_API2_STATUS(CompareMemoryInfo, _In_ const OrtMemoryInfo* info1, _In_ const OrtMemoryInfo* info2, _Out_ int* out);
+
+ /**
+ * Do not free the returned value
+ */
+ ORT_API2_STATUS(MemoryInfoGetName, _In_ const OrtMemoryInfo* ptr, _Out_ const char** out);
+ ORT_API2_STATUS(MemoryInfoGetId, _In_ const OrtMemoryInfo* ptr, _Out_ int* out);
+ ORT_API2_STATUS(MemoryInfoGetMemType, _In_ const OrtMemoryInfo* ptr, _Out_ OrtMemType* out);
+ ORT_API2_STATUS(MemoryInfoGetType, _In_ const OrtMemoryInfo* ptr, _Out_ OrtAllocatorType* out);
+
+ ORT_API2_STATUS(AllocatorAlloc, _Inout_ OrtAllocator* ptr, size_t size, _Outptr_ void** out);
+ ORT_API2_STATUS(AllocatorFree, _Inout_ OrtAllocator* ptr, void* p);
+ ORT_API2_STATUS(AllocatorGetInfo, _In_ const OrtAllocator* ptr, _Outptr_ const struct OrtMemoryInfo** out);
+
+ // The returned pointer doesn't have to be freed.
+ // Always returns the same instance on every invocation.
+ // Please note that this is a non-arena based allocator.
+ ORT_API2_STATUS(GetAllocatorWithDefaultOptions, _Outptr_ OrtAllocator** out);
+
+ // 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)
+ ORT_API2_STATUS(AddFreeDimensionOverride, _Inout_ OrtSessionOptions* options, _In_ const char* dim_denotation,
+ _In_ int64_t dim_value);
+
+ /**
+ * 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::string, std::string>
+ * std::map<std::string, int64_t>
+ * std::map<std::string, float>
+ * std::map<std::string, double>
+ * std::map<int64_t, std::string>
+ * std::map<int64_t, int64_t>
+ * std::map<int64_t, float>
+ * std::map<int64_t, double>
+ *
+ * Sequence types
+ * ==============
+ * std::vector<std::string>
+ * std::vector<int64_t>
+ * std::vector<float>
+ * std::vector<double>
+ * std::vector<std::map<std::string, float>>
+ * std::vector<std::map<int64_t, float>
+ */
+
+ /**
+ * If input OrtValue represents a map, you need to retrieve the keys and values
+ * separately. Use index=0 to retrieve keys and index=1 to retrieve values.
+ * If input OrtValue represents a sequence, use index to retrieve the index'th element
+ * of the sequence.
+ */
+ ORT_API2_STATUS(GetValue, _In_ const OrtValue* value, int index, _Inout_ OrtAllocator* allocator,
+ _Outptr_ OrtValue** out);
+
+ /**
+ * Returns 2 for type map and N for sequence where N is the number of elements
+ * in the sequence.
+ */
+ ORT_API2_STATUS(GetValueCount, _In_ const OrtValue* value, _Out_ size_t* out);
+
+ /**
+ * To construct a map, use num_values = 2 and 'in' should be an arrary of 2 OrtValues
+ * representing keys and values.
+ * To construct a sequence, use num_values = N where N is the number of the elements in the
+ * sequence. 'in' should be an arrary of N OrtValues.
+ * \value_type should be either map or sequence.
+ */
+ ORT_API2_STATUS(CreateValue, _In_reads_(num_values) const OrtValue* const* in, size_t num_values,
+ enum ONNXType value_type, _Outptr_ OrtValue** out);
+
+ /**
+ * Construct 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 between
+ * 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 know 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.
+ *
+ * \domain_name - domain name for the Opaque type, null terminated.
+ * \type_name - type name for the Opaque type, null terminated.
+ * \data_contianer - data to populate OrtValue
+ * \data_container_size - sizeof() of the data container. Must match the sizeof() of the expected
+ * data_container size internally.
+ */
+ 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);
+
+ /**
+ * Fetch data from an OrtValue that contains a value of non-standard type created for
+ * experiments or while awaiting standardization.
+ * \domain_name - domain name for the Opaque type, null terminated.
+ * \type_name - type name for the Opaque type, null terminated.
+ * \data_contianer - data to populate OrtValue
+ * \data_container_size - sizeof() of the data container. Must match the sizeof() of the expected
+ * data_container size internally.
+ */
+
+ 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);
+
+ /**
+ * Fetch a float stored as an attribute in the graph node
+ * \info - OrtKernelInfo instance
+ * \name - name of the attribute to be parsed
+ * \out - pointer to memory where the attribute is to be stored
+ */
+ ORT_API2_STATUS(KernelInfoGetAttribute_float, _In_ const OrtKernelInfo* info, _In_ const char* name,
+ _Out_ float* out);
+
+ /**
+ * Fetch a 64-bit int stored as an attribute in the graph node
+ * \info - OrtKernelInfo instance
+ * \name - name of the attribute to be parsed
+ * \out - pointer to memory where the attribute is to be stored
+ */
+ ORT_API2_STATUS(KernelInfoGetAttribute_int64, _In_ const OrtKernelInfo* info, _In_ const char* name,
+ _Out_ int64_t* out);
+ /**
+ * Fetch a string stored as an attribute in the graph node
+ * \info - OrtKernelInfo instance
+ * \name - name of the attribute to be parsed
+ * \out - pointer to memory where the attribute's contents are to be stored
+ * \size - actual size of string attribute
+ * (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 lesser 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.)
+ */
+ ORT_API2_STATUS(KernelInfoGetAttribute_string, _In_ const OrtKernelInfo* info, _In_ const char* name, _Out_ char* out,
+ _Inout_ size_t* size);
+
+ ORT_API2_STATUS(KernelContext_GetInputCount, _In_ const OrtKernelContext* context, _Out_ size_t* out);
+ ORT_API2_STATUS(KernelContext_GetOutputCount, _In_ const OrtKernelContext* context, _Out_ size_t* out);
+ ORT_API2_STATUS(KernelContext_GetInput, _In_ const OrtKernelContext* context, _In_ size_t index,
+ _Out_ const OrtValue** out);
+ 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);
+
+ ORT_CLASS_RELEASE(Env);
+ ORT_CLASS_RELEASE(Status); // nullptr for Status* indicates success
+ ORT_CLASS_RELEASE(MemoryInfo);
+ ORT_CLASS_RELEASE(Session); //Don't call ReleaseSession from Dllmain (because session owns a thread pool)
+ ORT_CLASS_RELEASE(Value);
+ ORT_CLASS_RELEASE(RunOptions);
+ ORT_CLASS_RELEASE(TypeInfo);
+ ORT_CLASS_RELEASE(TensorTypeAndShapeInfo);
+ ORT_CLASS_RELEASE(SessionOptions);
+ ORT_CLASS_RELEASE(CustomOpDomain);
+
+ // End of Version 1 - DO NOT MODIFY ABOVE (see above text for more information)
+
+ // Version 2 - In development, feel free to add/remove/rearrange here
+
+ /**
+ * GetDenotationFromTypeInfo
+ * This api 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.
+ */
+ ORT_API2_STATUS(GetDenotationFromTypeInfo, _In_ const OrtTypeInfo*, _Out_ const char** const denotation,
+ _Out_ size_t* len);
+
+ // OrtTypeInfo Casting methods
+
+ /**
+ * CastTypeInfoToMapTypeInfo
+ * This api 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.
+ * This is used by WinML to support model reflection APIs.
+ *
+ * Don't free the 'out' value
+ */
+ ORT_API2_STATUS(CastTypeInfoToMapTypeInfo, _In_ const OrtTypeInfo* type_info,
+ _Outptr_result_maybenull_ const OrtMapTypeInfo** out);
+
+ /**
+ * CastTypeInfoToSequenceTypeInfo
+ * 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.
+ *
+ * Don't free the 'out' value
+ */
+ ORT_API2_STATUS(CastTypeInfoToSequenceTypeInfo, _In_ const OrtTypeInfo* type_info,
+ _Outptr_result_maybenull_ const OrtSequenceTypeInfo** out);
+
+ // OrtMapTypeInfo Accessors
+
+ /**
+ * GetMapKeyType
+ * This api augments get the key type of a map. Key types are restricted to being scalar types and use ONNXTensorElementDataType.
+ * This is used by WinML to support model reflection APIs.
+ */
+ ORT_API2_STATUS(GetMapKeyType, _In_ const OrtMapTypeInfo* map_type_info, _Out_ enum ONNXTensorElementDataType* out);
+
+ /**
+ * GetMapValueType
+ * This api augments get the value type of a map.
+ */
+ ORT_API2_STATUS(GetMapValueType, _In_ const OrtMapTypeInfo* map_type_info, _Outptr_ OrtTypeInfo** type_info);
+
+ // OrtSequenceTypeInfo Accessors
+
+ /**
+ * GetSequenceElementType
+ * This api augments get the element type of a sequence.
+ * This is used by WinML to support model reflection APIs.
+ */
+ ORT_API2_STATUS(GetSequenceElementType, _In_ const OrtSequenceTypeInfo* sequence_type_info,
+ _Outptr_ OrtTypeInfo** type_info);
+
+ ORT_CLASS_RELEASE(MapTypeInfo);
+ ORT_CLASS_RELEASE(SequenceTypeInfo);
+
+ /**
+ * \param out is set to a null terminated string allocated using 'allocator'. The caller is responsible for freeing it.
+ * Profiling is turned ON automatically if enabled for the particular session by invoking EnableProfiling()
+ * on the SessionOptions instance used to create the session.
+ */
+ ORT_API2_STATUS(SessionEndProfiling, _In_ OrtSession* sess, _Inout_ OrtAllocator* allocator, _Outptr_ char** out);
+
+ /**
+ * \param out is a pointer to the newly created object. The pointer should be freed by calling ReleaseModelMetadata after use.
+ */
+ ORT_API2_STATUS(SessionGetModelMetadata, _In_ const OrtSession* sess, _Outptr_ OrtModelMetadata** out);
+
+ /**
+ * \param value is set to a null terminated string allocated using 'allocator'. The caller is responsible for freeing it.
+ */
+ ORT_API2_STATUS(ModelMetadataGetProducerName, _In_ const OrtModelMetadata* model_metadata,
+ _Inout_ OrtAllocator* allocator, _Outptr_ char** value);
+ ORT_API2_STATUS(ModelMetadataGetGraphName, _In_ const OrtModelMetadata* model_metadata,
+ _Inout_ OrtAllocator* allocator, _Outptr_ char** value);
+ ORT_API2_STATUS(ModelMetadataGetDomain, _In_ const OrtModelMetadata* model_metadata, _Inout_ OrtAllocator* allocator,
+ _Outptr_ char** value);
+ ORT_API2_STATUS(ModelMetadataGetDescription, _In_ const OrtModelMetadata* model_metadata,
+ _Inout_ OrtAllocator* allocator, _Outptr_ char** value);
+ /**
+ * \param value is set to a null terminated string allocated using 'allocator'. The caller is responsible for freeing it.
+ * 'value' will be a nullptr if the given key is not found in the custom metadata map.
+ */
+ ORT_API2_STATUS(ModelMetadataLookupCustomMetadataMap, _In_ const OrtModelMetadata* model_metadata,
+ _Inout_ OrtAllocator* allocator, _In_ const char* key, _Outptr_result_maybenull_ char** value);
+
+ ORT_API2_STATUS(ModelMetadataGetVersion, _In_ const OrtModelMetadata* model_metadata, _Out_ int64_t* value);
+
+ ORT_CLASS_RELEASE(ModelMetadata);
+
+ /*
+ * Creates an environment with global threadpools that will be shared across sessions.
+ * Use this in conjunction with DisablePerSessionThreads API or else the session will use
+ * its own thread pools.
+ */
+ ORT_API2_STATUS(CreateEnvWithGlobalThreadPools, OrtLoggingLevel logging_level, _In_ const char* logid,
+ _In_ const OrtThreadingOptions* t_options, _Outptr_ OrtEnv** out);
+
+ /*
+ * Calling this API will make the session use the global threadpools shared across sessions.
+ * This API should be used in conjunction with CreateEnvWithGlobalThreadPools API.
+ */
+ ORT_API2_STATUS(DisablePerSessionThreads, _Inout_ OrtSessionOptions* options);
+
+ ORT_API2_STATUS(CreateThreadingOptions, _Outptr_ OrtThreadingOptions** out);
+
+ ORT_CLASS_RELEASE(ThreadingOptions);
+
+ /**
+ * \param num_keys contains the number of keys in the custom metadata map
+ * \param keys is an array of null terminated strings (array count = num_keys) allocated using 'allocator'.
+ * The caller is responsible for freeing each string and the pointer array.
+ * 'keys' will be a nullptr if custom metadata map is empty.
+ */
+ 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);
+
+ // 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);
+
+ /**
+ * \param out_ptr will hold a pointer to the array of char *
+ * representing available providers.
+ * \param provider_length is a pointer to an int variable where
+ * the number of available providers will be added.
+ * The caller is responsible for freeing each char * and the pointer
+ * array by calling ReleaseAvailableProviders().
+ */
+ ORT_API2_STATUS(GetAvailableProviders, _Outptr_ char*** out_ptr,
+ _In_ int* provider_length);
+
+ /**
+ * \param ptr is the pointer to an array of available providers you
+ * get after calling GetAvailableProviders().
+ * \param providers_length is the number of available providers.
+ */
+ ORT_API2_STATUS(ReleaseAvailableProviders, _In_ char** ptr,
+ _In_ int providers_length);
+
+ /**
+ * \param value - A tensor created from OrtCreateTensor... function.
+ * \param index - index of string tensor element, length of element at index will be returned.
+ * \param out - number of UTF-8 bytes that the string contains
+ */
+ ORT_API2_STATUS(GetStringTensorElementLength, _In_ const OrtValue* value, size_t index, _Out_ size_t* out);
+
+ /**
+ * \param s string element contents in UTF-8 encoding. The string is NOT null-terminated.
+ * \param value A tensor created from OrtCreateTensor... function.
+ * \param s_len element length, get it from OrtGetStringTensorElementLength.
+ * \param index offset of element of tensor to return.
+ */
+ ORT_API2_STATUS(GetStringTensorElement, _In_ const OrtValue* value, size_t s_len, size_t index, _Out_writes_bytes_all_(s_len) void* s);
+
+ /**
+ * \param value - A tensor created from OrtCreateTensor... function.
+ * \param s - A null terminated UTF-8 encoded string.
+ * \param index - index of string tensor element to fill
+ */
+ ORT_API2_STATUS(FillStringTensorElement, _Inout_ OrtValue* value, _In_ const char* s, size_t index);
+
+ /**
+ * Set a single 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
+ * \param config_key A null terminated string representation of the config key
+ * \param config_value A null terminated string representation of the config value
+ * The config_key and the format of config_value are defined in onnxruntime_session_options_config_keys.h
+ */
+ ORT_API2_STATUS(AddSessionConfigEntry, _Inout_ OrtSessionOptions* options,
+ _In_z_ const char* config_key, _In_z_ const char* config_value);
+
+ /**
+ * \param sess valid OrtSession instance
+ * \param mem_info - valid OrtMemoryInfo instance
+ * \param - out a ptr to a new instance of OrtAllocator according to the spec within mem_info
+ * if successful
+ * \return OrtStatus or nullptr if successful
+ */
+ ORT_API2_STATUS(CreateAllocator, _In_ const OrtSession* sess, _In_ const OrtMemoryInfo* mem_info,
+ _Outptr_ OrtAllocator** out);
+
+ // Release instance of OrtAllocator obtained from CreateAllocator API
+ ORT_CLASS_RELEASE(Allocator);
+
+ ORT_API2_STATUS(RunWithBinding, _Inout_ OrtSession* sess, _In_ const OrtRunOptions* run_options, _In_ const OrtIoBinding* binding_ptr);
+
+ // Creates an IoBinding instance that allows one to bind pre-allocated OrtValues
+ // 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.
+ ORT_API2_STATUS(CreateIoBinding, _Inout_ OrtSession* sess, _Outptr_ OrtIoBinding** out);
+
+ // Release instance or OrtIoBinding obtained from CreateIoBinding API
+ ORT_CLASS_RELEASE(IoBinding);
+
+ /**
+ * The function will bind the OrtValue to a specified input name.
+ * The OrtValue must be a Tensor. ORT would use that value in place of input for the specified name.
+ * \param binding_ptr - an instance of OrtIoBinding created by CreateIoBinding()
+ * \param name - name for the model input
+ * \param val_ptr - OrtValue of Tensor type.
+ * \return OrtStatus instance on error which the caller is responsible to free or nullptr on success
+ */
+ ORT_API2_STATUS(BindInput, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtValue* val_ptr);
+
+ /**
+ * The function will bind the OrtValue to the specified output name.
+ * The OrtValue must be a Tensor. ORT would use that value in place of output for the specified name.
+ *
+ * \param binding_ptr - an instance of OrtIoBinding created by CreateIoBinding()
+ * \param name - name for the model output
+ * \param val_ptr - OrtValue of Tensor type.
+ * \return OrtStatus instance on error which the caller is responsible to free or nullptr on success
+ */
+ ORT_API2_STATUS(BindOutput, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtValue* val_ptr);
+
+ /**
+ * The function will bind the OrtValue to a device which specification is contained within OrtMemoryInfo
+ * You can either create an instance of OrtMemoryInfo with a device id or obtain one from the allocator that you are created/using
+ * This is useful when one or more outputs have dynamic shapes and, it is hard to pre-allocated and bind a chunk of
+ * memory within OrtValue ahead of time.
+ *
+ * \param binding_ptr - an instance of OrtIoBinding created by CreateIoBinding()
+ * \param name - name for the model output
+ * \param mem_info_ptr - OrtMemoryInfo
+ * \return OrtStatus instance on error which the caller is responsible to free or nullptr on success
+ */
+ ORT_API2_STATUS(BindOutputToDevice, _Inout_ OrtIoBinding* binding_ptr, _In_ const char* name, _In_ const OrtMemoryInfo* val_ptr);
+
+ /**
+ * The function 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 OrtValues are returned. This API is optional
+ * to use. If you knew the order of outputs and its names you used for binding you would not need to use this API.
+ *
+ * \param binding_ptr - a ptr to an instance of OrtIoBinding created obtained from CreateIoBinding()
+ * \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 buffer - pointer to a continuous buffer of non-zero terminated UTF-8 encoded strings. The number of strings stored is returned count parameter.
+ * this buffer will be allocated with the specified allocator and must be freed after it is no longer needed.
+ * \param lengths - a pointer to a continuous buffer of size_t lengths of strings returned in the buffer. The number of items is returned
+ * in the count. This buffer is allocated with the specified allocator and must be freed after it is no longer needed.
+ * \para count - is the number of strings returned. If the instance of OrtIoBiding has no bound outputs, zero is returned,
+ * no memory allocation is performed and buffer and lengths are nullptr on return.
+ */
+ 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);
+
+ /**
+ * The function returns an array of pointers to individually allocated OrtValues that contain results of a model execution with RunWithBinding()
+ * The array contains the same number of OrtValues and they are in the same order as they were bound with BindOutput()
+ * or BindOutputToDevice().
+ * The returned OrtValues must be individually released 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 OrtValues contained therein are individually released.
+ *
+ * \param binding_ptr - instance of OrtIoBidning
+ * \param allocator - instance of allocator to allocate output array
+ * \param output - pointer to the allocated buffer. Returns nullptr if no outputs.
+ * \param output_count - pointer to the number of OrtValues returned. Zero if no outputs.
+ */
+ ORT_API2_STATUS(GetBoundOutputValues, _In_ const OrtIoBinding* binding_ptr, _In_ OrtAllocator* allocator,
+ _Out_writes_all_(output_count) OrtValue*** output, _Out_ size_t* output_count);
+
+ /** Clears any previously specified bindings for inputs/outputs
+ */
+ void(ORT_API_CALL* ClearBoundInputs)(_Inout_ OrtIoBinding* binding_ptr) NO_EXCEPTION ORT_ALL_ARGS_NONNULL;
+ void(ORT_API_CALL* ClearBoundOutputs)(_Inout_ OrtIoBinding* binding_ptr) NO_EXCEPTION ORT_ALL_ARGS_NONNULL;
+
+ /**
+ * Provides element-level access into a tensor.
+ * \param location_values a pointer to an array of index values that specify an element's location in the tensor data blob
+ * \param location_values_count length of location_values
+ * \param out a pointer to the element specified by location_values
+ * e.g.
+ * Given a tensor with overall shape [3,224,224], an element at
+ * location [2,150,128] can be accessed directly.
+ *
+ * This function only works for numeric tensors.
+ * This is a no-copy method whose pointer is only valid until the backing OrtValue is free'd.
+ */
+ ORT_API2_STATUS(TensorAt, _Inout_ OrtValue* value, const int64_t* location_values, size_t location_values_count, _Outptr_ void** out);
+
+ /**
+ * Creates an allocator instance and registers it with the env to enable
+ * sharing 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 mem_info must be non-null.
+ * \param arena_cfg if nullptr defaults will be used.
+ * See docs/C_API.md for details.
+ */
+ ORT_API2_STATUS(CreateAndRegisterAllocator, _Inout_ OrtEnv* env, _In_ const OrtMemoryInfo* mem_info,
+ _In_ const OrtArenaCfg* arena_cfg);
+
+ /**
+ * Set the language projection for collecting telemetry data when Env is created
+ * \param projection the source projected language.
+ */
+ ORT_API2_STATUS(SetLanguageProjection, _In_ const OrtEnv* ort_env, _In_ OrtLanguageProjection projection);
+
+ /**
+ * On some platforms, this timer may not be as precise as nanoseconds
+ * For instance, on Windows and MacOS, the precision will be ~100ns
+ * \param out is set to the nanoseconds of profiling's start time
+ */
+ ORT_API2_STATUS(SessionGetProfilingStartTimeNs, _In_ const OrtSession* sess, _Outptr_ uint64_t* out);
+
+ /**
+ * Use this API to configure the global thread pool options to be used in the call to CreateEnvWithGlobalThreadPools.
+ * A value of 0 means ORT will pick the default.
+ * A value of 1 means the invoking thread will be used; no threads will be created in the thread pool.
+ */
+ ORT_API2_STATUS(SetGlobalIntraOpNumThreads, _Inout_ OrtThreadingOptions* tp_options, int intra_op_num_threads);
+ ORT_API2_STATUS(SetGlobalInterOpNumThreads, _Inout_ OrtThreadingOptions* tp_options, int inter_op_num_threads);
+
+ /**
+ * Use this API to configure the global thread pool options to be used in the call to CreateEnvWithGlobalThreadPools.
+ * Allow spinning of thread pools when their queues are empty. This API will set the value for both
+ * inter_op and intra_op threadpools.
+ * \param allow_spinning valid values are 1 and 0.
+ * 1: threadpool will spin to wait for queue to become non-empty, 0: it won't spin.
+ * Prefer a value of 0 if your CPU usage is very high.
+ */
+ ORT_API2_STATUS(SetGlobalSpinControl, _Inout_ OrtThreadingOptions* tp_options, int allow_spinning);
+
+ /**
+ * 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 API 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 name name of the initializer
+ * \param val OrtValue containing the initializer. Lifetime of 'val' and the underlying initializer buffer must be
+ * managed by the user (created using the CreateTensorWithDataAsOrtValue API) and it must outlive the session object
+ * to which it is added.
+ */
+ ORT_API2_STATUS(AddInitializer, _Inout_ OrtSessionOptions* options, _In_z_ const char* name,
+ _In_ const OrtValue* val);
+
+ /**
+ * Creates a custom environment with global threadpools and logger that will be shared across sessions.
+ * Use this in conjunction with DisablePerSessionThreads API or else the session will use
+ * its own thread pools.
+ *
+ * \param out should be freed by `ReleaseEnv` after use
+ */
+ ORT_API2_STATUS(CreateEnvWithCustomLoggerAndGlobalThreadPools, OrtLoggingFunction logging_function, _In_opt_ void* logger_param, OrtLoggingLevel logging_level,
+ _In_ const char* logid, _In_ const struct OrtThreadingOptions* tp_options, _Outptr_ OrtEnv** out);
+
+ /**
+ * 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.
+ */
+ ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_CUDA,
+ _In_ OrtSessionOptions* options, _In_ const OrtCUDAProviderOptions* cuda_options);
+
+ /**
+ * Append ROCM execution provider to the session options
+ * If ROCM is not available (due to a non rocm enabled build), this function will return failure.
+ */
+ ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_ROCM,
+ _In_ OrtSessionOptions* options, _In_ const OrtROCMProviderOptions* rocm_options);
+
+ /**
+ * Append OpenVINO execution provider to the session options
+ * If OpenVINO is not available (due to the OpenVINO provider shared library or its dependencies not being installed), this function will fail.
+ */
+ ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_OpenVINO,
+ _In_ OrtSessionOptions* options, _In_ const OrtOpenVINOProviderOptions* provider_options);
+
+ /**
+ * Use this API to configure the global thread pool options to be used in the call to CreateEnvWithGlobalThreadPools.
+ * When this API is called, flush-to-zero and denormal-as-zero are applied to threads in both intra and inter global 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.
+ */
+ ORT_API2_STATUS(SetGlobalDenormalAsZero, _Inout_ OrtThreadingOptions* tp_options);
+
+ /**
+ * (Deprecated) Use `CreateArenaCfgV2` instead
+ * Use this API to create the configuration of an arena that can eventually be used to define
+ * an arena based allocator's behavior
+ * \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
+ * \param out - a pointer to an OrtArenaCfg instance
+ * \return a nullptr in case of success or a pointer to an OrtStatus instance in case of failure
+ * See docs/C_API.md for details on what the following parameters mean and how to choose these values
+ */
+ 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);
+
+ /**
+ * Use this API 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 model_metadata - an instance of OrtModelMetadata
+ * \param allocator - allocator used to allocate the string that will be returned back
+ * \param value - is set to a null terminated string allocated using 'allocator'.
+ The caller is responsible for freeing it.
+ */
+ ORT_API2_STATUS(ModelMetadataGetGraphDescription, _In_ const OrtModelMetadata* model_metadata,
+ _Inout_ OrtAllocator* allocator, _Outptr_ char** value);
+ /**
+ * 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.
+ */
+ ORT_API2_STATUS(SessionOptionsAppendExecutionProvider_TensorRT,
+ _In_ OrtSessionOptions* options, _In_ const OrtTensorRTProviderOptions* tensorrt_options);
+
+ /**
+ * 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. Using this API makes sense only when doing multi-GPU inferencing.
+ */
+ ORT_API2_STATUS(SetCurrentGpuDeviceId, _In_ int device_id);
+
+ /**
+ * Get the current device id of the GPU execution provider (cuda/tensorrt/rocm).
+ */
+ ORT_API2_STATUS(GetCurrentGpuDeviceId, _In_ int* device_id);
+
+ /**
+ * Fetch an array of int64_t values stored as an attribute in the graph node
+ * \info - OrtKernelInfo instance
+ * \name - name of the attribute to be parsed
+ * \out - pointer to memory where the attribute's contents are to be stored
+ * \size - actual size of attribute array
+ * (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 lesser 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.)
+ */
+ ORT_API2_STATUS(KernelInfoGetAttributeArray_float, _In_ const OrtKernelInfo* info, _In_ const char* name,
+ _Out_ float* out, _Inout_ size_t* size);
+
+ /**
+ * Fetch an array of int64_t values stored as an attribute in the graph node
+ * \info - OrtKernelInfo instance
+ * \name - name of the attribute to be parsed
+ * \out - pointer to memory where the attribute's contents are to be stored
+ * \size - actual size of attribute array
+ * (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 lesser 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.)
+ */
+ ORT_API2_STATUS(KernelInfoGetAttributeArray_int64, _In_ const OrtKernelInfo* info, _In_ const char* name,
+ _Out_ int64_t* out, _Inout_ size_t* size);
+
+ /**
+ * Use this API to create the configuration of an arena that can eventually be used to define
+ * an arena based allocator's behavior
+ * \param arena_config_keys - keys to configure the arena
+ * \param arena_config_values - values to configure the arena
+ * \param num_keys - number of keys passed in
+ * Supported keys are (See docs/C_API.md 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.
+ Ultimately, the allocation size is determined by the allocation memory request.
+ Further allocation sizes are governed by the arena extend strategy.
+ */
+ 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);
+
+ /**
+ * 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
+ * \param config_key A null terminated string representation of the config key
+ * \param config_value A null terminated string representation of the config value
+ * The config_key and the format of config_value are defined in onnxruntime_run_options_config_keys.h
+ */
+ ORT_API2_STATUS(AddRunConfigEntry, _Inout_ OrtRunOptions* options,
+ _In_z_ const char* config_key, _In_z_ const char* config_value);
+
+ /*
+ * Creates an OrtPrepackedWeightsContainer instance.
+ * 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.
+ * \out - created OrtPrepackedWeightsContainer instance
+ */
+ ORT_API2_STATUS(CreatePrepackedWeightsContainer, _Outptr_ OrtPrepackedWeightsContainer** out);
+
+ /*
+ * Release OrtPrepackedWeightsContainer instance
+ * Note: The OrtPrepackedWeightsContainer instance must not be released until the sessions using it are released
+ */
+ ORT_CLASS_RELEASE(PrepackedWeightsContainer);
+
+ /**
+ * Same functionality offered by CreateSession() API 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 the AddInitializer() API 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.
+ * \env - OrtEnv instance instance
+ * \model_path - model path
+ * \options - OrtSessionOptions instance
+ * \prepacked_weights_container - OrtPrepackedWeightsContainer instance
+ * \out - created session instance
+ */
+ 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);
+
+ /**
+ * Same functionality offered by CreateSessionFromArray() API 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 the AddInitializer() API 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.
+ * \env - OrtEnv instance instance
+ * \model_data - model byte array
+ * \model_data_length - the size of the model byte array
+ * \options - OrtSessionOptions instance
+ * \prepacked_weights_container - OrtPrepackedWeightsContainer instance
+ * \out - created session instance
+ */
+ 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);
+};
+
+/*
+ * 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
+*/
+#define OrtCustomOpApi OrtApi
+
+// 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)
+typedef enum OrtCustomOpInputOutputCharacteristic {
+ // TODO: Support 'Variadic' inputs/outputs
+ INPUT_OUTPUT_REQUIRED = 0,
+ INPUT_OUTPUT_OPTIONAL,
+} 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; // Initialize to ORT_API_VERSION
+
+ // This callback creates the kernel, which is a user defined parameter that is passed to the Kernel* callbacks below.
+ 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);
+
+ // Op kernel callbacks
+ 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);
+};
+
+#ifdef __cplusplus
+}
+#endif
diff --git a/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_api.h b/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_api.h new file mode 100644 index 0000000..4c1b707 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_api.h @@ -0,0 +1,650 @@ +// 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.
+//
+// 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};).
+//
+// Only move assignment between objects is allowed, there are no copy constructors. Some objects have explicit 'Clone'
+// methods for this purpose.
+
+#pragma once
+#include "onnxruntime_c_api.h"
+#include <cstddef>
+#include <array>
+#include <memory>
+#include <stdexcept>
+#include <string>
+#include <vector>
+#include <utility>
+#include <type_traits>
+
+#ifdef ORT_NO_EXCEPTIONS
+#include <iostream>
+#endif
+
+namespace Ort {
+
+// All C++ methods that can fail will throw an exception of this type
+struct Exception : std::exception {
+ 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
+#define ORT_CXX_API_THROW(string, code) \
+ do { \
+ std::cerr << Ort::Exception(string, code) \
+ .what() \
+ << std::endl; \
+ abort(); \
+ } while (false)
+#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 <typename T>
+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 <typename T>
+#ifdef ORT_API_MANUAL_INIT
+const OrtApi* Global<T>::api_{};
+inline void InitApi() { Global<void>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); }
+#else
+const OrtApi* Global<T>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION);
+#endif
+
+// This returns a reference to the OrtApi interface in use, in case someone wants to use the C API functions
+inline const OrtApi& GetApi() { return *Global<void>::api_; }
+
+// This is a C++ wrapper for GetAvailableProviders() C API and returns
+// a vector of strings representing the available execution providers.
+std::vector<std::string> GetAvailableProviders();
+
+// 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); }
+
+ORT_DEFINE_RELEASE(Allocator);
+ORT_DEFINE_RELEASE(MemoryInfo);
+ORT_DEFINE_RELEASE(CustomOpDomain);
+ORT_DEFINE_RELEASE(Env);
+ORT_DEFINE_RELEASE(RunOptions);
+ORT_DEFINE_RELEASE(Session);
+ORT_DEFINE_RELEASE(SessionOptions);
+ORT_DEFINE_RELEASE(TensorTypeAndShapeInfo);
+ORT_DEFINE_RELEASE(SequenceTypeInfo);
+ORT_DEFINE_RELEASE(MapTypeInfo);
+ORT_DEFINE_RELEASE(TypeInfo);
+ORT_DEFINE_RELEASE(Value);
+ORT_DEFINE_RELEASE(ModelMetadata);
+ORT_DEFINE_RELEASE(ThreadingOptions);
+ORT_DEFINE_RELEASE(IoBinding);
+ORT_DEFINE_RELEASE(ArenaCfg);
+
+/*! \class Ort::Float16_t
+ * \brief it is a structure that represents float16 data.
+ * \details It is necessary for type dispatching to make use of C++ API
+ * The type is implicitly convertible to/from uint16_t.
+ * 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.
+ *
+ * Generally, you can feed any of your types as float16/blfoat16 data to create a tensor
+ * on top of it, providing it can form a continuous buffer with 16-bit elements with no padding.
+ * And you can also feed a array of uint16_t elements directly. For example,
+ *
+ * \code{.unparsed}
+ * uint16_t values[] = { 15360, 16384, 16896, 17408, 17664};
+ * constexpr size_t values_length = sizeof(values) / sizeof(values[0]);
+ * std::vector<int64_t> dims = {values_length}; // one dimensional example
+ * Ort::MemoryInfo info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault);
+ * // Note we are passing bytes count in this api, not number of elements -> sizeof(values)
+ * auto float16_tensor = Ort::Value::CreateTensor(info, values, sizeof(values),
+ * dims.data(), dims.size(), ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16);
+ * \endcode
+ *
+ * Here is another example, a little bit more elaborate. Let's assume that you use your own float16 type and you want to use
+ * a templated version of the API above so the type is automatically set based on your type. You will need to supply an extra
+ * template specialization.
+ *
+ * \code{.unparsed}
+ * namespace yours { struct half {}; } // assume this is your type, define this:
+ * namespace Ort {
+ * template<>
+ * struct TypeToTensorType<yours::half> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16; };
+ * } //namespace Ort
+ *
+ * std::vector<yours::half> values;
+ * std::vector<int64_t> dims = {values.size()}; // one dimensional example
+ * Ort::MemoryInfo info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault);
+ * // Here we are passing element count -> values.size()
+ * auto float16_tensor = Ort::Value::CreateTensor<yours::half>(info, values.data(), values.size(), dims.data(), dims.size());
+ *
+ * \endcode
+ */
+struct Float16_t {
+ uint16_t value;
+ constexpr Float16_t() noexcept : value(0) {}
+ constexpr Float16_t(uint16_t v) noexcept : value(v) {}
+ constexpr operator uint16_t() const noexcept { return value; }
+ constexpr bool operator==(const Float16_t& rhs) const noexcept { return value == rhs.value; };
+ constexpr bool operator!=(const Float16_t& rhs) const noexcept { return value != rhs.value; };
+};
+
+static_assert(sizeof(Float16_t) == sizeof(uint16_t), "Sizes must match");
+
+/*! \class Ort::BFloat16_t
+ * \brief is a structure that represents bfloat16 data.
+ * \details It is necessary for type dispatching to make use of C++ API
+ * The type is implicitly convertible to/from uint16_t.
+ * 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.
+ *
+ * See also code examples for Float16_t above.
+ */
+struct BFloat16_t {
+ uint16_t value;
+ constexpr BFloat16_t() noexcept : value(0) {}
+ constexpr BFloat16_t(uint16_t v) noexcept : value(v) {}
+ constexpr operator uint16_t() const noexcept { return value; }
+ constexpr bool operator==(const BFloat16_t& rhs) const noexcept { return value == rhs.value; };
+ constexpr bool operator!=(const BFloat16_t& rhs) const noexcept { return value != rhs.value; };
+};
+
+static_assert(sizeof(BFloat16_t) == sizeof(uint16_t), "Sizes must match");
+
+// This is used internally by the C++ API. This is the common base class used by the wrapper objects.
+template <typename T>
+struct Base {
+ using contained_type = T;
+
+ Base() = default;
+ Base(T* p) : p_{p} {
+ if (!p)
+ ORT_CXX_API_THROW("Allocation failure", ORT_FAIL);
+ }
+ ~Base() { OrtRelease(p_); }
+
+ operator T*() { return p_; }
+ operator const T*() const { return p_; }
+
+ T* release() {
+ T* p = p_;
+ p_ = nullptr;
+ return p;
+ }
+
+ protected:
+ Base(const Base&) = delete;
+ Base& operator=(const Base&) = delete;
+ Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; }
+ void operator=(Base&& v) noexcept {
+ OrtRelease(p_);
+ p_ = v.p_;
+ v.p_ = nullptr;
+ }
+
+ T* p_{};
+
+ template <typename>
+ friend struct Unowned; // This friend line is needed to keep the centos C++ compiler from giving an error
+};
+
+template <typename T>
+struct Base<const T> {
+ using contained_type = const T;
+
+ Base() = default;
+ Base(const T* p) : p_{p} {
+ if (!p)
+ ORT_CXX_API_THROW("Invalid instance ptr", ORT_INVALID_ARGUMENT);
+ }
+ ~Base() = default;
+
+ operator const T*() const { return p_; }
+
+ protected:
+ Base(const Base&) = delete;
+ Base& operator=(const Base&) = delete;
+ Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; }
+ void operator=(Base&& v) noexcept {
+ p_ = v.p_;
+ v.p_ = nullptr;
+ }
+
+ const T* p_{};
+};
+
+template <typename T>
+struct Unowned : T {
+ Unowned(decltype(T::p_) p) : T{p} {}
+ Unowned(Unowned&& v) : T{v.p_} {}
+ ~Unowned() { this->release(); }
+};
+
+struct AllocatorWithDefaultOptions;
+struct MemoryInfo;
+struct Env;
+struct TypeInfo;
+struct Value;
+struct ModelMetadata;
+
+struct Env : Base<OrtEnv> {
+ Env(std::nullptr_t) {}
+ Env(OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");
+ Env(const OrtThreadingOptions* tp_options, OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");
+ Env(OrtLoggingLevel logging_level, const char* logid, OrtLoggingFunction logging_function, void* logger_param);
+ Env(const OrtThreadingOptions* tp_options, OrtLoggingFunction logging_function, void* logger_param,
+ OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");
+ explicit Env(OrtEnv* p) : Base<OrtEnv>{p} {}
+
+ Env& EnableTelemetryEvents();
+ Env& DisableTelemetryEvents();
+
+ Env& CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg);
+
+ static const OrtApi* s_api;
+};
+
+struct CustomOpDomain : Base<OrtCustomOpDomain> {
+ explicit CustomOpDomain(std::nullptr_t) {}
+ explicit CustomOpDomain(const char* domain);
+
+ void Add(OrtCustomOp* op);
+};
+
+struct RunOptions : Base<OrtRunOptions> {
+ RunOptions(std::nullptr_t) {}
+ RunOptions();
+
+ RunOptions& SetRunLogVerbosityLevel(int);
+ int GetRunLogVerbosityLevel() const;
+
+ RunOptions& SetRunLogSeverityLevel(int);
+ int GetRunLogSeverityLevel() const;
+
+ RunOptions& SetRunTag(const char* run_tag);
+ const char* GetRunTag() const;
+
+ RunOptions& AddConfigEntry(const char* config_key, const char* config_value);
+
+ // terminate ALL currently executing Session::Run calls that were made using this RunOptions instance
+ RunOptions& SetTerminate();
+ // unset the terminate flag so this RunOptions instance can be used in a new Session::Run call
+ RunOptions& UnsetTerminate();
+};
+
+struct SessionOptions : Base<OrtSessionOptions> {
+ explicit SessionOptions(std::nullptr_t) {}
+ SessionOptions();
+ explicit SessionOptions(OrtSessionOptions* p) : Base<OrtSessionOptions>{p} {}
+
+ SessionOptions Clone() const;
+
+ SessionOptions& SetIntraOpNumThreads(int intra_op_num_threads);
+ SessionOptions& SetInterOpNumThreads(int inter_op_num_threads);
+ SessionOptions& SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level);
+
+ SessionOptions& EnableCpuMemArena();
+ SessionOptions& DisableCpuMemArena();
+
+ SessionOptions& SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_file);
+
+ SessionOptions& EnableProfiling(const ORTCHAR_T* profile_file_prefix);
+ SessionOptions& DisableProfiling();
+
+ SessionOptions& EnableMemPattern();
+ SessionOptions& DisableMemPattern();
+
+ SessionOptions& SetExecutionMode(ExecutionMode execution_mode);
+
+ SessionOptions& SetLogId(const char* logid);
+ SessionOptions& SetLogSeverityLevel(int level);
+
+ SessionOptions& Add(OrtCustomOpDomain* custom_op_domain);
+
+ SessionOptions& DisablePerSessionThreads();
+
+ SessionOptions& AddConfigEntry(const char* config_key, const char* config_value);
+ SessionOptions& AddInitializer(const char* name, const OrtValue* ort_val);
+
+ SessionOptions& AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options);
+ SessionOptions& AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options);
+ SessionOptions& AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options);
+ SessionOptions& AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options);
+};
+
+struct ModelMetadata : Base<OrtModelMetadata> {
+ explicit ModelMetadata(std::nullptr_t) {}
+ explicit ModelMetadata(OrtModelMetadata* p) : Base<OrtModelMetadata>{p} {}
+
+ char* GetProducerName(OrtAllocator* allocator) const;
+ char* GetGraphName(OrtAllocator* allocator) const;
+ char* GetDomain(OrtAllocator* allocator) const;
+ char* GetDescription(OrtAllocator* allocator) const;
+ char* GetGraphDescription(OrtAllocator* allocator) const;
+ char** GetCustomMetadataMapKeys(OrtAllocator* allocator, _Out_ int64_t& num_keys) const;
+ char* LookupCustomMetadataMap(const char* key, OrtAllocator* allocator) const;
+ int64_t GetVersion() const;
+};
+
+struct Session : Base<OrtSession> {
+ explicit Session(std::nullptr_t) {}
+ Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options);
+ Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options, OrtPrepackedWeightsContainer* prepacked_weights_container);
+ Session(Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options);
+
+ // Run that will allocate the output values
+ std::vector<Value> 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);
+ // Run for when there is a list of preallocated outputs
+ 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 struct IoBinding&);
+
+ size_t GetInputCount() const;
+ size_t GetOutputCount() const;
+ size_t GetOverridableInitializerCount() const;
+
+ char* GetInputName(size_t index, OrtAllocator* allocator) const;
+ char* GetOutputName(size_t index, OrtAllocator* allocator) const;
+ char* GetOverridableInitializerName(size_t index, OrtAllocator* allocator) const;
+ char* EndProfiling(OrtAllocator* allocator) const;
+ uint64_t GetProfilingStartTimeNs() const;
+ ModelMetadata GetModelMetadata() const;
+
+ TypeInfo GetInputTypeInfo(size_t index) const;
+ TypeInfo GetOutputTypeInfo(size_t index) const;
+ TypeInfo GetOverridableInitializerTypeInfo(size_t index) const;
+};
+
+struct TensorTypeAndShapeInfo : Base<OrtTensorTypeAndShapeInfo> {
+ explicit TensorTypeAndShapeInfo(std::nullptr_t) {}
+ explicit TensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* p) : Base<OrtTensorTypeAndShapeInfo>{p} {}
+
+ ONNXTensorElementDataType GetElementType() const;
+ size_t GetElementCount() const;
+
+ size_t GetDimensionsCount() const;
+ void GetDimensions(int64_t* values, size_t values_count) const;
+ void GetSymbolicDimensions(const char** values, size_t values_count) const;
+
+ std::vector<int64_t> GetShape() const;
+};
+
+struct SequenceTypeInfo : Base<OrtSequenceTypeInfo> {
+ explicit SequenceTypeInfo(std::nullptr_t) {}
+ explicit SequenceTypeInfo(OrtSequenceTypeInfo* p) : Base<OrtSequenceTypeInfo>{p} {}
+
+ TypeInfo GetSequenceElementType() const;
+};
+
+struct MapTypeInfo : Base<OrtMapTypeInfo> {
+ explicit MapTypeInfo(std::nullptr_t) {}
+ explicit MapTypeInfo(OrtMapTypeInfo* p) : Base<OrtMapTypeInfo>{p} {}
+
+ ONNXTensorElementDataType GetMapKeyType() const;
+ TypeInfo GetMapValueType() const;
+};
+
+struct TypeInfo : Base<OrtTypeInfo> {
+ explicit TypeInfo(std::nullptr_t) {}
+ explicit TypeInfo(OrtTypeInfo* p) : Base<OrtTypeInfo>{p} {}
+
+ Unowned<TensorTypeAndShapeInfo> GetTensorTypeAndShapeInfo() const;
+ Unowned<SequenceTypeInfo> GetSequenceTypeInfo() const;
+ Unowned<MapTypeInfo> GetMapTypeInfo() const;
+
+ ONNXType GetONNXType() const;
+};
+
+struct Value : Base<OrtValue> {
+ template <typename T>
+ static Value CreateTensor(const OrtMemoryInfo* info, T* p_data, size_t p_data_element_count, const int64_t* shape, size_t shape_len);
+ 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);
+ template <typename T>
+ static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len);
+ static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type);
+
+ static Value CreateMap(Value& keys, Value& values);
+ static Value CreateSequence(std::vector<Value>& values);
+
+ template <typename T>
+ static Value CreateOpaque(const char* domain, const char* type_name, const T&);
+
+ template <typename T>
+ void GetOpaqueData(const char* domain, const char* type_name, T&) const;
+
+ explicit Value(std::nullptr_t) {}
+ explicit Value(OrtValue* p) : Base<OrtValue>{p} {}
+ Value(Value&&) = default;
+ Value& operator=(Value&&) = default;
+
+ bool IsTensor() const;
+ 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;
+
+ size_t GetStringTensorDataLength() const;
+ void GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const;
+
+ template <typename T>
+ T* GetTensorMutableData();
+
+ template <typename T>
+ const T* GetTensorData() const;
+
+ template <typename T>
+ T& At(const std::vector<int64_t>& location);
+
+ TypeInfo GetTypeInfo() const;
+ TensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const;
+
+ size_t GetStringTensorElementLength(size_t element_index) const;
+ void GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const;
+
+ void FillStringTensor(const char* const* s, size_t s_len);
+ void FillStringTensorElement(const char* s, size_t index);
+};
+
+// Represents native memory allocation
+struct MemoryAllocation {
+ MemoryAllocation(OrtAllocator* allocator, void* p, size_t size);
+ ~MemoryAllocation();
+ MemoryAllocation(const MemoryAllocation&) = delete;
+ MemoryAllocation& operator=(const MemoryAllocation&) = delete;
+ MemoryAllocation(MemoryAllocation&&);
+ MemoryAllocation& operator=(MemoryAllocation&&);
+
+ void* get() { return p_; }
+ size_t size() const { return size_; }
+
+ private:
+ OrtAllocator* allocator_;
+ void* p_;
+ size_t size_;
+};
+
+struct AllocatorWithDefaultOptions {
+ AllocatorWithDefaultOptions();
+
+ operator OrtAllocator*() { return p_; }
+ operator const OrtAllocator*() const { return p_; }
+
+ void* Alloc(size_t size);
+ // The return value will own the allocation
+ MemoryAllocation GetAllocation(size_t size);
+ void Free(void* p);
+
+ const OrtMemoryInfo* GetInfo() const;
+
+ private:
+ OrtAllocator* p_{};
+};
+
+template <typename B>
+struct BaseMemoryInfo : B {
+ BaseMemoryInfo() = default;
+ explicit BaseMemoryInfo(typename B::contained_type* p) : B(p) {}
+ ~BaseMemoryInfo() = default;
+ BaseMemoryInfo(BaseMemoryInfo&&) = default;
+ BaseMemoryInfo& operator=(BaseMemoryInfo&&) = default;
+
+ std::string GetAllocatorName() const;
+ OrtAllocatorType GetAllocatorType() const;
+ int GetDeviceId() const;
+ OrtMemType GetMemoryType() const;
+ template <typename U>
+ bool operator==(const BaseMemoryInfo<U>& o) const;
+};
+
+struct UnownedMemoryInfo : BaseMemoryInfo<Base<const OrtMemoryInfo> > {
+ explicit UnownedMemoryInfo(std::nullptr_t) {}
+ explicit UnownedMemoryInfo(const OrtMemoryInfo* p) : BaseMemoryInfo(p) {}
+};
+
+struct MemoryInfo : BaseMemoryInfo<Base<OrtMemoryInfo> > {
+ static MemoryInfo CreateCpu(OrtAllocatorType type, OrtMemType mem_type1);
+
+ explicit MemoryInfo(std::nullptr_t) {}
+ explicit MemoryInfo(OrtMemoryInfo* p) : BaseMemoryInfo(p) {}
+ MemoryInfo(const char* name, OrtAllocatorType type, int id, OrtMemType mem_type);
+};
+
+struct Allocator : public Base<OrtAllocator> {
+ Allocator(const Session& session, const MemoryInfo&);
+
+ void* Alloc(size_t size) const;
+ // The return value will own the allocation
+ MemoryAllocation GetAllocation(size_t size);
+ void Free(void* p) const;
+ UnownedMemoryInfo GetInfo() const;
+};
+
+struct IoBinding : public Base<OrtIoBinding> {
+ private:
+ std::vector<std::string> GetOutputNamesHelper(OrtAllocator*) const;
+ std::vector<Value> GetOutputValuesHelper(OrtAllocator*) const;
+
+ public:
+ explicit IoBinding(Session& session);
+ void BindInput(const char* name, const Value&);
+ void BindOutput(const char* name, const Value&);
+ void BindOutput(const char* name, const MemoryInfo&);
+ std::vector<std::string> GetOutputNames() const;
+ std::vector<std::string> GetOutputNames(Allocator&) const;
+ std::vector<Value> GetOutputValues() const;
+ std::vector<Value> GetOutputValues(Allocator&) const;
+ void ClearBoundInputs();
+ void ClearBoundOutputs();
+};
+
+/*! \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 : Base<OrtArenaCfg> {
+ explicit ArenaCfg(std::nullptr_t) {}
+ /**
+ * \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);
+};
+
+//
+// Custom OPs (only needed to implement custom OPs)
+//
+
+struct CustomOpApi {
+ CustomOpApi(const OrtApi& api) : api_(api) {}
+
+ template <typename T> // T is only implemented for std::vector<float>, std::vector<int64_t>, float, int64_t, and string
+ T KernelInfoGetAttribute(_In_ const OrtKernelInfo* info, _In_ const char* name);
+
+ OrtTensorTypeAndShapeInfo* GetTensorTypeAndShape(_In_ const OrtValue* value);
+ size_t GetTensorShapeElementCount(_In_ const OrtTensorTypeAndShapeInfo* info);
+ ONNXTensorElementDataType GetTensorElementType(const OrtTensorTypeAndShapeInfo* info);
+ size_t GetDimensionsCount(_In_ const OrtTensorTypeAndShapeInfo* info);
+ void GetDimensions(_In_ const OrtTensorTypeAndShapeInfo* info, _Out_ int64_t* dim_values, size_t dim_values_length);
+ void SetDimensions(OrtTensorTypeAndShapeInfo* info, _In_ const int64_t* dim_values, size_t dim_count);
+
+ template <typename T>
+ T* GetTensorMutableData(_Inout_ OrtValue* value);
+ template <typename T>
+ const T* GetTensorData(_Inout_ const OrtValue* value);
+
+ std::vector<int64_t> GetTensorShape(const OrtTensorTypeAndShapeInfo* info);
+ void ReleaseTensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* input);
+ size_t KernelContext_GetInputCount(const OrtKernelContext* context);
+ const OrtValue* KernelContext_GetInput(const OrtKernelContext* context, _In_ size_t index);
+ size_t KernelContext_GetOutputCount(const OrtKernelContext* context);
+ OrtValue* KernelContext_GetOutput(OrtKernelContext* context, _In_ size_t index, _In_ const int64_t* dim_values, size_t dim_count);
+
+ void ThrowOnError(OrtStatus* result);
+
+ private:
+ const OrtApi& api_;
+};
+
+template <typename TOp, typename TKernel>
+struct CustomOpBase : OrtCustomOp {
+ CustomOpBase() {
+ OrtCustomOp::version = ORT_API_VERSION;
+ OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info) { return static_cast<const TOp*>(this_)->CreateKernel(*api, info); };
+ OrtCustomOp::GetName = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetName(); };
+
+ OrtCustomOp::GetExecutionProviderType = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetExecutionProviderType(); };
+
+ OrtCustomOp::GetInputTypeCount = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetInputTypeCount(); };
+ OrtCustomOp::GetInputType = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetInputType(index); };
+
+ OrtCustomOp::GetOutputTypeCount = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetOutputTypeCount(); };
+ OrtCustomOp::GetOutputType = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetOutputType(index); };
+
+ OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) { static_cast<TKernel*>(op_kernel)->Compute(context); };
+ OrtCustomOp::KernelDestroy = [](void* op_kernel) { delete static_cast<TKernel*>(op_kernel); };
+
+ OrtCustomOp::GetInputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetInputCharacteristic(index); };
+ OrtCustomOp::GetOutputCharacteristic = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetOutputCharacteristic(index); };
+ }
+
+ // 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;
+ }
+};
+
+} // namespace Ort
+
+#include "onnxruntime_cxx_inline.h"
diff --git a/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_inline.h b/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_inline.h new file mode 100644 index 0000000..e90fd36 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/onnxruntime_cxx_inline.h @@ -0,0 +1,1038 @@ +// 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.
+
+namespace Ort {
+
+inline void ThrowOnError(const OrtApi& ort, OrtStatus* status) {
+ if (status) {
+ std::string error_message = ort.GetErrorMessage(status);
+ OrtErrorCode error_code = ort.GetErrorCode(status);
+ ort.ReleaseStatus(status);
+ ORT_CXX_API_THROW(std::move(error_message), error_code);
+ }
+}
+
+inline void ThrowOnError(OrtStatus* status) {
+ ThrowOnError(GetApi(), status);
+}
+
+// This template converts a C++ type into it's ONNXTensorElementDataType
+template <typename T>
+struct TypeToTensorType;
+template <>
+struct TypeToTensorType<float> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT; };
+template <>
+struct TypeToTensorType<Float16_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16; };
+template <>
+struct TypeToTensorType<BFloat16_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16; };
+template <>
+struct TypeToTensorType<double> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE; };
+template <>
+struct TypeToTensorType<int8_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8; };
+template <>
+struct TypeToTensorType<int16_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16; };
+template <>
+struct TypeToTensorType<int32_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32; };
+template <>
+struct TypeToTensorType<int64_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64; };
+template <>
+struct TypeToTensorType<uint8_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8; };
+template <>
+struct TypeToTensorType<uint16_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16; };
+template <>
+struct TypeToTensorType<uint32_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32; };
+template <>
+struct TypeToTensorType<uint64_t> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64; };
+template <>
+struct TypeToTensorType<bool> { static constexpr ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL; };
+
+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<void>(ret);
+ }
+}
+
+inline MemoryAllocation::MemoryAllocation(MemoryAllocation&& o) : allocator_(nullptr), p_(nullptr), size_(0) {
+ *this = std::move(o);
+}
+
+inline MemoryAllocation& MemoryAllocation::operator=(MemoryAllocation&& o) {
+ 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;
+}
+
+inline AllocatorWithDefaultOptions::AllocatorWithDefaultOptions() {
+ ThrowOnError(GetApi().GetAllocatorWithDefaultOptions(&p_));
+}
+
+inline void* AllocatorWithDefaultOptions::Alloc(size_t size) {
+ void* out;
+ ThrowOnError(GetApi().AllocatorAlloc(p_, size, &out));
+ return out;
+}
+
+inline MemoryAllocation Ort::AllocatorWithDefaultOptions::GetAllocation(size_t size) {
+ void* out;
+ ThrowOnError(GetApi().AllocatorAlloc(p_, size, &out));
+ MemoryAllocation result(p_, out, size);
+ return result;
+}
+
+inline void AllocatorWithDefaultOptions::Free(void* p) {
+ ThrowOnError(GetApi().AllocatorFree(p_, p));
+}
+
+inline const OrtMemoryInfo* AllocatorWithDefaultOptions::GetInfo() const {
+ const OrtMemoryInfo* out;
+ ThrowOnError(GetApi().AllocatorGetInfo(p_, &out));
+ return out;
+}
+
+template <typename B>
+inline std::string BaseMemoryInfo<B>::GetAllocatorName() const {
+ const char* name = nullptr;
+ ThrowOnError(GetApi().MemoryInfoGetName(*this, &name));
+ return std::string(name);
+}
+
+template <typename B>
+inline OrtAllocatorType BaseMemoryInfo<B>::GetAllocatorType() const {
+ OrtAllocatorType type;
+ ThrowOnError(GetApi().MemoryInfoGetType(*this, &type));
+ return type;
+}
+
+template <typename B>
+int BaseMemoryInfo<B>::GetDeviceId() const {
+ int id = 0;
+ ThrowOnError(GetApi().MemoryInfoGetId(*this, &id));
+ return id;
+}
+
+template <typename B>
+inline OrtMemType BaseMemoryInfo<B>::GetMemoryType() const {
+ OrtMemType type;
+ ThrowOnError(GetApi().MemoryInfoGetMemType(*this, &type));
+ return type;
+}
+
+template <typename B>
+template <typename U>
+inline bool BaseMemoryInfo<B>::operator==(const BaseMemoryInfo<U>& o) const {
+ int comp_result = 0;
+ ThrowOnError(Ort::GetApi().CompareMemoryInfo(*this, o, &comp_result));
+ return comp_result == 0;
+}
+
+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, &p_));
+}
+
+inline Allocator::Allocator(const Session& sess, const MemoryInfo& mem_info) {
+ ThrowOnError(GetApi().CreateAllocator(sess, mem_info, &p_));
+}
+
+inline void* Allocator::Alloc(size_t size) const {
+ void* out = nullptr;
+ ThrowOnError(GetApi().AllocatorAlloc(p_, size, &out));
+ return out;
+}
+
+inline MemoryAllocation Ort::Allocator::GetAllocation(size_t size) {
+ void* out = nullptr;
+ ThrowOnError(GetApi().AllocatorAlloc(p_, size, &out));
+ MemoryAllocation result(p_, out, size);
+ return result;
+}
+
+inline void Allocator::Free(void* p) const {
+ ThrowOnError(GetApi().AllocatorFree(p_, p));
+}
+
+inline UnownedMemoryInfo Allocator::GetInfo() const {
+ const OrtMemoryInfo* out = nullptr;
+ ThrowOnError(GetApi().AllocatorGetInfo(p_, &out));
+ return UnownedMemoryInfo(out);
+}
+
+inline IoBinding::IoBinding(Session& session) {
+ ThrowOnError(GetApi().CreateIoBinding(session, &p_));
+}
+
+inline void IoBinding::BindInput(const char* name, const Value& value) {
+ ThrowOnError(GetApi().BindInput(p_, name, value));
+}
+
+inline void IoBinding::BindOutput(const char* name, const Value& value) {
+ ThrowOnError(GetApi().BindOutput(p_, name, value));
+}
+
+inline void IoBinding::BindOutput(const char* name, const MemoryInfo& mem_info) {
+ ThrowOnError(GetApi().BindOutputToDevice(p_, name, mem_info));
+}
+
+inline std::vector<std::string> IoBinding::GetOutputNamesHelper(OrtAllocator* allocator) const {
+ std::vector<std::string> result;
+ auto free_fn = [allocator](void* p) { if (p) allocator->Free(allocator, p); };
+ using Ptr = std::unique_ptr<void, decltype(free_fn)>;
+
+ char* buffer = nullptr;
+ size_t* lengths = nullptr;
+ size_t count = 0;
+ ThrowOnError(GetApi().GetBoundOutputNames(p_, 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<std::string> IoBinding::GetOutputNames() const {
+ AllocatorWithDefaultOptions allocator;
+ return GetOutputNamesHelper(allocator);
+}
+
+inline std::vector<std::string> IoBinding::GetOutputNames(Allocator& allocator) const {
+ return GetOutputNamesHelper(allocator);
+}
+
+inline std::vector<Value> Ort::IoBinding::GetOutputValuesHelper(OrtAllocator* allocator) const {
+ std::vector<Value> result;
+ size_t owned = 0;
+ size_t output_count = 0;
+ // Lambda to release the buffer when no longer needed and
+ // make sure that we destroy all instances on exception
+ auto free_fn = [&owned, &output_count, allocator](OrtValue** buffer) {
+ if (buffer) {
+ while (owned < output_count) {
+ auto* p = buffer + owned++;
+ GetApi().ReleaseValue(*p);
+ }
+ allocator->Free(allocator, buffer);
+ }
+ };
+ using Ptr = std::unique_ptr<OrtValue*, decltype(free_fn)>;
+
+ OrtValue** output_buffer = nullptr;
+ ThrowOnError(GetApi().GetBoundOutputValues(p_, allocator, &output_buffer, &output_count));
+ if (output_count == 0) {
+ return result;
+ }
+
+ Ptr buffer_g(output_buffer, free_fn);
+
+ result.reserve(output_count);
+ for (size_t i = 0; i < output_count; ++i) {
+ result.emplace_back(output_buffer[i]);
+ ++owned;
+ }
+ return result;
+}
+
+inline std::vector<Value> Ort::IoBinding::GetOutputValues(Allocator& allocator) const {
+ return GetOutputValuesHelper(allocator);
+}
+
+inline std::vector<Value> Ort::IoBinding::GetOutputValues() const {
+ AllocatorWithDefaultOptions allocator;
+ return GetOutputValuesHelper(allocator);
+}
+
+inline void IoBinding::ClearBoundInputs() {
+ GetApi().ClearBoundInputs(p_);
+}
+
+inline void IoBinding::ClearBoundOutputs() {
+ GetApi().ClearBoundOutputs(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 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::CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg) {
+ ThrowOnError(GetApi().CreateAndRegisterAllocator(p_, mem_info, arena_cfg));
+ return *this;
+}
+
+inline CustomOpDomain::CustomOpDomain(const char* domain) {
+ ThrowOnError(GetApi().CreateCustomOpDomain(domain, &p_));
+}
+
+inline void CustomOpDomain::Add(OrtCustomOp* op) {
+ ThrowOnError(GetApi().CustomOpDomain_Add(p_, op));
+}
+
+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 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 RunOptions& RunOptions::SetTerminate() {
+ ThrowOnError(GetApi().RunOptionsSetTerminate(p_));
+ return *this;
+}
+
+inline RunOptions& RunOptions::UnsetTerminate() {
+ ThrowOnError(GetApi().RunOptionsUnsetTerminate(p_));
+ return *this;
+}
+
+inline SessionOptions::SessionOptions() {
+ ThrowOnError(GetApi().CreateSessionOptions(&p_));
+}
+
+inline SessionOptions SessionOptions::Clone() const {
+ OrtSessionOptions* out;
+ ThrowOnError(GetApi().CloneSessionOptions(p_, &out));
+ return SessionOptions{out};
+}
+
+inline SessionOptions& SessionOptions::SetIntraOpNumThreads(int intra_op_num_threads) {
+ ThrowOnError(GetApi().SetIntraOpNumThreads(p_, intra_op_num_threads));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetInterOpNumThreads(int inter_op_num_threads) {
+ ThrowOnError(GetApi().SetInterOpNumThreads(p_, inter_op_num_threads));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level) {
+ ThrowOnError(GetApi().SetSessionGraphOptimizationLevel(p_, graph_optimization_level));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_filepath) {
+ ThrowOnError(GetApi().SetOptimizedModelFilePath(p_, optimized_model_filepath));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::EnableProfiling(const ORTCHAR_T* profile_file_prefix) {
+ ThrowOnError(GetApi().EnableProfiling(p_, profile_file_prefix));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::DisableProfiling() {
+ ThrowOnError(GetApi().DisableProfiling(p_));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::EnableMemPattern() {
+ ThrowOnError(GetApi().EnableMemPattern(p_));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::DisableMemPattern() {
+ ThrowOnError(GetApi().DisableMemPattern(p_));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::EnableCpuMemArena() {
+ ThrowOnError(GetApi().EnableCpuMemArena(p_));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::DisableCpuMemArena() {
+ ThrowOnError(GetApi().DisableCpuMemArena(p_));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetExecutionMode(ExecutionMode execution_mode) {
+ ThrowOnError(GetApi().SetSessionExecutionMode(p_, execution_mode));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetLogId(const char* logid) {
+ ThrowOnError(GetApi().SetSessionLogId(p_, logid));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::SetLogSeverityLevel(int level) {
+ ThrowOnError(GetApi().SetSessionLogSeverityLevel(p_, level));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::Add(OrtCustomOpDomain* custom_op_domain) {
+ ThrowOnError(GetApi().AddCustomOpDomain(p_, custom_op_domain));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AddConfigEntry(const char* config_key, const char* config_value) {
+ ThrowOnError(GetApi().AddSessionConfigEntry(p_, config_key, config_value));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AddInitializer(const char* name, const OrtValue* ort_val) {
+ ThrowOnError(GetApi().AddInitializer(p_, name, ort_val));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options) {
+ ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_CUDA(p_, &provider_options));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options) {
+ ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_ROCM(p_, &provider_options));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options) {
+ ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_TensorRT(p_, &provider_options));
+ return *this;
+}
+
+inline SessionOptions& SessionOptions::AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options) {
+ ThrowOnError(GetApi().SessionOptionsAppendExecutionProvider_OpenVINO(p_, &provider_options));
+ return *this;
+}
+
+inline Session::Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options) {
+ ThrowOnError(GetApi().CreateSession(env, model_path, options, &p_));
+}
+
+inline Session::Session(Env& env, const ORTCHAR_T* model_path, const SessionOptions& options,
+ OrtPrepackedWeightsContainer* prepacked_weights_container) {
+ ThrowOnError(GetApi().CreateSessionWithPrepackedWeightsContainer(env, model_path, options, prepacked_weights_container, &p_));
+}
+
+inline Session::Session(Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options) {
+ ThrowOnError(GetApi().CreateSessionFromArray(env, model_data, model_data_length, options, &p_));
+}
+
+inline std::vector<Value> Session::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_names_count) {
+ std::vector<Ort::Value> output_values;
+ for (size_t i = 0; i < output_names_count; i++)
+ output_values.emplace_back(nullptr);
+ Run(run_options, input_names, input_values, input_count, output_names, output_values.data(), output_names_count);
+ return output_values;
+}
+
+inline void Session::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<const OrtValue**>(const_cast<Value*>(input_values));
+ auto ort_output_values = reinterpret_cast<OrtValue**>(output_values);
+ ThrowOnError(GetApi().Run(p_, run_options, input_names, ort_input_values, input_count, output_names, output_count, ort_output_values));
+}
+
+inline void Session::Run(const RunOptions& run_options, const IoBinding& io_binding) {
+ ThrowOnError(GetApi().RunWithBinding(p_, run_options, io_binding));
+}
+
+inline size_t Session::GetInputCount() const {
+ size_t out;
+ ThrowOnError(GetApi().SessionGetInputCount(p_, &out));
+ return out;
+}
+
+inline size_t Session::GetOutputCount() const {
+ size_t out;
+ ThrowOnError(GetApi().SessionGetOutputCount(p_, &out));
+ return out;
+}
+
+inline size_t Session::GetOverridableInitializerCount() const {
+ size_t out;
+ ThrowOnError(GetApi().SessionGetOverridableInitializerCount(p_, &out));
+ return out;
+}
+
+inline char* Session::GetInputName(size_t index, OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().SessionGetInputName(p_, index, allocator, &out));
+ return out;
+}
+
+inline char* Session::GetOutputName(size_t index, OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().SessionGetOutputName(p_, index, allocator, &out));
+ return out;
+}
+
+inline char* Session::GetOverridableInitializerName(size_t index, OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().SessionGetOverridableInitializerName(p_, index, allocator, &out));
+ return out;
+}
+
+inline char* Session::EndProfiling(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().SessionEndProfiling(p_, allocator, &out));
+ return out;
+}
+
+inline uint64_t Session::GetProfilingStartTimeNs() const {
+ uint64_t out;
+ ThrowOnError(GetApi().SessionGetProfilingStartTimeNs(p_, &out));
+ return out;
+}
+
+inline ModelMetadata Session::GetModelMetadata() const {
+ OrtModelMetadata* out;
+ ThrowOnError(GetApi().SessionGetModelMetadata(p_, &out));
+ return ModelMetadata{out};
+}
+
+inline char* ModelMetadata::GetProducerName(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataGetProducerName(p_, allocator, &out));
+ return out;
+}
+
+inline char* ModelMetadata::GetGraphName(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataGetGraphName(p_, allocator, &out));
+ return out;
+}
+
+inline char* ModelMetadata::GetDomain(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataGetDomain(p_, allocator, &out));
+ return out;
+}
+
+inline char* ModelMetadata::GetDescription(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataGetDescription(p_, allocator, &out));
+ return out;
+}
+
+inline char* ModelMetadata::GetGraphDescription(OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataGetGraphDescription(p_, allocator, &out));
+ return out;
+}
+
+inline char* ModelMetadata::LookupCustomMetadataMap(const char* key, OrtAllocator* allocator) const {
+ char* out;
+ ThrowOnError(GetApi().ModelMetadataLookupCustomMetadataMap(p_, allocator, key, &out));
+ return out;
+}
+
+inline char** ModelMetadata::GetCustomMetadataMapKeys(OrtAllocator* allocator, _Out_ int64_t& num_keys) const {
+ char** out;
+ ThrowOnError(GetApi().ModelMetadataGetCustomMetadataMapKeys(p_, allocator, &out, &num_keys));
+ return out;
+}
+
+inline int64_t ModelMetadata::GetVersion() const {
+ int64_t out;
+ ThrowOnError(GetApi().ModelMetadataGetVersion(p_, &out));
+ return out;
+}
+
+inline TypeInfo Session::GetInputTypeInfo(size_t index) const {
+ OrtTypeInfo* out;
+ ThrowOnError(GetApi().SessionGetInputTypeInfo(p_, index, &out));
+ return TypeInfo{out};
+}
+
+inline TypeInfo Session::GetOutputTypeInfo(size_t index) const {
+ OrtTypeInfo* out;
+ ThrowOnError(GetApi().SessionGetOutputTypeInfo(p_, index, &out));
+ return TypeInfo{out};
+}
+
+inline TypeInfo Session::GetOverridableInitializerTypeInfo(size_t index) const {
+ OrtTypeInfo* out;
+ ThrowOnError(GetApi().SessionGetOverridableInitializerTypeInfo(p_, index, &out));
+ return TypeInfo{out};
+}
+
+inline ONNXTensorElementDataType TensorTypeAndShapeInfo::GetElementType() const {
+ ONNXTensorElementDataType out;
+ ThrowOnError(GetApi().GetTensorElementType(p_, &out));
+ return out;
+}
+
+inline size_t TensorTypeAndShapeInfo::GetElementCount() const {
+ size_t out;
+ ThrowOnError(GetApi().GetTensorShapeElementCount(p_, &out));
+ return static_cast<size_t>(out);
+}
+
+inline size_t TensorTypeAndShapeInfo::GetDimensionsCount() const {
+ size_t out;
+ ThrowOnError(GetApi().GetDimensionsCount(p_, &out));
+ return out;
+}
+
+inline void TensorTypeAndShapeInfo::GetDimensions(int64_t* values, size_t values_count) const {
+ ThrowOnError(GetApi().GetDimensions(p_, values, values_count));
+}
+
+inline void TensorTypeAndShapeInfo::GetSymbolicDimensions(const char** values, size_t values_count) const {
+ ThrowOnError(GetApi().GetSymbolicDimensions(p_, values, values_count));
+}
+
+inline std::vector<int64_t> TensorTypeAndShapeInfo::GetShape() const {
+ std::vector<int64_t> out(GetDimensionsCount(), 0);
+ GetDimensions(out.data(), out.size());
+ return out;
+}
+
+inline Unowned<TensorTypeAndShapeInfo> TypeInfo::GetTensorTypeAndShapeInfo() const {
+ const OrtTensorTypeAndShapeInfo* out;
+ ThrowOnError(GetApi().CastTypeInfoToTensorInfo(p_, &out));
+ return Unowned<TensorTypeAndShapeInfo>(const_cast<OrtTensorTypeAndShapeInfo*>(out));
+}
+
+inline Unowned<SequenceTypeInfo> TypeInfo::GetSequenceTypeInfo() const {
+ const OrtSequenceTypeInfo* out;
+ ThrowOnError(GetApi().CastTypeInfoToSequenceTypeInfo(p_, &out));
+ return Unowned<SequenceTypeInfo>{const_cast<OrtSequenceTypeInfo*>(out)};
+}
+
+inline TypeInfo SequenceTypeInfo::GetSequenceElementType() const {
+ OrtTypeInfo* output;
+ ThrowOnError(GetApi().GetSequenceElementType(p_, &output));
+ return TypeInfo{output};
+}
+
+inline Unowned<MapTypeInfo> TypeInfo::GetMapTypeInfo() const {
+ const OrtMapTypeInfo* out;
+ ThrowOnError(GetApi().CastTypeInfoToMapTypeInfo(p_, &out));
+ return Unowned<MapTypeInfo>{const_cast<OrtMapTypeInfo*>(out)};
+}
+
+inline ONNXTensorElementDataType MapTypeInfo::GetMapKeyType() const {
+ ONNXTensorElementDataType out;
+ ThrowOnError(GetApi().GetMapKeyType(p_, &out));
+ return out;
+}
+
+inline TypeInfo MapTypeInfo::GetMapValueType() const {
+ OrtTypeInfo* output;
+ ThrowOnError(GetApi().GetMapValueType(p_, &output));
+ return TypeInfo{output};
+}
+
+inline ONNXType TypeInfo::GetONNXType() const {
+ ONNXType out;
+ ThrowOnError(GetApi().GetOnnxTypeFromTypeInfo(p_, &out));
+ return out;
+}
+
+template <typename T>
+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<T>::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};
+}
+
+template <typename T>
+inline Value Value::CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len) {
+ return CreateTensor(allocator, shape, shape_len, TypeToTensorType<T>::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};
+}
+
+inline Value Value::CreateMap(Value& keys, Value& values) {
+ OrtValue* out;
+ OrtValue* inputs[2] = {keys, values};
+ ThrowOnError(GetApi().CreateValue(inputs, 2, ONNX_TYPE_MAP, &out));
+ return Value{out};
+}
+
+inline Value Value::CreateSequence(std::vector<Value>& values) {
+ OrtValue* out;
+ std::vector<OrtValue*> 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 <typename T>
+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};
+}
+
+template <typename T>
+inline void Value::GetOpaqueData(const char* domain, const char* type_name, T& out) const {
+ ThrowOnError(GetApi().GetOpaqueValue(domain, type_name, p_, &out, sizeof(T)));
+}
+
+inline bool Value::IsTensor() const {
+ int out;
+ ThrowOnError(GetApi().IsTensor(p_, &out));
+ return out != 0;
+}
+
+inline size_t Value::GetCount() const {
+ size_t out;
+ ThrowOnError(GetApi().GetValueCount(p_, &out));
+ return out;
+}
+
+inline Value Value::GetValue(int index, OrtAllocator* allocator) const {
+ OrtValue* out;
+ ThrowOnError(GetApi().GetValue(p_, index, allocator, &out));
+ return Value{out};
+}
+
+inline size_t Value::GetStringTensorDataLength() const {
+ size_t out;
+ ThrowOnError(GetApi().GetStringTensorDataLength(p_, &out));
+ return out;
+}
+
+inline size_t Value::GetStringTensorElementLength(size_t element_index) const {
+ size_t out;
+ ThrowOnError(GetApi().GetStringTensorElementLength(p_, element_index, &out));
+ return out;
+}
+
+inline void Value::GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const {
+ ThrowOnError(GetApi().GetStringTensorContent(p_, buffer, buffer_length, offsets, offsets_count));
+}
+
+inline void Value::GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const {
+ ThrowOnError(GetApi().GetStringTensorElement(p_, buffer_length, element_index, buffer));
+}
+
+inline void Value::FillStringTensor(const char* const* s, size_t s_len) {
+ ThrowOnError(GetApi().FillStringTensor(p_, s, s_len));
+}
+
+inline void Value::FillStringTensorElement(const char* s, size_t index) {
+ ThrowOnError(GetApi().FillStringTensorElement(p_, s, index));
+}
+
+template <typename T>
+T* Value::GetTensorMutableData() {
+ T* out;
+ ThrowOnError(GetApi().GetTensorMutableData(p_, (void**)&out));
+ return out;
+}
+
+template <typename T>
+const T* Value::GetTensorData() const {
+ T* out;
+ ThrowOnError(GetApi().GetTensorMutableData(p_, (void**)&out));
+ return out;
+}
+
+template <typename T>
+inline T& Value::At(const std::vector<int64_t>& location) {
+ static_assert(!std::is_same<T, std::string>::value, "this api does not support std::string");
+ T* out;
+ ThrowOnError(GetApi().TensorAt(p_, location.data(), location.size(), (void**)&out));
+ return *out;
+}
+
+inline TypeInfo Value::GetTypeInfo() const {
+ OrtTypeInfo* output;
+ ThrowOnError(GetApi().GetTypeInfo(p_, &output));
+ return TypeInfo{output};
+}
+
+inline TensorTypeAndShapeInfo Value::GetTensorTypeAndShapeInfo() const {
+ OrtTensorTypeAndShapeInfo* output;
+ ThrowOnError(GetApi().GetTensorTypeAndShape(p_, &output));
+ return TensorTypeAndShapeInfo{output};
+}
+
+//
+// Custom OP API Inlines
+//
+inline void CustomOpApi::ThrowOnError(OrtStatus* status) {
+ Ort::ThrowOnError(api_, status);
+}
+
+template <>
+inline float CustomOpApi::KernelInfoGetAttribute<float>(_In_ const OrtKernelInfo* info, _In_ const char* name) {
+ float out;
+ ThrowOnError(api_.KernelInfoGetAttribute_float(info, name, &out));
+ return out;
+}
+
+template <>
+inline int64_t CustomOpApi::KernelInfoGetAttribute<int64_t>(_In_ const OrtKernelInfo* info, _In_ const char* name) {
+ int64_t out;
+ ThrowOnError(api_.KernelInfoGetAttribute_int64(info, name, &out));
+ return out;
+}
+
+template <>
+inline std::string CustomOpApi::KernelInfoGetAttribute<std::string>(_In_ const OrtKernelInfo* info, _In_ const char* name) {
+ size_t size = 0;
+ std::string out;
+
+ // Feed nullptr for the data buffer to query the true size of the string attribute
+ OrtStatus* status = api_.KernelInfoGetAttribute_string(info, name, nullptr, &size);
+
+ if (status == nullptr) {
+ out.resize(size);
+ ThrowOnError(api_.KernelInfoGetAttribute_string(info, name, &out[0], &size));
+ out.resize(size - 1); // remove the terminating character '\0'
+ } else {
+ ThrowOnError(status);
+ }
+ return out;
+}
+
+template <>
+inline std::vector<float> CustomOpApi::KernelInfoGetAttribute(_In_ const OrtKernelInfo* info, _In_ const char* name) {
+ size_t size = 0;
+ std::vector<float> out;
+
+ // Feed nullptr for the data buffer to query the true size of the attribute
+ OrtStatus* status = api_.KernelInfoGetAttributeArray_float(info, name, nullptr, &size);
+
+ if (status == nullptr) {
+ out.resize(size);
+ ThrowOnError(api_.KernelInfoGetAttributeArray_float(info, name, out.data(), &size));
+ } else {
+ ThrowOnError(status);
+ }
+ return out;
+}
+
+template <>
+inline std::vector<int64_t> CustomOpApi::KernelInfoGetAttribute(_In_ const OrtKernelInfo* info, _In_ const char* name) {
+ size_t size = 0;
+ std::vector<int64_t> out;
+
+ // Feed nullptr for the data buffer to query the true size of the attribute
+ OrtStatus* status = api_.KernelInfoGetAttributeArray_int64(info, name, nullptr, &size);
+
+ if (status == nullptr) {
+ out.resize(size);
+ ThrowOnError(api_.KernelInfoGetAttributeArray_int64(info, name, out.data(), &size));
+ } else {
+ ThrowOnError(status);
+ }
+ return out;
+}
+inline OrtTensorTypeAndShapeInfo* CustomOpApi::GetTensorTypeAndShape(_In_ const OrtValue* value) {
+ OrtTensorTypeAndShapeInfo* out;
+ ThrowOnError(api_.GetTensorTypeAndShape(value, &out));
+ return out;
+}
+
+inline size_t CustomOpApi::GetTensorShapeElementCount(_In_ const OrtTensorTypeAndShapeInfo* info) {
+ size_t out;
+ ThrowOnError(api_.GetTensorShapeElementCount(info, &out));
+ return out;
+}
+
+inline ONNXTensorElementDataType CustomOpApi::GetTensorElementType(const OrtTensorTypeAndShapeInfo* info) {
+ ONNXTensorElementDataType out;
+ ThrowOnError(api_.GetTensorElementType(info, &out));
+ return out;
+}
+
+inline size_t CustomOpApi::GetDimensionsCount(_In_ const OrtTensorTypeAndShapeInfo* info) {
+ size_t out;
+ ThrowOnError(api_.GetDimensionsCount(info, &out));
+ return out;
+}
+
+inline void CustomOpApi::GetDimensions(_In_ const OrtTensorTypeAndShapeInfo* info, _Out_ int64_t* dim_values, size_t dim_values_length) {
+ ThrowOnError(api_.GetDimensions(info, dim_values, dim_values_length));
+}
+
+inline void CustomOpApi::SetDimensions(OrtTensorTypeAndShapeInfo* info, _In_ const int64_t* dim_values, size_t dim_count) {
+ ThrowOnError(api_.SetDimensions(info, dim_values, dim_count));
+}
+
+template <typename T>
+inline T* CustomOpApi::GetTensorMutableData(_Inout_ OrtValue* value) {
+ T* data;
+ ThrowOnError(api_.GetTensorMutableData(value, reinterpret_cast<void**>(&data)));
+ return data;
+}
+
+template <typename T>
+inline const T* CustomOpApi::GetTensorData(_Inout_ const OrtValue* value) {
+ return GetTensorMutableData<T>(const_cast<OrtValue*>(value));
+}
+
+inline std::vector<int64_t> CustomOpApi::GetTensorShape(const OrtTensorTypeAndShapeInfo* info) {
+ std::vector<int64_t> output(GetDimensionsCount(info));
+ GetDimensions(info, output.data(), output.size());
+ return output;
+}
+
+inline void CustomOpApi::ReleaseTensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* input) {
+ api_.ReleaseTensorTypeAndShapeInfo(input);
+}
+
+inline size_t CustomOpApi::KernelContext_GetInputCount(const OrtKernelContext* context) {
+ size_t out;
+ ThrowOnError(api_.KernelContext_GetInputCount(context, &out));
+ return out;
+}
+
+inline const OrtValue* CustomOpApi::KernelContext_GetInput(const OrtKernelContext* context, _In_ size_t index) {
+ const OrtValue* out;
+ ThrowOnError(api_.KernelContext_GetInput(context, index, &out));
+ return out;
+}
+
+inline size_t CustomOpApi::KernelContext_GetOutputCount(const OrtKernelContext* context) {
+ size_t out;
+ ThrowOnError(api_.KernelContext_GetOutputCount(context, &out));
+ return out;
+}
+
+inline OrtValue* CustomOpApi::KernelContext_GetOutput(OrtKernelContext* context, _In_ size_t index,
+ _In_ const int64_t* dim_values, size_t dim_count) {
+ OrtValue* out;
+ ThrowOnError(api_.KernelContext_GetOutput(context, index, dim_values, dim_count, &out));
+ return out;
+}
+
+inline SessionOptions& SessionOptions::DisablePerSessionThreads() {
+ ThrowOnError(GetApi().DisablePerSessionThreads(p_));
+ return *this;
+}
+
+inline std::vector<std::string> GetAvailableProviders() {
+ int len;
+ char** providers;
+ const OrtApi& api = GetApi();
+ ThrowOnError(api.GetAvailableProviders(&providers, &len));
+ std::vector<std::string> available_providers(providers, providers + len);
+ ThrowOnError(api.ReleaseAvailableProviders(providers, len));
+ return available_providers;
+}
+
+SessionOptions& AddInitializer(const char* name, const OrtValue* ort_val);
+
+} // namespace Ort
diff --git a/onnxruntime-1.8.1/build/native/include/onnxruntime_run_options_config_keys.h b/onnxruntime-1.8.1/build/native/include/onnxruntime_run_options_config_keys.h new file mode 100644 index 0000000..7ae8480 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/onnxruntime_run_options_config_keys.h @@ -0,0 +1,27 @@ +// 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";
diff --git a/onnxruntime-1.8.1/build/native/include/onnxruntime_session_options_config_keys.h b/onnxruntime-1.8.1/build/native/include/onnxruntime_session_options_config_keys.h new file mode 100644 index 0000000..fa10a88 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/onnxruntime_session_options_config_keys.h @@ -0,0 +1,62 @@ +// 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 128
+ *
+ * The string format of a SessionOptions Config Value is defined individually for each Config.
+ * The maximum length of the Config Value is 1024
+ */
+
+// 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"
+static const char* const kOrtSessionOptionsDisableQuantQDQ = "session.disable_quant_qdq";
+
+// 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 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": default, thread will spin a number of times before blocking
+static const char* const kOrtSessionOptionsConfigAllowInterOpSpinning = "session.inter_op.allow_spinning";
+static const char* const kOrtSessionOptionsConfigAllowIntraOpSpinning = "session.intra_op.allow_spinning";
diff --git a/onnxruntime-1.8.1/build/native/include/provider_options.h b/onnxruntime-1.8.1/build/native/include/provider_options.h new file mode 100644 index 0000000..0e084c0 --- /dev/null +++ b/onnxruntime-1.8.1/build/native/include/provider_options.h @@ -0,0 +1,18 @@ +// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+namespace onnxruntime {
+
+// data types for execution provider options
+
+using ProviderOptions = std::unordered_map<std::string, std::string>;
+using ProviderOptionsVector = std::vector<ProviderOptions>;
+using ProviderOptionsMap = std::unordered_map<std::string, ProviderOptions>;
+
+} // namespace onnxruntime
diff --git a/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.dll b/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.dll Binary files differnew file mode 100644 index 0000000..4d75499 --- /dev/null +++ b/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.dll diff --git a/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.lib b/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.lib Binary files differnew file mode 100644 index 0000000..b2d8868 --- /dev/null +++ b/onnxruntime-1.8.1/runtimes/win-x86/native/onnxruntime.lib |