onnxruntime_cxx_api.h

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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.

// Summary: The Ort C++ API is a header only wrapper around the Ort C API.
//
// The C++ API simplifies usage by returning values directly instead of error codes, throwing exceptions on errors
// and automatically releasing resources in the destructors. The primary purpose of C++ API is exception safety so
// all the resources follow RAII and do not leak memory.
//
// Each of the C++ wrapper classes holds only a pointer to the C internal object. Treat them like smart pointers.
// To create an empty object, pass 'nullptr' to the constructor (for example, Env e{nullptr};). However, you can't use them
// until you assign an instance that actually holds an underlying object.
//
// For Ort objects only move assignment between objects is allowed, there are no copy constructors.
// Some objects have explicit 'Clone' methods for this purpose.
//
// ConstXXXX types are copyable since they do not own the underlying C object, so you can pass them to functions as arguments
// by value or by reference. ConstXXXX types are restricted to const only interfaces.
//
// UnownedXXXX are similar to ConstXXXX but also allow non-const interfaces.
//
// The lifetime of the corresponding owning object must eclipse the lifetimes of the ConstXXXX/UnownedXXXX types. They exists so you do not
// have to fallback to C types and the API with the usual pitfalls. In general, do not use C API from your C++ code.

#pragma once
#include "onnxruntime_c_api.h"
#include "onnxruntime_float16.h"

#include <cstddef>
#include <cstdio>
#include <array>
#include <memory>
#include <stdexcept>
#include <string>
#include <vector>
#include <unordered_map>
#include <utility>
#include <type_traits>

#ifdef ORT_NO_EXCEPTIONS
#include <iostream>
#endif

/** \brief All C++ Onnxruntime APIs are defined inside this namespace
 *
 */
namespace Ort {

/** \brief All C++ methods that can fail will throw an exception of this type
 *
 * If <tt>ORT_NO_EXCEPTIONS</tt> is defined, then any error will result in a call to abort()
 */
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
// The #ifndef is for the very special case where the user of this library wants to define their own way of handling errors.
// NOTE: This header expects control flow to not continue after calling ORT_CXX_API_THROW
#ifndef ORT_CXX_API_THROW
#define ORT_CXX_API_THROW(string, code)       \
  do {                                        \
    std::cerr << Ort::Exception(string, code) \
                     .what()                  \
              << std::endl;                   \
    abort();                                  \
  } while (false)
#endif
#else
#define ORT_CXX_API_THROW(string, code) \
  throw Ort::Exception(string, code)
#endif

// This is used internally by the C++ API. This class holds the global variable that points to the OrtApi,
//  it's in a template so that we can define a global variable in a header and make
// it transparent to the users of the API.
template <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() noexcept { Global<void>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION); }

// Used by custom operator libraries that are not linked to onnxruntime. Sets the global API object, which is
// required by C++ APIs.
//
// Example mycustomop.cc:
//
// #define ORT_API_MANUAL_INIT
// #include <onnxruntime_cxx_api.h>
// #undef ORT_API_MANUAL_INIT
//
// OrtStatus* ORT_API_CALL RegisterCustomOps(OrtSessionOptions* options, const OrtApiBase* api_base) {
//   Ort::InitApi(api_base->GetApi(ORT_API_VERSION));
//   // ...
// }
//
inline void InitApi(const OrtApi* api) noexcept { Global<void>::api_ = api; }
#else
#if defined(_MSC_VER) && !defined(__clang__)
#pragma warning(push)
// "Global initializer calls a non-constexpr function." Therefore you can't use ORT APIs in the other global initializers.
// Please define ORT_API_MANUAL_INIT if it conerns you.
#pragma warning(disable : 26426)
#endif
const OrtApi* Global<T>::api_ = OrtGetApiBase()->GetApi(ORT_API_VERSION);
#if defined(_MSC_VER) && !defined(__clang__)
#pragma warning(pop)
#endif
#endif

/// This returns a reference to the OrtApi interface in use
inline const OrtApi& GetApi() noexcept { return *Global<void>::api_; }

/// <summary>
/// This function returns the onnxruntime version string
/// </summary>
/// <returns>version string major.minor.rev</returns>
std::string GetVersionString();

/// <summary>
/// This function returns the onnxruntime build information: including git branch,
/// git commit id, build type(Debug/Release/RelWithDebInfo) and cmake cpp flags.
/// </summary>
/// <returns>string</returns>
std::string GetBuildInfoString();

/// <summary>
/// This is a C++ wrapper for OrtApi::GetAvailableProviders() and
/// returns a vector of strings representing the available execution providers.
/// </summary>
/// <returns>vector of strings</returns>
std::vector<std::string> GetAvailableProviders();

/** \brief IEEE 754 half-precision floating point data type
 *
 * \details This struct is used for converting float to float16 and back
 * so the user could feed inputs and fetch outputs using these type.
 *
 * The size of the structure should align with uint16_t and one can freely cast
 * uint16_t buffers to/from Ort::Float16_t to feed and retrieve data.
 *
 * \code{.unparsed}
 * // This example demonstrates converion from float to float16
 * constexpr float values[] = {1.f, 2.f, 3.f, 4.f, 5.f};
 * std::vector<Ort::Float16_t> fp16_values;
 * fp16_values.reserve(std::size(values));
 * std::transform(std::begin(values), std::end(values), std::back_inserter(fp16_values),
 *     [](float value) { return Ort::Float16_t(value); });
 *
 * \endcode
 */
struct Float16_t : onnxruntime_float16::Float16Impl<Float16_t> {
 private:
  /// <summary>
  /// Constructor from a 16-bit representation of a float16 value
  /// No conversion is done here.
  /// </summary>
  /// <param name="v">16-bit representation</param>
  constexpr explicit Float16_t(uint16_t v) noexcept { val = v; }

 public:
  using Base = onnxruntime_float16::Float16Impl<Float16_t>;

  /// <summary>
  /// Default constructor
  /// </summary>
  Float16_t() = default;

  /// <summary>
  /// Explicit conversion to uint16_t representation of float16.
  /// </summary>
  /// <param name="v">uint16_t bit representation of float16</param>
  /// <returns>new instance of Float16_t</returns>
  constexpr static Float16_t FromBits(uint16_t v) noexcept { return Float16_t(v); }

  /// <summary>
  /// __ctor from float. Float is converted into float16 16-bit representation.
  /// </summary>
  /// <param name="v">float value</param>
  explicit Float16_t(float v) noexcept { val = Base::ToUint16Impl(v); }

  /// <summary>
  /// Converts float16 to float
  /// </summary>
  /// <returns>float representation of float16 value</returns>
  float ToFloat() const noexcept { return Base::ToFloatImpl(); }

  /// <summary>
  /// Checks if the value is negative
  /// </summary>
  /// <returns>true if negative</returns>
  using Base::IsNegative;

  /// <summary>
  /// Tests if the value is NaN
  /// </summary>
  /// <returns>true if NaN</returns>
  using Base::IsNaN;

  /// <summary>
  /// Tests if the value is finite
  /// </summary>
  /// <returns>true if finite</returns>
  using Base::IsFinite;

  /// <summary>
  /// Tests if the value represents positive infinity.
  /// </summary>
  /// <returns>true if positive infinity</returns>
  using Base::IsPositiveInfinity;

  /// <summary>
  /// Tests if the value represents negative infinity
  /// </summary>
  /// <returns>true if negative infinity</returns>
  using Base::IsNegativeInfinity;

  /// <summary>
  /// Tests if the value is either positive or negative infinity.
  /// </summary>
  /// <returns>True if absolute value is infinity</returns>
  using Base::IsInfinity;

  /// <summary>
  /// Tests if the value is NaN or zero. Useful for comparisons.
  /// </summary>
  /// <returns>True if NaN or zero.</returns>
  using Base::IsNaNOrZero;

  /// <summary>
  /// Tests if the value is normal (not zero, subnormal, infinite, or NaN).
  /// </summary>
  /// <returns>True if so</returns>
  using Base::IsNormal;

  /// <summary>
  /// Tests if the value is subnormal (denormal).
  /// </summary>
  /// <returns>True if so</returns>
  using Base::IsSubnormal;

  /// <summary>
  /// Creates an instance that represents absolute value.
  /// </summary>
  /// <returns>Absolute value</returns>
  using Base::Abs;

  /// <summary>
  /// Creates a new instance with the sign flipped.
  /// </summary>
  /// <returns>Flipped sign instance</returns>
  using Base::Negate;

  /// <summary>
  /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check
  /// for two values by or'ing the private bits together and stripping the sign. They are both zero,
  /// and therefore equivalent, if the resulting value is still zero.
  /// </summary>
  /// <param name="lhs">first value</param>
  /// <param name="rhs">second value</param>
  /// <returns>True if both arguments represent zero</returns>
  using Base::AreZero;

  /// <summary>
  /// User defined conversion operator. Converts Float16_t to float.
  /// </summary>
  explicit operator float() const noexcept { return ToFloat(); }

  using Base::operator==;
  using Base::operator!=;
  using Base::operator<;
};

static_assert(sizeof(Float16_t) == sizeof(uint16_t), "Sizes must match");

/** \brief bfloat16 (Brain Floating Point) data type
 *
 * \details This struct is used for converting float to bfloat16 and back
 * so the user could feed inputs and fetch outputs using these type.
 *
 * The size of the structure should align with uint16_t and one can freely cast
 * uint16_t buffers to/from Ort::BFloat16_t to feed and retrieve data.
 *
 * \code{.unparsed}
 * // This example demonstrates converion from float to float16
 * constexpr float values[] = {1.f, 2.f, 3.f, 4.f, 5.f};
 * std::vector<Ort::BFloat16_t> bfp16_values;
 * bfp16_values.reserve(std::size(values));
 * std::transform(std::begin(values), std::end(values), std::back_inserter(bfp16_values),
 *     [](float value) { return Ort::BFloat16_t(value); });
 *
 * \endcode
 */
struct BFloat16_t : onnxruntime_float16::BFloat16Impl<BFloat16_t> {
 private:
  /// <summary>
  /// Constructor from a uint16_t representation of bfloat16
  /// used in FromBits() to escape overload resolution issue with
  /// constructor from float.
  /// No conversion is done.
  /// </summary>
  /// <param name="v">16-bit bfloat16 value</param>
  constexpr explicit BFloat16_t(uint16_t v) noexcept { val = v; }

 public:
  using Base = onnxruntime_float16::BFloat16Impl<BFloat16_t>;

  BFloat16_t() = default;

  /// <summary>
  /// Explicit conversion to uint16_t representation of bfloat16.
  /// </summary>
  /// <param name="v">uint16_t bit representation of bfloat16</param>
  /// <returns>new instance of BFloat16_t</returns>
  static constexpr BFloat16_t FromBits(uint16_t v) noexcept { return BFloat16_t(v); }

  /// <summary>
  /// __ctor from float. Float is converted into bfloat16 16-bit representation.
  /// </summary>
  /// <param name="v">float value</param>
  explicit BFloat16_t(float v) noexcept { val = Base::ToUint16Impl(v); }

  /// <summary>
  /// Converts bfloat16 to float
  /// </summary>
  /// <returns>float representation of bfloat16 value</returns>
  float ToFloat() const noexcept { return Base::ToFloatImpl(); }

  /// <summary>
  /// Checks if the value is negative
  /// </summary>
  /// <returns>true if negative</returns>
  using Base::IsNegative;

  /// <summary>
  /// Tests if the value is NaN
  /// </summary>
  /// <returns>true if NaN</returns>
  using Base::IsNaN;

  /// <summary>
  /// Tests if the value is finite
  /// </summary>
  /// <returns>true if finite</returns>
  using Base::IsFinite;

  /// <summary>
  /// Tests if the value represents positive infinity.
  /// </summary>
  /// <returns>true if positive infinity</returns>
  using Base::IsPositiveInfinity;

  /// <summary>
  /// Tests if the value represents negative infinity
  /// </summary>
  /// <returns>true if negative infinity</returns>
  using Base::IsNegativeInfinity;

  /// <summary>
  /// Tests if the value is either positive or negative infinity.
  /// </summary>
  /// <returns>True if absolute value is infinity</returns>
  using Base::IsInfinity;

  /// <summary>
  /// Tests if the value is NaN or zero. Useful for comparisons.
  /// </summary>
  /// <returns>True if NaN or zero.</returns>
  using Base::IsNaNOrZero;

  /// <summary>
  /// Tests if the value is normal (not zero, subnormal, infinite, or NaN).
  /// </summary>
  /// <returns>True if so</returns>
  using Base::IsNormal;

  /// <summary>
  /// Tests if the value is subnormal (denormal).
  /// </summary>
  /// <returns>True if so</returns>
  using Base::IsSubnormal;

  /// <summary>
  /// Creates an instance that represents absolute value.
  /// </summary>
  /// <returns>Absolute value</returns>
  using Base::Abs;

  /// <summary>
  /// Creates a new instance with the sign flipped.
  /// </summary>
  /// <returns>Flipped sign instance</returns>
  using Base::Negate;

  /// <summary>
  /// IEEE defines that positive and negative zero are equal, this gives us a quick equality check
  /// for two values by or'ing the private bits together and stripping the sign. They are both zero,
  /// and therefore equivalent, if the resulting value is still zero.
  /// </summary>
  /// <param name="lhs">first value</param>
  /// <param name="rhs">second value</param>
  /// <returns>True if both arguments represent zero</returns>
  using Base::AreZero;

  /// <summary>
  /// User defined conversion operator. Converts BFloat16_t to float.
  /// </summary>
  explicit operator float() const noexcept { return ToFloat(); }

  // We do not have an inherited impl for the below operators
  // as the internal class implements them a little differently
  bool operator==(const BFloat16_t& rhs) const noexcept;
  bool operator!=(const BFloat16_t& rhs) const noexcept { return !(*this == rhs); }
  bool operator<(const BFloat16_t& rhs) const noexcept;
};

static_assert(sizeof(BFloat16_t) == sizeof(uint16_t), "Sizes must match");

/** \brief float8e4m3fn (Float8 Floating Point) data type
 * \details It is necessary for type dispatching to make use of C++ API
 * The type is implicitly convertible to/from uint8_t.
 * See https://onnx.ai/onnx/technical/float8.html for further details.
 */
struct Float8E4M3FN_t {
  uint8_t value;
  constexpr Float8E4M3FN_t() noexcept : value(0) {}
  constexpr Float8E4M3FN_t(uint8_t v) noexcept : value(v) {}
  constexpr operator uint8_t() const noexcept { return value; }
  // nan values are treated like any other value for operator ==, !=
  constexpr bool operator==(const Float8E4M3FN_t& rhs) const noexcept { return value == rhs.value; };
  constexpr bool operator!=(const Float8E4M3FN_t& rhs) const noexcept { return value != rhs.value; };
};

static_assert(sizeof(Float8E4M3FN_t) == sizeof(uint8_t), "Sizes must match");

/** \brief float8e4m3fnuz (Float8 Floating Point) data type
 * \details It is necessary for type dispatching to make use of C++ API
 * The type is implicitly convertible to/from uint8_t.
 * See https://onnx.ai/onnx/technical/float8.html for further details.
 */
struct Float8E4M3FNUZ_t {
  uint8_t value;
  constexpr Float8E4M3FNUZ_t() noexcept : value(0) {}
  constexpr Float8E4M3FNUZ_t(uint8_t v) noexcept : value(v) {}
  constexpr operator uint8_t() const noexcept { return value; }
  // nan values are treated like any other value for operator ==, !=
  constexpr bool operator==(const Float8E4M3FNUZ_t& rhs) const noexcept { return value == rhs.value; };
  constexpr bool operator!=(const Float8E4M3FNUZ_t& rhs) const noexcept { return value != rhs.value; };
};

static_assert(sizeof(Float8E4M3FNUZ_t) == sizeof(uint8_t), "Sizes must match");

/** \brief float8e5m2 (Float8 Floating Point) data type
 * \details It is necessary for type dispatching to make use of C++ API
 * The type is implicitly convertible to/from uint8_t.
 * See https://onnx.ai/onnx/technical/float8.html for further details.
 */
struct Float8E5M2_t {
  uint8_t value;
  constexpr Float8E5M2_t() noexcept : value(0) {}
  constexpr Float8E5M2_t(uint8_t v) noexcept : value(v) {}
  constexpr operator uint8_t() const noexcept { return value; }
  // nan values are treated like any other value for operator ==, !=
  constexpr bool operator==(const Float8E5M2_t& rhs) const noexcept { return value == rhs.value; };
  constexpr bool operator!=(const Float8E5M2_t& rhs) const noexcept { return value != rhs.value; };
};

static_assert(sizeof(Float8E5M2_t) == sizeof(uint8_t), "Sizes must match");

/** \brief float8e5m2fnuz (Float8 Floating Point) data type
 * \details It is necessary for type dispatching to make use of C++ API
 * The type is implicitly convertible to/from uint8_t.
 * See https://onnx.ai/onnx/technical/float8.html for further details.
 */
struct Float8E5M2FNUZ_t {
  uint8_t value;
  constexpr Float8E5M2FNUZ_t() noexcept : value(0) {}
  constexpr Float8E5M2FNUZ_t(uint8_t v) noexcept : value(v) {}
  constexpr operator uint8_t() const noexcept { return value; }
  // nan values are treated like any other value for operator ==, !=
  constexpr bool operator==(const Float8E5M2FNUZ_t& rhs) const noexcept { return value == rhs.value; };
  constexpr bool operator!=(const Float8E5M2FNUZ_t& rhs) const noexcept { return value != rhs.value; };
};

static_assert(sizeof(Float8E5M2FNUZ_t) == sizeof(uint8_t), "Sizes must match");

namespace detail {
// This is used internally by the C++ API. This macro is to make it easy to generate overloaded methods for all of the various OrtRelease* functions for every Ort* type
// This can't be done in the C API since C doesn't have function overloading.
#define ORT_DEFINE_RELEASE(NAME) \
  inline void OrtRelease(Ort##NAME* ptr) { GetApi().Release##NAME(ptr); }

ORT_DEFINE_RELEASE(Allocator);
ORT_DEFINE_RELEASE(MemoryInfo);
ORT_DEFINE_RELEASE(CustomOpDomain);
ORT_DEFINE_RELEASE(ThreadingOptions);
ORT_DEFINE_RELEASE(Env);
ORT_DEFINE_RELEASE(RunOptions);
ORT_DEFINE_RELEASE(LoraAdapter);
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(IoBinding);
ORT_DEFINE_RELEASE(ArenaCfg);
ORT_DEFINE_RELEASE(Status);
ORT_DEFINE_RELEASE(OpAttr);
ORT_DEFINE_RELEASE(Op);
ORT_DEFINE_RELEASE(KernelInfo);

#undef ORT_DEFINE_RELEASE

/** \brief This is a tagging template type. Use it with Base<T> to indicate that the C++ interface object
 *   has no ownership of the underlying C object.
 */
template <typename T>
struct Unowned {
  using Type = T;
};

/** \brief Used internally by the C++ API. C++ wrapper types inherit from this.
 *   This is a zero cost abstraction to wrap the C API objects and delete them on destruction.
 *
 * All of the C++ classes
 *  a) serve as containers for pointers to objects that are created by the underlying C API.
 *     Their size is just a pointer size, no need to dynamically allocate them. Use them by value.
 *  b) Each of struct XXXX, XXX instances function as smart pointers to the underlying C API objects.
 *     they would release objects owned automatically when going out of scope, they are move-only.
 *  c) ConstXXXX and UnownedXXX structs function as non-owning, copyable containers for the above pointers.
 *     ConstXXXX allow calling const interfaces only. They give access to objects that are owned by somebody else
 *     such as Onnxruntime or instances of XXXX classes.
 *  d) serve convenient interfaces that return C++ objects and further enhance exception and type safety so they can be used
 *     in C++ code.
 *
 */

/// <summary>
/// This is a non-const pointer holder that is move-only. Disposes of the pointer on destruction.
/// </summary>
template <typename T>
struct Base {
  using contained_type = T;

  constexpr Base() = default;
  constexpr explicit Base(contained_type* p) noexcept : p_{p} {}
  ~Base() { OrtRelease(p_); }

  Base(const Base&) = delete;
  Base& operator=(const Base&) = delete;

  Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; }
  Base& operator=(Base&& v) noexcept {
    OrtRelease(p_);
    p_ = v.release();
    return *this;
  }

  constexpr operator contained_type*() const noexcept { return p_; }

  /// \brief Relinquishes ownership of the contained C object pointer
  /// The underlying object is not destroyed
  contained_type* release() {
    T* p = p_;
    p_ = nullptr;
    return p;
  }

 protected:
  contained_type* p_{};
};

// Undefined. For const types use Base<Unowned<const T>>
template <typename T>
struct Base<const T>;

/// <summary>
/// Covers unowned pointers owned by either the ORT
/// or some other instance of CPP wrappers.
/// Used for ConstXXX and UnownedXXXX types that are copyable.
/// Also convenient to wrap raw OrtXX pointers .
/// </summary>
/// <typeparam name="T"></typeparam>
template <typename T>
struct Base<Unowned<T>> {
  using contained_type = typename Unowned<T>::Type;

  constexpr Base() = default;
  constexpr explicit Base(contained_type* p) noexcept : p_{p} {}

  ~Base() = default;

  Base(const Base&) = default;
  Base& operator=(const Base&) = default;

  Base(Base&& v) noexcept : p_{v.p_} { v.p_ = nullptr; }
  Base& operator=(Base&& v) noexcept {
    p_ = nullptr;
    std::swap(p_, v.p_);
    return *this;
  }

  constexpr operator contained_type*() const noexcept { return p_; }

 protected:
  contained_type* p_{};
};

// Light functor to release memory with OrtAllocator
struct AllocatedFree {
  OrtAllocator* allocator_;
  explicit AllocatedFree(OrtAllocator* allocator)
      : allocator_(allocator) {}
  void operator()(void* ptr) const {
    if (ptr) allocator_->Free(allocator_, ptr);
  }
};

}  // namespace detail

struct AllocatorWithDefaultOptions;
struct Env;
struct TypeInfo;
struct Value;
struct ModelMetadata;

/** \brief unique_ptr typedef used to own strings allocated by OrtAllocators
 *  and release them at the end of the scope. The lifespan of the given allocator
 *  must eclipse the lifespan of AllocatedStringPtr instance
 */
using AllocatedStringPtr = std::unique_ptr<char, detail::AllocatedFree>;

/** \brief The Status that holds ownership of OrtStatus received from C API
 *  Use it to safely destroy OrtStatus* returned from the C API. Use appropriate
 *  constructors to construct an instance of a Status object from exceptions.
 */
struct Status : detail::Base<OrtStatus> {
  explicit Status(std::nullptr_t) noexcept {}               ///< Create an empty object, must be assigned a valid one to be used
  explicit Status(OrtStatus* status) noexcept;              ///< Takes ownership of OrtStatus instance returned from the C API.
  explicit Status(const Exception&) noexcept;               ///< Creates status instance out of exception
  explicit Status(const std::exception&) noexcept;          ///< Creates status instance out of exception
  Status(const char* message, OrtErrorCode code) noexcept;  ///< Creates status instance out of null-terminated string message.
  std::string GetErrorMessage() const;
  OrtErrorCode GetErrorCode() const;
  bool IsOK() const noexcept;  ///< Returns true if instance represents an OK (non-error) status.
};

/** \brief The ThreadingOptions
 *
 * The ThreadingOptions used for set global threadpools' options of The Env.
 */
struct ThreadingOptions : detail::Base<OrtThreadingOptions> {
  /// \brief Wraps OrtApi::CreateThreadingOptions
  ThreadingOptions();

  /// \brief Wraps OrtApi::SetGlobalIntraOpNumThreads
  ThreadingOptions& SetGlobalIntraOpNumThreads(int intra_op_num_threads);

  /// \brief Wraps OrtApi::SetGlobalInterOpNumThreads
  ThreadingOptions& SetGlobalInterOpNumThreads(int inter_op_num_threads);

  /// \brief Wraps OrtApi::SetGlobalSpinControl
  ThreadingOptions& SetGlobalSpinControl(int allow_spinning);

  /// \brief Wraps OrtApi::SetGlobalDenormalAsZero
  ThreadingOptions& SetGlobalDenormalAsZero();

  /// \brief Wraps OrtApi::SetGlobalCustomCreateThreadFn
  ThreadingOptions& SetGlobalCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn);

  /// \brief Wraps OrtApi::SetGlobalCustomThreadCreationOptions
  ThreadingOptions& SetGlobalCustomThreadCreationOptions(void* ort_custom_thread_creation_options);

  /// \brief Wraps OrtApi::SetGlobalCustomJoinThreadFn
  ThreadingOptions& SetGlobalCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn);
};

/** \brief The Env (Environment)
 *
 * The Env holds the logging state used by all other objects.
 * <b>Note:</b> One Env must be created before using any other Onnxruntime functionality
 */
struct Env : detail::Base<OrtEnv> {
  explicit Env(std::nullptr_t) {}  ///< Create an empty Env object, must be assigned a valid one to be used

  /// \brief Wraps OrtApi::CreateEnv
  Env(OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");

  /// \brief Wraps OrtApi::CreateEnvWithCustomLogger
  Env(OrtLoggingLevel logging_level, const char* logid, OrtLoggingFunction logging_function, void* logger_param);

  /// \brief Wraps OrtApi::CreateEnvWithGlobalThreadPools
  Env(const OrtThreadingOptions* tp_options, OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");

  /// \brief Wraps OrtApi::CreateEnvWithCustomLoggerAndGlobalThreadPools
  Env(const OrtThreadingOptions* tp_options, OrtLoggingFunction logging_function, void* logger_param,
      OrtLoggingLevel logging_level = ORT_LOGGING_LEVEL_WARNING, _In_ const char* logid = "");

  /// \brief C Interop Helper
  explicit Env(OrtEnv* p) : Base<OrtEnv>{p} {}

  Env& EnableTelemetryEvents();   ///< Wraps OrtApi::EnableTelemetryEvents
  Env& DisableTelemetryEvents();  ///< Wraps OrtApi::DisableTelemetryEvents

  Env& UpdateEnvWithCustomLogLevel(OrtLoggingLevel log_severity_level);  ///< Wraps OrtApi::UpdateEnvWithCustomLogLevel

  Env& CreateAndRegisterAllocator(const OrtMemoryInfo* mem_info, const OrtArenaCfg* arena_cfg);  ///< Wraps OrtApi::CreateAndRegisterAllocator

  Env& CreateAndRegisterAllocatorV2(const std::string& provider_type, const OrtMemoryInfo* mem_info, const std::unordered_map<std::string, std::string>& options, const OrtArenaCfg* arena_cfg);  ///< Wraps OrtApi::CreateAndRegisterAllocatorV2
};

/** \brief Custom Op Domain
 *
 */
struct CustomOpDomain : detail::Base<OrtCustomOpDomain> {
  explicit CustomOpDomain(std::nullptr_t) {}  ///< Create an empty CustomOpDomain object, must be assigned a valid one to be used

  /// \brief Wraps OrtApi::CreateCustomOpDomain
  explicit CustomOpDomain(const char* domain);

  // This does not take ownership of the op, simply registers it.
  void Add(const OrtCustomOp* op);  ///< Wraps CustomOpDomain_Add
};

/// \brief LoraAdapter holds a set of Lora Parameters loaded from a single file
struct LoraAdapter : detail::Base<OrtLoraAdapter> {
  using Base = detail::Base<OrtLoraAdapter>;
  using Base::Base;

  explicit LoraAdapter(std::nullptr_t) {}  ///< Create an empty LoraAdapter object, must be assigned a valid one to be used
  /// \brief Wraps OrtApi::CreateLoraAdapter
  ///
  /// The function attempts to load the adapter from the specified file
  /// \param adapter_path The path to the Lora adapter
  /// \param allocator optional pointer to a device allocator. If nullptr, the data stays on CPU. It would still
  ///        be copied to device if required by the model at inference time.
  static LoraAdapter CreateLoraAdapter(const std::basic_string<ORTCHAR_T>& adapter_path,
                                       OrtAllocator* allocator);

  /// \brief Wraps OrtApi::CreateLoraAdapterFromArray
  ///
  /// The function attempts to load the adapter from the specified byte array.
  /// \param bytes The byte array containing file LoraAdapter format
  /// \param num_bytes The number of bytes in the byte array
  /// \param allocator optional pointer to a device allocator. If nullptr, the data stays on CPU. It would still
  ///        be copied to device if required by the model at inference time.
  static LoraAdapter CreateLoraAdapterFromArray(const void* bytes, size_t num_bytes,
                                                OrtAllocator* allocator);
};

/** \brief RunOptions
 *
 */
struct RunOptions : detail::Base<OrtRunOptions> {
  explicit RunOptions(std::nullptr_t) {}  ///< Create an empty RunOptions object, must be assigned a valid one to be used
  RunOptions();                           ///< Wraps OrtApi::CreateRunOptions

  RunOptions& SetRunLogVerbosityLevel(int);  ///< Wraps OrtApi::RunOptionsSetRunLogVerbosityLevel
  int GetRunLogVerbosityLevel() const;       ///< Wraps OrtApi::RunOptionsGetRunLogVerbosityLevel

  RunOptions& SetRunLogSeverityLevel(int);  ///< Wraps OrtApi::RunOptionsSetRunLogSeverityLevel
  int GetRunLogSeverityLevel() const;       ///< Wraps OrtApi::RunOptionsGetRunLogSeverityLevel

  RunOptions& SetRunTag(const char* run_tag);  ///< wraps OrtApi::RunOptionsSetRunTag
  const char* GetRunTag() const;               ///< Wraps OrtApi::RunOptionsGetRunTag

  RunOptions& AddConfigEntry(const char* config_key, const char* config_value);  ///< Wraps OrtApi::AddRunConfigEntry

  /** \brief Terminates all currently executing Session::Run calls that were made using this RunOptions instance
   *
   * If a currently executing session needs to be force terminated, this can be called from another thread to force it to fail with an error
   * Wraps OrtApi::RunOptionsSetTerminate
   */
  RunOptions& SetTerminate();

  /** \brief Clears the terminate flag so this RunOptions instance can be used in a new Session::Run call without it instantly terminating
   *
   * Wraps OrtApi::RunOptionsUnsetTerminate
   */
  RunOptions& UnsetTerminate();

  /** \brief Add the LoraAdapter to the list of active adapters.
   *  The setting does not affect RunWithBinding() calls.
   *
   * Wraps OrtApi::RunOptionsAddActiveLoraAdapter
   * \param adapter The LoraAdapter to be used as the active adapter
   */
  RunOptions& AddActiveLoraAdapter(const LoraAdapter& adapter);
};

namespace detail {
// Utility function that returns a SessionOption config entry key for a specific custom operator.
// Ex: custom_op.[custom_op_name].[config]
std::string MakeCustomOpConfigEntryKey(const char* custom_op_name, const char* config);
}  // namespace detail

/// <summary>
/// Class that represents session configuration entries for one or more custom operators.
///
/// Example:
///   Ort::CustomOpConfigs op_configs;
///   op_configs.AddConfig("my_custom_op", "device_type", "CPU");
///
/// Passed to Ort::SessionOptions::RegisterCustomOpsLibrary.
/// </summary>
struct CustomOpConfigs {
  CustomOpConfigs() = default;
  ~CustomOpConfigs() = default;
  CustomOpConfigs(const CustomOpConfigs&) = default;
  CustomOpConfigs& operator=(const CustomOpConfigs&) = default;
  CustomOpConfigs(CustomOpConfigs&& o) = default;
  CustomOpConfigs& operator=(CustomOpConfigs&& o) = default;

  /** \brief Adds a session configuration entry/value for a specific custom operator.
   *
   * \param custom_op_name The name of the custom operator for which to add a configuration entry.
   *                       Must match the name returned by the CustomOp's GetName() method.
   * \param config_key The name of the configuration entry.
   * \param config_value The value of the configuration entry.
   * \return A reference to this object to enable call chaining.
   */
  CustomOpConfigs& AddConfig(const char* custom_op_name, const char* config_key, const char* config_value);

  /** \brief Returns a flattened map of custom operator configuration entries and their values.
   *
   * The keys has been flattened to include both the custom operator name and the configuration entry key name.
   * For example, a prior call to AddConfig("my_op", "key", "value") corresponds to the flattened key/value pair
   * {"my_op.key", "value"}.
   *
   * \return An unordered map of flattened configurations.
   */
  const std::unordered_map<std::string, std::string>& GetFlattenedConfigs() const;

 private:
  std::unordered_map<std::string, std::string> flat_configs_;
};

/** \brief Options object used when creating a new Session object
 *
 * Wraps ::OrtSessionOptions object and methods
 */

struct SessionOptions;

namespace detail {
// we separate const-only methods because passing const ptr to non-const methods
// is only discovered when inline methods are compiled which is counter-intuitive
template <typename T>
struct ConstSessionOptionsImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  SessionOptions Clone() const;  ///< Creates and returns a copy of this SessionOptions object. Wraps OrtApi::CloneSessionOptions

  std::string GetConfigEntry(const char* config_key) const;  ///< Wraps OrtApi::GetSessionConfigEntry
  bool HasConfigEntry(const char* config_key) const;         ///< Wraps OrtApi::HasSessionConfigEntry
  std::string GetConfigEntryOrDefault(const char* config_key, const std::string& def);
};

template <typename T>
struct SessionOptionsImpl : ConstSessionOptionsImpl<T> {
  using B = ConstSessionOptionsImpl<T>;
  using B::B;

  SessionOptionsImpl& SetIntraOpNumThreads(int intra_op_num_threads);                              ///< Wraps OrtApi::SetIntraOpNumThreads
  SessionOptionsImpl& SetInterOpNumThreads(int inter_op_num_threads);                              ///< Wraps OrtApi::SetInterOpNumThreads
  SessionOptionsImpl& SetGraphOptimizationLevel(GraphOptimizationLevel graph_optimization_level);  ///< Wraps OrtApi::SetSessionGraphOptimizationLevel
  SessionOptionsImpl& SetDeterministicCompute(bool value);                                         ///< Wraps OrtApi::SetDeterministicCompute

  SessionOptionsImpl& EnableCpuMemArena();   ///< Wraps OrtApi::EnableCpuMemArena
  SessionOptionsImpl& DisableCpuMemArena();  ///< Wraps OrtApi::DisableCpuMemArena

  SessionOptionsImpl& SetOptimizedModelFilePath(const ORTCHAR_T* optimized_model_file);  ///< Wraps OrtApi::SetOptimizedModelFilePath

  SessionOptionsImpl& EnableProfiling(const ORTCHAR_T* profile_file_prefix);  ///< Wraps OrtApi::EnableProfiling
  SessionOptionsImpl& DisableProfiling();                                     ///< Wraps OrtApi::DisableProfiling

  SessionOptionsImpl& EnableOrtCustomOps();  ///< Wraps OrtApi::EnableOrtCustomOps

  SessionOptionsImpl& EnableMemPattern();   ///< Wraps OrtApi::EnableMemPattern
  SessionOptionsImpl& DisableMemPattern();  ///< Wraps OrtApi::DisableMemPattern

  SessionOptionsImpl& SetExecutionMode(ExecutionMode execution_mode);  ///< Wraps OrtApi::SetSessionExecutionMode

  SessionOptionsImpl& SetLogId(const char* logid);     ///< Wraps OrtApi::SetSessionLogId
  SessionOptionsImpl& SetLogSeverityLevel(int level);  ///< Wraps OrtApi::SetSessionLogSeverityLevel

  SessionOptionsImpl& Add(OrtCustomOpDomain* custom_op_domain);  ///< Wraps OrtApi::AddCustomOpDomain

  SessionOptionsImpl& DisablePerSessionThreads();  ///< Wraps OrtApi::DisablePerSessionThreads

  SessionOptionsImpl& AddConfigEntry(const char* config_key, const char* config_value);  ///< Wraps OrtApi::AddSessionConfigEntry

  SessionOptionsImpl& AddInitializer(const char* name, const OrtValue* ort_val);                                             ///< Wraps OrtApi::AddInitializer
  SessionOptionsImpl& AddExternalInitializers(const std::vector<std::string>& names, const std::vector<Value>& ort_values);  ///< Wraps OrtApi::AddExternalInitializers
  SessionOptionsImpl& AddExternalInitializersFromFilesInMemory(const std::vector<std::basic_string<ORTCHAR_T>>& external_initializer_file_names,
                                                               const std::vector<char*>& external_initializer_file_buffer_array,
                                                               const std::vector<size_t>& external_initializer_file_lengths);  ///< Wraps OrtApi::AddExternalInitializersFromFilesInMemory

  SessionOptionsImpl& AppendExecutionProvider_CUDA(const OrtCUDAProviderOptions& provider_options);          ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CUDA
  SessionOptionsImpl& AppendExecutionProvider_CUDA_V2(const OrtCUDAProviderOptionsV2& provider_options);     ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CUDA_V2
  SessionOptionsImpl& AppendExecutionProvider_ROCM(const OrtROCMProviderOptions& provider_options);          ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_ROCM
  SessionOptionsImpl& AppendExecutionProvider_OpenVINO(const OrtOpenVINOProviderOptions& provider_options);  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_OpenVINO
  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_OpenVINO_V2
  SessionOptionsImpl& AppendExecutionProvider_OpenVINO_V2(const std::unordered_map<std::string, std::string>& provider_options = {});
  SessionOptionsImpl& AppendExecutionProvider_TensorRT(const OrtTensorRTProviderOptions& provider_options);       ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_TensorRT
  SessionOptionsImpl& AppendExecutionProvider_TensorRT_V2(const OrtTensorRTProviderOptionsV2& provider_options);  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_TensorRT
  SessionOptionsImpl& AppendExecutionProvider_MIGraphX(const OrtMIGraphXProviderOptions& provider_options);       ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_MIGraphX
  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_CANN
  SessionOptionsImpl& AppendExecutionProvider_CANN(const OrtCANNProviderOptions& provider_options);
  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_Dnnl
  SessionOptionsImpl& AppendExecutionProvider_Dnnl(const OrtDnnlProviderOptions& provider_options);
  /// Wraps OrtApi::SessionOptionsAppendExecutionProvider. Currently supports QNN, SNPE and XNNPACK.
  SessionOptionsImpl& AppendExecutionProvider(const std::string& provider_name,
                                              const std::unordered_map<std::string, std::string>& provider_options = {});

  SessionOptionsImpl& SetCustomCreateThreadFn(OrtCustomCreateThreadFn ort_custom_create_thread_fn);  ///< Wraps OrtApi::SessionOptionsSetCustomCreateThreadFn
  SessionOptionsImpl& SetCustomThreadCreationOptions(void* ort_custom_thread_creation_options);      ///< Wraps OrtApi::SessionOptionsSetCustomThreadCreationOptions
  SessionOptionsImpl& SetCustomJoinThreadFn(OrtCustomJoinThreadFn ort_custom_join_thread_fn);        ///< Wraps OrtApi::SessionOptionsSetCustomJoinThreadFn

  ///< Registers the custom operator from the specified shared library via OrtApi::RegisterCustomOpsLibrary_V2.
  ///< The custom operator configurations are optional. If provided, custom operator configs are set via
  ///< OrtApi::AddSessionConfigEntry.
  SessionOptionsImpl& RegisterCustomOpsLibrary(const ORTCHAR_T* library_name, const CustomOpConfigs& custom_op_configs = {});

  SessionOptionsImpl& RegisterCustomOpsUsingFunction(const char* function_name);  ///< Wraps OrtApi::RegisterCustomOpsUsingFunction

  ///< Wraps OrtApi::SessionOptionsAppendExecutionProvider_VitisAI
  SessionOptionsImpl& AppendExecutionProvider_VitisAI(const std::unordered_map<std::string, std::string>& provider_options = {});
};
}  // namespace detail

using UnownedSessionOptions = detail::SessionOptionsImpl<detail::Unowned<OrtSessionOptions>>;
using ConstSessionOptions = detail::ConstSessionOptionsImpl<detail::Unowned<const OrtSessionOptions>>;

/** \brief Wrapper around ::OrtSessionOptions
 *
 */
struct SessionOptions : detail::SessionOptionsImpl<OrtSessionOptions> {
  explicit SessionOptions(std::nullptr_t) {}                                                   ///< Create an empty SessionOptions object, must be assigned a valid one to be used
  SessionOptions();                                                                            ///< Wraps OrtApi::CreateSessionOptions
  explicit SessionOptions(OrtSessionOptions* p) : SessionOptionsImpl<OrtSessionOptions>{p} {}  ///< Used for interop with the C API
  UnownedSessionOptions GetUnowned() const { return UnownedSessionOptions{this->p_}; }
  ConstSessionOptions GetConst() const { return ConstSessionOptions{this->p_}; }
};

/** \brief Wrapper around ::OrtModelMetadata
 *
 */
struct ModelMetadata : detail::Base<OrtModelMetadata> {
  explicit ModelMetadata(std::nullptr_t) {}                                   ///< Create an empty ModelMetadata object, must be assigned a valid one to be used
  explicit ModelMetadata(OrtModelMetadata* p) : Base<OrtModelMetadata>{p} {}  ///< Used for interop with the C API

  /** \brief Returns a copy of the producer name.
   *
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetProducerNameAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetProducerName

  /** \brief Returns a copy of the graph name.
   *
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetGraphNameAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetGraphName

  /** \brief Returns a copy of the domain name.
   *
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetDomainAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetDomain

  /** \brief Returns a copy of the description.
   *
   * \param allocator to allocate memory for the copy of the string returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetDescriptionAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetDescription

  /** \brief Returns a copy of the graph description.
   *
   * \param allocator to allocate memory for the copy of the string returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetGraphDescriptionAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetGraphDescription

  /** \brief Returns a vector of copies of the custom metadata keys.
   *
   * \param allocator to allocate memory for the copy of the string returned
   * \return a instance std::vector of smart pointers that would deallocate the buffers when out of scope.
   *  The OrtAllocator instance must be valid at the point of memory release.
   */
  std::vector<AllocatedStringPtr> GetCustomMetadataMapKeysAllocated(OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataGetCustomMetadataMapKeys

  /** \brief Looks up a value by a key in the Custom Metadata map
   *
   * \param key zero terminated string key to lookup
   * \param allocator to allocate memory for the copy of the string returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  maybe nullptr if key is not found.
   *
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr LookupCustomMetadataMapAllocated(const char* key, OrtAllocator* allocator) const;  ///< Wraps OrtApi::ModelMetadataLookupCustomMetadataMap

  int64_t GetVersion() const;  ///< Wraps OrtApi::ModelMetadataGetVersion
};

struct IoBinding;

namespace detail {

// we separate const-only methods because passing const ptr to non-const methods
// is only discovered when inline methods are compiled which is counter-intuitive
template <typename T>
struct ConstSessionImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  size_t GetInputCount() const;                   ///< Returns the number of model inputs
  size_t GetOutputCount() const;                  ///< Returns the number of model outputs
  size_t GetOverridableInitializerCount() const;  ///< Returns the number of inputs that have defaults that can be overridden

  /** \brief Returns a copy of input name at the specified index.
   *
   * \param index must less than the value returned by GetInputCount()
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetInputNameAllocated(size_t index, OrtAllocator* allocator) const;

  /** \brief Returns a copy of output name at then specified index.
   *
   * \param index must less than the value returned by GetOutputCount()
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetOutputNameAllocated(size_t index, OrtAllocator* allocator) const;

  /** \brief Returns a copy of the overridable initializer name at then specified index.
   *
   * \param index must less than the value returned by GetOverridableInitializerCount()
   * \param allocator to allocate memory for the copy of the name returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr GetOverridableInitializerNameAllocated(size_t index, OrtAllocator* allocator) const;  ///< Wraps OrtApi::SessionGetOverridableInitializerName

  uint64_t GetProfilingStartTimeNs() const;  ///< Wraps OrtApi::SessionGetProfilingStartTimeNs
  ModelMetadata GetModelMetadata() const;    ///< Wraps OrtApi::SessionGetModelMetadata

  TypeInfo GetInputTypeInfo(size_t index) const;                   ///< Wraps OrtApi::SessionGetInputTypeInfo
  TypeInfo GetOutputTypeInfo(size_t index) const;                  ///< Wraps OrtApi::SessionGetOutputTypeInfo
  TypeInfo GetOverridableInitializerTypeInfo(size_t index) const;  ///< Wraps OrtApi::SessionGetOverridableInitializerTypeInfo
};

template <typename T>
struct SessionImpl : ConstSessionImpl<T> {
  using B = ConstSessionImpl<T>;
  using B::B;

  /** \brief Run the model returning results in an Ort allocated vector.
   *
   * Wraps OrtApi::Run
   *
   * The caller provides a list of inputs and a list of the desired outputs to return.
   *
   * See the output logs for more information on warnings/errors that occur while processing the model.
   * Common errors are.. (TODO)
   *
   * \param[in] run_options
   * \param[in] input_names Array of null terminated strings of length input_count that is the list of input names
   * \param[in] input_values Array of Value objects of length input_count that is the list of input values
   * \param[in] input_count Number of inputs (the size of the input_names & input_values arrays)
   * \param[in] output_names Array of C style strings of length output_count that is the list of output names
   * \param[in] output_count Number of outputs (the size of the output_names array)
   * \return A std::vector of Value objects that directly maps to the output_names array (eg. output_name[0] is the first entry of the returned vector)
   */
  std::vector<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);

  /** \brief Run the model returning results in user provided outputs
   * Same as Run(const RunOptions&, const char* const*, const Value*, size_t,const char* const*, size_t)
   */
  void Run(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count,
           const char* const* output_names, Value* output_values, size_t output_count);

  void Run(const RunOptions& run_options, const IoBinding&);  ///< Wraps OrtApi::RunWithBinding

  /** \brief Run the model asynchronously in a thread owned by intra op thread pool
   *
   * Wraps OrtApi::RunAsync
   *
   * \param[in] run_options
   * \param[in] input_names Array of null terminated UTF8 encoded strings of the input names
   * \param[in] input_values Array of Value objects of length input_count
   * \param[in] input_count Number of elements in the input_names and inputs arrays
   * \param[in] output_names Array of null terminated UTF8 encoded strings of the output names
   * \param[out] output_values Array of provided Values to be filled with outputs.
   *             On calling RunAsync, output_values[i] could either be initialized by a null pointer or a preallocated OrtValue*.
   *             Later, on invoking the callback, each output_values[i] of null will be filled with an OrtValue* allocated by onnxruntime.
   *             Then, an OrtValue** pointer will be casted from output_values, and pass to the callback.
   *             NOTE: it is customer's duty to finally release output_values and each of its member,
   *             regardless of whether the member (Ort::Value) is allocated by onnxruntime or preallocated by the customer.
   * \param[in] output_count Number of elements in the output_names and outputs array
   * \param[in] callback Callback function on model run completion
   * \param[in] user_data User data that pass back to the callback
   */
  void RunAsync(const RunOptions& run_options, const char* const* input_names, const Value* input_values, size_t input_count,
                const char* const* output_names, Value* output_values, size_t output_count, RunAsyncCallbackFn callback, void* user_data);

  /** \brief End profiling and return a copy of the profiling file name.
   *
   * \param allocator to allocate memory for the copy of the string returned
   * \return a instance of smart pointer that would deallocate the buffer when out of scope.
   *  The OrtAllocator instances must be valid at the point of memory release.
   */
  AllocatedStringPtr EndProfilingAllocated(OrtAllocator* allocator);  ///< Wraps OrtApi::SessionEndProfiling

  /** \brief Set DynamicOptions for EPs (Execution Providers)
   *
   * Wraps OrtApi::SetEpDynamicOptions
   *
   * Valid options can be found in `include\onnxruntime\core\session\onnxruntime_session_options_config_keys.h`
   * Look for `kOrtEpDynamicOptions`
   *
   * \param[in] keys Array of null terminated UTF8 encoded strings of EP dynamic option keys
   * \param[in] values Array of null terminated UTF8 encoded string of EP dynamic option values
   * \param[in] kv_len Number of elements in the keys and values arrays
   */
  void SetEpDynamicOptions(const char* const* keys, const char* const* values, size_t kv_len);
};

}  // namespace detail

using ConstSession = detail::ConstSessionImpl<detail::Unowned<const OrtSession>>;
using UnownedSession = detail::SessionImpl<detail::Unowned<OrtSession>>;

/** \brief Wrapper around ::OrtSession
 *
 */
struct Session : detail::SessionImpl<OrtSession> {
  explicit Session(std::nullptr_t) {}                                                   ///< Create an empty Session object, must be assigned a valid one to be used
  Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options);  ///< Wraps OrtApi::CreateSession
  Session(const Env& env, const ORTCHAR_T* model_path, const SessionOptions& options,
          OrtPrepackedWeightsContainer* prepacked_weights_container);                                        ///< Wraps OrtApi::CreateSessionWithPrepackedWeightsContainer
  Session(const Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options);  ///< Wraps OrtApi::CreateSessionFromArray
  Session(const Env& env, const void* model_data, size_t model_data_length, const SessionOptions& options,
          OrtPrepackedWeightsContainer* prepacked_weights_container);  ///< Wraps OrtApi::CreateSessionFromArrayWithPrepackedWeightsContainer

  ConstSession GetConst() const { return ConstSession{this->p_}; }
  UnownedSession GetUnowned() const { return UnownedSession{this->p_}; }
};

namespace detail {
template <typename T>
struct MemoryInfoImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  std::string GetAllocatorName() const;
  OrtAllocatorType GetAllocatorType() const;
  int GetDeviceId() const;
  OrtMemoryInfoDeviceType GetDeviceType() const;
  OrtMemType GetMemoryType() const;

  template <typename U>
  bool operator==(const MemoryInfoImpl<U>& o) const;
};
}  // namespace detail

// Const object holder that does not own the underlying object
using ConstMemoryInfo = detail::MemoryInfoImpl<detail::Unowned<const OrtMemoryInfo>>;

/** \brief Wrapper around ::OrtMemoryInfo
 *
 */
struct MemoryInfo : detail::MemoryInfoImpl<OrtMemoryInfo> {
  static MemoryInfo CreateCpu(OrtAllocatorType type, OrtMemType mem_type1);
  explicit MemoryInfo(std::nullptr_t) {}                                       ///< No instance is created
  explicit MemoryInfo(OrtMemoryInfo* p) : MemoryInfoImpl<OrtMemoryInfo>{p} {}  ///< Take ownership of a pointer created by C Api
  MemoryInfo(const char* name, OrtAllocatorType type, int id, OrtMemType mem_type);
  ConstMemoryInfo GetConst() const { return ConstMemoryInfo{this->p_}; }
};

namespace detail {
template <typename T>
struct TensorTypeAndShapeInfoImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  ONNXTensorElementDataType GetElementType() const;  ///< Wraps OrtApi::GetTensorElementType
  size_t GetElementCount() const;                    ///< Wraps OrtApi::GetTensorShapeElementCount

  size_t GetDimensionsCount() const;  ///< Wraps OrtApi::GetDimensionsCount

  /** \deprecated use GetShape() returning std::vector
   * [[deprecated]]
   * This interface is unsafe to use
   */
  [[deprecated("use GetShape()")]] void GetDimensions(int64_t* values, size_t values_count) const;  ///< Wraps OrtApi::GetDimensions

  void GetSymbolicDimensions(const char** values, size_t values_count) const;  ///< Wraps OrtApi::GetSymbolicDimensions

  std::vector<int64_t> GetShape() const;  ///< Uses GetDimensionsCount & GetDimensions to return a std::vector of the shape
};

}  // namespace detail

using ConstTensorTypeAndShapeInfo = detail::TensorTypeAndShapeInfoImpl<detail::Unowned<const OrtTensorTypeAndShapeInfo>>;

/** \brief Wrapper around ::OrtTensorTypeAndShapeInfo
 *
 */
struct TensorTypeAndShapeInfo : detail::TensorTypeAndShapeInfoImpl<OrtTensorTypeAndShapeInfo> {
  explicit TensorTypeAndShapeInfo(std::nullptr_t) {}                                                ///< Create an empty TensorTypeAndShapeInfo object, must be assigned a valid one to be used
  explicit TensorTypeAndShapeInfo(OrtTensorTypeAndShapeInfo* p) : TensorTypeAndShapeInfoImpl{p} {}  ///< Used for interop with the C API
  ConstTensorTypeAndShapeInfo GetConst() const { return ConstTensorTypeAndShapeInfo{this->p_}; }
};

namespace detail {
template <typename T>
struct SequenceTypeInfoImpl : Base<T> {
  using B = Base<T>;
  using B::B;
  TypeInfo GetSequenceElementType() const;  ///< Wraps OrtApi::GetSequenceElementType
};

}  // namespace detail

using ConstSequenceTypeInfo = detail::SequenceTypeInfoImpl<detail::Unowned<const OrtSequenceTypeInfo>>;

/** \brief Wrapper around ::OrtSequenceTypeInfo
 *
 */
struct SequenceTypeInfo : detail::SequenceTypeInfoImpl<OrtSequenceTypeInfo> {
  explicit SequenceTypeInfo(std::nullptr_t) {}                                                         ///< Create an empty SequenceTypeInfo object, must be assigned a valid one to be used
  explicit SequenceTypeInfo(OrtSequenceTypeInfo* p) : SequenceTypeInfoImpl<OrtSequenceTypeInfo>{p} {}  ///< Used for interop with the C API
  ConstSequenceTypeInfo GetConst() const { return ConstSequenceTypeInfo{this->p_}; }
};

namespace detail {
template <typename T>
struct OptionalTypeInfoImpl : Base<T> {
  using B = Base<T>;
  using B::B;
  TypeInfo GetOptionalElementType() const;  ///< Wraps OrtApi::CastOptionalTypeToContainedTypeInfo
};

}  // namespace detail

// This is always owned by the TypeInfo and can only be obtained from it.
using ConstOptionalTypeInfo = detail::OptionalTypeInfoImpl<detail::Unowned<const OrtOptionalTypeInfo>>;

namespace detail {
template <typename T>
struct MapTypeInfoImpl : detail::Base<T> {
  using B = Base<T>;
  using B::B;
  ONNXTensorElementDataType GetMapKeyType() const;  ///< Wraps OrtApi::GetMapKeyType
  TypeInfo GetMapValueType() const;                 ///< Wraps OrtApi::GetMapValueType
};

}  // namespace detail

using ConstMapTypeInfo = detail::MapTypeInfoImpl<detail::Unowned<const OrtMapTypeInfo>>;

/** \brief Wrapper around ::OrtMapTypeInfo
 *
 */
struct MapTypeInfo : detail::MapTypeInfoImpl<OrtMapTypeInfo> {
  explicit MapTypeInfo(std::nullptr_t) {}                                          ///< Create an empty MapTypeInfo object, must be assigned a valid one to be used
  explicit MapTypeInfo(OrtMapTypeInfo* p) : MapTypeInfoImpl<OrtMapTypeInfo>{p} {}  ///< Used for interop with the C API
  ConstMapTypeInfo GetConst() const { return ConstMapTypeInfo{this->p_}; }
};

namespace detail {
template <typename T>
struct TypeInfoImpl : detail::Base<T> {
  using B = Base<T>;
  using B::B;

  ConstTensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const;  ///< Wraps OrtApi::CastTypeInfoToTensorInfo
  ConstSequenceTypeInfo GetSequenceTypeInfo() const;              ///< Wraps OrtApi::CastTypeInfoToSequenceTypeInfo
  ConstMapTypeInfo GetMapTypeInfo() const;                        ///< Wraps OrtApi::CastTypeInfoToMapTypeInfo
  ConstOptionalTypeInfo GetOptionalTypeInfo() const;              ///< wraps OrtApi::CastTypeInfoToOptionalTypeInfo

  ONNXType GetONNXType() const;
};
}  // namespace detail

/// <summary>
/// Contains a constant, unowned OrtTypeInfo that can be copied and passed around by value.
/// Provides access to const OrtTypeInfo APIs.
/// </summary>
using ConstTypeInfo = detail::TypeInfoImpl<detail::Unowned<const OrtTypeInfo>>;

/// <summary>
/// Type information that may contain either TensorTypeAndShapeInfo or
/// the information about contained sequence or map depending on the ONNXType.
/// </summary>
struct TypeInfo : detail::TypeInfoImpl<OrtTypeInfo> {
  explicit TypeInfo(std::nullptr_t) {}                                 ///< Create an empty TypeInfo object, must be assigned a valid one to be used
  explicit TypeInfo(OrtTypeInfo* p) : TypeInfoImpl<OrtTypeInfo>{p} {}  ///< C API Interop

  ConstTypeInfo GetConst() const { return ConstTypeInfo{this->p_}; }
};

namespace detail {
// This structure is used to feed  sparse tensor values
// information for use with FillSparseTensor<Format>() API
// if the data type for the sparse tensor values is numeric
// use data.p_data, otherwise, use data.str pointer to feed
// values. data.str is an array of const char* that are zero terminated.
// number of strings in the array must match shape size.
// For fully sparse tensors use shape {0} and set p_data/str
// to nullptr.
struct OrtSparseValuesParam {
  const int64_t* values_shape;
  size_t values_shape_len;
  union {
    const void* p_data;
    const char** str;
  } data;
};

// Provides a way to pass shape in a single
// argument
struct Shape {
  const int64_t* shape;
  size_t shape_len;
};

template <typename T>
struct ConstValueImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  /// <summary>
  /// Obtains a pointer to a user defined data for experimental purposes
  /// </summary>
  template <typename R>
  void GetOpaqueData(const char* domain, const char* type_name, R&) const;  ///< Wraps OrtApi::GetOpaqueValue

  bool IsTensor() const;  ///< Returns true if Value is a tensor, false for other types like map/sequence/etc
  bool HasValue() const;  /// < Return true if OrtValue contains data and returns false if the OrtValue is a None

  size_t GetCount() const;  // If a non tensor, returns 2 for map and N for sequence, where N is the number of elements
  Value GetValue(int index, OrtAllocator* allocator) const;

  /// <summary>
  /// This API returns a full length of string data contained within either a tensor or a sparse Tensor.
  /// For sparse tensor it returns a full length of stored non-empty strings (values). The API is useful
  /// for allocating necessary memory and calling GetStringTensorContent().
  /// </summary>
  /// <returns>total length of UTF-8 encoded bytes contained. No zero terminators counted.</returns>
  size_t GetStringTensorDataLength() const;

  /// <summary>
  /// The API copies all of the UTF-8 encoded string data contained within a tensor or a sparse tensor
  /// into a supplied buffer. Use GetStringTensorDataLength() to find out the length of the buffer to allocate.
  /// The user must also allocate offsets buffer with the number of entries equal to that of the contained
  /// strings.
  ///
  /// Strings are always assumed to be on CPU, no X-device copy.
  /// </summary>
  /// <param name="buffer">user allocated buffer</param>
  /// <param name="buffer_length">length in bytes of the allocated buffer</param>
  /// <param name="offsets">a pointer to the offsets user allocated buffer</param>
  /// <param name="offsets_count">count of offsets, must be equal to the number of strings contained.
  ///   that can be obtained from the shape of the tensor or from GetSparseTensorValuesTypeAndShapeInfo()
  ///   for sparse tensors</param>
  void GetStringTensorContent(void* buffer, size_t buffer_length, size_t* offsets, size_t offsets_count) const;

  /// <summary>
  /// Returns a const typed pointer to the tensor contained data.
  /// No type checking is performed, the caller must ensure the type matches the tensor type.
  /// </summary>
  /// <typeparam name="T"></typeparam>
  /// <returns>const pointer to data, no copies made</returns>
  template <typename R>
  const R* GetTensorData() const;  ///< Wraps OrtApi::GetTensorMutableData   /// <summary>

  /// <summary>
  /// Returns a non-typed pointer to a tensor contained data.
  /// </summary>
  /// <returns>const pointer to data, no copies made</returns>
  const void* GetTensorRawData() const;

  /// <summary>
  /// The API returns type information for data contained in a tensor. For sparse
  /// tensors it returns type information for contained non-zero values.
  /// It returns dense shape for sparse tensors.
  /// </summary>
  /// <returns>TypeInfo</returns>
  TypeInfo GetTypeInfo() const;

  /// <summary>
  /// The API returns type information for data contained in a tensor. For sparse
  /// tensors it returns type information for contained non-zero values.
  /// It returns dense shape for sparse tensors.
  /// </summary>
  /// <returns>TensorTypeAndShapeInfo</returns>
  TensorTypeAndShapeInfo GetTensorTypeAndShapeInfo() const;

  /// <summary>
  /// This API returns information about the memory allocation used to hold data.
  /// </summary>
  /// <returns>Non owning instance of MemoryInfo</returns>
  ConstMemoryInfo GetTensorMemoryInfo() const;

  /// <summary>
  /// The API copies UTF-8 encoded bytes for the requested string element
  /// contained within a tensor or a sparse tensor into a provided buffer.
  /// Use GetStringTensorElementLength() to obtain the length of the buffer to allocate.
  /// </summary>
  /// <param name="buffer_length"></param>
  /// <param name="element_index"></param>
  /// <param name="buffer"></param>
  void GetStringTensorElement(size_t buffer_length, size_t element_index, void* buffer) const;

  /// <summary>
  /// Returns string tensor UTF-8 encoded string element.
  /// Use of this API is recommended over GetStringTensorElement() that takes void* buffer pointer.
  /// </summary>
  /// <param name="element_index"></param>
  /// <returns>std::string</returns>
  std::string GetStringTensorElement(size_t element_index) const;

  /// <summary>
  /// The API returns a byte length of UTF-8 encoded string element
  /// contained in either a tensor or a spare tensor values.
  /// </summary>
  /// <param name="element_index"></param>
  /// <returns>byte length for the specified string element</returns>
  size_t GetStringTensorElementLength(size_t element_index) const;

#if !defined(DISABLE_SPARSE_TENSORS)
  /// <summary>
  /// The API returns the sparse data format this OrtValue holds in a sparse tensor.
  /// If the sparse tensor was not fully constructed, i.e. Use*() or Fill*() API were not used
  /// the value returned is ORT_SPARSE_UNDEFINED.
  /// </summary>
  /// <returns>Format enum</returns>
  OrtSparseFormat GetSparseFormat() const;

  /// <summary>
  /// The API returns type and shape information for stored non-zero values of the
  /// sparse tensor. Use GetSparseTensorValues() to obtain values buffer pointer.
  /// </summary>
  /// <returns>TensorTypeAndShapeInfo values information</returns>
  TensorTypeAndShapeInfo GetSparseTensorValuesTypeAndShapeInfo() const;

  /// <summary>
  /// The API returns type and shape information for the specified indices. Each supported
  /// indices have their own enum values even if a give format has more than one kind of indices.
  /// Use GetSparseTensorIndicesData() to obtain pointer to indices buffer.
  /// </summary>
  /// <param name="format">enum requested</param>
  /// <returns>type and shape information</returns>
  TensorTypeAndShapeInfo GetSparseTensorIndicesTypeShapeInfo(OrtSparseIndicesFormat format) const;

  /// <summary>
  /// The API retrieves a pointer to the internal indices buffer. The API merely performs
  /// a convenience data type casting on the return type pointer. Make sure you are requesting
  /// the right type, use GetSparseTensorIndicesTypeShapeInfo();
  /// </summary>
  /// <typeparam name="T">type to cast to</typeparam>
  /// <param name="indices_format">requested indices kind</param>
  /// <param name="num_indices">number of indices entries</param>
  /// <returns>Pinter to the internal sparse tensor buffer containing indices. Do not free this pointer.</returns>
  template <typename R>
  const R* GetSparseTensorIndicesData(OrtSparseIndicesFormat indices_format, size_t& num_indices) const;

  /// <summary>
  /// Returns true if the OrtValue contains a sparse tensor
  /// </summary>
  /// <returns></returns>
  bool IsSparseTensor() const;

  /// <summary>
  /// The API returns a pointer to an internal buffer of the sparse tensor
  /// containing non-zero values. The API merely does casting. Make sure you
  /// are requesting the right data type by calling GetSparseTensorValuesTypeAndShapeInfo()
  /// first.
  /// </summary>
  /// <typeparam name="T">numeric data types only. Use GetStringTensor*() to retrieve strings.</typeparam>
  /// <returns>a pointer to the internal values buffer. Do not free this pointer.</returns>
  template <typename R>
  const R* GetSparseTensorValues() const;

#endif
};

template <typename T>
struct ValueImpl : ConstValueImpl<T> {
  using B = ConstValueImpl<T>;
  using B::B;

  /// <summary>
  /// Returns a non-const typed pointer to an OrtValue/Tensor contained buffer
  /// No type checking is performed, the caller must ensure the type matches the tensor type.
  /// </summary>
  /// <returns>non-const pointer to data, no copies made</returns>
  template <typename R>
  R* GetTensorMutableData();

  /// <summary>
  /// Returns a non-typed non-const pointer to a tensor contained data.
  /// </summary>
  /// <returns>pointer to data, no copies made</returns>
  void* GetTensorMutableRawData();

  /// <summary>
  //  Obtain a reference to an element of data at the location specified
  /// by the vector of dims.
  /// </summary>
  /// <typeparam name="R"></typeparam>
  /// <param name="location">[in] expressed by a vecotr of dimensions offsets</param>
  /// <returns></returns>
  template <typename R>
  R& At(const std::vector<int64_t>& location);

  /// <summary>
  /// Set all strings at once in a string tensor
  /// </summary>
  /// <param name="s">[in] An array of strings. Each string in this array must be null terminated.</param>
  /// <param name="s_len">[in] Count of strings in s (Must match the size of \p value's tensor shape)</param>
  void FillStringTensor(const char* const* s, size_t s_len);

  /// <summary>
  /// Set a single string in a string tensor
  /// </summary>
  /// <param name="s">[in] A null terminated UTF-8 encoded string</param>
  /// <param name="index">[in] Index of the string in the tensor to set</param>
  void FillStringTensorElement(const char* s, size_t index);

  /// <summary>
  /// Allocate if necessary and obtain a pointer to a UTF-8
  /// encoded string element buffer indexed by the flat element index,
  /// of the specified length.
  ///
  /// This API is for advanced usage. It avoids a need to construct
  /// an auxiliary array of string pointers, and allows to write data directly
  /// (do not zero terminate).
  /// </summary>
  /// <param name="index"></param>
  /// <param name="buffer_length"></param>
  /// <returns>a pointer to a writable buffer</returns>
  char* GetResizedStringTensorElementBuffer(size_t index, size_t buffer_length);

#if !defined(DISABLE_SPARSE_TENSORS)
  /// <summary>
  /// Supplies COO format specific indices and marks the contained sparse tensor as being a COO format tensor.
  /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
  /// allocated buffers lifespan must eclipse that of the OrtValue.
  /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
  /// </summary>
  /// <param name="indices_data">pointer to the user allocated buffer with indices. Use nullptr for fully sparse tensors.</param>
  /// <param name="indices_num">number of indices entries. Use 0 for fully sparse tensors</param>
  void UseCooIndices(int64_t* indices_data, size_t indices_num);

  /// <summary>
  /// Supplies CSR format specific indices and marks the contained sparse tensor as being a CSR format tensor.
  /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
  /// allocated buffers lifespan must eclipse that of the OrtValue.
  /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
  /// </summary>
  /// <param name="inner_data">pointer to the user allocated buffer with inner indices or nullptr for fully sparse tensors</param>
  /// <param name="inner_num">number of csr inner indices or 0 for fully sparse tensors</param>
  /// <param name="outer_data">pointer to the user allocated buffer with outer indices or nullptr for fully sparse tensors</param>
  /// <param name="outer_num">number of csr outer indices or 0 for fully sparse tensors</param>
  void UseCsrIndices(int64_t* inner_data, size_t inner_num, int64_t* outer_data, size_t outer_num);

  /// <summary>
  /// Supplies BlockSparse format specific indices and marks the contained sparse tensor as being a BlockSparse format tensor.
  /// Values are supplied with a CreateSparseTensor() API. The supplied indices are not copied and the user
  /// allocated buffers lifespan must eclipse that of the OrtValue.
  /// The location of the indices is assumed to be the same as specified by OrtMemoryInfo argument at the creation time.
  /// </summary>
  /// <param name="indices_shape">indices shape or a {0} for fully sparse</param>
  /// <param name="indices_data">user allocated buffer with indices or nullptr for fully spare tensors</param>
  void UseBlockSparseIndices(const Shape& indices_shape, int32_t* indices_data);

  /// <summary>
  /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
  /// and copy the values and COO indices into it. If data_mem_info specifies that the data is located
  /// at difference device than the allocator, a X-device copy will be performed if possible.
  /// </summary>
  /// <param name="data_mem_info">specified buffer memory description</param>
  /// <param name="values_param">values buffer information.</param>
  /// <param name="indices_data">coo indices buffer or nullptr for fully sparse data</param>
  /// <param name="indices_num">number of COO indices or 0 for fully sparse data</param>
  void FillSparseTensorCoo(const OrtMemoryInfo* data_mem_info, const OrtSparseValuesParam& values_param,
                           const int64_t* indices_data, size_t indices_num);

  /// <summary>
  /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
  /// and copy the values and CSR indices into it. If data_mem_info specifies that the data is located
  /// at difference device than the allocator, a X-device copy will be performed if possible.
  /// </summary>
  /// <param name="data_mem_info">specified buffer memory description</param>
  /// <param name="values">values buffer information</param>
  /// <param name="inner_indices_data">csr inner indices pointer or nullptr for fully sparse tensors</param>
  /// <param name="inner_indices_num">number of csr inner indices or 0 for fully sparse tensors</param>
  /// <param name="outer_indices_data">pointer to csr indices data or nullptr for fully sparse tensors</param>
  /// <param name="outer_indices_num">number of csr outer indices or 0</param>
  void FillSparseTensorCsr(const OrtMemoryInfo* data_mem_info,
                           const OrtSparseValuesParam& values,
                           const int64_t* inner_indices_data, size_t inner_indices_num,
                           const int64_t* outer_indices_data, size_t outer_indices_num);

  /// <summary>
  /// The API will allocate memory using the allocator instance supplied to the CreateSparseTensor() API
  /// and copy the values and BlockSparse indices into it. If data_mem_info specifies that the data is located
  /// at difference device than the allocator, a X-device copy will be performed if possible.
  /// </summary>
  /// <param name="data_mem_info">specified buffer memory description</param>
  /// <param name="values">values buffer information</param>
  /// <param name="indices_shape">indices shape. use {0} for fully sparse tensors</param>
  /// <param name="indices_data">pointer to indices data or nullptr for fully sparse tensors</param>
  void FillSparseTensorBlockSparse(const OrtMemoryInfo* data_mem_info,
                                   const OrtSparseValuesParam& values,
                                   const Shape& indices_shape,
                                   const int32_t* indices_data);

#endif
};

}  // namespace detail

using ConstValue = detail::ConstValueImpl<detail::Unowned<const OrtValue>>;
using UnownedValue = detail::ValueImpl<detail::Unowned<OrtValue>>;

/** \brief Wrapper around ::OrtValue
 *
 */
struct Value : detail::ValueImpl<OrtValue> {
  using Base = detail::ValueImpl<OrtValue>;
  using OrtSparseValuesParam = detail::OrtSparseValuesParam;
  using Shape = detail::Shape;

  explicit Value(std::nullptr_t) {}         ///< Create an empty Value object, must be assigned a valid one to be used
  explicit Value(OrtValue* p) : Base{p} {}  ///< Used for interop with the C API
  Value(Value&&) = default;
  Value& operator=(Value&&) = default;

  ConstValue GetConst() const { return ConstValue{this->p_}; }
  UnownedValue GetUnowned() const { return UnownedValue{this->p_}; }

  /** \brief Creates a tensor with a user supplied buffer. Wraps OrtApi::CreateTensorWithDataAsOrtValue.
   * \tparam T The numeric datatype. This API is not suitable for strings.
   * \param info Memory description of where the p_data buffer resides (CPU vs GPU etc).
   * \param p_data Pointer to the data buffer.
   * \param p_data_element_count The number of elements in the data buffer.
   * \param shape Pointer to the tensor shape dimensions.
   * \param shape_len The number of tensor shape dimensions.
   */
  template <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);

  /** \brief Creates a tensor with a user supplied buffer. Wraps OrtApi::CreateTensorWithDataAsOrtValue.
   *
   * \param info Memory description of where the p_data buffer resides (CPU vs GPU etc).
   * \param p_data Pointer to the data buffer.
   * \param p_data_byte_count The number of bytes in the data buffer.
   * \param shape Pointer to the tensor shape dimensions.
   * \param shape_len The number of tensor shape dimensions.
   * \param type The data type.
   */
  static Value CreateTensor(const OrtMemoryInfo* info, void* p_data, size_t p_data_byte_count, const int64_t* shape, size_t shape_len,
                            ONNXTensorElementDataType type);

  /** \brief Creates an OrtValue with a tensor using a supplied OrtAllocator. Wraps OrtApi::CreateTensorAsOrtValue.
   *         This overload will allocate the buffer for the tensor  according to the supplied shape and data type.
   *         The allocated buffer will be owned by the returned OrtValue and will be freed when the OrtValue is released.
   *         The input data would need to be copied into the allocated buffer.
   *         This API is not suitable for strings.
   *
   * \tparam T The numeric datatype. This API is not suitable for strings.
   * \param allocator The allocator to use.
   * \param shape Pointer to the tensor shape dimensions.
   * \param shape_len The number of tensor shape dimensions.
   */
  template <typename T>
  static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len);

  /** \brief Creates an OrtValue with a tensor using the supplied OrtAllocator.
   *   Wraps OrtApi::CreateTensorAsOrtValue.
   *   The allocated buffer will be owned by the returned OrtValue and will be freed when the OrtValue is released.
   *   The input data would need to be copied into the allocated buffer.
   *   This API is not suitable for strings.
   *
   * \param allocator The allocator to use.
   * \param shape Pointer to the tensor shape dimensions.
   * \param shape_len The number of tensor shape dimensions.
   * \param type The data type.
   */
  static Value CreateTensor(OrtAllocator* allocator, const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type);

  /** \brief Creates an OrtValue with a Map Onnx type representation.
   *  The API would ref-count the supplied OrtValues and they will be released
   *  when the returned OrtValue is released. The caller may release keys and values after the call
   *  returns.
   *
   * \param keys an OrtValue containing a tensor with primitive data type keys.
   * \param values an OrtValue that may contain a tensor. Ort currently supports only primitive data type values.
   */
  static Value CreateMap(const Value& keys, const Value& values);  ///< Wraps OrtApi::CreateValue

  /** \brief Creates an OrtValue with a Sequence Onnx type representation.
   *  The API would ref-count the supplied OrtValues and they will be released
   *  when the returned OrtValue is released. The caller may release the values after the call
   *  returns.
   *
   * \param values a vector of OrtValues that must have the same Onnx value type.
   */
  static Value CreateSequence(const std::vector<Value>& values);  ///< Wraps OrtApi::CreateValue

  /** \brief Creates an OrtValue wrapping an Opaque type.
   *  This is used for experimental support of non-tensor types.
   *
   * \tparam T - the type of the value.
   * \param domain - zero terminated utf-8 string. Domain of the type.
   * \param type_name - zero terminated utf-8 string. Name of the type.
   * \param value - the value to be wrapped.
   */
  template <typename T>
  static Value CreateOpaque(const char* domain, const char* type_name, const T& value);  ///< Wraps OrtApi::CreateOpaqueValue

#if !defined(DISABLE_SPARSE_TENSORS)
  /// <summary>
  /// This is a simple forwarding method to the other overload that helps deducing
  /// data type enum value from the type of the buffer.
  /// </summary>
  /// <typeparam name="T">numeric datatype. This API is not suitable for strings.</typeparam>
  /// <param name="info">Memory description where the user buffers reside (CPU vs GPU etc)</param>
  /// <param name="p_data">pointer to the user supplied buffer, use nullptr for fully sparse tensors</param>
  /// <param name="dense_shape">a would be dense shape of the tensor</param>
  /// <param name="values_shape">non zero values shape. Use a single 0 shape for fully sparse tensors.</param>
  /// <returns></returns>
  template <typename T>
  static Value CreateSparseTensor(const OrtMemoryInfo* info, T* p_data, const Shape& dense_shape,
                                  const Shape& values_shape);

  /// <summary>
  /// Creates an OrtValue instance containing SparseTensor. This constructs
  /// a sparse tensor that makes use of user allocated buffers. It does not make copies
  /// of the user provided data and does not modify it. The lifespan of user provided buffers should
  /// eclipse the life span of the resulting OrtValue. This call constructs an instance that only contain
  /// a pointer to non-zero values. To fully populate the sparse tensor call Use<Format>Indices() API below
  /// to supply a sparse format specific indices.
  /// This API is not suitable for string data. Use CreateSparseTensor() with allocator specified so strings
  /// can be properly copied into the allocated buffer.
  /// </summary>
  /// <param name="info">Memory description where the user buffers reside (CPU vs GPU etc)</param>
  /// <param name="p_data">pointer to the user supplied buffer, use nullptr for fully sparse tensors</param>
  /// <param name="dense_shape">a would be dense shape of the tensor</param>
  /// <param name="values_shape">non zero values shape. Use a single 0 shape for fully sparse tensors.</param>
  /// <param name="type">data type</param>
  /// <returns>Ort::Value instance containing SparseTensor</returns>
  static Value CreateSparseTensor(const OrtMemoryInfo* info, void* p_data, const Shape& dense_shape,
                                  const Shape& values_shape, ONNXTensorElementDataType type);

  /// <summary>
  /// This is a simple forwarding method to the below CreateSparseTensor.
  /// This helps to specify data type enum in terms of C++ data type.
  /// Use CreateSparseTensor<T>
  /// </summary>
  /// <typeparam name="T">numeric data type only. String data enum must be specified explicitly.</typeparam>
  /// <param name="allocator">allocator to use</param>
  /// <param name="dense_shape">a would be dense shape of the tensor</param>
  /// <returns>Ort::Value</returns>
  template <typename T>
  static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape);

  /// <summary>
  /// Creates an instance of OrtValue containing sparse tensor. The created instance has no data.
  /// The data must be supplied by on of the FillSparseTensor<Format>() methods that take both non-zero values
  /// and indices. The data will be copied into a buffer that would be allocated using the supplied allocator.
  /// Use this API to create OrtValues that contain sparse tensors with all supported data types including
  /// strings.
  /// </summary>
  /// <param name="allocator">allocator to use. The allocator lifespan must eclipse that of the resulting OrtValue</param>
  /// <param name="dense_shape">a would be dense shape of the tensor</param>
  /// <param name="type">data type</param>
  /// <returns>an instance of Ort::Value</returns>
  static Value CreateSparseTensor(OrtAllocator* allocator, const Shape& dense_shape, ONNXTensorElementDataType type);

#endif  // !defined(DISABLE_SPARSE_TENSORS)
};

/// <summary>
/// Represents native memory allocation coming from one of the
/// OrtAllocators registered with OnnxRuntime.
/// Use it to wrap an allocation made by an allocator
/// so it can be automatically released when no longer needed.
/// </summary>
struct MemoryAllocation {
  MemoryAllocation(OrtAllocator* allocator, void* p, size_t size);
  ~MemoryAllocation();
  MemoryAllocation(const MemoryAllocation&) = delete;
  MemoryAllocation& operator=(const MemoryAllocation&) = delete;
  MemoryAllocation(MemoryAllocation&&) noexcept;
  MemoryAllocation& operator=(MemoryAllocation&&) noexcept;

  void* get() { return p_; }
  size_t size() const { return size_; }

 private:
  OrtAllocator* allocator_;
  void* p_;
  size_t size_;
};

namespace detail {
template <typename T>
struct AllocatorImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  void* Alloc(size_t size);
  MemoryAllocation GetAllocation(size_t size);
  void Free(void* p);
  ConstMemoryInfo GetInfo() const;
};

}  // namespace detail

/** \brief Wrapper around ::OrtAllocator default instance that is owned by Onnxruntime
 *
 */
struct AllocatorWithDefaultOptions : detail::AllocatorImpl<detail::Unowned<OrtAllocator>> {
  explicit AllocatorWithDefaultOptions(std::nullptr_t) {}  ///< Convenience to create a class member and then replace with an instance
  AllocatorWithDefaultOptions();
};

/** \brief Wrapper around ::OrtAllocator
 *
 */
struct Allocator : detail::AllocatorImpl<OrtAllocator> {
  explicit Allocator(std::nullptr_t) {}  ///< Convenience to create a class member and then replace with an instance
  Allocator(const Session& session, const OrtMemoryInfo*);
};

using UnownedAllocator = detail::AllocatorImpl<detail::Unowned<OrtAllocator>>;

namespace detail {
namespace binding_utils {
// Bring these out of template
std::vector<std::string> GetOutputNamesHelper(const OrtIoBinding* binding, OrtAllocator*);
std::vector<Value> GetOutputValuesHelper(const OrtIoBinding* binding, OrtAllocator*);
}  // namespace binding_utils

template <typename T>
struct ConstIoBindingImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  std::vector<std::string> GetOutputNames() const;
  std::vector<std::string> GetOutputNames(OrtAllocator*) const;
  std::vector<Value> GetOutputValues() const;
  std::vector<Value> GetOutputValues(OrtAllocator*) const;
};

template <typename T>
struct IoBindingImpl : ConstIoBindingImpl<T> {
  using B = ConstIoBindingImpl<T>;
  using B::B;

  void BindInput(const char* name, const Value&);
  void BindOutput(const char* name, const Value&);
  void BindOutput(const char* name, const OrtMemoryInfo*);
  void ClearBoundInputs();
  void ClearBoundOutputs();
  void SynchronizeInputs();
  void SynchronizeOutputs();
};

}  // namespace detail

using ConstIoBinding = detail::ConstIoBindingImpl<detail::Unowned<const OrtIoBinding>>;
using UnownedIoBinding = detail::IoBindingImpl<detail::Unowned<OrtIoBinding>>;

/** \brief Wrapper around ::OrtIoBinding
 *
 */
struct IoBinding : detail::IoBindingImpl<OrtIoBinding> {
  explicit IoBinding(std::nullptr_t) {}  ///< Create an empty object for convenience. Sometimes, we want to initialize members later.
  explicit IoBinding(Session& session);
  ConstIoBinding GetConst() const { return ConstIoBinding{this->p_}; }
  UnownedIoBinding GetUnowned() const { return UnownedIoBinding{this->p_}; }
};

/*! \struct Ort::ArenaCfg
 * \brief it is a structure that represents the configuration of an arena based allocator
 * \details Please see docs/C_API.md for details
 */
struct ArenaCfg : detail::Base<OrtArenaCfg> {
  explicit ArenaCfg(std::nullptr_t) {}  ///< Create an empty ArenaCfg object, must be assigned a valid one to be used
  /**
   * Wraps OrtApi::CreateArenaCfg
   * \param max_mem - use 0 to allow ORT to choose the default
   * \param arena_extend_strategy -  use -1 to allow ORT to choose the default, 0 = kNextPowerOfTwo, 1 = kSameAsRequested
   * \param initial_chunk_size_bytes - use -1 to allow ORT to choose the default
   * \param max_dead_bytes_per_chunk - use -1 to allow ORT to choose the default
   * See docs/C_API.md for details on what the following parameters mean and how to choose these values
   */
  ArenaCfg(size_t max_mem, int arena_extend_strategy, int initial_chunk_size_bytes, int max_dead_bytes_per_chunk);
};

//
// Custom OPs (only needed to implement custom OPs)
//

/// <summary>
/// This struct provides life time management for custom op attribute
/// </summary>
struct OpAttr : detail::Base<OrtOpAttr> {
  OpAttr(const char* name, const void* data, int len, OrtOpAttrType type);
};

/**
 * Macro that logs a message using the provided logger. Throws an exception if OrtApi::Logger_LogMessage fails.
 * Example: ORT_CXX_LOG(logger, ORT_LOGGING_LEVEL_INFO, "Log a message");
 *
 * \param logger The Ort::Logger instance to use. Must be a value or reference.
 * \param message_severity The logging severity level of the message.
 * \param message A null-terminated UTF-8 message to log.
 */
#define ORT_CXX_LOG(logger, message_severity, message)                                       \
  do {                                                                                       \
    if (message_severity >= logger.GetLoggingSeverityLevel()) {                              \
      Ort::ThrowOnError(logger.LogMessage(message_severity, ORT_FILE, __LINE__,              \
                                          static_cast<const char*>(__FUNCTION__), message)); \
    }                                                                                        \
  } while (false)

/**
 * Macro that logs a message using the provided logger. Can be used in noexcept code since errors are silently ignored.
 * Example: ORT_CXX_LOG_NOEXCEPT(logger, ORT_LOGGING_LEVEL_INFO, "Log a message");
 *
 * \param logger The Ort::Logger instance to use. Must be a value or reference.
 * \param message_severity The logging severity level of the message.
 * \param message A null-terminated UTF-8 message to log.
 */
#define ORT_CXX_LOG_NOEXCEPT(logger, message_severity, message)                              \
  do {                                                                                       \
    if (message_severity >= logger.GetLoggingSeverityLevel()) {                              \
      static_cast<void>(logger.LogMessage(message_severity, ORT_FILE, __LINE__,              \
                                          static_cast<const char*>(__FUNCTION__), message)); \
    }                                                                                        \
  } while (false)

/**
 * Macro that logs a printf-like formatted message using the provided logger. Throws an exception if
 * OrtApi::Logger_LogMessage fails or if a formatting error occurs.
 * Example: ORT_CXX_LOGF(logger, ORT_LOGGING_LEVEL_INFO, "Log an int: %d", 12);
 *
 * \param logger The Ort::Logger instance to use. Must be a value or reference.
 * \param message_severity The logging severity level of the message.
 * \param format A null-terminated UTF-8 format string forwarded to a printf-like function.
 *               Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats.
 * \param ... Zero or more variadic arguments referenced by the format string.
 */
#define ORT_CXX_LOGF(logger, message_severity, /*format,*/...)                                            \
  do {                                                                                                    \
    if (message_severity >= logger.GetLoggingSeverityLevel()) {                                           \
      Ort::ThrowOnError(logger.LogFormattedMessage(message_severity, ORT_FILE, __LINE__,                  \
                                                   static_cast<const char*>(__FUNCTION__), __VA_ARGS__)); \
    }                                                                                                     \
  } while (false)

/**
 * Macro that logs a printf-like formatted message using the provided logger. Can be used in noexcept code since errors
 * are silently ignored.
 * Example: ORT_CXX_LOGF_NOEXCEPT(logger, ORT_LOGGING_LEVEL_INFO, "Log an int: %d", 12);
 *
 * \param logger The Ort::Logger instance to use. Must be a value or reference.
 * \param message_severity The logging severity level of the message.
 * \param format A null-terminated UTF-8 format string forwarded to a printf-like function.
 *               Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats.
 * \param ... Zero or more variadic arguments referenced by the format string.
 */
#define ORT_CXX_LOGF_NOEXCEPT(logger, message_severity, /*format,*/...)                                   \
  do {                                                                                                    \
    if (message_severity >= logger.GetLoggingSeverityLevel()) {                                           \
      static_cast<void>(logger.LogFormattedMessage(message_severity, ORT_FILE, __LINE__,                  \
                                                   static_cast<const char*>(__FUNCTION__), __VA_ARGS__)); \
    }                                                                                                     \
  } while (false)

/// <summary>
/// This class represents an ONNX Runtime logger that can be used to log information with an
/// associated severity level and source code location (file path, line number, function name).
///
/// A Logger can be obtained from within custom operators by calling Ort::KernelInfo::GetLogger().
/// Instances of Ort::Logger are the size of two pointers and can be passed by value.
///
/// Use the ORT_CXX_LOG macros to ensure the source code location is set properly from the callsite
/// and to take advantage of a cached logging severity level that can bypass calls to the underlying C API.
/// </summary>
struct Logger {
  /**
   * Creates an empty Ort::Logger. Must be initialized from a valid Ort::Logger before use.
   */
  Logger() = default;

  /**
   * Creates an empty Ort::Logger. Must be initialized from a valid Ort::Logger before use.
   */
  explicit Logger(std::nullptr_t) {}

  /**
   * Creates a logger from an ::OrtLogger instance. Caches the logger's current severity level by calling
   * OrtApi::Logger_GetLoggingSeverityLevel. Throws an exception if OrtApi::Logger_GetLoggingSeverityLevel fails.
   *
   * \param logger The ::OrtLogger to wrap.
   */
  explicit Logger(const OrtLogger* logger);

  ~Logger() = default;

  Logger(const Logger&) = default;
  Logger& operator=(const Logger&) = default;

  Logger(Logger&& v) noexcept = default;
  Logger& operator=(Logger&& v) noexcept = default;

  /**
   * Returns the logger's current severity level from the cached member.
   *
   * \return The current ::OrtLoggingLevel.
   */
  OrtLoggingLevel GetLoggingSeverityLevel() const noexcept;

  /**
   * Logs the provided message via OrtApi::Logger_LogMessage. Use the ORT_CXX_LOG or ORT_CXX_LOG_NOEXCEPT
   * macros to properly set the source code location and to use the cached severity level to potentially bypass
   * calls to the underlying C API.
   *
   * \param log_severity_level The message's logging severity level.
   * \param file_path The filepath of the file in which the message is logged. Usually the value of ORT_FILE.
   * \param line_number The file line number in which the message is logged. Usually the value of __LINE__.
   * \param func_name The name of the function in which the message is logged. Usually the value of __FUNCTION__.
   * \param message The message to log.
   * \return A Ort::Status value to indicate error or success.
   */
  Status LogMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, int line_number,
                    const char* func_name, const char* message) const noexcept;

  /**
   * Logs a printf-like formatted message via OrtApi::Logger_LogMessage. Use the ORT_CXX_LOGF or ORT_CXX_LOGF_NOEXCEPT
   * macros to properly set the source code location and to use the cached severity level to potentially bypass
   * calls to the underlying C API. Returns an error status if a formatting error occurs.
   *
   * \param log_severity_level The message's logging severity level.
   * \param file_path The filepath of the file in which the message is logged. Usually the value of ORT_FILE.
   * \param line_number The file line number in which the message is logged. Usually the value of __LINE__.
   * \param func_name The name of the function in which the message is logged. Usually the value of __FUNCTION__.
   * \param format A null-terminated UTF-8 format string forwarded to a printf-like function.
   *               Refer to https://en.cppreference.com/w/cpp/io/c/fprintf for information on valid formats.
   * \param args Zero or more variadic arguments referenced by the format string.
   * \return A Ort::Status value to indicate error or success.
   */
  template <typename... Args>
  Status LogFormattedMessage(OrtLoggingLevel log_severity_level, const ORTCHAR_T* file_path, int line_number,
                             const char* func_name, const char* format, Args&&... args) const noexcept;

 private:
  const OrtLogger* logger_{};
  OrtLoggingLevel cached_severity_level_{};
};

/// <summary>
/// This class wraps a raw pointer OrtKernelContext* that is being passed
/// to the custom kernel Compute() method. Use it to safely access context
/// attributes, input and output parameters with exception safety guarantees.
/// See usage example in onnxruntime/test/testdata/custom_op_library/custom_op_library.cc
/// </summary>
struct KernelContext {
  explicit KernelContext(OrtKernelContext* context);
  size_t GetInputCount() const;
  size_t GetOutputCount() const;
  // If input is optional and is not present, the method returns en empty ConstValue
  // which can be compared to nullptr.
  ConstValue GetInput(size_t index) const;
  // If outout is optional and is not present, the method returns en empty UnownedValue
  // which can be compared to nullptr.
  UnownedValue GetOutput(size_t index, const int64_t* dim_values, size_t dim_count) const;
  UnownedValue GetOutput(size_t index, const std::vector<int64_t>& dims) const;
  void* GetGPUComputeStream() const;
  Logger GetLogger() const;
  OrtAllocator* GetAllocator(const OrtMemoryInfo& memory_info) const;
  OrtKernelContext* GetOrtKernelContext() const { return ctx_; }
  void ParallelFor(void (*fn)(void*, size_t), size_t total, size_t num_batch, void* usr_data) const;

 private:
  OrtKernelContext* ctx_;
};

struct KernelInfo;

namespace detail {
namespace attr_utils {
void GetAttr(const OrtKernelInfo* p, const char* name, float&);
void GetAttr(const OrtKernelInfo* p, const char* name, int64_t&);
void GetAttr(const OrtKernelInfo* p, const char* name, std::string&);
void GetAttrs(const OrtKernelInfo* p, const char* name, std::vector<float>&);
void GetAttrs(const OrtKernelInfo* p, const char* name, std::vector<int64_t>&);
}  // namespace attr_utils

template <typename T>
struct KernelInfoImpl : Base<T> {
  using B = Base<T>;
  using B::B;

  KernelInfo Copy() const;

  template <typename R>  // R is only implemented for float, int64_t, and string
  R GetAttribute(const char* name) const {
    R val;
    attr_utils::GetAttr(this->p_, name, val);
    return val;
  }

  template <typename R>  // R is only implemented for std::vector<float>, std::vector<int64_t>
  std::vector<R> GetAttributes(const char* name) const {
    std::vector<R> result;
    attr_utils::GetAttrs(this->p_, name, result);
    return result;
  }

  Value GetTensorAttribute(const char* name, OrtAllocator* allocator) const;

  size_t GetInputCount() const;
  size_t GetOutputCount() const;

  std::string GetInputName(size_t index) const;
  std::string GetOutputName(size_t index) const;

  TypeInfo GetInputTypeInfo(size_t index) const;
  TypeInfo GetOutputTypeInfo(size_t index) const;

  ConstValue GetTensorConstantInput(size_t index, int* is_constant) const;

  std::string GetNodeName() const;
  Logger GetLogger() const;
};

}  // namespace detail

using ConstKernelInfo = detail::KernelInfoImpl<detail::Unowned<const OrtKernelInfo>>;

/// <summary>
/// This struct owns the OrtKernInfo* pointer when a copy is made.
/// For convenient wrapping of OrtKernelInfo* passed to kernel constructor
/// and query attributes, warp the pointer with Ort::Unowned<KernelInfo> instance
/// so it does not destroy the pointer the kernel does not own.
/// </summary>
struct KernelInfo : detail::KernelInfoImpl<OrtKernelInfo> {
  explicit KernelInfo(std::nullptr_t) {}     ///< Create an empty instance to initialize later
  explicit KernelInfo(OrtKernelInfo* info);  ///< Take ownership of the instance
  ConstKernelInfo GetConst() const { return ConstKernelInfo{this->p_}; }
};

/// <summary>
/// Create and own custom defined operation.
/// </summary>
struct Op : detail::Base<OrtOp> {
  explicit Op(std::nullptr_t) {}  ///< Create an empty Operator object, must be assigned a valid one to be used

  explicit Op(OrtOp*);  ///< Take ownership of the OrtOp

  static Op Create(const OrtKernelInfo* info, const char* op_name, const char* domain,
                   int version, const char** type_constraint_names,
                   const ONNXTensorElementDataType* type_constraint_values,
                   size_t type_constraint_count,
                   const OpAttr* attr_values,
                   size_t attr_count,
                   size_t input_count, size_t output_count);

  void Invoke(const OrtKernelContext* context,
              const Value* input_values,
              size_t input_count,
              Value* output_values,
              size_t output_count);

  // For easier refactoring
  void Invoke(const OrtKernelContext* context,
              const OrtValue* const* input_values,
              size_t input_count,
              OrtValue* const* output_values,
              size_t output_count);
};

/// <summary>
/// Provide access to per-node attributes and input shapes, so one could compute and set output shapes.
/// </summary>
struct ShapeInferContext {
  struct SymbolicInteger {
    SymbolicInteger(int64_t i) : i_(i), is_int_(true) {};
    SymbolicInteger(const char* s) : s_(s), is_int_(false) {};
    SymbolicInteger(const SymbolicInteger&) = default;
    SymbolicInteger(SymbolicInteger&&) = default;

    SymbolicInteger& operator=(const SymbolicInteger&) = default;
    SymbolicInteger& operator=(SymbolicInteger&&) = default;

    bool operator==(const SymbolicInteger& dim) const {
      if (is_int_ == dim.is_int_) {
        if (is_int_) {
          return i_ == dim.i_;
        } else {
          return std::string{s_} == std::string{dim.s_};
        }
      }
      return false;
    }

    bool IsInt() const { return is_int_; }
    int64_t AsInt() const { return i_; }
    const char* AsSym() const { return s_; }

    static constexpr int INVALID_INT_DIM = -2;

   private:
    union {
      int64_t i_;
      const char* s_;
    };
    bool is_int_;
  };

  using Shape = std::vector<SymbolicInteger>;

  ShapeInferContext(const OrtApi* ort_api, OrtShapeInferContext* ctx);

  const Shape& GetInputShape(size_t indice) const { return input_shapes_.at(indice); }

  size_t GetInputCount() const { return input_shapes_.size(); }

  Status SetOutputShape(size_t indice, const Shape& shape, ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);

  int64_t GetAttrInt(const char* attr_name);

  using Ints = std::vector<int64_t>;
  Ints GetAttrInts(const char* attr_name);

  float GetAttrFloat(const char* attr_name);

  using Floats = std::vector<float>;
  Floats GetAttrFloats(const char* attr_name);

  std::string GetAttrString(const char* attr_name);

  using Strings = std::vector<std::string>;
  Strings GetAttrStrings(const char* attr_name);

 private:
  const OrtOpAttr* GetAttrHdl(const char* attr_name) const;
  const OrtApi* ort_api_;
  OrtShapeInferContext* ctx_;
  std::vector<Shape> input_shapes_;
};

using ShapeInferFn = Ort::Status (*)(Ort::ShapeInferContext&);

#define MAX_CUSTOM_OP_END_VER (1UL << 31) - 1

template <typename TOp, typename TKernel, bool WithStatus = false>
struct CustomOpBase : OrtCustomOp {
  CustomOpBase() {
    OrtCustomOp::version = ORT_API_VERSION;
    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::GetInputMemoryType = [](const OrtCustomOp* this_, size_t index) { return static_cast<const TOp*>(this_)->GetInputMemoryType(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); };

#if defined(_MSC_VER) && !defined(__clang__)
#pragma warning(push)
#pragma warning(disable : 26409)
#endif
    OrtCustomOp::KernelDestroy = [](void* op_kernel) { delete static_cast<TKernel*>(op_kernel); };
#if defined(_MSC_VER) && !defined(__clang__)
#pragma warning(pop)
#endif
    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); };

    OrtCustomOp::GetVariadicInputMinArity = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetVariadicInputMinArity(); };
    OrtCustomOp::GetVariadicInputHomogeneity = [](const OrtCustomOp* this_) { return static_cast<int>(static_cast<const TOp*>(this_)->GetVariadicInputHomogeneity()); };
    OrtCustomOp::GetVariadicOutputMinArity = [](const OrtCustomOp* this_) { return static_cast<const TOp*>(this_)->GetVariadicOutputMinArity(); };
    OrtCustomOp::GetVariadicOutputHomogeneity = [](const OrtCustomOp* this_) { return static_cast<int>(static_cast<const TOp*>(this_)->GetVariadicOutputHomogeneity()); };
#ifdef __cpp_if_constexpr
    if constexpr (WithStatus) {
#else
    if (WithStatus) {
#endif
      OrtCustomOp::CreateKernelV2 = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info, void** op_kernel) -> OrtStatusPtr {
        return static_cast<const TOp*>(this_)->CreateKernelV2(*api, info, op_kernel);
      };
      OrtCustomOp::KernelComputeV2 = [](void* op_kernel, OrtKernelContext* context) -> OrtStatusPtr {
        return static_cast<TKernel*>(op_kernel)->ComputeV2(context);
      };
    } else {
      OrtCustomOp::CreateKernelV2 = nullptr;
      OrtCustomOp::KernelComputeV2 = nullptr;

      OrtCustomOp::CreateKernel = [](const OrtCustomOp* this_, const OrtApi* api, const OrtKernelInfo* info) { return static_cast<const TOp*>(this_)->CreateKernel(*api, info); };
      OrtCustomOp::KernelCompute = [](void* op_kernel, OrtKernelContext* context) {
        static_cast<TKernel*>(op_kernel)->Compute(context);
      };
    }

    SetShapeInferFn<TOp>(0);

    OrtCustomOp::GetStartVersion = [](const OrtCustomOp* this_) {
      return static_cast<const TOp*>(this_)->start_ver_;
    };

    OrtCustomOp::GetEndVersion = [](const OrtCustomOp* this_) {
      return static_cast<const TOp*>(this_)->end_ver_;
    };

    OrtCustomOp::GetMayInplace = nullptr;
    OrtCustomOp::ReleaseMayInplace = nullptr;
    OrtCustomOp::GetAliasMap = nullptr;
    OrtCustomOp::ReleaseAliasMap = nullptr;
  }

  // Default implementation of GetExecutionProviderType that returns nullptr to default to the CPU provider
  const char* GetExecutionProviderType() const { return nullptr; }

  // Default implementations of GetInputCharacteristic() and GetOutputCharacteristic() below
  // (inputs and outputs are required by default)
  OrtCustomOpInputOutputCharacteristic GetInputCharacteristic(size_t /*index*/) const {
    return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED;
  }

  OrtCustomOpInputOutputCharacteristic GetOutputCharacteristic(size_t /*index*/) const {
    return OrtCustomOpInputOutputCharacteristic::INPUT_OUTPUT_REQUIRED;
  }

  // Default implemention of GetInputMemoryType() that returns OrtMemTypeDefault
  OrtMemType GetInputMemoryType(size_t /*index*/) const {
    return OrtMemTypeDefault;
  }

  // Default implementation of GetVariadicInputMinArity() returns 1 to specify that a variadic input
  // should expect at least 1 argument.
  int GetVariadicInputMinArity() const {
    return 1;
  }

  // Default implementation of GetVariadicInputHomegeneity() returns true to specify that all arguments
  // to a variadic input should be of the same type.
  bool GetVariadicInputHomogeneity() const {
    return true;
  }

  // Default implementation of GetVariadicOutputMinArity() returns 1 to specify that a variadic output
  // should produce at least 1 output value.
  int GetVariadicOutputMinArity() const {
    return 1;
  }

  // Default implementation of GetVariadicOutputHomegeneity() returns true to specify that all output values
  // produced by a variadic output should be of the same type.
  bool GetVariadicOutputHomogeneity() const {
    return true;
  }

  // Declare list of session config entries used by this Custom Op.
  // Implement this function in order to get configs from CustomOpBase::GetSessionConfigs().
  // This default implementation returns an empty vector of config entries.
  std::vector<std::string> GetSessionConfigKeys() const {
    return std::vector<std::string>{};
  }

  template <typename C>
  decltype(&C::InferOutputShape) SetShapeInferFn(decltype(&C::InferOutputShape)) {
    OrtCustomOp::InferOutputShapeFn = [](const OrtCustomOp*, OrtShapeInferContext* ort_ctx) -> OrtStatusPtr {
      ShapeInferContext ctx(&GetApi(), ort_ctx);
      return C::InferOutputShape(ctx);
    };
    return {};
  }

  template <typename C>
  void SetShapeInferFn(...) {
    OrtCustomOp::InferOutputShapeFn = {};
  }

 protected:
  // Helper function that returns a map of session config entries specified by CustomOpBase::GetSessionConfigKeys.
  void GetSessionConfigs(std::unordered_map<std::string, std::string>& out, ConstSessionOptions options) const;

  int start_ver_ = 1;
  int end_ver_ = MAX_CUSTOM_OP_END_VER;
};

}  // namespace Ort

#include "onnxruntime_cxx_inline.h"