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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"

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