#pragma once

#include <ATen/SequenceNumber.h>
#include <ATen/core/boxing/KernelFunction.h>
#include <ATen/core/boxing/impl/boxing.h>
#include <ATen/core/dispatch/CppSignature.h>
#include <ATen/core/dispatch/OperatorEntry.h>
#include <ATen/core/dispatch/RegistrationHandleRAII.h>
#include <ATen/record_function.h>
#include <c10/core/SafePyObject.h>
#include <c10/util/Exception.h>
#include <c10/util/LeftRight.h>
#include <condition_variable>
#include <list>
#include <mutex>
#include <type_traits>

#include <ATen/core/enum_tag.h>
#include <ATen/core/grad_mode.h>

#ifndef NDEBUG
#include <iostream>
#endif

namespace c10 {

TORCH_API bool show_dispatch_trace();
TORCH_API void dispatch_trace_nesting_incr();
TORCH_API void dispatch_trace_nesting_decr();
TORCH_API int64_t dispatch_trace_nesting_value();

struct DispatchTraceNestingGuard {
  DispatchTraceNestingGuard() {
    dispatch_trace_nesting_incr();
  }
  ~DispatchTraceNestingGuard() {
    dispatch_trace_nesting_decr();
  }
};

class TORCH_API OperatorHandle;
template <class FuncType>
class TypedOperatorHandle;

/**
 * Implement this interface and register your instance with the dispatcher
 * to get notified when operators are registered or deregistered with
 * the dispatcher.
 *
 * NB: registration events only occur when a 'def' occurs; we don't trigger
 * on 'impl' or 'fallback' calls.
 */
class TORCH_API OpRegistrationListener {
 public:
  virtual ~OpRegistrationListener();

  virtual void onOperatorRegistered(const OperatorHandle& op) = 0;
  virtual void onOperatorDeregistered(const OperatorHandle& op) = 0;
};

namespace detail {
class RegistrationListenerList;
}
class SchemaRegistrationHandleRAII;

/**
 * Top-level dispatch interface for dispatching via the dynamic dispatcher.
 * Most end users shouldn't use this directly; if you're trying to register
 * ops look in op_registration
 */
class TORCH_API Dispatcher final {
 private:
  // For direct access to backend fallback information
  friend class impl::OperatorEntry;

  struct OperatorDef final {
    explicit OperatorDef(OperatorName&& op_name) : op(std::move(op_name)) {}

    impl::OperatorEntry op;

    // These refer to the number of outstanding RegistrationHandleRAII
    // for this operator.  def_count reflects only def() registrations
    // (in the new world, this should only ever be 1, but old style
    // registrations may register the schema multiple times, which
    // will increase this count).  def_and_impl_count reflects the number
    // of combined def() and impl() registrations.  When the last def() gets
    // unregistered, we must immediately call the Deregistered listeners, but we
    // must not actually delete the handle as there are other outstanding RAII
    // destructors which will try to destruct and they had better still have a
    // working operator handle in this case
    size_t def_count = 0;
    size_t def_and_impl_count = 0;
  };
  friend class OperatorHandle;
  template <class>
  friend class TypedOperatorHandle;

  struct Guard final {
    Guard() : alive(true) {}
    std::atomic<bool> alive;
    std::mutex mutex;
  };

 public:
  ~Dispatcher();

  // Implementation note: this class abstracts over the fact that we have
  // per-operator dispatch tables.  This could be easily adjusted to have a
  // single global hash table.
  static Dispatcher& realSingleton();

  C10_ALWAYS_INLINE static Dispatcher& singleton() {
#if !defined C10_MOBILE
    // Implemented inline so that steady-state code needn't incur
    // function-call overhead. We can't just inline `realSingleton`
    // because the function-local static would get duplicated across
    // all DSOs that include & use this header, leading to multiple
    // singleton instances.
    static Dispatcher& s = realSingleton();
    return s;
#else
    // For C10_MOBILE, we should never inline a static function that
    // has a static member, since the generated code calls
    // __cxa_guard_acquire and __cxa_guard_release which help
    // implement exactly once semantics for the initialization of the
    // static Dispatcher& s above (for the non-mobile case). That
    // additional code when duplicated across all operator stubs
    // for every backend results in a lot of additional code
    // being generated by the compiler.
    return realSingleton();
#endif
  }

  // ------------------------------------------------------------------------
  //
  // Accessing operators by schema
  //
  // ------------------------------------------------------------------------

  /**
   * Looks for an operator schema with the given name and overload name
   * and returns it if it is registered WITH A SCHEMA.
   * Returns nullopt otherwise.
   */
  std::optional<OperatorHandle> findSchema(const OperatorName& operator_name);

  /**
   * Variant of findSchema that results in less code generated at the call site.
   * It (1) takes const char* pointer rather than OperatorName (so we skip
   * generating std::string constructor calls at the call site), and (2)
   * it raises an exception if the operator is not found (so we skip
   * generating exception raising code at the call site)
   *
   * Irritatingly, we still have to generate the handful of instructions
   * for dealing with an exception being thrown during static initialization
   * (e.g. __cxa_guard_abort).  If we could annotate this method noexcept we
   * could avoid this code too, but as the name of the function suggests,
   * it does throw exceptions.
   */
  OperatorHandle findSchemaOrThrow(const char* name, const char* overload_name);

  // Like findSchema, but also returns OperatorHandle even if there is no schema
  std::optional<OperatorHandle> findOp(const OperatorName& operator_name);

  // Returns a list of all operator names present in the operatorLookupTable_
  const std::vector<OperatorName> getAllOpNames();

  // Returns a list of all operator names present in the operatorLookupTable_
  // for a given dispatch key
  const std::vector<OperatorName> getAllOpNamesForDispatchKey(DispatchKey k);

  // ------------------------------------------------------------------------
  //
  // Invoking operators
  //
  // ------------------------------------------------------------------------

  template <class Return, class... Args>
  Return call(const TypedOperatorHandle<Return(Args...)>& op, Args... args)
      const;

  template <class Return, class... Args>
  static Return callWithDispatchKeySlowPath(
      const TypedOperatorHandle<Return(Args...)>& op,
      at::StepCallbacks& stepCallbacks,
      DispatchKeySet dispatchKeySet,
      const KernelFunction& kernel,
      Args... args);

  // Like call, but intended for use in a redispatch in kernels that have
  // explicitly performed the DispatchKey update calculatulation. This will take
  // the DispatchKeySet completely as is and dispatch to the kernel of the
  // corresponding highest priority key in the set. Note that this version of
  // redispatch treats the inputted DispatchKeySet *as is*, and does NOT mask
  // out the highest priority key. See Note [Plumbing Keys Through The
  // Dispatcher]
  template <class Return, class... Args>
  Return redispatch(
      const TypedOperatorHandle<Return(Args...)>& op,
      DispatchKeySet currentDispatchKeySet,
      Args... args) const;

  // Invoke an operator via the boxed calling convention using an IValue stack
  void callBoxed(const OperatorHandle& op, Stack* stack) const;
  void callBoxedForDispatchKey(
      const OperatorHandle& op,
      DispatchKey dk,
      Stack* stack) const;

  // TODO: This will only be useful if we write a backend fallback that plumbs
  // dispatch keys (currently there are none) See Note [Plumbing Keys Through
  // The Dispatcher]
  void redispatchBoxed(
      const OperatorHandle& op,
      DispatchKeySet dispatchKeySet,
      Stack* stack) const;

  bool hasBackendFallbackForDispatchKey(DispatchKey dk) {
    auto dispatch_ix = getDispatchTableIndexForDispatchKey(dk);
    if (dispatch_ix < 0)
      return false;
    return backendFallbackKernels_[dispatch_ix].kernel.isValid();
  }

  // Used by torchdeploy/multipy for multiple interpreters racing.
  void waitForDef(const FunctionSchema& schema);
  void waitForImpl(
      const OperatorName& op_name,
      std::optional<DispatchKey> dispatch_key);

  // ------------------------------------------------------------------------
  //
  // Performing registrations (NON user public; use op_registration)
  //
  // ------------------------------------------------------------------------

  /**
   * Register a new operator schema.
   *
   * If a schema with the same operator name and overload name already exists,
   * this function will check that both schemas are exactly identical.
   */
  RegistrationHandleRAII registerDef(
      FunctionSchema schema,
      std::string debug,
      std::vector<at::Tag> tags = {});

  /**
   * Register a kernel to the dispatch table for an operator.
   * If dispatch_key is nullopt, then this registers a fallback kernel.
   *
   * @return A RAII object that manages the lifetime of the registration.
   *         Once that object is destructed, the kernel will be deregistered.
   */
  // NB: steals the inferred function schema, as we may need to hold on to
  // it for a bit until the real schema turns up
  RegistrationHandleRAII registerImpl(
      OperatorName op_name,
      std::optional<DispatchKey> dispatch_key,
      KernelFunction kernel,
      std::optional<impl::CppSignature> cpp_signature,
      std::unique_ptr<FunctionSchema> inferred_function_schema,
      std::string debug);

  /**
   * Given an operator, tells the Dispatcher that we have implemented a fake
   * impl for this op in the given Python module. Call this a "pystub".
   */
  RegistrationHandleRAII registerPythonModule(
      const OperatorName& op_name,
      const char* pymodule,
      const char* context);

  /**
   * Given an operator, throws if we have a pystub.
   */
  void throwIfHasPythonModule(OperatorName op_name);

  std::optional<std::pair<const char*, const char*>> getPyStub(
      OperatorName op_name);

  /**
   * Register a new operator by name.
   */
  RegistrationHandleRAII registerName(OperatorName op_name);

  /**
   * Register a fallback kernel for a backend.
   * If an operator is called but there is no concrete kernel for the dispatch
   * key of the given operator arguments, it will check if there is such a
   * fallback kernel for the given dispatch key and, if yes, call that one.
   */
  RegistrationHandleRAII registerFallback(
      DispatchKey dispatch_key,
      KernelFunction kernel,
      std::string debug);

  /**
   * Use to register whenever we had a TORCH_LIBRARY declaration in the frontend
   * API.  These invocations are only permitted once per program, so we raise
   * an error if this is called again for the same namespace.
   */
  RegistrationHandleRAII registerLibrary(std::string ns, std::string debug);

  // ------------------------------------------------------------------------
  //
  // Listeners on registrations
  //
  // ------------------------------------------------------------------------

  /**
   * Add a listener that gets called whenever a new op is registered or an
   * existing op is deregistered. Immediately after registering, this listener
   * gets called for all previously registered ops, so it can be used to keep
   * track of ops registered with this dispatcher.
   */
  RegistrationHandleRAII addRegistrationListener(
      std::unique_ptr<OpRegistrationListener> listener);

  void checkInvariants() const;

  //
  // ------------------------------------------------------------------------
  //
  // Assertions
  //
  // ------------------------------------------------------------------------

  /**
   * For testing purposes.
   * Returns a list of all operators that were created through calls to
   * registerImpl(), without any corresponding calls to registerDef(). After
   * static initialization is done this is almost certainly a bug, as the
   * created OperatorHandle won't have any schema associated with it and users
   * calling the op through the dispatcher won't be able to access it
   *
   * Note that we cannot enforce this invariant "as we go" during static
   * initialization, due to undefined static initialization order- we have no
   * guarantees over the order in which .def() and .impl() calls are registered
   * in the dispatcher at static initialization time. So this function should
   * only be called after static initialization.
   */
  std::vector<OperatorHandle> findDanglingImpls() const;

  /**
   * Useful for inspecting global Dispatcher registration state.
   * Returns the names of all operators with a kernel registered for the
   * specified DispatchKey. If no DispatchKey is specified, it returns all
   * registered operators.
   */
  std::vector<OperatorName> getRegistrationsForDispatchKey(
      std::optional<DispatchKey> k) const;

 private:
  Dispatcher();

  static int64_t sequenceNumberForRunningRecordFunction(
      DispatchKey dispatchKey,
      DispatchKeySet dispatchKeySet);
  static void runRecordFunction(
      at::RecordFunction& guard,
      at::RecordFunction::schema_ref_t schema_ref,
      DispatchKey dispatchKey,
      DispatchKeySet dispatchKeySet);
  static void runRecordFunction(
      at::RecordFunction& guard,
      at::RecordFunction::schema_ref_t schema_ref,
      DispatchKey dispatchKey,
      DispatchKeySet dispatchKeySet,
      c10::ArrayRef<const c10::IValue> args);

#ifdef FBCODE_CAFFE2
  static bool profilingOperatorEvents();
  static void fireOpStartUSDT(
      at::RecordFunction::schema_ref_t schema_ref,
      std::vector<void*>& argsAddresses,
      std::vector<const char*>& argsTypes);
  static void fireOpEndUSDT(at::RecordFunction::schema_ref_t schema_ref);
#endif // FBCODE_CAFFE2

  OperatorHandle findOrRegisterSchema_(FunctionSchema&& schema);
  OperatorHandle findOrRegisterName_(const OperatorName& op_name);

  void deregisterDef_(const OperatorHandle& op, const OperatorName& op_name);
  void deregisterImpl_(
      const OperatorHandle& op,
      const OperatorName& op_name,
      std::optional<DispatchKey> dispatch_key,
      impl::OperatorEntry::AnnotatedKernelContainerIterator kernel_handle);
  void deregisterName_(const OperatorHandle& op, const OperatorName& op_name);
  void deregisterFallback_(DispatchKey dispatchKey);
  void deregisterLibrary_(const std::string& ns);
  void cleanup(const OperatorHandle& op, const OperatorName& op_name);
  void checkSchemaCompatibility(
      const OperatorHandle& op,
      const FunctionSchema& schema,
      const std::string& debug);

  std::list<OperatorDef> operators_;
#if !defined(C10_MOBILE)
  LeftRight<ska::flat_hash_map<OperatorName, OperatorHandle>>
      operatorLookupTable_;
#else
  RWSafeLeftRightWrapper<ska::flat_hash_map<OperatorName, OperatorHandle>>
      operatorLookupTable_;
#endif
  // Map from namespace to debug string (saying, e.g., where the library was
  // defined)
  ska::flat_hash_map<std::string, std::string> libraries_;

  std::array<impl::AnnotatedKernel, num_runtime_entries>
      backendFallbackKernels_;

  std::unique_ptr<detail::RegistrationListenerList> listeners_;

  // This condition variable gets notified whenever we add a new def/impl to the
  // dispatch table.  This is primarily used by multipy/torchdeploy, when
  // we have multiple interpreters trying to register to the dispatch table.
  // In this situation, whenever the non-primary interpreter would have tried
  // to register to the dispatch table, instead it will check to see if the
  // expected registration has already been made, and if it hasn't, wait on
  // this condition variable to see if it was just racing with the primary
  // interpreter.
  //
  // We expect it to be rare for there to be any waiters on this condition
  // variable.  This is mostly just to help give better diagnostics if
  // something goes horribly wrong
  std::condition_variable cond_var_;

  // Protect concurrent access to the dispatcher.  We store this in a
  // `shared_ptr` as we return callbacks that call back into dispatcher methods,
  // and we need to be able to handle and guard against the event when the
  // `Dispatcher` has been destroyed before the callbacks fire.
  std::shared_ptr<Guard> guard_;
};

/**
 * This is a handle to an operator schema registered with the dispatcher.
 * This handle can be used to register kernels with the dispatcher or
 * to lookup a kernel for a certain set of arguments.
 */
class TORCH_API OperatorHandle {
  template <typename T>
  friend struct std::hash;

 public:
  OperatorHandle(OperatorHandle&&) noexcept = default;
  OperatorHandle& operator=(OperatorHandle&&) noexcept = default;
  OperatorHandle(const OperatorHandle&) = default;
  OperatorHandle& operator=(const OperatorHandle&) = default;
  // NOLINTNEXTLINE(performance-trivially-destructible)
  ~OperatorHandle();

  const OperatorName& operator_name() const {
    return operatorDef_->op.operator_name();
  }

  bool hasSchema() const {
    return operatorDef_->op.hasSchema();
  }

  const FunctionSchema& schema() const {
    return operatorDef_->op.schema();
  }

  const std::string& debug() const {
    return operatorDef_->op.debug();
  }

  std::string dumpState() const {
    return operatorDef_->op.dumpState();
  }

  bool hasKernelForDispatchKey(DispatchKey k) const {
    return operatorDef_->op.hasKernelForDispatchKey(k);
  }

  bool isKernelFallthroughKernel(DispatchKey k) const {
    return operatorDef_->op.kernelForDispatchKey(k).isFallthrough();
  }

  bool hasKernelForAnyDispatchKey(DispatchKeySet k) const {
    return operatorDef_->op.hasKernelForAnyDispatchKey(k);
  }

  bool hasComputedKernelForDispatchKey(DispatchKey k) const {
    return operatorDef_->op.hasComputedKernelForDispatchKey(k);
  }

  SafeKernelFunction getComputedKernelForDispatchKey(DispatchKey k) const {
    return operatorDef_->op.getComputedKernelForDispatchKey(k);
  }

  std::string dumpComputedTable() const {
    return operatorDef_->op.dumpComputedTable();
  }

  void checkInvariants() const {
    operatorDef_->op.checkInvariants();
  }

  c10::ArrayRef<at::Tag> getTags() const {
    return operatorDef_->op.getTags();
  }

  void setReportErrorCallback_(std::unique_ptr<c10::SafePyObject> callback) {
    operatorDef_->op.setReportErrorCallback_(std::move(callback));
  }

  bool hasTag(const at::Tag& tag) const {
    for (const auto& tag_ : getTags()) {
      if (tag == tag_) {
        return true;
      }
    }
    return false;
  }

  template <class FuncType>
  TypedOperatorHandle<FuncType> typed() const {
    // NB: This assert is not 100% sound: you can retrieve a typed() operator
    // handle prior to ANY C++ signature being registered on the operator
    // and the check will say everything is OK (at which point you can then
    // smuggle in a kernel that is typed incorrectly).  For everything
    // in core library this won't happen, because all the static registrations
    // will be done by the time a typed() handle is acquired.
#if !defined C10_MOBILE
    operatorDef_->op.assertSignatureIsCorrect<FuncType>();
    if (fn_has_symint<FuncType>::value) {
      operatorDef_->op.assertSignatureIsCorrect<
          typename fn_remove_symint<FuncType>::type>();
    }
#endif
    return TypedOperatorHandle<FuncType>(operatorIterator_);
  }

  void callBoxed(Stack* stack) const {
    c10::Dispatcher::singleton().callBoxed(*this, stack);
  }

  void callBoxed(Stack& stack) const {
    callBoxed(&stack);
  }

  void callBoxedForDispatchKey(DispatchKey dk, Stack& stack) const {
    c10::Dispatcher::singleton().callBoxedForDispatchKey(*this, dk, &stack);
  }

  void redispatchBoxed(DispatchKeySet ks, Stack* stack) const {
    c10::Dispatcher::singleton().redispatchBoxed(*this, ks, stack);
  }

  template <typename F>
  PyObject* getPythonOp(
      c10::impl::PyInterpreter* self_interpreter,
      F slow_accessor) const {
    return operatorDef_->op.getPythonOp(self_interpreter, slow_accessor);
  }

  bool operator==(const OperatorHandle& other) const {
    return operatorDef_ == other.operatorDef_;
  }

  bool operator!=(const OperatorHandle& other) const {
    return operatorDef_ != other.operatorDef_;
  }

 private:
  explicit OperatorHandle(
      std::list<Dispatcher::OperatorDef>::iterator operatorIterator)
      : operatorDef_(&*operatorIterator), operatorIterator_(operatorIterator) {}
  friend class Dispatcher;
  template <class>
  friend class TypedOperatorHandle;

  // Storing a direct pointer to the OperatorDef even though we
  // already have the iterator saves an instruction in the critical
  // dispatch path. The iterator is effectively a
  // pointer-to-std::list-node, and (at least in libstdc++'s
  // implementation) the element is at an offset 16 bytes from that,
  // because the prev/next pointers come first in the list node
  // struct. So, an add instruction would be necessary to convert from the
  // iterator to an OperatorDef*.
  Dispatcher::OperatorDef* operatorDef_;

  // We need to store this iterator in order to make
  // Dispatcher::cleanup() fast -- it runs a lot on program
  // termination (and presuambly library unloading).
  std::list<Dispatcher::OperatorDef>::iterator operatorIterator_;
};

/**
 * This is a handle to an operator schema registered with the dispatcher.
 * It holds the same information as an OperatorHandle, but it is templated
 * on the operator arguments and allows calling the operator in an
 * unboxed way.
 */
template <class FuncType>
class TypedOperatorHandle final {
  static_assert(
      guts::false_t<FuncType>(),
      "FuncType in OperatorHandle::typed<FuncType> was not a valid function type");
};
template <class Return, class... Args>
class TypedOperatorHandle<Return(Args...)> final : public OperatorHandle {
 public:
  TypedOperatorHandle(TypedOperatorHandle&&) noexcept = default;
  TypedOperatorHandle& operator=(TypedOperatorHandle&&) noexcept = default;
  TypedOperatorHandle(const TypedOperatorHandle&) = default;
  TypedOperatorHandle& operator=(const TypedOperatorHandle&) = default;

  // See [Note: Argument forwarding in the dispatcher] for why Args doesn't use
  // &&
  C10_ALWAYS_INLINE Return call(Args... args) const {
    return c10::Dispatcher::singleton().call<Return, Args...>(
        *this, std::forward<Args>(args)...);
  }

  // See [Note: Argument forwarding in the dispatcher] for why Args doesn't use
  // &&
  C10_ALWAYS_INLINE Return
  redispatch(DispatchKeySet currentDispatchKeySet, Args... args) const {
    return c10::Dispatcher::singleton().redispatch<Return, Args...>(
        *this, currentDispatchKeySet, std::forward<Args>(args)...);
  }

 private:
  explicit TypedOperatorHandle(
      std::list<Dispatcher::OperatorDef>::iterator operatorIterator)
      : OperatorHandle(operatorIterator) {}
  friend class OperatorHandle;
};

namespace detail {
template <class... Args>
inline void unused_arg_(const Args&... /*unused*/) {}

// CaptureKernelCall is intended to capture return values from Dispatcher
// unboxed kernel calls. A record function may request to get outputs from the
// kernel calls. For boxed kernels, it's straightforward, the returned values
// are in the stack object. The stack can be passed to record functions. For
// unboxed kernels, we need to handle different kinds of return values, cache
// them temporarily, then release the values for the actual function call
// return.
template <typename ReturnType>
struct CaptureKernelCall {
  template <typename F, typename... Args>
  CaptureKernelCall(
      const F& kernel,
      const TypedOperatorHandle<ReturnType(Args...)>& op,
      const DispatchKeySet& dispatchKeySet,
      Args&&... args)
      // Calls the kernel and capture the result in output_.
      : output_{kernel.template call<ReturnType, Args...>(
            op,
            dispatchKeySet,
            std::forward<Args>(args)...)} {}
  // Wraps the return values in a Stack.
  Stack getOutputs() {
    Stack stack;
    impl::push_outputs<ReturnType, false>::copy(output_, &stack);
    return stack;
  }
  // Since we are returning the output_, we don't expect the output_ to be used
  // afterward. Copy elision and RVO do not apply to class data members. Using
  // move semantic to avoid copies when possible.
  ReturnType release() && {
    return std::move(output_);
  }

 private:
  ReturnType output_;
};

// Handle the lvalue reference differently since it should not be moved.
template <>
inline at::Tensor& CaptureKernelCall<at::Tensor&>::release() && {
  return output_;
}

// Handle case where the kernel returns void.
template <>
struct CaptureKernelCall<void> {
  template <typename F, typename... Args>
  CaptureKernelCall(
      const F& kernel,
      const TypedOperatorHandle<void(Args...)>& op,
      const DispatchKeySet& dispatchKeySet,
      Args&&... args) {
    // Calling the kernel and no need to capture void.
    kernel.template call<void, Args...>(
        op, dispatchKeySet, std::forward<Args>(args)...);
  }
  Stack getOutputs() {
    return Stack();
  }
  void release() && {}
};

TORCH_API void _print_dispatch_trace(
    const std::string& label,
    const std::string& op_name,
    const DispatchKeySet& dispatchKeySet);

} // namespace detail

// See [Note: Argument forwarding in the dispatcher] for why Args doesn't use &&
template <class Return, class... Args>
inline Return Dispatcher::callWithDispatchKeySlowPath(
    const TypedOperatorHandle<Return(Args...)>& op,
    at::StepCallbacks& stepCallbacks,
    DispatchKeySet dispatchKeySet,
    const KernelFunction& kernel,
    Args... args) {
  // If callbacks need inputs, we box the arguments and pass them to the guard.
  // Note: For perf reasons we wouldn't want to prematurely box the arguments.
  at::RecordFunction guard(std::move(stepCallbacks));
  TORCH_INTERNAL_ASSERT_DEBUG_ONLY(op.operatorDef_->op.isObserved());
  auto dispatchKey = dispatchKeySet.highestPriorityTypeId();
  auto& schema = op.schema();
  auto schema_ref = std::reference_wrapper<const FunctionSchema>(schema);
  constexpr auto num_boxed_args = impl::boxed_size<Args...>();
  if constexpr (num_boxed_args != 0) {
    if (guard.needsInputs()) {
      // If we used std::array<IValue, num_boxed_args> here, we would
      // have to spend time default constructing the IValues in
      // boxedArgs. aligned_storage has no such requirement.
      // NOLINTNEXTLINE(*array*)
      alignas(IValue) std::byte boxedArgs[num_boxed_args * sizeof(IValue)];
      // For debugging only; could be removed (but the compiler will do
      // that for us and it's nice to have the extra assurance of
      // correctness from our debug builds).
      IValue* boxedArgsPtr = reinterpret_cast<IValue*>(boxedArgs);
      impl::boxArgsToStack(boxedArgsPtr, args...);
      TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
          reinterpret_cast<std::byte*>(boxedArgsPtr) ==
          boxedArgs + num_boxed_args * sizeof(IValue));
      // I don't *think* we need std::launder here, because IValue has
      // no subclasses and no const or reference fields.
      runRecordFunction(
          guard,
          schema_ref,
          dispatchKey,
          dispatchKeySet,
          c10::ArrayRef<const c10::IValue>(
              reinterpret_cast<IValue*>(boxedArgs), num_boxed_args));
      boxedArgsPtr = reinterpret_cast<IValue*>(boxedArgs);
      for (size_t ii = 0; ii < num_boxed_args; ++ii) {
        (boxedArgsPtr + ii)->~IValue();
      }
    } else {
      runRecordFunction(guard, schema_ref, dispatchKey, dispatchKeySet);
    }
  } else {
    runRecordFunction(guard, schema_ref, dispatchKey, dispatchKeySet);
  }

  if (C10_UNLIKELY(guard.needsOutputs())) {
    // Calls the kernel and capture the output temporarily to pass to
    // RecordFunction.
    detail::CaptureKernelCall<Return> captureKernelCall(
        kernel, op, dispatchKeySet, std::forward<Args>(args)...);
    guard.setOutputs(captureKernelCall.getOutputs());
    // Releases the captured output to return to caller.
    return std::move(captureKernelCall).release();
  }

  // keeping the guard alive while executing the kernel
  return kernel.template call<Return, Args...>(
      op, dispatchKeySet, std::forward<Args>(args)...);
}

// See [Note: Argument forwarding in the dispatcher] for why Args doesn't use &&
template <class Return, class... Args>
C10_ALWAYS_INLINE_UNLESS_MOBILE Return Dispatcher::call(
    const TypedOperatorHandle<Return(Args...)>& op,
    Args... args) const {
  auto dispatchKeySet =
      op.operatorDef_->op.dispatchKeyExtractor()
          .template getDispatchKeySetUnboxed<Args...>(args...);
#if defined(HAS_TORCH_SHOW_DISPATCH_TRACE) || !defined(NDEBUG)
  DispatchTraceNestingGuard debug_guard;
  if (show_dispatch_trace()) {
    detail::_print_dispatch_trace(
        "[call]", toString(op.operator_name()), dispatchKeySet);
  }
#endif
  const KernelFunction& kernel = op.operatorDef_->op.lookup(dispatchKeySet);
#ifndef PYTORCH_DISABLE_PER_OP_PROFILING
  auto step_callbacks =
      at::getStepCallbacksUnlessEmpty(at::RecordScope::FUNCTION);
  if (C10_UNLIKELY(
          step_callbacks.has_value() && op.operatorDef_->op.isObserved())) {
    return callWithDispatchKeySlowPath<Return, Args...>(
        op,
        *step_callbacks,
        dispatchKeySet,
        kernel,
        std::forward<Args>(args)...);
  }
#endif // PYTORCH_DISABLE_PER_OP_PROFILING

#ifdef FBCODE_CAFFE2
  if (profilingOperatorEvents()) {
    std::vector<void*> argsAddresses = {(void*)(&args)...};
    std::vector<const char*> argsTypes = {(typeid(args).name())...};
    struct FireOpRAII {
      FireOpRAII(
          at::RecordFunction::schema_ref_t schema_ref,
          std::vector<void*>& argsAddresses,
          std::vector<const char*>& argsTypes)
          : schema_ref_(schema_ref) {
        fireOpStartUSDT(schema_ref, argsAddresses, argsTypes);
      }
      ~FireOpRAII() {
        fireOpEndUSDT(schema_ref_);
      }
      at::RecordFunction::schema_ref_t schema_ref_;
    } event(op.schema(), argsAddresses, argsTypes);
    return kernel.template call<Return, Args...>(
        op, dispatchKeySet, std::forward<Args>(args)...);
  } else {
    return kernel.template call<Return, Args...>(
        op, dispatchKeySet, std::forward<Args>(args)...);
  }
#else
  return kernel.template call<Return, Args...>(
      op, dispatchKeySet, std::forward<Args>(args)...);
#endif // FBCODE_CAFFE2
}

// See [Note: Argument forwarding in the dispatcher] for why Args doesn't use &&
template <class Return, class... Args>
inline Return Dispatcher::redispatch(
    const TypedOperatorHandle<Return(Args...)>& op,
    DispatchKeySet currentDispatchKeySet,
    Args... args) const {
  // do not use RecordFunction on redispatch
#if defined(HAS_TORCH_SHOW_DISPATCH_TRACE) || !defined(NDEBUG)
  DispatchTraceNestingGuard debug_guard;
  if (show_dispatch_trace()) {
    detail::_print_dispatch_trace(
        "[redispatch]", toString(op.operator_name()), currentDispatchKeySet);
  }
#endif
  const KernelFunction& kernel =
      op.operatorDef_->op.lookup(currentDispatchKeySet);
  return kernel.template call<Return, Args...>(
      op, currentDispatchKeySet, std::forward<Args>(args)...);
}

inline void Dispatcher::callBoxed(const OperatorHandle& op, Stack* stack)
    const {
  // note: this doesn't need the mutex because write operations on the list keep
  // iterators intact.
  const auto& entry = op.operatorDef_->op;
  auto dispatchKeySet =
      entry.dispatchKeyExtractor().getDispatchKeySetBoxed(stack);
#if defined(HAS_TORCH_SHOW_DISPATCH_TRACE) || !defined(NDEBUG)
  DispatchTraceNestingGuard debug_guard;
  if (show_dispatch_trace()) {
    detail::_print_dispatch_trace(
        "[callBoxed]", toString(op.operator_name()), dispatchKeySet);
  }
#endif
  const auto& kernel = entry.lookup(dispatchKeySet);
#ifndef PYTORCH_DISABLE_PER_OP_PROFILING
  auto step_callbacks =
      at::getStepCallbacksUnlessEmpty(at::RecordScope::FUNCTION);
  if (C10_UNLIKELY(step_callbacks.has_value() && entry.isObserved())) {
    at::RecordFunction guard(std::move(*step_callbacks));
    auto dispatchKey = dispatchKeySet.highestPriorityTypeId();
    auto& schema = op.schema();
    auto schema_ref = std::reference_wrapper<const FunctionSchema>(schema);
    guard.needsInputs()
        ? runRecordFunction(
              guard,
              schema_ref,
              dispatchKey,
              dispatchKeySet,
              c10::ArrayRef<const c10::IValue>(stack->data(), stack->size()))
        : runRecordFunction(guard, schema_ref, dispatchKey, dispatchKeySet);

    // keeping the guard alive while executing the kernel
    kernel.callBoxed(op, dispatchKeySet, stack);

    if (C10_UNLIKELY(guard.needsOutputs())) {
      guard.setOutputs(*stack);
    }
    return;
  }
#endif // PYTORCH_DISABLE_PER_OP_PROFILING
  kernel.callBoxed(op, dispatchKeySet, stack);
}

// NB: this doesn't count as a "true" dispatcher jump, so no instrumentation
inline void Dispatcher::callBoxedForDispatchKey(
    const OperatorHandle& op,
    DispatchKey dk,
    Stack* stack) const {
  // note: this doesn't need the mutex because write operations on the list keep
  // iterators intact.
  const auto& entry = op.operatorDef_->op;
  // We still compute this as we're obligated to pass it on to the internal
  // kernel, if it is a boxed fallback
  auto dispatchKeySet =
      entry.dispatchKeyExtractor().getDispatchKeySetBoxed(stack);
  const auto& kernel = ([&]() {
    if (op.hasKernelForDispatchKey(dk)) {
      return entry.kernelForDispatchKey(dk);
    } else {
      auto idx = getDispatchTableIndexForDispatchKey(dk);
      TORCH_INTERNAL_ASSERT(idx >= 0);
      return backendFallbackKernels_[idx].kernel;
    }
  })();
  kernel.callBoxed(op, dispatchKeySet, stack);
}

inline void Dispatcher::redispatchBoxed(
    const OperatorHandle& op,
    DispatchKeySet dispatchKeySet,
    Stack* stack) const {
  // note: this doesn't need the mutex because write operations on the list keep
  // iterators intact.
  const auto& entry = op.operatorDef_->op;
#if defined(HAS_TORCH_SHOW_DISPATCH_TRACE) || !defined(NDEBUG)
  DispatchTraceNestingGuard debug_guard;
  if (show_dispatch_trace()) {
    detail::_print_dispatch_trace(
        "[redispatchBoxed]", toString(op.operator_name()), dispatchKeySet);
  }
#endif
  const auto& kernel = entry.lookup(dispatchKeySet);
  kernel.callBoxed(op, dispatchKeySet, stack);
}

} // namespace c10

namespace std {

template <>
struct hash<c10::OperatorHandle> {
  size_t operator()(const c10::OperatorHandle& op) const noexcept {
    return std::hash<void*>{}(static_cast<void*>(op.operatorDef_));
  }
};

} // namespace std
