Debug/gen/chromeos/services/machine_learning/public/mojom/model.mojom.h

// chromeos/services/machine_learning/public/mojom/model.mojom.h is auto generated by mojom_bindings_generator.py, do not edit

// Copyright 2013 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.

#ifndef CHROMEOS_SERVICES_MACHINE_LEARNING_PUBLIC_MOJOM_MODEL_MOJOM_H_
#define CHROMEOS_SERVICES_MACHINE_LEARNING_PUBLIC_MOJOM_MODEL_MOJOM_H_

#include <stdint.h>

#include <limits>
#include <type_traits>
#include <utility>

#include "third_party/abseil-cpp/absl/types/optional.h"
#include "mojo/public/cpp/bindings/clone_traits.h"
#include "mojo/public/cpp/bindings/equals_traits.h"
#include "mojo/public/cpp/bindings/lib/serialization.h"
#include "mojo/public/cpp/bindings/struct_ptr.h"
#include "mojo/public/cpp/bindings/struct_traits.h"
#include "mojo/public/cpp/bindings/union_traits.h"

#include "third_party/perfetto/include/perfetto/tracing/traced_value_forward.h"

#include "chromeos/services/machine_learning/public/mojom/model.mojom-shared.h"
#include "chromeos/services/machine_learning/public/mojom/model.mojom-forward.h"
#include "chromeos/services/machine_learning/public/mojom/graph_executor.mojom-forward.h"
#include <string>
#include <vector>

#include "mojo/public/cpp/bindings/lib/control_message_handler.h"
#include "mojo/public/cpp/bindings/raw_ptr_impl_ref_traits.h"


#include "base/component_export.h"

#ifdef KYTHE_IS_RUNNING
#pragma kythe_inline_metadata "Metadata comment"
#endif


namespace chromeos {
namespace machine_learning {
namespace mojom {

class ModelProxy;

template <typename ImplRefTraits>
class ModelStub;

class ModelRequestValidator;
class ModelResponseValidator;


// @generated_from: chromeos.machine_learning.mojom.Model
class COMPONENT_EXPORT(MLSERVICE_MOJOM) Model
    : public ModelInterfaceBase {
 public:
  static const char Name_[];
  static std::pair<uint32_t, const void*> MessageToMethodInfo_(mojo::Message& message);
  static const char* MessageToMethodName_(mojo::Message& message);
  static constexpr uint32_t Version_ = 0;
  static constexpr bool PassesAssociatedKinds_ = false;
  static constexpr bool HasSyncMethods_ = false;
  static constexpr bool HasUninterruptableMethods_ = false;

  using Base_ = ModelInterfaceBase;
  using Proxy_ = ModelProxy;

  template <typename ImplRefTraits>
  using Stub_ = ModelStub<ImplRefTraits>;

  using RequestValidator_ = ModelRequestValidator;
  using ResponseValidator_ = ModelResponseValidator;
  enum MethodMinVersions : uint32_t {
    kREMOVED_0MinVersion = 0,
    kCreateGraphExecutorMinVersion = 0,
  };

// crbug.com/1340245 - this causes binary size bloat on Fuchsia, and we're OK
// with not having this data in traces there.
#if !BUILDFLAG(IS_FUCHSIA)
  struct REMOVED_0_Sym {
    NOINLINE static void IPCSymbol();
  };
  struct CreateGraphExecutor_Sym {
    NOINLINE static void IPCSymbol();
  };
#endif // !BUILDFLAG(IS_FUCHSIA)
  virtual ~Model() = default;


  using REMOVED_0Callback = base::OnceCallback<void(CreateGraphExecutorResult)>;
  
// @generated_from: chromeos.machine_learning.mojom.Model.REMOVED_0
  virtual void REMOVED_0(::mojo::PendingReceiver<::chromeos::machine_learning::mojom::GraphExecutor> receiver, REMOVED_0Callback callback) = 0;


  using CreateGraphExecutorCallback = base::OnceCallback<void(CreateGraphExecutorResult)>;
  
// @generated_from: chromeos.machine_learning.mojom.Model.CreateGraphExecutor
  virtual void CreateGraphExecutor(GraphExecutorOptionsPtr options, ::mojo::PendingReceiver<::chromeos::machine_learning::mojom::GraphExecutor> receiver, CreateGraphExecutorCallback callback) = 0;
};



// @generated_from: chromeos.machine_learning.mojom.Model
class COMPONENT_EXPORT(MLSERVICE_MOJOM) ModelProxy
    : public Model {
 public:
  using InterfaceType = Model;

  explicit ModelProxy(mojo::MessageReceiverWithResponder* receiver);
  
// @generated_from: chromeos.machine_learning.mojom.Model.REMOVED_0
  void REMOVED_0(::mojo::PendingReceiver<::chromeos::machine_learning::mojom::GraphExecutor> receiver, REMOVED_0Callback callback) final;
  
// @generated_from: chromeos.machine_learning.mojom.Model.CreateGraphExecutor
  void CreateGraphExecutor(GraphExecutorOptionsPtr options, ::mojo::PendingReceiver<::chromeos::machine_learning::mojom::GraphExecutor> receiver, CreateGraphExecutorCallback callback) final;

 private:
  mojo::MessageReceiverWithResponder* receiver_;
};
class COMPONENT_EXPORT(MLSERVICE_MOJOM) ModelStubDispatch {
 public:
  static bool Accept(Model* impl, mojo::Message* message);
  static bool AcceptWithResponder(
      Model* impl,
      mojo::Message* message,
      std::unique_ptr<mojo::MessageReceiverWithStatus> responder);
};

template <typename ImplRefTraits =
              mojo::RawPtrImplRefTraits<Model>>
class ModelStub
    : public mojo::MessageReceiverWithResponderStatus {
 public:
  using ImplPointerType = typename ImplRefTraits::PointerType;

  ModelStub() = default;
  ~ModelStub() override = default;

  void set_sink(ImplPointerType sink) { sink_ = std::move(sink); }
  ImplPointerType& sink() { return sink_; }

  bool Accept(mojo::Message* message) override {
    if (ImplRefTraits::IsNull(sink_))
      return false;
    return ModelStubDispatch::Accept(
        ImplRefTraits::GetRawPointer(&sink_), message);
  }

  bool AcceptWithResponder(
      mojo::Message* message,
      std::unique_ptr<mojo::MessageReceiverWithStatus> responder) override {
    if (ImplRefTraits::IsNull(sink_))
      return false;
    return ModelStubDispatch::AcceptWithResponder(
        ImplRefTraits::GetRawPointer(&sink_), message, std::move(responder));
  }

 private:
  ImplPointerType sink_;
};
class COMPONENT_EXPORT(MLSERVICE_MOJOM) ModelRequestValidator : public mojo::MessageReceiver {
 public:
  bool Accept(mojo::Message* message) override;
};
class COMPONENT_EXPORT(MLSERVICE_MOJOM) ModelResponseValidator : public mojo::MessageReceiver {
 public:
  bool Accept(mojo::Message* message) override;
};





// @generated_from: chromeos.machine_learning.mojom.GraphExecutorOptions
class COMPONENT_EXPORT(MLSERVICE_MOJOM) GraphExecutorOptions {
 public:
  template <typename T>
  using EnableIfSame = std::enable_if_t<std::is_same<GraphExecutorOptions, T>::value>;
  using DataView = GraphExecutorOptionsDataView;
  using Data_ = internal::GraphExecutorOptions_Data;

  template <typename... Args>
  static GraphExecutorOptionsPtr New(Args&&... args) {
    return GraphExecutorOptionsPtr(
        absl::in_place, std::forward<Args>(args)...);
  }

  template <typename U>
  static GraphExecutorOptionsPtr From(const U& u) {
    return mojo::TypeConverter<GraphExecutorOptionsPtr, U>::Convert(u);
  }

  template <typename U>
  U To() const {
    return mojo::TypeConverter<U, GraphExecutorOptions>::Convert(*this);
  }


  GraphExecutorOptions();

  explicit GraphExecutorOptions(
      bool use_nnapi);

  GraphExecutorOptions(
      bool use_nnapi,
      bool use_gpu);

  GraphExecutorOptions(
      bool use_nnapi,
      bool use_gpu,
      GpuDelegateApi gpu_delegate_api);


  ~GraphExecutorOptions();

  // Clone() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Clone() or copy
  // constructor/assignment are available for members.
  template <typename StructPtrType = GraphExecutorOptionsPtr>
  GraphExecutorOptionsPtr Clone() const;

  // Equals() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Equals() or == operator
  // are available for members.
  template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
  bool Equals(const T& other) const;

  template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
  bool operator==(const T& rhs) const { return Equals(rhs); }
  size_t Hash(size_t seed) const;
  template <typename UserType>
  static std::vector<uint8_t> Serialize(UserType* input) {
    return mojo::internal::SerializeImpl<
        GraphExecutorOptions::DataView, std::vector<uint8_t>>(input);
  }

  template <typename UserType>
  static mojo::Message SerializeAsMessage(UserType* input) {
    return mojo::internal::SerializeAsMessageImpl<
        GraphExecutorOptions::DataView>(input);
  }

  // The returned Message is serialized only if the message is moved
  // cross-process or cross-language. Otherwise if the message is Deserialized
  // as the same UserType |input| will just be moved to |output| in
  // DeserializeFromMessage.
  template <typename UserType>
  static mojo::Message WrapAsMessage(UserType input) {
    return mojo::Message(std::make_unique<
        internal::GraphExecutorOptions_UnserializedMessageContext<
            UserType, GraphExecutorOptions::DataView>>(0, 0, std::move(input)),
        MOJO_CREATE_MESSAGE_FLAG_NONE);
  }

  template <typename UserType>
  static bool Deserialize(const void* data,
                          size_t data_num_bytes,
                          UserType* output) {
    mojo::Message message;
    return mojo::internal::DeserializeImpl<GraphExecutorOptions::DataView>(
        message, data, data_num_bytes, output, Validate);
  }

  template <typename UserType>
  static bool Deserialize(const std::vector<uint8_t>& input,
                          UserType* output) {
    return GraphExecutorOptions::Deserialize(
        input.size() == 0 ? nullptr : &input.front(), input.size(), output);
  }

  template <typename UserType>
  static bool DeserializeFromMessage(mojo::Message input,
                                     UserType* output) {
    auto context = input.TakeUnserializedContext<
        internal::GraphExecutorOptions_UnserializedMessageContext<
            UserType, GraphExecutorOptions::DataView>>();
    if (context) {
      *output = std::move(context->TakeData());
      return true;
    }
    input.SerializeIfNecessary();
    return mojo::internal::DeserializeImpl<GraphExecutorOptions::DataView>(
        input, input.payload(), input.payload_num_bytes(), output, Validate);
  }

  
// @generated_from: chromeos.machine_learning.mojom.GraphExecutorOptions.use_nnapi
  bool use_nnapi;
  
// @generated_from: chromeos.machine_learning.mojom.GraphExecutorOptions.use_gpu
  bool use_gpu;
  
// @generated_from: chromeos.machine_learning.mojom.GraphExecutorOptions.gpu_delegate_api
  GpuDelegateApi gpu_delegate_api;

  // Serialise this struct into a trace.
  void WriteIntoTrace(perfetto::TracedValue traced_context) const;

 private:
  static bool Validate(const void* data,
                       mojo::internal::ValidationContext* validation_context);
};

// The comparison operators are templates, so they are only instantiated if they
// are used. Thus, the bindings generator does not need to know whether
// comparison operators are available for members.
template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
bool operator<(const T& lhs, const T& rhs);

template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
bool operator<=(const T& lhs, const T& rhs) {
  return !(rhs < lhs);
}

template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
bool operator>(const T& lhs, const T& rhs) {
  return rhs < lhs;
}

template <typename T, GraphExecutorOptions::EnableIfSame<T>* = nullptr>
bool operator>=(const T& lhs, const T& rhs) {
  return !(lhs < rhs);
}





// @generated_from: chromeos.machine_learning.mojom.BuiltinModelSpec
class COMPONENT_EXPORT(MLSERVICE_MOJOM) BuiltinModelSpec {
 public:
  template <typename T>
  using EnableIfSame = std::enable_if_t<std::is_same<BuiltinModelSpec, T>::value>;
  using DataView = BuiltinModelSpecDataView;
  using Data_ = internal::BuiltinModelSpec_Data;

  template <typename... Args>
  static BuiltinModelSpecPtr New(Args&&... args) {
    return BuiltinModelSpecPtr(
        absl::in_place, std::forward<Args>(args)...);
  }

  template <typename U>
  static BuiltinModelSpecPtr From(const U& u) {
    return mojo::TypeConverter<BuiltinModelSpecPtr, U>::Convert(u);
  }

  template <typename U>
  U To() const {
    return mojo::TypeConverter<U, BuiltinModelSpec>::Convert(*this);
  }


  BuiltinModelSpec();

  explicit BuiltinModelSpec(
      BuiltinModelId id);


  ~BuiltinModelSpec();

  // Clone() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Clone() or copy
  // constructor/assignment are available for members.
  template <typename StructPtrType = BuiltinModelSpecPtr>
  BuiltinModelSpecPtr Clone() const;

  // Equals() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Equals() or == operator
  // are available for members.
  template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
  bool Equals(const T& other) const;

  template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
  bool operator==(const T& rhs) const { return Equals(rhs); }
  size_t Hash(size_t seed) const;
  template <typename UserType>
  static std::vector<uint8_t> Serialize(UserType* input) {
    return mojo::internal::SerializeImpl<
        BuiltinModelSpec::DataView, std::vector<uint8_t>>(input);
  }

  template <typename UserType>
  static mojo::Message SerializeAsMessage(UserType* input) {
    return mojo::internal::SerializeAsMessageImpl<
        BuiltinModelSpec::DataView>(input);
  }

  // The returned Message is serialized only if the message is moved
  // cross-process or cross-language. Otherwise if the message is Deserialized
  // as the same UserType |input| will just be moved to |output| in
  // DeserializeFromMessage.
  template <typename UserType>
  static mojo::Message WrapAsMessage(UserType input) {
    return mojo::Message(std::make_unique<
        internal::BuiltinModelSpec_UnserializedMessageContext<
            UserType, BuiltinModelSpec::DataView>>(0, 0, std::move(input)),
        MOJO_CREATE_MESSAGE_FLAG_NONE);
  }

  template <typename UserType>
  static bool Deserialize(const void* data,
                          size_t data_num_bytes,
                          UserType* output) {
    mojo::Message message;
    return mojo::internal::DeserializeImpl<BuiltinModelSpec::DataView>(
        message, data, data_num_bytes, output, Validate);
  }

  template <typename UserType>
  static bool Deserialize(const std::vector<uint8_t>& input,
                          UserType* output) {
    return BuiltinModelSpec::Deserialize(
        input.size() == 0 ? nullptr : &input.front(), input.size(), output);
  }

  template <typename UserType>
  static bool DeserializeFromMessage(mojo::Message input,
                                     UserType* output) {
    auto context = input.TakeUnserializedContext<
        internal::BuiltinModelSpec_UnserializedMessageContext<
            UserType, BuiltinModelSpec::DataView>>();
    if (context) {
      *output = std::move(context->TakeData());
      return true;
    }
    input.SerializeIfNecessary();
    return mojo::internal::DeserializeImpl<BuiltinModelSpec::DataView>(
        input, input.payload(), input.payload_num_bytes(), output, Validate);
  }

  
// @generated_from: chromeos.machine_learning.mojom.BuiltinModelSpec.id
  BuiltinModelId id;

  // Serialise this struct into a trace.
  void WriteIntoTrace(perfetto::TracedValue traced_context) const;

 private:
  static bool Validate(const void* data,
                       mojo::internal::ValidationContext* validation_context);
};

// The comparison operators are templates, so they are only instantiated if they
// are used. Thus, the bindings generator does not need to know whether
// comparison operators are available for members.
template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
bool operator<(const T& lhs, const T& rhs);

template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
bool operator<=(const T& lhs, const T& rhs) {
  return !(rhs < lhs);
}

template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
bool operator>(const T& lhs, const T& rhs) {
  return rhs < lhs;
}

template <typename T, BuiltinModelSpec::EnableIfSame<T>* = nullptr>
bool operator>=(const T& lhs, const T& rhs) {
  return !(lhs < rhs);
}










// @generated_from: chromeos.machine_learning.mojom.FlatBufferModelSpec
class COMPONENT_EXPORT(MLSERVICE_MOJOM) FlatBufferModelSpec {
 public:
  template <typename T>
  using EnableIfSame = std::enable_if_t<std::is_same<FlatBufferModelSpec, T>::value>;
  using DataView = FlatBufferModelSpecDataView;
  using Data_ = internal::FlatBufferModelSpec_Data;

  template <typename... Args>
  static FlatBufferModelSpecPtr New(Args&&... args) {
    return FlatBufferModelSpecPtr(
        absl::in_place, std::forward<Args>(args)...);
  }

  template <typename U>
  static FlatBufferModelSpecPtr From(const U& u) {
    return mojo::TypeConverter<FlatBufferModelSpecPtr, U>::Convert(u);
  }

  template <typename U>
  U To() const {
    return mojo::TypeConverter<U, FlatBufferModelSpec>::Convert(*this);
  }


  FlatBufferModelSpec();

  FlatBufferModelSpec(
      const std::string& model_string,
      const base::flat_map<std::string, int32_t>& inputs,
      const base::flat_map<std::string, int32_t>& outputs,
      const std::string& metrics_model_name);


  ~FlatBufferModelSpec();

  // Clone() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Clone() or copy
  // constructor/assignment are available for members.
  template <typename StructPtrType = FlatBufferModelSpecPtr>
  FlatBufferModelSpecPtr Clone() const;

  // Equals() is a template so it is only instantiated if it is used. Thus, the
  // bindings generator does not need to know whether Equals() or == operator
  // are available for members.
  template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
  bool Equals(const T& other) const;

  template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
  bool operator==(const T& rhs) const { return Equals(rhs); }
  template <typename UserType>
  static std::vector<uint8_t> Serialize(UserType* input) {
    return mojo::internal::SerializeImpl<
        FlatBufferModelSpec::DataView, std::vector<uint8_t>>(input);
  }

  template <typename UserType>
  static mojo::Message SerializeAsMessage(UserType* input) {
    return mojo::internal::SerializeAsMessageImpl<
        FlatBufferModelSpec::DataView>(input);
  }

  // The returned Message is serialized only if the message is moved
  // cross-process or cross-language. Otherwise if the message is Deserialized
  // as the same UserType |input| will just be moved to |output| in
  // DeserializeFromMessage.
  template <typename UserType>
  static mojo::Message WrapAsMessage(UserType input) {
    return mojo::Message(std::make_unique<
        internal::FlatBufferModelSpec_UnserializedMessageContext<
            UserType, FlatBufferModelSpec::DataView>>(0, 0, std::move(input)),
        MOJO_CREATE_MESSAGE_FLAG_NONE);
  }

  template <typename UserType>
  static bool Deserialize(const void* data,
                          size_t data_num_bytes,
                          UserType* output) {
    mojo::Message message;
    return mojo::internal::DeserializeImpl<FlatBufferModelSpec::DataView>(
        message, data, data_num_bytes, output, Validate);
  }

  template <typename UserType>
  static bool Deserialize(const std::vector<uint8_t>& input,
                          UserType* output) {
    return FlatBufferModelSpec::Deserialize(
        input.size() == 0 ? nullptr : &input.front(), input.size(), output);
  }

  template <typename UserType>
  static bool DeserializeFromMessage(mojo::Message input,
                                     UserType* output) {
    auto context = input.TakeUnserializedContext<
        internal::FlatBufferModelSpec_UnserializedMessageContext<
            UserType, FlatBufferModelSpec::DataView>>();
    if (context) {
      *output = std::move(context->TakeData());
      return true;
    }
    input.SerializeIfNecessary();
    return mojo::internal::DeserializeImpl<FlatBufferModelSpec::DataView>(
        input, input.payload(), input.payload_num_bytes(), output, Validate);
  }

  
// @generated_from: chromeos.machine_learning.mojom.FlatBufferModelSpec.model_string
  std::string model_string;
  
// @generated_from: chromeos.machine_learning.mojom.FlatBufferModelSpec.inputs
  base::flat_map<std::string, int32_t> inputs;
  
// @generated_from: chromeos.machine_learning.mojom.FlatBufferModelSpec.outputs
  base::flat_map<std::string, int32_t> outputs;
  
// @generated_from: chromeos.machine_learning.mojom.FlatBufferModelSpec.metrics_model_name
  std::string metrics_model_name;

  // Serialise this struct into a trace.
  void WriteIntoTrace(perfetto::TracedValue traced_context) const;

 private:
  static bool Validate(const void* data,
                       mojo::internal::ValidationContext* validation_context);
};

// The comparison operators are templates, so they are only instantiated if they
// are used. Thus, the bindings generator does not need to know whether
// comparison operators are available for members.
template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
bool operator<(const T& lhs, const T& rhs);

template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
bool operator<=(const T& lhs, const T& rhs) {
  return !(rhs < lhs);
}

template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
bool operator>(const T& lhs, const T& rhs) {
  return rhs < lhs;
}

template <typename T, FlatBufferModelSpec::EnableIfSame<T>* = nullptr>
bool operator>=(const T& lhs, const T& rhs) {
  return !(lhs < rhs);
}

template <typename StructPtrType>
GraphExecutorOptionsPtr GraphExecutorOptions::Clone() const {
  return New(
      mojo::Clone(use_nnapi),
      mojo::Clone(use_gpu),
      mojo::Clone(gpu_delegate_api)
  );
}

template <typename T, GraphExecutorOptions::EnableIfSame<T>*>
bool GraphExecutorOptions::Equals(const T& other_struct) const {
  if (!mojo::Equals(this->use_nnapi, other_struct.use_nnapi))
    return false;
  if (!mojo::Equals(this->use_gpu, other_struct.use_gpu))
    return false;
  if (!mojo::Equals(this->gpu_delegate_api, other_struct.gpu_delegate_api))
    return false;
  return true;
}

template <typename T, GraphExecutorOptions::EnableIfSame<T>*>
bool operator<(const T& lhs, const T& rhs) {
  if (lhs.use_nnapi < rhs.use_nnapi)
    return true;
  if (rhs.use_nnapi < lhs.use_nnapi)
    return false;
  if (lhs.use_gpu < rhs.use_gpu)
    return true;
  if (rhs.use_gpu < lhs.use_gpu)
    return false;
  if (lhs.gpu_delegate_api < rhs.gpu_delegate_api)
    return true;
  if (rhs.gpu_delegate_api < lhs.gpu_delegate_api)
    return false;
  return false;
}
template <typename StructPtrType>
BuiltinModelSpecPtr BuiltinModelSpec::Clone() const {
  return New(
      mojo::Clone(id)
  );
}

template <typename T, BuiltinModelSpec::EnableIfSame<T>*>
bool BuiltinModelSpec::Equals(const T& other_struct) const {
  if (!mojo::Equals(this->id, other_struct.id))
    return false;
  return true;
}

template <typename T, BuiltinModelSpec::EnableIfSame<T>*>
bool operator<(const T& lhs, const T& rhs) {
  if (lhs.id < rhs.id)
    return true;
  if (rhs.id < lhs.id)
    return false;
  return false;
}
template <typename StructPtrType>
FlatBufferModelSpecPtr FlatBufferModelSpec::Clone() const {
  return New(
      mojo::Clone(model_string),
      mojo::Clone(inputs),
      mojo::Clone(outputs),
      mojo::Clone(metrics_model_name)
  );
}

template <typename T, FlatBufferModelSpec::EnableIfSame<T>*>
bool FlatBufferModelSpec::Equals(const T& other_struct) const {
  if (!mojo::Equals(this->model_string, other_struct.model_string))
    return false;
  if (!mojo::Equals(this->inputs, other_struct.inputs))
    return false;
  if (!mojo::Equals(this->outputs, other_struct.outputs))
    return false;
  if (!mojo::Equals(this->metrics_model_name, other_struct.metrics_model_name))
    return false;
  return true;
}

template <typename T, FlatBufferModelSpec::EnableIfSame<T>*>
bool operator<(const T& lhs, const T& rhs) {
  if (lhs.model_string < rhs.model_string)
    return true;
  if (rhs.model_string < lhs.model_string)
    return false;
  if (lhs.inputs < rhs.inputs)
    return true;
  if (rhs.inputs < lhs.inputs)
    return false;
  if (lhs.outputs < rhs.outputs)
    return true;
  if (rhs.outputs < lhs.outputs)
    return false;
  if (lhs.metrics_model_name < rhs.metrics_model_name)
    return true;
  if (rhs.metrics_model_name < lhs.metrics_model_name)
    return false;
  return false;
}


}  // namespace mojom
}  // namespace machine_learning
}  // namespace chromeos

namespace mojo {


template <>
struct COMPONENT_EXPORT(MLSERVICE_MOJOM) StructTraits<::chromeos::machine_learning::mojom::GraphExecutorOptions::DataView,
                                         ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr> {
  static bool IsNull(const ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr& input) { return !input; }
  static void SetToNull(::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr* output) { output->reset(); }

  static decltype(::chromeos::machine_learning::mojom::GraphExecutorOptions::use_nnapi) use_nnapi(
      const ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr& input) {
    return input->use_nnapi;
  }

  static decltype(::chromeos::machine_learning::mojom::GraphExecutorOptions::use_gpu) use_gpu(
      const ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr& input) {
    return input->use_gpu;
  }

  static decltype(::chromeos::machine_learning::mojom::GraphExecutorOptions::gpu_delegate_api) gpu_delegate_api(
      const ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr& input) {
    return input->gpu_delegate_api;
  }

  static bool Read(::chromeos::machine_learning::mojom::GraphExecutorOptions::DataView input, ::chromeos::machine_learning::mojom::GraphExecutorOptionsPtr* output);
};


template <>
struct COMPONENT_EXPORT(MLSERVICE_MOJOM) StructTraits<::chromeos::machine_learning::mojom::BuiltinModelSpec::DataView,
                                         ::chromeos::machine_learning::mojom::BuiltinModelSpecPtr> {
  static bool IsNull(const ::chromeos::machine_learning::mojom::BuiltinModelSpecPtr& input) { return !input; }
  static void SetToNull(::chromeos::machine_learning::mojom::BuiltinModelSpecPtr* output) { output->reset(); }

  static decltype(::chromeos::machine_learning::mojom::BuiltinModelSpec::id) id(
      const ::chromeos::machine_learning::mojom::BuiltinModelSpecPtr& input) {
    return input->id;
  }

  static bool Read(::chromeos::machine_learning::mojom::BuiltinModelSpec::DataView input, ::chromeos::machine_learning::mojom::BuiltinModelSpecPtr* output);
};


template <>
struct COMPONENT_EXPORT(MLSERVICE_MOJOM) StructTraits<::chromeos::machine_learning::mojom::FlatBufferModelSpec::DataView,
                                         ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr> {
  static bool IsNull(const ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr& input) { return !input; }
  static void SetToNull(::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr* output) { output->reset(); }

  static const decltype(::chromeos::machine_learning::mojom::FlatBufferModelSpec::model_string)& model_string(
      const ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr& input) {
    return input->model_string;
  }

  static const decltype(::chromeos::machine_learning::mojom::FlatBufferModelSpec::inputs)& inputs(
      const ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr& input) {
    return input->inputs;
  }

  static const decltype(::chromeos::machine_learning::mojom::FlatBufferModelSpec::outputs)& outputs(
      const ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr& input) {
    return input->outputs;
  }

  static const decltype(::chromeos::machine_learning::mojom::FlatBufferModelSpec::metrics_model_name)& metrics_model_name(
      const ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr& input) {
    return input->metrics_model_name;
  }

  static bool Read(::chromeos::machine_learning::mojom::FlatBufferModelSpec::DataView input, ::chromeos::machine_learning::mojom::FlatBufferModelSpecPtr* output);
};

}  // namespace mojo

#endif  // CHROMEOS_SERVICES_MACHINE_LEARNING_PUBLIC_MOJOM_MODEL_MOJOM_H_

/* Metadata comment
eyJtZXRhIjogW3siZW5kIjogMTgwOCwgImJlZ2luIjogMTgwMywgImVkZ2UiOiAiJS9reXRoZS9l
ZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZpbmVzIiwgInZuYW1lIjogeyJjb3Jw
dXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJvbWl1bS9zcmMiLCAibGFuZ3VhZ2Ui
OiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1hY2hpbmVfbGVhcm5pbmcubW9qb20u
TW9kZWwifX0sIHsiZW5kIjogMzE0NSwgImJlZ2luIjogMzEzNiwgImVkZ2UiOiAiJS9reXRoZS9l
ZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZpbmVzIiwgInZuYW1lIjogeyJjb3Jw
dXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJvbWl1bS9zcmMiLCAibGFuZ3VhZ2Ui
OiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1hY2hpbmVfbGVhcm5pbmcubW9qb20u
TW9kZWwuUkVNT1ZFRF8wIn19LCB7ImVuZCI6IDM0NzMsICJiZWdpbiI6IDM0NTQsICJlZGdlIjog
IiUva3l0aGUvZWRnZS9nZW5lcmF0ZXMiLCAidHlwZSI6ICJhbmNob3JfZGVmaW5lcyIsICJ2bmFt
ZSI6IHsiY29ycHVzIjogImNocm9taXVtLmdvb2dsZXNvdXJjZS5jb20vY2hyb21pdW0vc3JjIiwg
Imxhbmd1YWdlIjogIm1vam9tIiwgInNpZ25hdHVyZSI6ICJjaHJvbWVvcy5tYWNoaW5lX2xlYXJu
aW5nLm1vam9tLk1vZGVsLkNyZWF0ZUdyYXBoRXhlY3V0b3IifX0sIHsiZW5kIjogMzk2OSwgImJl
Z2luIjogMzk2MCwgImVkZ2UiOiAiJS9reXRoZS9lZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFu
Y2hvcl9kZWZpbmVzIiwgInZuYW1lIjogeyJjb3JwdXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNl
LmNvbS9jaHJvbWl1bS9zcmMiLCAibGFuZ3VhZ2UiOiAibW9qb20iLCAic2lnbmF0dXJlIjogImNo
cm9tZW9zLm1hY2hpbmVfbGVhcm5pbmcubW9qb20uTW9kZWwuUkVNT1ZFRF8wIn19LCB7ImVuZCI6
IDQxOTgsICJiZWdpbiI6IDQxNzksICJlZGdlIjogIiUva3l0aGUvZWRnZS9nZW5lcmF0ZXMiLCAi
dHlwZSI6ICJhbmNob3JfZGVmaW5lcyIsICJ2bmFtZSI6IHsiY29ycHVzIjogImNocm9taXVtLmdv
b2dsZXNvdXJjZS5jb20vY2hyb21pdW0vc3JjIiwgImxhbmd1YWdlIjogIm1vam9tIiwgInNpZ25h
dHVyZSI6ICJjaHJvbWVvcy5tYWNoaW5lX2xlYXJuaW5nLm1vam9tLk1vZGVsLkNyZWF0ZUdyYXBo
RXhlY3V0b3IifX0sIHsiZW5kIjogNjEzMCwgImJlZ2luIjogNjExMCwgImVkZ2UiOiAiJS9reXRo
ZS9lZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZpbmVzIiwgInZuYW1lIjogeyJj
b3JwdXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJvbWl1bS9zcmMiLCAibGFuZ3Vh
Z2UiOiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1hY2hpbmVfbGVhcm5pbmcubW9q
b20uR3JhcGhFeGVjdXRvck9wdGlvbnMifX0sIHsiZW5kIjogMTAxNTYsICJiZWdpbiI6IDEwMTQ3
LCAiZWRnZSI6ICIlL2t5dGhlL2VkZ2UvZ2VuZXJhdGVzIiwgInR5cGUiOiAiYW5jaG9yX2RlZmlu
ZXMiLCAidm5hbWUiOiB7ImNvcnB1cyI6ICJjaHJvbWl1bS5nb29nbGVzb3VyY2UuY29tL2Nocm9t
aXVtL3NyYyIsICJsYW5ndWFnZSI6ICJtb2pvbSIsICJzaWduYXR1cmUiOiAiY2hyb21lb3MubWFj
aGluZV9sZWFybmluZy5tb2pvbS5HcmFwaEV4ZWN1dG9yT3B0aW9ucy51c2Vfbm5hcGkifX0sIHsi
ZW5kIjogMTAyNTYsICJiZWdpbiI6IDEwMjQ5LCAiZWRnZSI6ICIlL2t5dGhlL2VkZ2UvZ2VuZXJh
dGVzIiwgInR5cGUiOiAiYW5jaG9yX2RlZmluZXMiLCAidm5hbWUiOiB7ImNvcnB1cyI6ICJjaHJv
bWl1bS5nb29nbGVzb3VyY2UuY29tL2Nocm9taXVtL3NyYyIsICJsYW5ndWFnZSI6ICJtb2pvbSIs
ICJzaWduYXR1cmUiOiAiY2hyb21lb3MubWFjaGluZV9sZWFybmluZy5tb2pvbS5HcmFwaEV4ZWN1
dG9yT3B0aW9ucy51c2VfZ3B1In19LCB7ImVuZCI6IDEwMzg0LCAiYmVnaW4iOiAxMDM2OCwgImVk
Z2UiOiAiJS9reXRoZS9lZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZpbmVzIiwg
InZuYW1lIjogeyJjb3JwdXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJvbWl1bS9z
cmMiLCAibGFuZ3VhZ2UiOiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1hY2hpbmVf
bGVhcm5pbmcubW9qb20uR3JhcGhFeGVjdXRvck9wdGlvbnMuZ3B1X2RlbGVnYXRlX2FwaSJ9fSwg
eyJlbmQiOiAxMTUwOCwgImJlZ2luIjogMTE0OTIsICJlZGdlIjogIiUva3l0aGUvZWRnZS9nZW5l
cmF0ZXMiLCAidHlwZSI6ICJhbmNob3JfZGVmaW5lcyIsICJ2bmFtZSI6IHsiY29ycHVzIjogImNo
cm9taXVtLmdvb2dsZXNvdXJjZS5jb20vY2hyb21pdW0vc3JjIiwgImxhbmd1YWdlIjogIm1vam9t
IiwgInNpZ25hdHVyZSI6ICJjaHJvbWVvcy5tYWNoaW5lX2xlYXJuaW5nLm1vam9tLkJ1aWx0aW5N
b2RlbFNwZWMifX0sIHsiZW5kIjogMTUyNTgsICJiZWdpbiI6IDE1MjU2LCAiZWRnZSI6ICIlL2t5
dGhlL2VkZ2UvZ2VuZXJhdGVzIiwgInR5cGUiOiAiYW5jaG9yX2RlZmluZXMiLCAidm5hbWUiOiB7
ImNvcnB1cyI6ICJjaHJvbWl1bS5nb29nbGVzb3VyY2UuY29tL2Nocm9taXVtL3NyYyIsICJsYW5n
dWFnZSI6ICJtb2pvbSIsICJzaWduYXR1cmUiOiAiY2hyb21lb3MubWFjaGluZV9sZWFybmluZy5t
b2pvbS5CdWlsdGluTW9kZWxTcGVjLmlkIn19LCB7ImVuZCI6IDE2Mzc3LCAiYmVnaW4iOiAxNjM1
OCwgImVkZ2UiOiAiJS9reXRoZS9lZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZp
bmVzIiwgInZuYW1lIjogeyJjb3JwdXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJv
bWl1bS9zcmMiLCAibGFuZ3VhZ2UiOiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1h
Y2hpbmVfbGVhcm5pbmcubW9qb20uRmxhdEJ1ZmZlck1vZGVsU3BlYyJ9fSwgeyJlbmQiOiAyMDM1
MiwgImJlZ2luIjogMjAzNDAsICJlZGdlIjogIiUva3l0aGUvZWRnZS9nZW5lcmF0ZXMiLCAidHlw
ZSI6ICJhbmNob3JfZGVmaW5lcyIsICJ2bmFtZSI6IHsiY29ycHVzIjogImNocm9taXVtLmdvb2ds
ZXNvdXJjZS5jb20vY2hyb21pdW0vc3JjIiwgImxhbmd1YWdlIjogIm1vam9tIiwgInNpZ25hdHVy
ZSI6ICJjaHJvbWVvcy5tYWNoaW5lX2xlYXJuaW5nLm1vam9tLkZsYXRCdWZmZXJNb2RlbFNwZWMu
bW9kZWxfc3RyaW5nIn19LCB7ImVuZCI6IDIwNDgxLCAiYmVnaW4iOiAyMDQ3NSwgImVkZ2UiOiAi
JS9reXRoZS9lZGdlL2dlbmVyYXRlcyIsICJ0eXBlIjogImFuY2hvcl9kZWZpbmVzIiwgInZuYW1l
IjogeyJjb3JwdXMiOiAiY2hyb21pdW0uZ29vZ2xlc291cmNlLmNvbS9jaHJvbWl1bS9zcmMiLCAi
bGFuZ3VhZ2UiOiAibW9qb20iLCAic2lnbmF0dXJlIjogImNocm9tZW9zLm1hY2hpbmVfbGVhcm5p
bmcubW9qb20uRmxhdEJ1ZmZlck1vZGVsU3BlYy5pbnB1dHMifX0sIHsiZW5kIjogMjA2MTIsICJi
ZWdpbiI6IDIwNjA1LCAiZWRnZSI6ICIlL2t5dGhlL2VkZ2UvZ2VuZXJhdGVzIiwgInR5cGUiOiAi
YW5jaG9yX2RlZmluZXMiLCAidm5hbWUiOiB7ImNvcnB1cyI6ICJjaHJvbWl1bS5nb29nbGVzb3Vy
Y2UuY29tL2Nocm9taXVtL3NyYyIsICJsYW5ndWFnZSI6ICJtb2pvbSIsICJzaWduYXR1cmUiOiAi
Y2hyb21lb3MubWFjaGluZV9sZWFybmluZy5tb2pvbS5GbGF0QnVmZmVyTW9kZWxTcGVjLm91dHB1
dHMifX0sIHsiZW5kIjogMjA3NDAsICJiZWdpbiI6IDIwNzIyLCAiZWRnZSI6ICIlL2t5dGhlL2Vk
Z2UvZ2VuZXJhdGVzIiwgInR5cGUiOiAiYW5jaG9yX2RlZmluZXMiLCAidm5hbWUiOiB7ImNvcnB1
cyI6ICJjaHJvbWl1bS5nb29nbGVzb3VyY2UuY29tL2Nocm9taXVtL3NyYyIsICJsYW5ndWFnZSI6
ICJtb2pvbSIsICJzaWduYXR1cmUiOiAiY2hyb21lb3MubWFjaGluZV9sZWFybmluZy5tb2pvbS5G
bGF0QnVmZmVyTW9kZWxTcGVjLm1ldHJpY3NfbW9kZWxfbmFtZSJ9fV0sICJ0eXBlIjogImt5dGhl
MCJ9
*/