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

// chromeos/services/machine_learning/public/mojom/graph_executor.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_GRAPH_EXECUTOR_MOJOM_H_
#define CHROMEOS_SERVICES_MACHINE_LEARNING_PUBLIC_MOJOM_GRAPH_EXECUTOR_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/graph_executor.mojom-shared.h"
#include "chromeos/services/machine_learning/public/mojom/graph_executor.mojom-forward.h"
#include "chromeos/services/machine_learning/public/mojom/tensor.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 GraphExecutorProxy;

template <typename ImplRefTraits>
class GraphExecutorStub;

class GraphExecutorRequestValidator;
class GraphExecutorResponseValidator;


// @generated_from: chromeos.machine_learning.mojom.GraphExecutor
class COMPONENT_EXPORT(MLSERVICE_MOJOM) GraphExecutor
    : public GraphExecutorInterfaceBase {
 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_ = GraphExecutorInterfaceBase;
  using Proxy_ = GraphExecutorProxy;

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

  using RequestValidator_ = GraphExecutorRequestValidator;
  using ResponseValidator_ = GraphExecutorResponseValidator;
  enum MethodMinVersions : uint32_t {
    kExecuteMinVersion = 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 Execute_Sym {
    NOINLINE static void IPCSymbol();
  };
#endif // !BUILDFLAG(IS_FUCHSIA)
  virtual ~GraphExecutor() = default;


  using ExecuteCallback = base::OnceCallback<void(ExecuteResult, absl::optional<std::vector<::chromeos::machine_learning::mojom::TensorPtr>>)>;
  
// @generated_from: chromeos.machine_learning.mojom.GraphExecutor.Execute
  virtual void Execute(base::flat_map<std::string, ::chromeos::machine_learning::mojom::TensorPtr> inputs, const std::vector<std::string>& output_names, ExecuteCallback callback) = 0;
};



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

  explicit GraphExecutorProxy(mojo::MessageReceiverWithResponder* receiver);
  
// @generated_from: chromeos.machine_learning.mojom.GraphExecutor.Execute
  void Execute(base::flat_map<std::string, ::chromeos::machine_learning::mojom::TensorPtr> inputs, const std::vector<std::string>& output_names, ExecuteCallback callback) final;

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

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

  GraphExecutorStub() = default;
  ~GraphExecutorStub() 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 GraphExecutorStubDispatch::Accept(
        ImplRefTraits::GetRawPointer(&sink_), message);
  }

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

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





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

namespace mojo {

}  // namespace mojo

#endif  // CHROMEOS_SERVICES_MACHINE_LEARNING_PUBLIC_MOJOM_GRAPH_EXECUTOR_MOJOM_H_

/* Metadata comment
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*/