//    "/job:localhost/replica:0/task:0/device:GPU:1"}
// Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1.
//
// Implicit copies onto `device_name` are allowed, replicating the value once
// per device in `underlying_devices`. Implicit copies off of the device throw
// an error.
//
// All component tensors must have the same dtype. Currently they must also have

#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Attributes of an op.
class AbstractOpAttrs {
 protected:
  enum AbstractOpAttrsKind { kEager, kTfrt };
  explicit AbstractOpAttrs(AbstractOpAttrsKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.
  AbstractOpAttrsKind getKind() const { return kind_; }
  virtual ~AbstractOpAttrs() = default;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kEager || ptr->getKind() == kTfrt;
  }

 protected:
  explicit ImmediateExecutionTensorHandle(AbstractTensorHandleKind kind)
      : AbstractTensorHandle(kind) {}
  ~ImmediateExecutionTensorHandle() override {}
};

namespace internal {
struct ImmediateExecutionTensorHandleDeleter {

};

struct TF_DeviceList {
  std::vector<tensorflow::DeviceAttributes> response;
};

struct TF_Function {
  tensorflow::FunctionRecord* record;
};

struct TF_ApiDefMap {
  explicit TF_ApiDefMap(const tensorflow::OpList& op_list)
      :
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
        api_def_map(op_list),
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

template <typename F>
class Cleanup {
 public:
  Cleanup() : released_(true), f_() {}

  template <typename G>
  explicit Cleanup(G&& f)          // NOLINT
      : f_(std::forward<G>(f)) {}  // NOLINT(build/c++11)

  Cleanup(Cleanup&& src)  // NOLINT
      : released_(src.is_released()), f_(src.release()) {}

  // Implicitly move-constructible from any compatible Cleanup<G>.
  // The source will be released as if src.release() were called.

using tensorflow::ops::Mul;
using tensorflow::ops::ReluGrad;

namespace tensorflow {
namespace gradients {
namespace {

class ReluGradientFunction : public GradientFunction {
 public:
  explicit ReluGradientFunction(vector<AbstractTensorHandle*> f_outputs)
      : forward_outputs_(f_outputs) {
    for (auto output : forward_outputs_) {
      if (output) {
        output->Ref();
      }
    }
  }

namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);
  ~GraphFunction() override;

  // GraphFunction maybe stay alive for the duration of the returned
  // FunctionDef.
  Status GetFunctionDef(const FunctionDef** fdef) override;

  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringBoolGauge2 : TFE_MonitoringGauge<bool, 2> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};

struct TFE_MonitoringBuckets {
  explicit TFE_MonitoringBuckets(
      std::function<std::unique_ptr<tensorflow::monitoring::Buckets>(void)>
          fn) {
    create_buckets = fn;
  }

    advances.
*   Trolling, insulting/derogatory comments, and personal or political attacks.
*   Public or private harassment.
*   Publishing others' private information, such as a physical or electronic
    address, without explicit permission.
*   Conduct which could reasonably be considered inappropriate for the forum in
    which it occurs.

// tracing or immediate execution mode.
class AbstractOperation {
 protected:
  enum AbstractOperationKind {
    kGraph,
    kMlir,
    kEager,
    kTfrt,
    kTape,
    kOpHandler
  };
  explicit AbstractOperation(AbstractOperationKind kind) : kind_(kind) {}
  virtual ~AbstractOperation() {}

 public:
  AbstractOperationKind getKind() const { return kind_; }