void* ext;  // reserved for future use

  // Graph C API version.
  int32_t major_version;
  int32_t minor_version;
  int32_t patch_version;

  // Backend device type supported by the optimizer.
  const char* device_type;
  TP_OptimizerConfigs* optimizer_configs;  // output, set by plugin
  TP_Optimizer* optimizer;                 // output, set by plugin
} TP_OptimizerRegistrationParams;

// off, and an execution operation for named operations. Often execution will
// simply wrap op execution on one or more physical devices.
//
// device_info is an opaque caller-defined type stored with the custom device
// which is passed to the functions referenced in the TFE_CustomDevice struct
// `device` (execute, delete_device, etc.). It can for example contain the
// names of wrapped devices.
//

    tensor_stack.pop_back();
    auto op_id_it = tensor_tape.find(tensor_id);
    if (op_id_it == tensor_tape.end()) {
      continue;
    }
    int64_t op_id = op_id_it->second;
    auto op_it = op_tape->find(op_id);
    auto result_op_it = result.op_tape.find(op_id);
    if (op_id == -1 || op_it == op_tape->end() ||
        result_op_it != result.op_tape.end()) {
      continue;
    }

              TFE_TensorHandle* axis);

// If there is a device of type `device_type`, returns true
// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.

  // Length of the list if is_list is true. Undefined otherwise.
  int64_t list_size;

  // Type of elements of the list if is_list != 0.
  // Type of the single value stored in the attribute if is_list == 0.
  TF_AttrType type;

  // Total size the attribute value.
  // The units of total_size depend on is_list and type.
  // (1) If type == TF_ATTR_STRING and is_list == 0
  //     then total_size is the byte size of the string

    TF_Status* status);

// Information about the shape of a Tensor and its type.
struct TF_ShapeAndType {
  // Number of dimensions. -1 indicates unknown rank.
  int num_dims;
  // Array of dimensions. -1 indicates unknown dim.
  int64_t* dims;
  // The data type. May be 0 to denote unknown type.
  TF_DataType dtype;
};

typedef struct TF_ShapeAndType TF_ShapeAndType;

using OwnedTFBuffer = std::unique_ptr<TF_Buffer, TFBufferDeleter>;

class CGraphOptimizer : public CustomGraphOptimizer {
 public:
  explicit CGraphOptimizer(TP_Optimizer optimizer, const char* device_type)
      : optimizer_(optimizer), device_type_(device_type) {
    if (optimizer.create_func != nullptr) {
      c_optimizer_ = (*optimizer_.create_func)();
    } else {
      c_optimizer_ = nullptr;
    }
  }

// A create function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void* create(TF_OpKernelConstruction* ctx) {
  TF_DataType type;
  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.

#endif  // TF_Bool

// Macro used to calculate struct size for maintaining ABI stability across
// different struct implementations.
#ifndef TF_OFFSET_OF_END
#define TF_OFFSET_OF_END(TYPE, MEMBER) \
  (offsetof(TYPE, MEMBER) + sizeof(((TYPE *)0)->MEMBER))
#endif  // TF_OFFSET_OF_END

                                    Tensor* tensor);

absl::StatusOr<xla::PjRtCApiClient*> GetPjRtCApiClient(
    const DeviceType& device_type);

absl::Status ResetPjRtClient(const DeviceType& device_type);

}  // namespace tensorflow