void TF_DeleteServer(TF_Server* server) {
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
  delete server;
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
}

void TF_RegisterLogListener(void (*listener)(const char*)) {
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
  tensorflow::logging::RegisterListener(listener);
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
}

  std::vector<std::string> devices{
      "/job:localhost/replica:0/task:0/device:CPU:0",
      "/job:localhost/replica:0/task:0/device:CPU:1"};
  ParallelDevice parallel_device(devices);
  const FunctionDef assert_and_collective = FunctionDefHelper::Define(
      // Name
      "AssertAndCollective",
      // Args
      {"x: float", "condition: bool"},
      // Return values

TF_Library* TF_LoadPluggableDeviceLibrary(const char* library_filename,
                                          TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "PluggableDevice plugin functionality is not supported on mobile");
  return nullptr;
#else
  TF_Library* lib_handle = new TF_Library;
  static tensorflow::mutex mu(tensorflow::LINKER_INITIALIZED);

  TF_RETURN_IF_ERROR(ValidateTPOptimizerConfigs(optimizer_configs));

  CGraphOptimizerRegister(
      [=]() { return new CGraphOptimizer(optimizer, params.device_type); },
      optimizer_configs, params.device_type);

  return absl::OkStatus();
}

}  // namespace grappler
}  // namespace tensorflow

void TF_GetNodesToPreserveListSize(const TF_GrapplerItem* item, int* num_values,

  const char* first_device = "/job:worker/replica:0/task:1/device:CPU:0";
  const char* second_device = "/job:worker/replica:0/task:2/device:CPU:0";
  const char* device_name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  std::array<const char*, 2> underlying_devices{first_device, second_device};
  RegisterParallelDevice(context.get(), device_name, underlying_devices,
                         status.get());

// Public C API entry points
//
// These are only the generic entry points for the C API. This file does not
// have any visibility into the graph/eager implementation and is only providing
// C bindings to the abstract classes defined in the
// c_api_unified_experimental_internal.h header.
//
// =============================================================================

using tensorflow::AbstractFunction;
using tensorflow::AbstractTensorHandle;

};

TEST_F(CApiFunctionTest, OneOp_ZeroInputs_OneOutput) {
  /*
   *                constant
   *                   |
   *                   v
   */
  // Define
  TF_Operation* c = ScalarConst(10, func_graph_, s_, "scalar10");
  Define(-1, {}, {}, {c}, {});

  // Use, run, and verify
  TF_Operation* func_op = Use({});
  Run({}, func_op, 10);
  VerifyFDef({"scalar10_0"}, {}, {{"scalar10", DT_INT32}},

namespace internal {
Status Reset(AbstractOperation* op_, const char* op,
             const char* raw_device_name, ForwardOperation* forward_op_) {
  forward_op_->op_name = op;
  forward_op_->attrs.Reset(op);
  return op_->Reset(op, raw_device_name);
}
Status AddInput(AbstractOperation* op_, AbstractTensorHandle* input,
                ForwardOperation* forward_op_) {

  const string composite_device_name =
      "/job:localhost/replica:0/task:0/device:COMPOSITE:0";
  EXPECT_EQ(TFE_TensorHandleDeviceName(packed_handle, status),
            composite_device_name);
  EXPECT_EQ(TFE_TensorHandleBackingDeviceName(packed_handle, status),
            composite_device_name);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

                            const char* const* underlying_devices,
                            int num_underlying_devices,
                            TFE_CustomDevice* device, void** device_info) {
  device->copy_tensor_to_device = &CopyToParallelDevice;
  device->copy_tensor_from_device = &CopyTensorFromParallelDevice;
  device->delete_device = &DeleteParallelDevice;
  device->execute = &ParallelDeviceExecute;