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,

// A simple logging device to test custom device registration.
#include <memory>

#include "absl/strings/match.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/custom_device_testutil.h"
#include "tensorflow/c/tf_status.h"

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/platform/stacktrace_handler.h"
#include "tensorflow/core/platform/test.h"

#define ASSERT_TF_OK(x) ASSERT_EQ(TF_OK, TF_GetCode(x)) << TF_Message(x)
#define EXPECT_TF_OK(x) EXPECT_EQ(TF_OK, TF_GetCode(x)) << TF_Message(x)

static const char* content = "abcdefghijklmnopqrstuvwxyz1234567890";
// We will work with content_view instead of content.

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;

                                  absl::optional<int64_t> step_id) const {
  for (int device_index = 0; device_index < underlying_devices_.size();
       ++device_index) {
    DeviceThread* device_thread = device_threads_[device_index].get();
    std::vector<TFE_TensorHandle*> device_inputs;
    device_inputs.reserve(inputs.size());
    for (int input_index = 0; input_index < inputs.size(); ++input_index) {

  const char* device_name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  const char* first_device_name =
      "/job:localhost/replica:0/task:0/device:CPU:0";
  const char* second_device_name =
      "/job:localhost/replica:0/task:0/device:CPU:1";
  std::array<const char*, 2> underlying_devices{first_device_name,
                                                second_device_name};