TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server.release();

  // Update the server def with a new set of names (worker instead of
  // localhost).
  tensorflow::ServerDef updated_server_def = GetServerDef("worker", 2);

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server.release();
}

TEST(CAPI, RemoteExecute) { TestRemoteExecute(false); }
TEST(CAPI, RemoteExecuteAsync) { TestRemoteExecute(true); }

void TestRemoteExecuteSilentCopiesOp(bool async, bool remote,

  tensorflow::TensorProto from_tensor_proto;
  status->status = BufferToMessage(from, &from_tensor_proto);
  if (!status->status.ok()) {
    return;
  }
  status->status =
      tensorflow::down_cast<tensorflow::TensorInterface*>(to->tensor)
          ->FromProto(from_tensor_proto);
}
// --------------------------------------------------------------------------

  TFE_ContextRemoveFunction(ctx, "AddVariablesFunction", status);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();
}

TEST(CAPI, TestLocalFunctionWithPackedInput) {
  TestFunctionWithPackedInput(/*remote=*/false);
}

  if (func) {
    TFE_ContextRemoveFunction(ctx, "MatMulFunction", status);
  }
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();

      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =
          tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>(
              unwrapped_handle);
      tensorflow::ImmediateExecutionTensorHandle* result;
      status->status = custom_device_handle->device()->Pack(

    if (!t) {
      return tensorflow::errors::InvalidArgument(
          "Unable to cast input to GraphTensor");
    }
    inputs_.push_back(t->output_);
    *output = tensorflow::down_cast<TracingTensorHandle*>(outputs[0]);
    return absl::OkStatus();
  }

  Status Finalize(OutputList* outputs, AbstractFunction** f) override {
    std::vector<TF_Output> graph_outputs;

using MaybeParallelTensorOwned =
    absl::variant<std::unique_ptr<ParallelTensor>, TensorHandlePtr>;

using MaybeParallelTensorUnowned =
    absl::variant<ParallelTensor*, TFE_TensorHandle*>;

// A ParallelDevice on its own is not registered with a TFE_Context, and so has
// no device name (e.g. for `tf.device`). `NamedParallelDevice` associates a
// name with it, which lets us pack its `ParallelTensor`s into TFE_TensorHandles

      tensorflow::unwrap(h);
  // TODO(b/175427838): It would be nice to be able to use tensorflow::isa here.
  if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
    return tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>(
               unwrapped_handle)
        ->DevicePointer();
  }
  // TODO(b/175427838): It would be nice to be able to use tensorflow::isa here.

  TF_AbstractFunction* func =
      TF_FinalizeFunction(graph_ctx, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  // Note: TF_OutputList does not own the underlying AbstractTensors, those
  // need to be deleted explicitly.
  TF_DeleteAbstractTensor(TF_OutputListGet(add_outputs, 0));

  // Build eager context.
  TFE_ContextOptions* opts = TFE_NewContextOptions();