TF_Status* status = TF_NewStatus();
  TFE_Op* op = TFE_NewOp(ctx, "ReadVariableOp", status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpAddInput(op, var, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  int num_retvals = 1;
  TFE_Execute(op, out_value, &num_retvals, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

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

  TFE_Op* func = TFE_NewOp(ctx, "AddVariablesFunction", status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_OpAddInput(func, packed_handle, status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  if (remote) {
    TFE_OpSetDevice(func, task1_name, status);
    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

    if (TF_GetCode(status) != TF_OK) return;
  }
  TFE_OpAddAttrs(op_.get(), attributes);
  for (int input_index = 0; input_index < inputs.size(); ++input_index) {
    TFE_OpAddInput(op_.get(), inputs[input_index], status);
    if (TF_GetCode(status) != TF_OK) return;
  }
  std::vector<TFE_TensorHandle*> unwrapped_results(expected_max_outputs);
  int real_num_outputs = expected_max_outputs;

  status->status = tensorflow::unwrap(op)->SetDeviceName(device_name);
}

const char* TFE_OpGetDevice(const TFE_Op* op, TF_Status* status) {
  return tensorflow::unwrap(op)->DeviceName().c_str();
}

void TFE_OpAddInput(TFE_Op* op, TFE_TensorHandle* input, TF_Status* status) {
  status->status = tensorflow::unwrap(op)->AddInput(tensorflow::unwrap(input));
}

void TFE_OpAddInputList(TFE_Op* op, TFE_TensorHandle** inputs, int num_inputs,