text: // Copyright 2018 The AITS DNNC Authors.All Rights Reserved.
  //
  // Licensed to the Apache Software Foundation(ASF) under one
  // or more contributor license agreements.See the NOTICE file
  // distributed with this work for additional information
  // regarding copyright ownership.The ASF licenses this file
  // to you under the Apache License, Version 2.0 (the
  // "License"); you may not use this file except in compliance
  // with the License.You may obtain a copy of the License at
  //
  //   http://www.apache.org/licenses/LICENSE-2.0
  //
  // Unless required by applicable law or agreed to in writing,
  // software distributed under the License is distributed on an
  // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, either express or implied.See the License for the
  // specific language governing permissionsand limitations
  // under the License.
  //
  // This file is part of AITS DNN compiler maintained at
  // https://github.com/ai-techsystems/dnnCompiler
  //
  
  #include "operators/Xor.h"
  
  using namespace dnnc;
  using namespace Eigen;
  
  #ifdef DNNC_XOR_TEST
  #include <iostream>
  int main() {
    float d1[6] = {1., 2., 3., 4., 5., 0.};
    float d2[6] = {1., 2., 3., 4., 5., 0.};
    int d3[6] = {0, 1, 2, 3, 6, 5};
    int d4[6] = {1, 0, 6, 4, 6, 5};
    tensor<float> a({2, 3});
    a.load(d1);
    tensor<float> b({2, 3});
    b.load(d2);
    tensor<int> c({2, 3});
    c.load(d3);
    tensor<int> d({2, 3});
    d.load(d4);
  
    // Xor<int, float> m("localOpName");
    // auto result = m.compute(a, b);
    Xor<int, int> m("localOpName");
    auto result = m.compute(c, d);
  
    std::cout << result;
    std::cout << "\n";
  
    return 0;
  }
  #endif
  