text: #pragma once
  //------------------------------------------------------------------------------
  //
  //   Copyright 2018-2019 Fetch.AI Limited
  //
  //   Licensed 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 permissions and
  //   limitations under the License.
  //
  //------------------------------------------------------------------------------
  
  #include <cassert>
  #include <memory>
  #include <vector>
  
  #include "math/ml/loss_functions/mean_square_error.hpp"
  
  namespace fetch {
  namespace ml {
  namespace ops {
  
  template <class T>
  class MeanSquareError
  {
  public:
    using ArrayType    = T;
    using Datatype     = typename ArrayType::Type;
    using ArrayPtrType = std::shared_ptr<ArrayType>;
  
    MeanSquareError()          = default;
    virtual ~MeanSquareError() = default;
  
    virtual typename ArrayType::Type Forward(std::vector<ArrayType> const &inputs)
    {
      assert(inputs.size() == 2);
      assert(inputs[0].shape() == inputs[1].shape());
  
      typename ArrayType::Type ret = fetch::math::MeanSquareError(inputs[0], inputs[1]);
      return ret;
    }
  
    virtual ArrayType Backward(std::vector<ArrayType> const &inputs)
    {
      assert(inputs.size() == 2);
      assert(inputs[0].shape() == inputs[1].shape());
      return fetch::math::Subtract(inputs[0], inputs[1]);
    }
  
    static constexpr char const *DESCRIPTOR = "MeanSquareError";
  };
  
  }  // namespace ops
  }  // namespace ml
  }  // namespace fetch
  