text: /*******************************************************************************
   * Copyright (c) 2015-2018 Skymind, Inc.
   *
   * This program and the accompanying materials are made available under the
   * terms of the Apache License, Version 2.0 which is available at
   * https://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.
   *
   * SPDX-License-Identifier: Apache-2.0
   ******************************************************************************/
  
  //
  // @author Yurii Shyrma (iuriish@yahoo.com), created on 14.07.2018
  //
  
  #ifndef LIBND4J_GRADCHECK_H
  #define LIBND4J_GRADCHECK_H
  
  
  #include <NDArray.h>
  #include <ops/declarable/DeclarableOp.h>
  
  namespace nd4j {
  
  class GradCheck {
  
      public:
          enum LossFunc {MEAN = 0, SUM = 1};
      private:
          static constexpr double EPSILON = 1e-5;
          static constexpr double MAXRELERR = 1e-5;
          static constexpr double MINABSERR = 1e-6;
          static void fillGradArrays(const LossFunc loss, const std::vector<NDArray*>& gradArrs);
  
  
      public:
  
          /**
          *  performs numerical check of gradients in back prop
          *
          *  opFF - feed forward operation
          *  opBP - back propagation operation
          *  argsHolderFF - argument holder for feed forward operation
          *  argsHolderBP - argument holder for back propagation operation
          *  whatArrsToCheck - specifies what output gradient arrays to check, for example {0, 1, 0} means that only second output gradient array will be checked, default value is empty array which means to check all arrays
          *  IdxRange - specifies indexes range over which array elements will be checked, for example {0.2, 0.7} means range [0.2*array_length, 0.7*array_length), default value is {0., 1.}
          *  loss - type of scalar loss function, it specifies what elements values will be filled into input gradient arrays automatically, default value is SUM
          */
          static bool checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, const OpArgsHolder& argsHolderFF, const OpArgsHolder& argsHolderBP,
                                const std::vector<bool>& whatArrsToCheck = std::vector<bool>(), const std::vector<double>& IdxRange = {0., 1.}, const LossFunc loss = SUM);
  
  };
  
  
  
  
  
  // //////////////////////////////////////////////////////////////////////////
  // ///// IMLEMENTATION OF INLINE METHODS /////
  // //////////////////////////////////////////////////////////////////////////
  
  // template<typename T>
  // FORCEINLINE bool ShapeUtils::isPermutNecessary(const std::vector<int>& permut) {
  
  //     for(int i=0; i<permut.size(); ++i)
  //         if(permut[i] != i)
  //             return true;
  
  //     return false;
  // }
  
  
  
  }
  
  #endif //LIBND4J_GRADCHECK_H
  