/*
All modification made by Intel Corporation: © 2016 Intel Corporation

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Copyright (c) 2014, 2015, The Regents of the University of California (Regents)
All rights reserved.

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Copyright (c) 2014, 2015, the respective contributors
All rights reserved.
For the list of contributors go to https://github.com/BVLC/caffe/blob/master/CONTRIBUTORS.md


Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

    * Redistributions of source code must retain the above copyright notice,
      this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
    * Neither the name of Intel Corporation nor the names of its contributors
      may be used to endorse or promote products derived from this software
      without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
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*/

#ifndef CAFFE_SGD_SOLVERS_HPP_
#define CAFFE_SGD_SOLVERS_HPP_

#include <string>
#include <vector>

#include "caffe/solver.hpp"

namespace caffe {

/**
 * @brief Optimizes the parameters of a Net using
 *        stochastic gradient descent (SGD) with momentum.
 */
template <typename Dtype>
class SGDSolver : public Solver<Dtype> {
 public:
  explicit SGDSolver(const SolverParameter& param)
      : Solver<Dtype>(param) { PreSolve(); }
  explicit SGDSolver(const string& param_file)
      : Solver<Dtype>(param_file) { PreSolve(); }
  virtual inline const char* type() const { return "SGD"; }

  const vector<shared_ptr<Blob<Dtype> > >& history() { return history_; }

 protected:
  void PreSolve();
  Dtype GetLearningRate();
  virtual void ApplyUpdate();
  virtual void ApplyUpdate(int param_id);
  virtual void Normalize(int param_id);
  virtual void Regularize(int param_id);
  virtual void ComputeUpdateValue(int param_id, Dtype rate);
  virtual void ClipGradients();
  virtual void SnapshotSolverState(const string& model_filename);
  virtual void SnapshotSolverStateToBinaryProto(const string& model_filename);
  virtual void SnapshotSolverStateToHDF5(const string& model_filename);
  virtual void RestoreSolverStateFromHDF5(const string& state_file);
  virtual void RestoreSolverStateFromBinaryProto(const string& state_file);
  // history maintains the historical momentum data.
  // update maintains update related data and is not needed in snapshots.
  // temp maintains other information that might be needed in computation
  //   of gradients/updates and is not needed in snapshots
  vector<shared_ptr<Blob<Dtype> > > history_, update_, temp_;

  // loss history for 'plateau' LR policy (should be stored in snapshots)
  Dtype minimum_loss_;
  int iter_last_event_;

  DISABLE_COPY_AND_ASSIGN(SGDSolver);
};

template <typename Dtype>
class NesterovSolver : public SGDSolver<Dtype> {
 public:
  explicit NesterovSolver(const SolverParameter& param)
      : SGDSolver<Dtype>(param) {}
  explicit NesterovSolver(const string& param_file)
      : SGDSolver<Dtype>(param_file) {}
  virtual inline const char* type() const { return "Nesterov"; }

 protected:
  virtual void ComputeUpdateValue(int param_id, Dtype rate);

  DISABLE_COPY_AND_ASSIGN(NesterovSolver);
};

template <typename Dtype>
class AdaGradSolver : public SGDSolver<Dtype> {
 public:
  explicit AdaGradSolver(const SolverParameter& param)
      : SGDSolver<Dtype>(param) { constructor_sanity_check(); }
  explicit AdaGradSolver(const string& param_file)
      : SGDSolver<Dtype>(param_file) { constructor_sanity_check(); }
  virtual inline const char* type() const { return "AdaGrad"; }

 protected:
  virtual void ComputeUpdateValue(int param_id, Dtype rate);
  void constructor_sanity_check() {
    CHECK_EQ(0, this->param_.momentum())
        << "Momentum cannot be used with AdaGrad.";
  }

  DISABLE_COPY_AND_ASSIGN(AdaGradSolver);
};


template <typename Dtype>
class RMSPropSolver : public SGDSolver<Dtype> {
 public:
  explicit RMSPropSolver(const SolverParameter& param)
      : SGDSolver<Dtype>(param) { constructor_sanity_check(); }
  explicit RMSPropSolver(const string& param_file)
      : SGDSolver<Dtype>(param_file) { constructor_sanity_check(); }
  virtual inline const char* type() const { return "RMSProp"; }

 protected:
  virtual void ComputeUpdateValue(int param_id, Dtype rate);
  void constructor_sanity_check() {
    CHECK_EQ(0, this->param_.momentum())
        << "Momentum cannot be used with RMSProp.";
    CHECK_GE(this->param_.rms_decay(), 0)
        << "rms_decay should lie between 0 and 1.";
    CHECK_LT(this->param_.rms_decay(), 1)
        << "rms_decay should lie between 0 and 1.";
  }

  DISABLE_COPY_AND_ASSIGN(RMSPropSolver);
};

template <typename Dtype>
class AdaDeltaSolver : public SGDSolver<Dtype> {
 public:
  explicit AdaDeltaSolver(const SolverParameter& param)
      : SGDSolver<Dtype>(param) { AdaDeltaPreSolve(); }
  explicit AdaDeltaSolver(const string& param_file)
      : SGDSolver<Dtype>(param_file) { AdaDeltaPreSolve(); }
  virtual inline const char* type() const { return "AdaDelta"; }

 protected:
  void AdaDeltaPreSolve();
  virtual void ComputeUpdateValue(int param_id, Dtype rate);

  DISABLE_COPY_AND_ASSIGN(AdaDeltaSolver);
};

/**
 * @brief AdamSolver, an algorithm for first-order gradient-based optimization
 *        of stochastic objective functions, based on adaptive estimates of
 *        lower-order moments. Described in [1].
 *
 * [1] D. P. Kingma and J. L. Ba, "ADAM: A Method for Stochastic Optimization."
 *     arXiv preprint arXiv:1412.6980v8 (2014).
 */
template <typename Dtype>
class AdamSolver : public SGDSolver<Dtype> {
 public:
  explicit AdamSolver(const SolverParameter& param)
      : SGDSolver<Dtype>(param) { AdamPreSolve();}
  explicit AdamSolver(const string& param_file)
      : SGDSolver<Dtype>(param_file) { AdamPreSolve(); }
  virtual inline const char* type() const { return "Adam"; }

 protected:
  void AdamPreSolve();
  virtual void ComputeUpdateValue(int param_id, Dtype rate);

  DISABLE_COPY_AND_ASSIGN(AdamSolver);
};

}  // namespace caffe

#endif  // CAFFE_SGD_SOLVERS_HPP_
