text: /*
   * Copyright (c) 2017, David Fridovich-Keil.
   * All rights reserved.
   *
   * Redistribution and use in source and binary forms, with or without
   * modification, are permitted provided that the following conditions are
   * met:
   *
   *    1. Redistributions of source code must retain the above copyright
   *       notice, this list of conditions and the following disclaimer.
   *
   *    2. 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.
   *
   *    3. Neither the name of the copyright holder 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 HOLDER OR CONTRIBUTORS BE
   * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
   * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
   * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
   * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
   * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
   * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
   * POSSIBILITY OF SUCH DAMAGE.
   *
   * Please contact the author(s) of this library if you have any questions.
   * Authors: David Fridovich-Keil   ( dfk@eecs.berkeley.edu )
   *          Sara Fridovich-Keil    ( saraf@princeton.edu )
   */
  
  ///////////////////////////////////////////////////////////////////////////////
  //
  // Defines the backprop parameters base struct.
  //
  // ////////////////////////////////////////////////////////////////////////////
  
  #ifndef MININET_TRAINER_BACKPROP_PARAMS_H
  #define MININET_TRAINER_BACKPROP_PARAMS_H
  
  #include "../util/types.h"
  
  namespace mininet {
  
  struct BackpropParams {
    // Maximum allowable average loss (on the validation set) for a batch.
    // Used as a stopping criterion.
    double max_avg_loss_ = 1e-4;
  
    // Batch size. Amount of data to be used in each SGD iteration.
    size_t batch_size_ = 20;
  
    // Number of iterations per epoch.
    size_t num_iters_per_epoch_ = 10;
  
    // Number of epochs.
    size_t num_epochs_ = 10;
  
    // Initial learning rate.
    double learning_rate_ = 0.1;
  
    // Learning rate decay factor (multiply by this each new epoch).
    double learning_rate_decay_ = 0.5;
  
    // Momentum multiplier.
    double momentum_ = 0.0;
  
    // Weight decay rate (L2 regularizer).
    double weight_decay_ = 0.0;
  }; //\struct BackpropParameters
  
  }  //\namespace mininet
  
  #endif
  