////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2014-2023, Lawrence Livermore National Security, LLC.
// Produced at the Lawrence Livermore National Laboratory.
// Written by the LBANN Research Team (B. Van Essen, et al.) listed in
// the CONTRIBUTORS file. <lbann-dev@llnl.gov>
//
// LLNL-CODE-697807.
// All rights reserved.
//
// This file is part of LBANN: Livermore Big Artificial Neural Network
// Toolkit. For details, see http://software.llnl.gov/LBANN or
// https://github.com/LLNL/LBANN.
//
// Licensed under the Apache License, Version 2.0 (the "Licensee"); 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.
//
// save_topk_models .hpp .cpp - Callback to save top k models
////////////////////////////////////////////////////////////////////////////////

#ifndef LBANN_CALLBACKS_CALLBACK_SAVE_TOPK_MODELS_HPP_INCLUDED
#define LBANN_CALLBACKS_CALLBACK_SAVE_TOPK_MODELS_HPP_INCLUDED

#include "lbann/callbacks/save_model.hpp"

namespace lbann {
namespace callback {

/** @class save_topk_models
 *  @brief Save the top K models for, e.g., inference and other analysis.
 *  @note May end up saving more than k models if multiple models
 *        (trainers) have the same metric score
 */
class save_topk_models : public save_model
{
public:
  /** @brief Constructor
   *  @param dir directory in which to save model
   *  @param k number of models to save, should be less than number of trainers
   *  @param metric_name evaluation metric
   *  @param ascending_ordering use ascending ordering for the topk; descending
   *        order is default.
   */
  save_topk_models(std::string dir,
                   int k,
                   std::string metric_name,
                   bool ascending_ordering = false)
    : save_model(dir, true),
      m_k(k),
      m_metric_name(metric_name),
      m_ascending_ordering(ascending_ordering)
  {}
  save_topk_models(const save_topk_models&) = default;
  save_topk_models& operator=(const save_topk_models&) = default;
  save_topk_models* copy() const override
  {
    return new save_topk_models(*this);
  }
  void on_test_end(model* m) override;
  std::string name() const override { return "save_topk_models"; }

private:
  // determine if a trainer's model is in top k, computation done by
  // trainer master processes
  bool am_in_topk(model* m);
  int m_k;
  std::string m_metric_name;
  bool m_ascending_ordering;
};

// Builder function
std::unique_ptr<callback_base> build_save_topk_models_callback_from_pbuf(
  const google::protobuf::Message&,
  std::shared_ptr<lbann_summary> const&);

} // namespace callback
} // namespace lbann

#endif // LBANN_CALLBACKS_CALLBACK_SAVE_TOPK_MODELS_HPP_INCLUDED
