variable_minibatch.hpp

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// 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.
//
// lbann_variable_minibatch .hpp .cpp - Callback for variable-size mini-batches

#ifndef LBANN_CALLBACKS_VARIABLE_MINIBATCH_HPP_INCLUDED
#define LBANN_CALLBACKS_VARIABLE_MINIBATCH_HPP_INCLUDED

#include "lbann/callbacks/callback.hpp"

namespace lbann {
namespace callback {

class variable_minibatch : public callback_base
{
public:
  variable_minibatch(size_t starting_mbsize);
  variable_minibatch(const variable_minibatch&) = default;
  variable_minibatch& operator=(const variable_minibatch&) = default;
  void on_train_begin(model* m) override;
  void on_epoch_end(model* m) override;

protected:
  virtual bool
  schedule(model* m, size_t& new_mbsize, float& new_lr, size_t& ramp_time) = 0;
  void change_learning_rate(model* m, float new_lr) const;
  float get_current_learning_rate(model* m) const;

  size_t m_starting_mbsize;
  size_t m_current_mini_batch_size;
  size_t m_ramp_count = 0;
  float m_lr_incr = 0.0f;
};

class step_minibatch : public variable_minibatch
{
public:
  step_minibatch(size_t starting_mbsize, size_t step, size_t ramp_time = 0);
  step_minibatch(const step_minibatch&) = default;
  step_minibatch& operator=(const step_minibatch&) = delete;
  step_minibatch* copy() const override { return new step_minibatch(*this); }
  std::string name() const override { return "step minibatch"; }

protected:
  bool schedule(model* m,
                size_t& new_mbsize,
                float& new_lr,
                size_t& ramp_time) override;

private:
  void write_specific_proto(lbann_data::Callback& proto) const final;

  size_t m_step;
  size_t m_ramp_time;
};

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

class minibatch_schedule : public variable_minibatch
{
public:
  struct minibatch_step
  {
    size_t epoch;
    size_t mbsize;
    float lr;
    size_t ramp_time;
    minibatch_step(size_t _epoch, size_t _mbsize, float _lr, size_t _ramp_time)
      : epoch(_epoch), mbsize(_mbsize), lr(_lr), ramp_time(_ramp_time)
    {}
  };

  minibatch_schedule(size_t starting_mbsize, std::vector<minibatch_step> steps);
  minibatch_schedule(const minibatch_schedule&) = default;
  minibatch_schedule& operator=(const minibatch_schedule&) = delete;
  minibatch_schedule* copy() const override
  {
    return new minibatch_schedule(*this);
  }
  std::string name() const override { return "minibatch schedule"; }

protected:
  bool schedule(model* m,
                size_t& new_mbsize,
                float& new_lr,
                size_t& ramp_time) override;

private:
  void write_specific_proto(lbann_data::Callback& proto) const final;

  std::vector<minibatch_step> m_steps;
};

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

} // namespace callback
} // namespace lbann

#endif // LBANN_CALLBACKS_VARIABLE_MINIBATCH_HPP_INCLUDED