hypergradient_adam_impl.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.

#ifndef LBANN_OPTIMIZERS_HYPERGRADIENT_ADAM_IMPL_HPP_INCLUDED
#define LBANN_OPTIMIZERS_HYPERGRADIENT_ADAM_IMPL_HPP_INCLUDED

#include "lbann/optimizers/hypergradient_adam.hpp"
#include "lbann/utils/serialize.hpp"

namespace lbann {

template <typename TensorDataType>
template <class Archive>
void hypergradient_adam<TensorDataType>::serialize(Archive& ar)
{
  ar(cereal::base_class<data_type_optimizer<TensorDataType>>(this),
     CEREAL_NVP(m_hyper_learning_rate),
     CEREAL_NVP(m_beta1),
     CEREAL_NVP(m_beta2),
     CEREAL_NVP(m_eps),
     CEREAL_NVP(m_current_beta1),
     CEREAL_NVP(m_current_beta2),
     CEREAL_NVP(m_moment1),
     CEREAL_NVP(m_moment2),
     CEREAL_NVP(m_old_gradient));
}

} // namespace lbann

#endif // LBANN_OPTIMIZERS_HYPERGRADIENT_ADAM_IMPL_HPP_INCLUDED