////////////////////////////////////////////////////////////////////////////////
// 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_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED
#define LBANN_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED

#include "lbann/layers/data_type_layer.hpp"

namespace lbann {

/** @brief Cutout a square from an image
 *
 *  Expects two inputs: a 3D image tensor in CHW format and a scalar
 *  length of the cutout square.
 */
template <typename TensorDataType, data_layout Layout, El::Device Device>
class cutout_layer : public data_type_layer<TensorDataType>
{
  static_assert(Layout == data_layout::DATA_PARALLEL,
                "cutout_layer only supports DATA_PARALLEL");
  static_assert(Device == El::Device::CPU, "cutou_layer only supports CPU");

public:
  /** @name Public Types */
  ///@{

  /** @brief The tensor type expected in this object. */
  using AbsDistMatrixType = El::AbstractDistMatrix<TensorDataType>;

  ///@}

public:
  cutout_layer(lbann_comm* comm) : data_type_layer<TensorDataType>(comm)
  {
    this->m_expected_num_parent_layers = 2;
  }

  cutout_layer* copy() const override { return new cutout_layer(*this); }

  /** @name Serialization */
  ///@{

  template <typename ArchiveT>
  void serialize(ArchiveT& ar);

  ///@}

  std::string get_type() const override { return "cutout"; }
  data_layout get_data_layout() const override { return Layout; }
  El::Device get_device_allocation() const override { return Device; }

  void fp_compute() override;

protected:
  friend class cereal::access;
  cutout_layer() : cutout_layer(nullptr) {}

  void setup_dims(DataReaderMetaData& dr_metadata) override;

  void write_specific_proto(lbann_data::Layer& proto) const final;
};

#ifndef LBANN_CUTOUT_LAYER_INSTANTIATE
#define PROTO(T)                                                               \
  extern template class cutout_layer<T,                                        \
                                     data_layout::DATA_PARALLEL,               \
                                     El::Device::CPU>

#include "lbann/macros/instantiate.hpp"
#undef PROTO
#endif // LBANN_CUTOUT_LAYER_INSTANTIATE

} // namespace lbann

#endif // LBANN_LAYERS_IMAGE_CUTOUT_HPP_INCLUDED
