distconv_layer_norm.hpp

////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2014-2022, 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_LAYERSE_REGULARIZERS_DISTCONV_LAYER_NORM
#define LBANN_LAYERSE_REGULARIZERS_DISTCONV_LAYER_NORM

#ifdef LBANN_HAS_DISTCONV

namespace distconv {
template <typename Backend, typename DataType>
class LayerNormalization
{
  using LocaleMPI = tensor::LocaleMPI;

  template <typename Allocator>
  using DCTensor = tensor::Tensor<DataType, LocaleMPI, Allocator>;

public:
  LayerNormalization(Backend& backend, DataType epsilon)
    : m_backend(backend), m_epsilon(epsilon)
  {}

  template <typename Allocator>
  void calculate_forward_stats(const DCTensor<Allocator>& input,
                               DCTensor<Allocator>& statistics);

  template <typename Allocator>
  void apply_normalization(const DCTensor<Allocator>& input,
                           DCTensor<Allocator>& statistics,
                           DCTensor<Allocator>& output);

  template <typename Allocator>
  void calculate_backward_stats(const DCTensor<Allocator>& input,
                                const DCTensor<Allocator>& output_grad,
                                const DCTensor<Allocator>& statistics,
                                DCTensor<Allocator>& statistics_grad);

  template <typename Allocator>
  void apply_grad(const DCTensor<Allocator>& input,
                  const DCTensor<Allocator>& output_grad,
                  const DCTensor<Allocator>& statistics,
                  const DCTensor<Allocator>& statistics_grad,
                  DCTensor<Allocator>& input_grad);

protected:
  Backend& m_backend;

private:
  DataType m_epsilon;

}; // class definition LayerNorm
} // namespace distconv

#endif // LBANN_HAS_DISTCONV
#endif // LBANN_LAYERS_REGULARIZERS_DISTCONV_LAYER_NORM