/***************************************************************************************************
 * Copyright (c) 2017 - 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 * SPDX-License-Identifier: BSD-3-Clause
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 * list of conditions and the following disclaimer.
 *
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 * this list of conditions and the following disclaimer in the documentation
 * and/or other materials provided with the distribution.
 *
 * 3. Neither the name of the copyright holder nor the names of its
 * contributors may be used to endorse or promote products derived from
 * this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
 * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 **************************************************************************************************/
/*! \file
  \brief Functor performing linear combination operations used by epilogues.
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/numeric_types.h"
#include "cutlass/array.h"
#include "cutlass/functional.h"
#include "cutlass/numeric_conversion.h"
#include "cutlass/epilogue/thread/scale_type.h"
#include "cutlass/epilogue/thread/linear_combination_params.h"

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace cutlass {
namespace epilogue {
namespace thread {

/////////////////////////////////////////////////////////////////////////////////////////////////

/// Applies a linear combination operator to an array of elements.
///
/// D = alpha * accumulator + beta * source + uniform
///
template <
  typename ElementOutput_,                             ///< Data type used to load and store tensors
  int Count,                                           ///< Number of elements computed per operation.
                                                       ///< Usually it is 128/sizeof_bits<ElementOutput_>,
                                                       ///< but we use 64 or 32 sometimes when there are not enough data to store
  typename ElementAccumulator_ = ElementOutput_,       ///< Accumulator data type
  typename ElementCompute_ = ElementOutput_,           ///< Data type used to compute linear combination
  FloatRoundStyle Round = FloatRoundStyle::round_to_nearest
>
class LeftSiLUAndMul {
public:

  using ElementOutput = ElementOutput_;
  using ElementAccumulator = ElementAccumulator_;
  using ElementCompute = ElementCompute_;

  static int const kCount = Count;
  using FragmentOutput = Array<ElementOutput, kCount>;
  using FragmentAccumulator = Array<ElementAccumulator, kCount>;
  using ComputeFragment = Array<ElementCompute, kCount>;

  static FloatRoundStyle const kRound = Round;

  struct Params{};

private:

  //
  // Data members
  //

  ElementCompute alpha_;
  ElementCompute beta_;

public:

  /// Constructs the function object, possibly loading from pointers in host memory
  CUTLASS_HOST_DEVICE
  LeftSiLUAndMul(Params const &/*params*/) {}

  /// Returns true if source is needed
  CUTLASS_HOST_DEVICE
  bool is_source_needed() const {
    return true;
  }

  /// Functionally required for serial reduction in the epilogue
  CUTLASS_HOST_DEVICE
  void set_k_partition(int k_partition, int k_partition_count) {
    assert(false);
  }

  /// Computes linear scaling: D = alpha * accumulator + beta * source
  CUTLASS_HOST_DEVICE
  FragmentOutput operator()(
    FragmentAccumulator const &lhs, 
    FragmentAccumulator const &rhs) const {

    // Convert source to interal compute numeric type
    NumericArrayConverter<ElementCompute, ElementAccumulator, kCount, Round> accumulator_to_compute;

    // Convert to destination numeric type
    NumericArrayConverter<ElementOutput, ElementCompute, kCount, Round> compute_to_output;

    ComputeFragment converted_lhs = accumulator_to_compute(lhs);
    ComputeFragment converted_rhs = accumulator_to_compute(rhs);

    cutlass::epilogue::thread::SiLu<ComputeFragment> silu;
    cutlass::multiplies<ComputeFragment> mul;
    auto silu_lhs = silu(converted_lhs);
    return compute_to_output(mul(silu_lhs, converted_rhs));
  }

  CUTLASS_HOST_DEVICE
  ElementOutput operator()(
      ElementAccumulator const& lhs,
      ElementAccumulator const& rhs
  ) const {
      ElementCompute convert_lhs(lhs); 
      ElementCompute convert_rhs(rhs); 
      cutlass::epilogue::thread::SiLu<ElementCompute> silu;
      cutlass::multiplies<ElementCompute> mul;
      auto silu_lhs = silu(convert_lhs);
      return ElementOutput(mul(silu_lhs, convert_rhs));
  }
};

/////////////////////////////////////////////////////////////////////////////////////////////////

} // namespace thread
} // namespace epilogue
} // namespace cutlass

/////////////////////////////////////////////////////////////////////////////////////////////////
