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/*! \file
    \brief This defines a "fragment" iterator for visiting the fragments of an accumulator tile
      that participate in one warp-level store operation.

      Typically, the accumulator tile is the largest single block of register-backed storage 
      within the kernel. Storing it to memory is best accomplished by partitioning it into
      smaller tiles and storing these sequentially.

      Round trips through shared memory during the Epilogue phase require partitioning, as
      shared memory capacity is typically insufficient for a threadblock's total accumulator
      size.
*/

#pragma once

#if !(defined(__clang__) && defined(__CUDA__))

#include "cutlass/wmma_array.h"
#include "cutlass/layout/matrix.h"

#include "cutlass/epilogue/warp/wmma_tensor_op_policy.h"

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

namespace cutlass {
namespace epilogue {
namespace warp {

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

/// 
template <
  typename WarpShape,         ///< shape of warp-level GEMM (concept: MatrixShape)
  typename OperatorShape,     ///< matrix multiply operation shape (concept: gemm::GemmShape)
  typename OperatorElementC,  ///< matrix multiply operation data type (concept: data type)
  typename OperatorFragmentC, ///< matrix multiply operation fragment (concept: nvcuda::cuda::fragment)
  typename Layout             ///< target shared memory layout
>
class FragmentIteratorWmmaTensorOp;

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

/// Partial specialization for row-major shared memory
template <
  typename WarpShape_,         ///< shape of the warp-level GEMM tile
  typename OperatorShape_,     ///< matrix multiply operation shape (concept: gemm::GemmShape)
  typename OperatorElementC_,  ///< matrix multiply operation data type (concept: data type)
  typename OperatorFragmentC_  ///< matrix multiply operation fragment (concept: nvcuda::cuda::fragment)
>
class FragmentIteratorWmmaTensorOp<WarpShape_, OperatorShape_, OperatorElementC_, OperatorFragmentC_, layout::RowMajor> {
public:

  using WarpShape = WarpShape_;
  using OperatorShape = OperatorShape_;
  using OperatorElementC = OperatorElementC_;
  using OperatorFragmentC = OperatorFragmentC_;
  using Layout = layout::RowMajor;

  using Policy = WmmaTensorOpPolicy<WarpShape, OperatorShape, Layout>;

  /// This is the fragment size produced by one access of the iterator.
  using Fragment = WmmaFragmentArray<OperatorFragmentC, Policy::OperatorCount::kColumn>;

  /// This is the complete warp-level accumulator tile.
  using AccumulatorTile = WmmaFragmentArray<OperatorFragmentC, Policy::OperatorCount::kCount>;

  using OutputAccumulatorTile = AccumulatorTile;

private:

  /// Internal access type
  using AccessType = WmmaFragmentArray<OperatorFragmentC, Policy::kWmmaFragmentsPerAccess>;

private:

  //
  // Data members
  //

  /// Accumulator tile
  AccessType const *accumulators_;

  /// Internal index
  int index_;

public:

  /// Constructs an iterator
  CUTLASS_HOST_DEVICE
  FragmentIteratorWmmaTensorOp(AccumulatorTile const &accum): 
    accumulators_(reinterpret_cast<AccessType const *>(&accum)), 
    index_(0) { 
  }

  /// Increments
  CUTLASS_HOST_DEVICE
  FragmentIteratorWmmaTensorOp &operator++() {
    ++index_;
    return *this;
  }

  /// Decrements
  CUTLASS_HOST_DEVICE
  FragmentIteratorWmmaTensorOp &operator--() {
    --index_;
    return *this;
  }

  /// Loads a fragment from the referenced part of the accumulator tile
  CUTLASS_HOST_DEVICE
  void load(Fragment &frag, int index_offset = 0) const {
    AccessType *frag_ptr = reinterpret_cast<AccessType *>(&frag);

    CUTLASS_PRAGMA_UNROLL
    for(int n=0; n < Policy::OperatorCount::kColumn; n++) {
      
      int accumulator_access_offset = index_ * Policy::OperatorCount::kColumn + n;

      frag_ptr[n] = accumulators_[accumulator_access_offset];
    }
  }
};


} // namespace warp
} // namespace epilogue
} // namespace cutlass

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

#else
#error (defined(__clang__) && defined(__CUDA__))
#endif // !defined(__clang__)

