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/*! \file
    \brief Template for a pipelined softmax-GEMM kernel.
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/numeric_types.h"
#include "cutlass/arch/arch.h"

#include "cutlass/layout/matrix.h"
#include "cutlass/gemm/threadblock/default_mma_core.h"
#include "cutlass/gemm/threadblock/mma_softmax_mainloop_fusion_multistage.h"
#include "cutlass/transform/threadblock/predicated_scale_bias_vector_iterator.h"
#include "cutlass/transform/threadblock/predicated_scale_bias_vector_access_iterator.h"
#include "cutlass/transform/threadblock/regular_scale_bias_vector_access_iterator.h"
#include "cutlass/gemm/warp/scale_bias_tile_iterator.h"
#include "cutlass/transform/threadblock/predicated_tile_iterator.h"

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

namespace cutlass {
namespace gemm {
namespace threadblock {

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

template <
    /// Element type for A matrix operand
    typename ElementA,
    /// Layout type for A matrix operand
    typename LayoutA,
    /// Access granularity of A matrix in units of elements
    int kAlignmentA,
    /// Element type for B matrix operand
    typename ElementB,
    /// Layout type for B matrix operand
    typename LayoutB,
    /// Access granularity of B matrix in units of elements
    int kAlignmentB,
    /// Element type for Scale/Bias vectors
    typename ElementScaleBias,
    /// Layout type for Scale/Bias vectors
    typename LayoutScaleBias,
    /// Element type for internal accumulation
    typename ElementAccumulator,
    /// Layout type for C and D matrix operands
    typename LayoutC,
    /// Operator class tag
    typename OperatorClass,
    /// Tag indicating architecture to tune for
    typename ArchTag,
    /// Threadblock-level tile size (concept: GemmShape)
    typename ThreadblockShape,
    /// Warp-level tile size (concept: GemmShape)
    typename WarpShape,
    /// Instruction-level tile size (concept: GemmShape)
    typename InstructionShape,
    /// Number of stages used in the pipelined mainloop
    int Stages,
    /// Whether problem has been transformed. This determines to which operand
    /// the softmax is applied.
    bool InternalTranspose,
    /// Operation perfomed by GEMM
    typename Operator,
    /// Store the accumulators in row major or column major.  Row major is used
    /// when output layout is interleaved.
    bool AccumulatorsInRowMajor = false,
    /// Use zfill or predicate for SM80 out-of-bound cp.async 
    SharedMemoryClearOption SharedMemoryClear = SharedMemoryClearOption::kNone
    >
struct DefaultMmaSoftmaxMainloopFusion {

  static cutlass::arch::CacheOperation::Kind const CacheOpA =
      ((sizeof_bits<ElementA>::value * kAlignmentA) == 128)
          ? cutlass::arch::CacheOperation::Global
          : cutlass::arch::CacheOperation::Always;

  static cutlass::arch::CacheOperation::Kind const CacheOpB =
      ((sizeof_bits<ElementB>::value * kAlignmentB) == 128)
          ? cutlass::arch::CacheOperation::Global
          : cutlass::arch::CacheOperation::Always;

  static cutlass::arch::CacheOperation::Kind const CacheOpGammaBeta = CacheOpA;

  // Define the MmaCore components
  using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
      ThreadblockShape, WarpShape, InstructionShape, ElementA, LayoutA,
      ElementB, LayoutB, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp,
      Stages, Operator, false, CacheOpA, CacheOpB>;

  // Define iterators over tiles from the A operand
  using ThreadMapA = typename MmaCore::IteratorThreadMapA;
  using AccessTypeA = cutlass::Array<ElementA, kAlignmentA>;
  using IteratorA =
      cutlass::transform::threadblock::PredicatedTileAccessIterator<
          cutlass::MatrixShape<ThreadblockShape::kM, ThreadblockShape::kK>,
          ElementA, LayoutA, 1, ThreadMapA, AccessTypeA>;

  // Define iterators over tiles from the B operand
  using ThreadMapB = typename MmaCore::IteratorThreadMapB;
  using AccessTypeB = cutlass::Array<ElementB, kAlignmentB>;
  using IteratorB =
      cutlass::transform::threadblock::PredicatedTileAccessIterator<
          cutlass::MatrixShape<ThreadblockShape::kK, ThreadblockShape::kN>,
          ElementB, LayoutB, 0, ThreadMapB, AccessTypeB>;

  /// Define iterators over tiles from scale/bias vectors
  using IteratorNormSum =
      cutlass::transform::threadblock::PredicatedScaleBiasVectorIterator<
          cutlass::MatrixShape<1, WarpShape::kN>,
          ElementScaleBias,
          LayoutScaleBias>;

  // Define the threadblock-scoped multistage matrix multiply
  using ThreadblockMma = cutlass::gemm::threadblock::MmaSoftmaxMainloopFusionMultistage<
      typename MmaCore::Shape, IteratorA, typename MmaCore::SmemIteratorA,
      MmaCore::kCacheOpA, IteratorB, typename MmaCore::SmemIteratorB,
      MmaCore::kCacheOpB, IteratorNormSum,
      ElementAccumulator, layout::RowMajor,
      typename MmaCore::MmaPolicy, Stages, InternalTranspose, SharedMemoryClear>;
};

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

} // namespace threadblock
} // namespace gemm
} // namespace cutlass 

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