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/*! \file
    \brief Defines basic properties needed by CTA-level GEMMs assuming expectations about data
      layout of the global memory fragments, data types, and internal tile sizes.

      Partial specializations for threadblock::Mma operations targeting TensorOp instructions.
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/array.h"

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


#include "cutlass/layout/tensor_op_multiplicand_sm70.h"
#include "cutlass/transform/pitch_linear_thread_map.h"
#include "cutlass/transform/threadblock/regular_tile_iterator_tensor_op_sm70.h"

#include "cutlass/gemm/warp/mma_tensor_op_sm70.h"
#include "cutlass/gemm/threadblock/default_mma_core.h"

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

namespace cutlass {
namespace gemm {
namespace threadblock {

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

/// Partial specialization:
///
///   A: column-major
///   B: row-major
///   Operator: tensor op class
///
/// This uses the default warp-level operator given tile sizes
template <
    /// Shape of threadblock-scoped matrix multiply operator (concept:
    /// GemmShape)
    typename Shape_,
    /// Shape of warp-level matrix multiply operator (concept: GemmShape)
    typename WarpShape_,
    /// Data type of A operand
    typename ElementA_,
    /// Data type of B operand
    typename ElementB_,
    /// Data type of accumulator
    typename ElementC_,
    /// Layout of accumulator
    typename LayoutC_,
    /// Operation performed by GEMM
    typename Operator_>
struct DefaultMmaCore<Shape_, WarpShape_, GemmShape<8, 8, 4>, ElementA_,
                      layout::ColumnMajor, ElementB_, layout::RowMajor,
                      ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_
                      > {
  using Shape = Shape_;
  using WarpShape = WarpShape_;
  using InstructionShape = GemmShape<8, 8, 4>;
  using ElementA = ElementA_;
  using LayoutA = layout::ColumnMajor;
  using ElementB = ElementB_;
  using LayoutB = layout::RowMajor;
  using ElementC = ElementC_;
  using LayoutC = LayoutC_;
  using OperatorClass = arch::OpClassTensorOp;

  /// Default Operator
  using Operator = Operator_;

  /// Number of warps present
  using WarpCount = GemmShape<
    Shape::kM / WarpShape::kM,
    Shape::kN / WarpShape::kN,
    Shape::kK / WarpShape::kK
  >;

  // Divisility requirements
  static_assert(
    !(Shape::kM % WarpShape::kM) &&
    !(Shape::kN % WarpShape::kN),
    "Threadblock-scoped GEMM should be divisible by warp-scoped GEMM size."
  );

  /// Number of threads per warp
  static int const kWarpSize = warp::WarpSize<arch::OpClassTensorOp>::value;

  /// Number of threads total
  static int const kThreads = WarpCount::kCount * kWarpSize;

  /// Size of a threadblock-scoped access
  static int const kAccessSizeInBits = 128;

  //
  // Shared memory layouts
  //

  using SmemLayoutA = 
    layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<
      sizeof_bits<ElementA>::value>;

  // Shared memory layout
  using SmemLayoutB = 
    layout::RowMajorVoltaTensorOpMultiplicandBCongruous<
      sizeof_bits<ElementB>::value>;

  //
  // Iterators to write to shared memory
  //

  /// ThreadMap of iterator A
  using IteratorThreadMapA = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kM, Shape::kK>,
    kThreads,
    layout::PitchLinearShape<8, 4>,
    kAccessSizeInBits / sizeof_bits<ElementA>::value
  >;

  /// Shared memory iterator to A operand
  using SmemIteratorA = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kM, Shape::kK>, 
    ElementA, 
    SmemLayoutA,
    1,
    IteratorThreadMapA
  >;

  /// Policy of iterator B
  using IteratorThreadMapB = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kN, Shape::kK>,
    kThreads,
    layout::PitchLinearShape<8, 4>,
    kAccessSizeInBits / sizeof_bits<ElementB>::value
  >;

  /// Shared memory iterator to B operand
  using SmemIteratorB = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kK, Shape::kN>, 
    ElementB, 
    SmemLayoutB,
    0,
    IteratorThreadMapB
  >;

  //
  // Warp-level matrix multiply operator
  //

  // Define the warp-level tensor op
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
    cutlass::arch::Mma<
      cutlass::gemm::GemmShape<16, 16, 4>,
      32,
      ElementA,
      LayoutA,
      ElementB,
      LayoutB,
      ElementC,
      cutlass::layout::RowMajor,
      cutlass::arch::OpMultiplyAdd
    >,
    cutlass::MatrixShape<1, 1>
  >;

  using MmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
    WarpShape,
    ElementA,
    SmemLayoutA,
    ElementB,
    SmemLayoutB,
    ElementC,
    LayoutC,
    Policy
  >;

  /// Policy used to define MmaPipelined 
  using MmaPolicy = MmaPolicy<
    MmaTensorOp,
    MatrixShape<0, 0>,
    MatrixShape<0, 0>,
    WarpCount::kK
  >;
};

/// Partial specialization:
///
///   A: row-major
///   B: column-major
///   Operator: tensor op class
///
/// This uses the default warp-level operator given tile sizes
template <
    /// Shape of threadblock-scoped matrix multiply operator (concept:
    /// GemmShape)
    typename Shape_,
    /// Shape of warp-level matrix multiply operator (concept: GemmShape)
    typename WarpShape_,
    /// Data type of A operand
    typename ElementA_,
    /// Data type of B operand
    typename ElementB_,
    /// Data type of accumulator
    typename ElementC_,
    /// Layout of accumulator
    typename LayoutC_,
    /// Operation performed by GEMM
    typename Operator_>
struct DefaultMmaCore<Shape_, WarpShape_, GemmShape<8, 8, 4>, ElementA_,
                      layout::RowMajor, ElementB_, layout::ColumnMajor,
                      ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_
                      > {
  using Shape = Shape_;
  using WarpShape = WarpShape_;
  using InstructionShape = GemmShape<8, 8, 4>;
  using ElementA = ElementA_;
  using LayoutA = layout::RowMajor;
  using ElementB = ElementB_;
  using LayoutB = layout::ColumnMajor;
  using ElementC = ElementC_;
  using LayoutC = LayoutC_;
  using OperatorClass = arch::OpClassTensorOp;

  /// Default Operator
  using Operator = Operator_;

  /// Number of warps present
  using WarpCount = GemmShape<
    Shape::kM / WarpShape::kM,
    Shape::kN / WarpShape::kN,
    Shape::kK / WarpShape::kK
  >;

  // Divisility requirements
  static_assert(
    !(Shape::kM % WarpShape::kM) &&
    !(Shape::kN % WarpShape::kN),
    "Threadblock-scoped GEMM should be divisible by warp-scoped GEMM size."
  );

  /// Number of threads per warp
  static int const kWarpSize = warp::WarpSize<arch::OpClassTensorOp>::value;

  /// Number of threads total
  static int const kThreads = WarpCount::kCount * kWarpSize;

  /// Size of a threadblock-scoped access
  static int const kAccessSizeInBits = 128;

  //
  // Shared memory layouts
  //

  using SmemLayoutA = layout::RowMajorVoltaTensorOpMultiplicandCrosswise<
      sizeof_bits<ElementA>::value, Shape::kK>;

  // Shared memory layout
  using SmemLayoutB = layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise<
      sizeof_bits<ElementB>::value, Shape::kK>;

  //
  // Iterators to write to shared memory
  //

  /// ThreadMap of iterator A
  using IteratorThreadMapA = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kK, Shape::kM>,
    kThreads,
    layout::PitchLinearShape<4, 8>,
    kAccessSizeInBits / sizeof_bits<ElementA>::value
  >;

  /// Shared memory iterator to A operand
  using SmemIteratorA = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kM, Shape::kK>, 
    ElementA, 
    SmemLayoutA,
    0,
    IteratorThreadMapA
  >;

  /// ThreadMap of iterator B
  using IteratorThreadMapB = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kK, Shape::kN>,
    kThreads,
    layout::PitchLinearShape<4, 8>,
    kAccessSizeInBits / sizeof_bits<ElementB>::value
  >;

  /// Shared memory iterator to B operand
  using SmemIteratorB = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kK, Shape::kN>, 
    ElementB, 
    SmemLayoutB,
    1,
    IteratorThreadMapB
  >;

  //
  // Warp-level matrix multiply operator
  //

  // Define the warp-level tensor op
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
    cutlass::arch::Mma<
      cutlass::gemm::GemmShape<16, 16, 4>,
      32,
      ElementA,
      LayoutA,
      ElementB,
      LayoutB,
      ElementC,
      cutlass::layout::RowMajor,
      cutlass::arch::OpMultiplyAdd
    >,
    cutlass::MatrixShape<1, 1>
  >;

  using MmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
    WarpShape,
    ElementA,
    SmemLayoutA,
    ElementB,
    SmemLayoutB,
    ElementC,
    LayoutC,
    Policy
  >;

  /// Policy used to define MmaPipelined 
  using MmaPolicy = MmaPolicy<
    MmaTensorOp,
    MatrixShape<0, 0>,
    MatrixShape<0, 0>,
    WarpCount::kK
  >;
};

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

/// Partial specialization:
///
///   A: row-major
///   B: row-major
///   Operator: tensor op class
///
/// This uses the default warp-level operator given tile sizes
template <
    /// Shape of threadblock-scoped matrix multiply operator (concept:
    /// GemmShape)
    typename Shape_,
    /// Shape of warp-level matrix multiply operator (concept: GemmShape)
    typename WarpShape_,
    /// Data type of A operand
    typename ElementA_,
    /// Data type of B operand
    typename ElementB_,
    /// Data type of accumulator
    typename ElementC_,
    /// Layout of accumulator
    typename LayoutC_,
    /// Operation performed by GEMM
    typename Operator_>
struct DefaultMmaCore<Shape_, WarpShape_, GemmShape<8, 8, 4>, ElementA_,
                      layout::RowMajor, ElementB_, layout::RowMajor, ElementC_,
                      LayoutC_, arch::OpClassTensorOp, 2, Operator_
                      > {
  using Shape = Shape_;
  using WarpShape = WarpShape_;
  using InstructionShape = GemmShape<8, 8, 4>;
  using ElementA = ElementA_;
  using LayoutA = layout::RowMajor;
  using ElementB = ElementB_;
  using LayoutB = layout::RowMajor;
  using ElementC = ElementC_;
  using LayoutC = LayoutC_;
  using OperatorClass = arch::OpClassTensorOp;

  /// Default Operator
  using Operator = Operator_;

  /// Number of warps present
  using WarpCount = GemmShape<
    Shape::kM / WarpShape::kM,
    Shape::kN / WarpShape::kN,
    Shape::kK / WarpShape::kK
  >;

  // Divisility requirements
  static_assert(
    !(Shape::kM % WarpShape::kM) &&
    !(Shape::kN % WarpShape::kN),
    "Threadblock-scoped GEMM should be divisible by warp-scoped GEMM size."
  );

  /// Number of threads per warp
  static int const kWarpSize = warp::WarpSize<arch::OpClassTensorOp>::value;

  /// Number of threads total
  static int const kThreads = WarpCount::kCount * kWarpSize;

  /// Size of a threadblock-scoped access
  static int const kAccessSizeInBits = 128;

  //
  // Shared memory layouts
  //

  using SmemLayoutA = layout::RowMajorVoltaTensorOpMultiplicandCrosswise<
      sizeof_bits<ElementA>::value, Shape::kK>;

  // Shared memory layout
  using SmemLayoutB = layout::RowMajorVoltaTensorOpMultiplicandBCongruous<
      sizeof_bits<ElementB>::value>;

  //
  // Iterators to write to shared memory
  //

  /// ThreadMap of iterator A
  using IteratorThreadMapA = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kK, Shape::kM>,
    kThreads,
    layout::PitchLinearShape<4, 8>,
    kAccessSizeInBits / sizeof_bits<ElementA>::value
  >;

  /// Shared memory iterator to A operand
  using SmemIteratorA = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kM, Shape::kK>, 
    ElementA, 
    SmemLayoutA,
    0,
    IteratorThreadMapA
  >;

  /// Policy of iterator B
  using IteratorThreadMapB = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kN, Shape::kK>,
    kThreads,
    layout::PitchLinearShape<8, 4>,
    kAccessSizeInBits / sizeof_bits<ElementB>::value
  >;

  /// Shared memory iterator to B operand
  using SmemIteratorB = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kK, Shape::kN>, 
    ElementB, 
    SmemLayoutB,
    0,
    IteratorThreadMapB
  >;

  //
  // Warp-level matrix multiply operator
  //

  // Define the warp-level tensor op
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
    cutlass::arch::Mma<
      cutlass::gemm::GemmShape<16, 16, 4>,
      32,
      ElementA,
      LayoutA,
      ElementB,
      LayoutB,
      ElementC,
      cutlass::layout::RowMajor,
      cutlass::arch::OpMultiplyAdd
    >,
    cutlass::MatrixShape<1, 1>
  >;

  using MmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
    WarpShape,
    ElementA,
    SmemLayoutA,
    ElementB,
    SmemLayoutB,
    ElementC,
    LayoutC,
    Policy
  >;

  /// Policy used to define MmaPipelined 
  using MmaPolicy = MmaPolicy<
    MmaTensorOp,
    MatrixShape<0, 0>,
    MatrixShape<0, 0>,
    WarpCount::kK
  >;
};

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

/// Partial specialization:
///
///   A: column-major
///   B: column-major
///   Operator: tensor op class
///
/// This uses the default warp-level operator given tile sizes
template <
    /// Shape of threadblock-scoped matrix multiply operator (concept:
    /// GemmShape)
    typename Shape_,
    /// Shape of warp-level matrix multiply operator (concept: GemmShape)
    typename WarpShape_,
    /// Data type of A operand
    typename ElementA_,
    /// Data type of B operand
    typename ElementB_,
    /// Data type of accumulator
    typename ElementC_,
    /// Layout of accumulator
    typename LayoutC_,
    /// Operation performed by GEMM
    typename Operator_>
struct DefaultMmaCore<Shape_, WarpShape_, GemmShape<8, 8, 4>, ElementA_,
                      layout::ColumnMajor, ElementB_, layout::ColumnMajor,
                      ElementC_, LayoutC_, arch::OpClassTensorOp, 2, Operator_
                      > {
  using Shape = Shape_;
  using WarpShape = WarpShape_;
  using InstructionShape = GemmShape<8, 8, 4>;
  using ElementA = ElementA_;
  using LayoutA = layout::ColumnMajor;
  using ElementB = ElementB_;
  using LayoutB = layout::ColumnMajor;
  using ElementC = ElementC_;
  using LayoutC = LayoutC_;
  using OperatorClass = arch::OpClassTensorOp;

  /// Default Operator
  using Operator = Operator_;

  /// Number of warps present
  using WarpCount = GemmShape<
    Shape::kM / WarpShape::kM,
    Shape::kN / WarpShape::kN,
    Shape::kK / WarpShape::kK
  >;

  // Divisility requirements
  static_assert(
    !(Shape::kM % WarpShape::kM) &&
    !(Shape::kN % WarpShape::kN),
    "Threadblock-scoped GEMM should be divisible by warp-scoped GEMM size."
  );

  /// Number of threads per warp
  static int const kWarpSize = warp::WarpSize<arch::OpClassTensorOp>::value;

  /// Number of threads total
  static int const kThreads = WarpCount::kCount * kWarpSize;

  /// Size of a threadblock-scoped access
  static int const kAccessSizeInBits = 128;

  //
  // Shared memory layouts
  //

  using SmemLayoutA = layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<
      sizeof_bits<ElementA>::value>;

  // Shared memory layout
  using SmemLayoutB = layout::ColumnMajorVoltaTensorOpMultiplicandCrosswise<
      sizeof_bits<ElementB>::value, Shape::kK>;

  //
  // Iterators to write to shared memory
  //

  /// ThreadMap of iterator A
  using IteratorThreadMapA = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kM, Shape::kK>,
    kThreads,
    layout::PitchLinearShape<8, 4>,
    kAccessSizeInBits / sizeof_bits<ElementA>::value
  >;

  /// Shared memory iterator to A operand
  using SmemIteratorA = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kM, Shape::kK>, 
    ElementA, 
    SmemLayoutA,
    1,
    IteratorThreadMapA
  >;

  /// ThreadMap of iterator B
  using IteratorThreadMapB = transform::PitchLinearWarpRakedThreadMap<
    layout::PitchLinearShape<Shape::kK, Shape::kN>,
    kThreads,
    layout::PitchLinearShape<4, 8>,
    kAccessSizeInBits / sizeof_bits<ElementB>::value
  >;

  /// Shared memory iterator to B operand
  using SmemIteratorB = transform::threadblock::RegularTileIterator<
    MatrixShape<Shape::kK, Shape::kN>, 
    ElementB, 
    SmemLayoutB,
    1,
    IteratorThreadMapB
  >;

  //
  // Warp-level matrix multiply operator
  //

  // Define the warp-level tensor op
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
    cutlass::arch::Mma<
      cutlass::gemm::GemmShape<16, 16, 4>,
      32,
      ElementA,
      LayoutA,
      ElementB,
      LayoutB,
      ElementC,
      cutlass::layout::RowMajor,
      cutlass::arch::OpMultiplyAdd
    >,
    cutlass::MatrixShape<1, 1>
  >;

  using MmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
    WarpShape,
    ElementA,
    SmemLayoutA,
    ElementB,
    SmemLayoutB,
    ElementC,
    LayoutC,
    Policy
  >;

  /// Policy used to define MmaPipelined 
  using MmaPolicy = MmaPolicy<
    MmaTensorOp,
    MatrixShape<0, 0>,
    MatrixShape<0, 0>,
    WarpCount::kK
  >;
};

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