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/*! \file
    \brief Default warp-level GEMM operators selected by data type, size, and layouts of operands.
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/gemm/warp/mma_complex_tensor_op.h"
#include "cutlass/gemm/warp/mma_complex_tensor_op_fast_f32.h"
#include "cutlass/gemm/warp/mma_gaussian_complex_tensor_op.h"
#include "cutlass/layout/tensor_op_multiplicand_sm80.h"

namespace cutlass {
namespace gemm {
namespace warp {

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

template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Data type of A elements
    typename ElementA_,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA_,
    /// Data type of B elements
    typename ElementB_,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB_,
    /// Element type of C matrix
    typename ElementC_,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC_,
    /// Complex transform on A operand
    ComplexTransform TransformA = ComplexTransform::kNone,
    /// Complex transform on B operand
    ComplexTransform TransformB = ComplexTransform::kNone,
    /// Multiply-add operator (arch::OpMultiplyAddComplex, arch::OpMultiplyGaussianComplex)
    typename Operator_ = arch::OpMultiplyAddComplex>
struct DefaultMmaComplexTensorOp;

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

/// Partial specialization for complex<T>*complex<T> case
//  4 real-valued mma operations
//  A = (ar + j ai), B (br +j bi), D = AB
//  D = dr + j di = (ar*br - ai*bi) + j (ar*bi + ai*br) 
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Real-valued underlying type of complex-valued A operand
    typename RealElementA,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Real-valued underlying type of complex-valued B operand
    typename RealElementB,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Real-valued underlying type of complex-valued C operand
    typename RealElementC,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<RealElementA>,
    LayoutA,
    complex<RealElementB>,
    LayoutB,
    complex<RealElementC>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddComplex> {

  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        RealElementA,
        cutlass::layout::RowMajor,
        RealElementB,
        cutlass::layout::ColumnMajor,
        RealElementC,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaComplexTensorOp<
    WarpShape_,
    complex<RealElementA>,
    LayoutA,
    complex<RealElementB>,
    LayoutB,
    complex<RealElementC>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};

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

/// Partial specialization for complex<T>*complex<T> case using GaussianComplex operation
//  3 real-valued mma operations
//  A  = (ar + j ai), B = (br +j bi), D = AB
//  P1 = (ar + ai) * br, P2 = - ar * (br - bi), P3 = ai * (br + bi) 
//  D  = dr + j di = (P1 - P3) + j (P1 + P2)
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Real-valued underlying type of complex-valued A operand
    typename RealElementA,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Real-valued underlying type of complex-valued B operand
    typename RealElementB,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Real-valued underlying type of complex-valued C operand
    typename RealElementC,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<RealElementA>,
    LayoutA,
    complex<RealElementB>,
    LayoutB,
    complex<RealElementC>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddGaussianComplex> {

  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        RealElementA,
        cutlass::layout::RowMajor,
        RealElementB,
        cutlass::layout::ColumnMajor,
        RealElementC,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaGaussianComplexTensorOp<
    WarpShape_,
    complex<RealElementA>,
    LayoutA,
    complex<RealElementB>,
    LayoutB,
    complex<RealElementC>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};
/////////////////////////////////////////////////////////////////////////////////////////////////

/////////////////////////////////////////////////////////////////////////////////////////////////
/// Partial specialization - input and output types are complex<float>*complex<float> 
//  Use TF32 tensor operation internally
//  4 real-valued MMA.1688.F32.TF32 operations on TF32 
//  A = (ar + j ai), B (br +j bi), D = AB
//  D = dr + j di = (ar*br - ai*bi) + j (ar*bi + ai*br) 
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddComplex> {

  // Complex floating point tensor operation use MMA.1688.F32.TF32 mma instruction
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        tfloat32_t,
        cutlass::layout::RowMajor,
        tfloat32_t,
        cutlass::layout::ColumnMajor,
        float,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaComplexTensorOp<
    WarpShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};

/////////////////////////////////////////////////////////////////////////////////////////////////
/// Partial specialization - input and output types are complex<float>*complex<float> 
//  Use BF16 tensor operation internally
//  4 real-valued MMA.1688.F32.BF16 operations on BF16
//  A = (ar + j ai), B (br +j bi), D = AB
//  D = dr + j di = (ar*br - ai*bi) + j (ar*bi + ai*br) 
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddFastBF16> {

  // Complex floating point tensor operation use MMA.1688.F32.BF16 mma instruction
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        bfloat16_t,
        cutlass::layout::RowMajor,
        bfloat16_t,
        cutlass::layout::ColumnMajor,
        float,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaComplexTensorOp<
    WarpShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};

/////////////////////////////////////////////////////////////////////////////////////////////////
/// Partial specialization - input and output types are complex<float>*complex<float> 
//  Use F16 tensor operation internally
//  4 real-valued MMA.1688.F32.F16 operations on F16
//  A = (ar + j ai), B (br +j bi), D = AB
//  D = dr + j di = (ar*br - ai*bi) + j (ar*bi + ai*br) 
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddFastF16> {

  // Complex floating point tensor operation use MMA.1688.F32.F16 mma instruction
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        half_t,
        cutlass::layout::RowMajor,
        half_t,
        cutlass::layout::ColumnMajor,
        float,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaComplexTensorOp<
    WarpShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};

/////////////////////////////////////////////////////////////////////////////////////////////////
/// 3xTF32 or 4xTF32 (fast and accurate complex<float> operation)
/// Partial specialization - input and output types are complex<float> * complex<float> 
//  Use 3xTF32 or 4xTF32 tensor operation internally
//  4 real-valued MMA.1688.F32.TF32 operations on TF32 
//  A = (ar + j ai), B (br +j bi), D = AB
//  D = dr + j di = 3x[(ar*br - ai*bi) + j (ar*bi + ai*br)]
/////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////////////////

template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename WarpShape_,
    /// Shape of one matrix production operation (concept: GemmShape)
    typename InstructionShape_,
    /// Layout of A matrix (concept: MatrixLayout)
    typename LayoutA,
    /// Layout of B matrix (concept: MatrixLayout)
    typename LayoutB,
    /// Layout of C matrix (concept: MatrixLayout)
    typename LayoutC,
    /// Complex transform on A operand
    ComplexTransform TransformA,
    /// Complex transform on B operand
    ComplexTransform TransformB>
struct DefaultMmaComplexTensorOp<
    WarpShape_,
    InstructionShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC,
    TransformA,
    TransformB,
    arch::OpMultiplyAddComplexFastF32> {

  // Complex floating point tensor operation use MMA.1688.F32.TF32 mma instruction
  using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
      cutlass::arch::Mma<
        InstructionShape_, 
        32, 
        tfloat32_t,
        cutlass::layout::RowMajor,
        tfloat32_t,
        cutlass::layout::ColumnMajor,
        float,
        cutlass::layout::RowMajor, 
        arch::OpMultiplyAdd>,
      cutlass::MatrixShape<1, 1>
    >;

  // Define the warp-level tensor op
  using Type = cutlass::gemm::warp::MmaComplexTensorOpFastF32<
    WarpShape_,
    complex<float>,
    LayoutA,
    complex<float>,
    LayoutB,
    complex<float>,
    LayoutC, 
    Policy,
    TransformA,
    TransformB>;
};

} // namespace warp
} // namespace gemm
} // namespace cutlass
