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#include <iostream>
#include "cutlass/cutlass.h"
#include "cute/tensor.hpp"
#include "cute/atom/mma_atom.hpp"
#include "cutlass/numeric_types.h"
#include "cutlass/gemm/device/gemm_universal_adapter.h"
#include "cutlass/gemm/kernel/gemm_universal.hpp"
#include "cutlass/gemm/collective/collective_builder.hpp"
#include "cutlass/epilogue/dispatch_policy.hpp"
#include "cutlass/epilogue/collective/collective_builder.hpp"
#include "cutlass/epilogue/thread/activation.h"
#include "../../../../common/cutlass_unit_test.h"
#include "../../gemm_testbed_3x.hpp"

using namespace cute;

// * Test list
// 1. 128x128_tnt
// 2. 128x256_tnt
// 3. 256x128_tnt
// 4. 256x256_tnt

#if defined(CUTLASS_ARCH_MMA_SM100_SUPPORTED)

// 1. 
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x128x256_0_tnt_align32_q_1sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = cutlass::half_t;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_1, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_128, _128, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized1Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized1SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 2.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x256x256_0_tnt_align32_q_1sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = cutlass::half_t;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_1, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_128, _256, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized1Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized1SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 3.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x128x256_0_tnt_align32_q_2sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = cutlass::half_t;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_2, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_256, _128, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized2Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized2SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 4.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x256x256_0_tnt_align32_q_2sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = cutlass::half_t;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_2, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_256, _256, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized2Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized2SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 1.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x128x256_0_tnt_align32_q_1sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x128x256_0_tnt_align32_q_1sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 1,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 2.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x256x256_0_tnt_align32_q_1sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_128x256x256_0_tnt_align32_q_1sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 1,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 3.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x128x256_0_tnt_align32_q_2sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x128x256_0_tnt_align32_q_2sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 1,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 4.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x256x256_0_tnt_align32_q_2sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_f16_e4m3_256x256x256_0_tnt_align32_q_2sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 1,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}


// 1. 
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x128x256_0_tnt_align32_q_1sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = void;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_1, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_128, _128, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized1Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized1SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 2.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x256x256_0_tnt_align32_q_1sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = void;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_1, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_128, _256, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized1Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized1SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 3.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x128x256_0_tnt_align32_q_2sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = void;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_2, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_256, _128, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized2Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized2SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 4.
namespace cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x256x256_0_tnt_align32_q_2sm {

    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;
    using LayoutD = cutlass::layout::RowMajor;

    using ElementA = cutlass::float_e3m2_t;
    using ElementB = cutlass::float_e3m2_t;
    using ElementC = void;
    using ElementD = cutlass::float_e4m3_t;

    constexpr int kAlignmentA = 256;
    constexpr int kAlignmentB = 128;
    constexpr int kAlignmentD = 128 / cutlass::sizeof_bits<ElementD>::value;
    constexpr int kAlignmentC = cute::is_same_v<ElementC, void> ? kAlignmentD : 128 / cutlass::sizeof_bits<ElementC>::value;

    using ProblemShape = Shape<int,int,int,int>;
    using ClusterShape = cute::Shape<cute::_2, cute::_1, cute::_1>;
    using MmaTileShape = Shape<_256, _256, _256>;
    using ArchTag = cutlass::arch::Sm100;
    using OpClassEpilogue = cutlass::arch::OpClassSparseTensorOp;
    using OpClassMainLoop = cutlass::arch::OpClassSparseTensorOp;
    using EpilogueTile = cutlass::epilogue::collective::EpilogueTileAuto;
    using EpilogueScheduleType = cutlass::epilogue::TmaWarpSpecialized2Sm;
    using KernelScheduleType = cutlass::gemm::KernelSparseTmaWarpSpecialized2SmSm100;
    using ElementAccumulator = float;
    using ElementEpilogueCompute = float;
    using ElementBias = cutlass::half_t;
    using TileScheduler = cutlass::gemm::PersistentScheduler;

    using CollectiveEpilogue =
        typename cutlass::epilogue::collective::CollectiveBuilder<
            ArchTag,
            OpClassEpilogue,
            MmaTileShape,
            ClusterShape,
            EpilogueTile,
            ElementAccumulator,
            ElementEpilogueCompute,
            ElementC, LayoutC, kAlignmentC,
            ElementD, LayoutD, kAlignmentD,
            EpilogueScheduleType
        >::CollectiveOp;

    using StageCount = cutlass::gemm::collective::StageCountAutoCarveoutEpi<CollectiveEpilogue>;

    using CollectiveMainloop =
        typename cutlass::gemm::collective::CollectiveBuilder<
            ArchTag,
            OpClassMainLoop,
            ElementA, LayoutA, kAlignmentA,
            ElementB, LayoutB, kAlignmentB,
            ElementAccumulator,
            MmaTileShape,
            ClusterShape,
            StageCount,
            KernelScheduleType
        >::CollectiveOp;

    using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
        cute::Shape<int,int,int,int>,
        CollectiveMainloop,
        CollectiveEpilogue,
        void>;

    using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
}

// 1.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x128x256_0_tnt_align32_q_1sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x128x256_0_tnt_align32_q_1sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 0,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 2.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x256x256_0_tnt_align32_q_1sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_128x256x256_0_tnt_align32_q_1sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 0,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 3.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x128x256_0_tnt_align32_q_2sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x128x256_0_tnt_align32_q_2sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 0,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

// 4.
TEST(cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x256x256_0_tnt_align32_q_2sm, functional) {
  namespace gemm = cutlass3x_sm100_sptensorop_spgemm_e3m2_e3m2_f32_void_e4m3_256x256x256_0_tnt_align32_q_2sm;
  EXPECT_TRUE(test::gemm::device::TestSmall<gemm::Gemm>(
    1, 0,
    test::gemm::device::CheckEquality::RELATIVE,
    test::gemm::device::ScalarLoc::ON_DEVICE,
    test::gemm::device::VectorScale::ENABLED,
    {256, 2560}));
}

#endif // #if defined(CUTLASS_ARCH_MMA_SM100_SUPPORTED)
