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/*! \file
    \brief Unit tests for thread-level GEMM
*/
#include "cutlass/arch/wmma.h"

#ifdef CUTLASS_ARCH_WMMA_SM70_ENABLED

#include <fstream>

#include "../../common/cutlass_unit_test.h"

#include "cutlass/aligned_buffer.h"
#include "cutlass/half.h"

#include "cutlass/epilogue/thread/linear_combination.h"
#include "cutlass/gemm/warp/default_mma_wmma_tensor_op.h"
#include "cutlass/epilogue/threadblock/default_epilogue_wmma_tensor_op.h"

#include "cutlass/util/host_tensor.h"
#include "cutlass/util/tensor_view_io.h"
#include "cutlass/util/reference/host/tensor_fill.h"

#include "testbed.h"

/////////////////////////////////////////////////////////////////////////////////////////////////
//
// F16 acumulation
//
/////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SM70_Epilogue_threadblock_epilogue, f16_wmma_tensor_op_64x64_64x64x16) {
    //
    // Define the warp-level matrix multiply
    //
    using ElementOutput = cutlass::half_t;
    using ElementAccumulator = cutlass::half_t;
    using ElementCompute = cutlass::half_t;
    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 16>;
    using WarpShape = cutlass::gemm::GemmShape<64, 64, 16>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
    using ElementA = cutlass::half_t;
    using ElementB = cutlass::half_t;
    using ElementC = ElementAccumulator;
    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;

    using WarpMmaTensorOp =
            typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
                    WarpShape, InstructionShape, ElementA, LayoutA, ElementB,
                    LayoutB, ElementC, LayoutC>::Type;

    //
    // Output operator
    //

    using OutputOp = cutlass::epilogue::thread::LinearCombination<
            ElementOutput, kElementsPerAccess, ElementAccumulator,
            ElementCompute>;

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpilogueWmmaTensorOp<Shape, WarpMmaTensorOp, kPartitionsK,
                                        OutputOp, kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpilogueTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

TEST(SM70_Epilogue_threadblock_epilogue, f16_wmma_tensor_op_64x128_64x64x16) {
    //
    // Define the warp-level matrix multiply
    //
    using ElementOutput = cutlass::half_t;
    using ElementAccumulator = cutlass::half_t;
    using ElementCompute = cutlass::half_t;
    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 128, 16>;
    using WarpShape = cutlass::gemm::GemmShape<64, 64, 16>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
    using ElementA = cutlass::half_t;
    using ElementB = cutlass::half_t;
    using ElementC = ElementAccumulator;
    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;

    using WarpMmaTensorOp =
            typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
                    WarpShape, InstructionShape, ElementA, LayoutA, ElementB,
                    LayoutB, ElementC, LayoutC>::Type;

    //
    // Output operator
    //

    using OutputOp = cutlass::epilogue::thread::LinearCombination<
            ElementOutput, kElementsPerAccess, ElementAccumulator,
            ElementCompute>;

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpilogueWmmaTensorOp<Shape, WarpMmaTensorOp, kPartitionsK,
                                        OutputOp, kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpilogueTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

/////////////////////////////////////////////////////////////////////////////////////////////////
//
// F32 acumulation and F32 output
//
/////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SM70_Epilogue_threadblock_epilogue, f32_wmma_tensor_op_64x64_64x64x16) {
    //
    // Define the warp-level matrix multiply
    //
    using ElementOutput = float;
    using ElementAccumulator = float;
    using ElementCompute = cutlass::half_t;
    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 16>;
    using WarpShape = cutlass::gemm::GemmShape<64, 64, 16>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 16, 16>;
    using ElementA = cutlass::half_t;
    using ElementB = cutlass::half_t;
    using ElementC = ElementAccumulator;
    using LayoutA = cutlass::layout::RowMajor;
    using LayoutB = cutlass::layout::ColumnMajor;
    using LayoutC = cutlass::layout::RowMajor;

    using WarpMmaTensorOp =
            typename cutlass::gemm::warp::DefaultMmaTensorOpWmma<
                    WarpShape, InstructionShape, ElementA, LayoutA, ElementB,
                    LayoutB, ElementC, LayoutC>::Type;

    //
    // Output operator
    //

    using OutputOp = cutlass::epilogue::thread::LinearCombination<
            ElementOutput, kElementsPerAccess, ElementAccumulator,
            ElementCompute>;

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpilogueWmmaTensorOp<Shape, WarpMmaTensorOp, kPartitionsK,
                                        OutputOp, kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpilogueTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}
/////////////////////////////////////////////////////////////////////////////////////////////////

#endif  // CUTLASS_ARCH_WMMA_ENABLED
