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/*! \file
    \brief Unit tests for thread-level GEMM
*/

#include <fstream>

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

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

#include "cutlass/epilogue/thread/linear_combination_planar_complex.h"

// Tensor Op
#include "cutlass/gemm/warp/default_mma_tensor_op.h"

// Volta Tensor Op
#include "cutlass/gemm/warp/mma_tensor_op_sm70.h"
#include "cutlass/epilogue/warp/fragment_iterator_volta_tensor_op.h"

// Simt
#include "cutlass/gemm/warp/mma_simt.h"
#include "cutlass/gemm/warp/mma_simt_policy.h"

// Epilogue components

#include "cutlass/epilogue/threadblock/default_epilogue_planar_complex.h"

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

#include "testbed_planar_complex.h"

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

TEST(Epilogue_threadblock_epilogue,
     planar_complex_f32_f32_tensor_op_64x64_32x32x8) {
    //
    // Define the warp-level matrix multiply
    //

    using ElementOutput = float;
    using ElementAccumulator = float;
    using ElementCompute = float;
    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 8>;
    using WarpShape = cutlass::gemm::GemmShape<32, 32, 8>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 8, 8>;
    using Element = cutlass::half_t;

    using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using WarpMmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
            WarpShape, InstructionShape, Element, LayoutA, Element, LayoutB,
            ElementAccumulator, cutlass::layout::RowMajor>::Type;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaTensorOp, cutlass::arch::OpClassTensorOp,
                    cutlass::arch::Sm75, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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

TEST(Epilogue_threadblock_epilogue,
     planar_complex_f16_f32_tensor_op_64x64_32x32x8) {
    //
    // Define the warp-level matrix multiply
    //

    using ElementOutput = cutlass::half_t;
    using ElementAccumulator = float;
    using ElementCompute = float;
    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 8>;
    using WarpShape = cutlass::gemm::GemmShape<32, 32, 8>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 8, 8>;
    using Element = cutlass::half_t;

    using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using WarpMmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
            WarpShape, InstructionShape, Element, LayoutA, Element, LayoutB,
            ElementAccumulator, cutlass::layout::RowMajor>::Type;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaTensorOp, cutlass::arch::OpClassTensorOp,
                    cutlass::arch::Sm75, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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

TEST(Epilogue_threadblock_epilogue,
     planar_complex_f16_f16_tensor_op_64x64_32x32x8) {
    //
    // 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, 8>;
    using WarpShape = cutlass::gemm::GemmShape<32, 32, 8>;
    using InstructionShape = cutlass::gemm::GemmShape<16, 8, 8>;
    using Element = cutlass::half_t;

    using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
            cutlass::sizeof_bits<Element>::value, 64>;

    using WarpMmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
            WarpShape, InstructionShape, Element, LayoutA, Element, LayoutB,
            ElementAccumulator, cutlass::layout::RowMajor>::Type;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaTensorOp, cutlass::arch::OpClassTensorOp,
                    cutlass::arch::Sm75, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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

TEST(Epilogue_threadblock_epilogue,
     planar_complex_f32_f32_volta_tensor_op_64x64_32x32x4) {
    //
    // Define the warp-level matrix multiply
    //

    using ElementOutput = float;
    using ElementAccumulator = float;
    using ElementCompute = float;

    int const kElementsPerAccess =
            128 / cutlass::sizeof_bits<ElementOutput>::value;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<32, 32, 4>;
    using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
    using Element = cutlass::half_t;

    using LayoutA =
            cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<
                    cutlass::sizeof_bits<Element>::value>;
    using LayoutB =
            cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<
                    cutlass::sizeof_bits<Element>::value>;

    using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
            cutlass::arch::Mma<cutlass::gemm::GemmShape<16, 16, 4>, 32, Element,
                               cutlass::layout::ColumnMajor, Element,
                               cutlass::layout::RowMajor, ElementAccumulator,
                               cutlass::layout::RowMajor,
                               cutlass::arch::OpMultiplyAdd>,
            cutlass::MatrixShape<1, 1> >;

    using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
            WarpShape, Element, LayoutA, Element, LayoutB, ElementAccumulator,
            cutlass::layout::RowMajor, Policy>;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaTensorOp, cutlass::arch::OpClassTensorOp,
                    cutlass::arch::Sm70, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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

TEST(Epilogue_threadblock_epilogue, planar_complex_simt_f32_64x64_32x32x8) {
    //
    // Define the warp-level matrix multiply
    //

    using ElementOutput = float;
    using ElementAccumulator = float;
    using ElementCompute = float;
    int const kElementsPerAccess = 1;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 8>;
    using WarpShape = cutlass::gemm::GemmShape<32, 32, 8>;
    using Element = float;
    using ElementC = ElementAccumulator;
    using LayoutA = cutlass::layout::ColumnMajor;
    using LayoutB = cutlass::layout::RowMajor;
    using LayoutC = cutlass::layout::RowMajor;

    using ElementOutput = Element;
    using ElementAccumulator = Element;
    using ElementCompute = Element;

    using WarpMmaSimt = cutlass::gemm::warp::MmaSimt<
            WarpShape, Element, LayoutA, Element, LayoutB, Element, LayoutC,
            cutlass::gemm::warp::MmaSimtPolicy<
                    cutlass::MatrixShape<4, 8>,
                    cutlass::layout::RowMajorInterleaved<2>,
                    cutlass::gemm::GemmShape<4, 4, 1> > >;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaSimt, cutlass::arch::OpClassSimt,
                    cutlass::arch::Sm50, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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

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

TEST(Epilogue_threadblock_epilogue, planar_complex_simt_f64_64x64_16x32x8) {
    //
    // Define the warp-level matrix multiply
    //

    using ElementOutput = double;
    using ElementAccumulator = double;
    using ElementCompute = double;
    int const kElementsPerAccess = 1;
    int const kPartitionsK = 1;

    using Shape = cutlass::gemm::GemmShape<64, 64, 8>;
    using WarpShape = cutlass::gemm::GemmShape<16, 32, 8>;
    using Element = double;
    using ElementC = ElementAccumulator;
    using LayoutA = cutlass::layout::ColumnMajor;
    using LayoutB = cutlass::layout::RowMajor;
    using LayoutC = cutlass::layout::RowMajor;

    using ElementOutput = Element;
    using ElementAccumulator = Element;
    using ElementCompute = Element;

    using WarpMmaSimt = cutlass::gemm::warp::MmaSimt<
            WarpShape, Element, LayoutA, Element, LayoutB, Element, LayoutC,
            cutlass::gemm::warp::MmaSimtPolicy<
                    cutlass::MatrixShape<4, 8>,
                    cutlass::layout::RowMajorInterleaved<2>,
                    cutlass::gemm::GemmShape<4, 4, 1> > >;

    //
    // Output operator
    //

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

    //
    // Define the epilogue
    //

    using Epilogue = typename cutlass::epilogue::threadblock::
            DefaultEpiloguePlanarComplex<
                    Shape, WarpMmaSimt, cutlass::arch::OpClassSimt,
                    cutlass::arch::Sm50, kPartitionsK, OutputOp,
                    kElementsPerAccess>::Epilogue;

    //
    // Instantiate epilogue
    //

    EpiloguePlanarComplexTestbed<Epilogue> testbed;

    bool passed = testbed.run_all();

    EXPECT_TRUE(passed);
}

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