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/*! \file
    \brief 
    Default kernel-level implicit GEMM convolution definitions combine threadblock-scoped 
      matrix multiply-add with the appropriate threadblock-scoped epilogue.  
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/conv/kernel/default_conv2d.h"

#include "cutlass/conv/threadblock/conv2d_fprop_activation_tile_access_iterator_analytic.h"
#include "cutlass/conv/threadblock/conv2d_fprop_activation_tile_access_iterator_optimized.h"
#include "cutlass/conv/threadblock/conv2d_fprop_activation_tile_access_iterator_fixed_channels.h"
#include "cutlass/conv/threadblock/conv2d_fprop_activation_tile_access_iterator_few_channels.h"

#include "cutlass/conv/threadblock/conv2d_fprop_filter_tile_access_iterator_analytic.h"
#include "cutlass/conv/threadblock/conv2d_fprop_filter_tile_access_iterator_optimized.h"
#include "cutlass/conv/threadblock/conv2d_fprop_filter_tile_access_iterator_fixed_channels.h"
#include "cutlass/conv/threadblock/conv2d_fprop_filter_tile_access_iterator_few_channels.h"

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

namespace cutlass {
namespace conv {
namespace kernel {

/////////////////////////////////////////////////////////////////////////////////////////////////
/// Defines a kernel for Conv2dGroupFpro
template <
  typename ElementA,
  typename LayoutA,
  typename ElementB,
  typename LayoutB,
  typename ElementC,
  typename LayoutC,
  typename ElementAccumulator,
  typename OperatorClass,
  typename ArchTag,
  typename ThreadblockShape,
  typename WarpShape,
  typename InstructionShape,
  typename EpilogueOutputOp,
  typename ThreadblockSwizzle,
  int Stages,
  typename MathOperatorTag,
  conv::GroupMode GroupMode,
  conv::IteratorAlgorithm IteratorAlgorithm = IteratorAlgorithm::kOptimized,
  conv::StrideSupport StrideSupport = StrideSupport::kStrided,
  /// Access granularity of A matrix in units of elements
  int AlignmentA = 128 / cutlass::sizeof_bits<ElementA>::value,
  /// Access granularity of B matrix in units of elements
  int AlignmentB = 128 / cutlass::sizeof_bits<ElementB>::value
> struct DefaultConv2dGroupFprop;

/////////////////////////////////////////////////////////////////////////////////////////////////
//                         OpClassTensorOp convolutions 
/////////////////////////////////////////////////////////////////////////////////////////////////

/// Defines a kernel for Conv2dGroupFprop specialization for Analytic IteratorAlgorithm and multistage 
/// pipeline that supports all GroupMode.
template <
  typename ElementA,
  typename LayoutA,
  typename ElementB,
  typename LayoutB,
  typename ElementC,
  typename LayoutC,
  typename ElementAccumulator,
  typename ArchTag,
  typename ThreadblockShape,
  typename WarpShape,
  typename InstructionShape,
  typename EpilogueOutputOp,
  typename ThreadblockSwizzle,
  int Stages,
  typename MathOperatorTag,
  conv::GroupMode GroupMode,
  conv::StrideSupport StrideSupport, 
  int AlignmentA,
  int AlignmentB
>
struct DefaultConv2dGroupFprop <
  ElementA,
  LayoutA,
  ElementB,
  LayoutB,
  ElementC,
  LayoutC,
  ElementAccumulator,
  arch::OpClassTensorOp,
  ArchTag,
  ThreadblockShape,
  WarpShape,
  InstructionShape,
  EpilogueOutputOp,
  ThreadblockSwizzle,
  Stages,
  MathOperatorTag,
  GroupMode,
  IteratorAlgorithm::kAnalytic,
  StrideSupport,
  AlignmentA,
  AlignmentB
> {

  static_assert(std::is_same<LayoutA, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutB, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutC, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");

  // Define the core components from GEMM
  using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
      ThreadblockShape, WarpShape, InstructionShape, ElementA, layout::RowMajor,
      ElementB, layout::ColumnMajor, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp,
      Stages, MathOperatorTag>;

  // Define iterators over tiles from the A operand
  using ThreadMapA = typename MmaCore::IteratorThreadMapA;
  using AccessTypeA = cutlass::AlignedArray<ElementA, AlignmentA>;
  using IteratorA =
    cutlass::conv::threadblock::Conv2dFpropActivationTileAccessIteratorAnalytic<
      cutlass::MatrixShape<ThreadblockShape::kM, ThreadblockShape::kK>,
      ElementA, LayoutA,
      ThreadMapA,
      AccessTypeA,
      GroupMode
    >;

  using SmemIteratorA = typename MmaCore::SmemIteratorA;

  // Define iterators over tiles from the B operand
  using ThreadMapB = typename MmaCore::IteratorThreadMapB;
  using AccessTypeB = cutlass::AlignedArray<ElementB, AlignmentB>;
  using IteratorB =
    cutlass::conv::threadblock::Conv2dFpropFilterTileAccessIteratorAnalytic<
      cutlass::MatrixShape<ThreadblockShape::kK, ThreadblockShape::kN>,
      ElementB, LayoutB,
      ThreadMapB,
      AccessTypeB,
      GroupMode
    >;
  
  using SmemIteratorB = typename MmaCore::SmemIteratorB;

  // Warp-level GEMM components
  using WarpMmaTensorOp = typename MmaCore::MmaTensorOp;
  using MmaPolicy = typename MmaCore::MmaPolicy;

  static cutlass::arch::CacheOperation::Kind const CacheOpB =
      ((sizeof_bits<ElementB>::value * AlignmentB) == 128)
          ? cutlass::arch::CacheOperation::Global
          : cutlass::arch::CacheOperation::Always;

  // Define the Mma
  using Mma = threadblock::ImplicitGemmMultistage<
    ThreadblockShape,
    IteratorA,
    SmemIteratorA,
    arch::CacheOperation::Always,
    IteratorB,
    SmemIteratorB,
    CacheOpB,
    MmaPolicy,
    Stages 
  >;

  static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;

  // Define the epilogue
  using Epilogue = typename epilogue::threadblock::DefaultEpilogueTensorOp<
    ThreadblockShape,
    WarpMmaTensorOp,
    kPartitionsK,
    EpilogueOutputOp,
    EpilogueOutputOp::kCount
  >::Epilogue;

  // Define the kernel
  using Kernel = cutlass::conv::kernel::ImplicitGemmConvolution<
    Mma,
    Epilogue,
    ThreadblockSwizzle,
    conv::Operator::kFprop,
    Conv2dProblemSize,
    GroupMode
  >;
};

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

/// Defines a kernel for Conv2dGroupFprop specialization for Optimized IteratorAlgorithm and multistage
/// pipeline that supports GroupMode::kSingleGroup.
template <
  typename ElementA,
  typename LayoutA,
  typename ElementB,
  typename LayoutB,
  typename ElementC,
  typename LayoutC,
  typename ElementAccumulator,
  typename ArchTag,
  typename ThreadblockShape,
  typename WarpShape,
  typename InstructionShape,
  typename EpilogueOutputOp,
  typename ThreadblockSwizzle,
  int Stages,
  typename MathOperatorTag,
  conv::StrideSupport StrideSupport,
  int AlignmentA,
  int AlignmentB
>
struct DefaultConv2dGroupFprop <
  ElementA,
  LayoutA,
  ElementB,
  LayoutB,
  ElementC,
  LayoutC,
  ElementAccumulator,
  arch::OpClassTensorOp,
  ArchTag,
  ThreadblockShape,
  WarpShape,
  InstructionShape,
  EpilogueOutputOp,
  ThreadblockSwizzle,
  Stages,
  MathOperatorTag,
  GroupMode::kSingleGroup,
  IteratorAlgorithm::kOptimized,
  StrideSupport,
  AlignmentA,
  AlignmentB
> {

  static_assert(std::is_same<LayoutA, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutB, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutC, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");

  // Define the core components from GEMM
  using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
      ThreadblockShape, WarpShape, InstructionShape, ElementA, layout::RowMajor,
      ElementB, layout::ColumnMajor, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp,
      Stages, MathOperatorTag>;

  // Define iterators over tiles from the A operand
  using ThreadMapA = typename MmaCore::IteratorThreadMapA;
  using AccessTypeA = cutlass::AlignedArray<ElementA, AlignmentA>;
  using IteratorA =
    cutlass::conv::threadblock::Conv2dFpropActivationTileAccessIteratorOptimized<
      cutlass::MatrixShape<ThreadblockShape::kM, ThreadblockShape::kK>,
      ElementA, LayoutA,
      ThreadMapA,
      AccessTypeA
    >;

  using SmemIteratorA = typename MmaCore::SmemIteratorA;

  // Define iterators over tiles from the B operand
  using ThreadMapB = typename MmaCore::IteratorThreadMapB;
  using AccessTypeB = cutlass::AlignedArray<ElementB, AlignmentB>;
  using IteratorB =
    cutlass::conv::threadblock::Conv2dFpropFilterTileAccessIteratorOptimized<
      cutlass::MatrixShape<ThreadblockShape::kK, ThreadblockShape::kN>,
      ElementB, LayoutB,
      ThreadMapB,
      AccessTypeB
    >;

  using SmemIteratorB = typename MmaCore::SmemIteratorB;

  // Warp-level GEMM components
  using WarpMmaTensorOp = typename MmaCore::MmaTensorOp;
  using MmaPolicy = typename MmaCore::MmaPolicy;

  static cutlass::arch::CacheOperation::Kind const CacheOpB =
      ((sizeof_bits<ElementB>::value * AlignmentB) == 128)
          ? cutlass::arch::CacheOperation::Global
          : cutlass::arch::CacheOperation::Always;

  // Define the Mma
  using Mma = threadblock::ImplicitGemmMultistage<
    ThreadblockShape,
    IteratorA,
    SmemIteratorA,
    arch::CacheOperation::Always,
    IteratorB,
    SmemIteratorB,
    CacheOpB,
    MmaPolicy,
    Stages
  >;

  static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;

  // Define the epilogue
  using Epilogue = typename epilogue::threadblock::DefaultEpilogueTensorOp<
    ThreadblockShape,
    WarpMmaTensorOp,
    kPartitionsK,
    EpilogueOutputOp,
    EpilogueOutputOp::kCount
  >::Epilogue;

  // Define the kernel
  using Kernel = cutlass::conv::kernel::ImplicitGemmConvolution<
    Mma,
    Epilogue,
    ThreadblockSwizzle,
    conv::Operator::kFprop,
    Conv2dProblemSize,
    GroupMode::kSingleGroup
  >;
};

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

/// Defines a kernel for Conv2dGroupFprop specialization for Optimized IteratorAlgorithm and
/// 2 stage pipeline that supports GroupMode::kSingleGroup.
template <
  typename ElementA,
  typename LayoutA,
  typename ElementB,
  typename LayoutB,
  typename ElementC,
  typename LayoutC,
  typename ElementAccumulator,
  typename ArchTag,
  typename ThreadblockShape,
  typename WarpShape,
  typename InstructionShape,
  typename EpilogueOutputOp,
  typename ThreadblockSwizzle,
  typename MathOperatorTag,
  conv::StrideSupport StrideSupport,
  int AlignmentA,
  int AlignmentB
>
struct DefaultConv2dGroupFprop <
  ElementA,
  LayoutA,
  ElementB,
  LayoutB,
  ElementC,
  LayoutC,
  ElementAccumulator,
  arch::OpClassTensorOp,
  ArchTag,
  ThreadblockShape,
  WarpShape,
  InstructionShape,
  EpilogueOutputOp,
  ThreadblockSwizzle,
  2,
  MathOperatorTag,
  GroupMode::kSingleGroup,
  IteratorAlgorithm::kOptimized,
  StrideSupport,
  AlignmentA,
  AlignmentB
> {

  static_assert(std::is_same<LayoutA, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutB, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");
  static_assert(std::is_same<LayoutC, cutlass::layout::TensorNHWC>::value,
    "Current group conv only support NHWC layout");

  // Define the core components from GEMM
  using MmaCore = typename cutlass::gemm::threadblock::DefaultMmaCore<
    ThreadblockShape, WarpShape, InstructionShape, ElementA, layout::RowMajor,
    ElementB, layout::ColumnMajor, ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp,
    2, MathOperatorTag>;

  // Define iterators over tiles from the A operand
  using ThreadMapA = typename MmaCore::IteratorThreadMapA;
  using AccessTypeA = cutlass::AlignedArray<ElementA, AlignmentA>;
  using IteratorA =
    cutlass::conv::threadblock::TileIterator<
      cutlass::conv::threadblock::Conv2dFpropActivationTileAccessIteratorOptimized<
        cutlass::MatrixShape<ThreadblockShape::kM, ThreadblockShape::kK>,
        ElementA,
        LayoutA,
        ThreadMapA,
        AccessTypeA
      >
    >;

  using SmemIteratorA = typename MmaCore::SmemIteratorA;

  // Define iterators over tiles from the B operand
  using ThreadMapB = typename MmaCore::IteratorThreadMapB;
  using AccessTypeB = cutlass::AlignedArray<ElementB, AlignmentB>;
  using IteratorB =
    cutlass::conv::threadblock::TileIterator<
      cutlass::conv::threadblock::Conv2dFpropFilterTileAccessIteratorOptimized<
        cutlass::MatrixShape<ThreadblockShape::kK, ThreadblockShape::kN>,
        ElementB,
        LayoutB,
        ThreadMapB,
        AccessTypeB
      >
    >;

  using SmemIteratorB = typename MmaCore::SmemIteratorB;

  // Warp-level GEMM components
  using WarpMmaTensorOp = typename MmaCore::MmaTensorOp;
  using MmaPolicy = typename MmaCore::MmaPolicy;

  // Define the Mma
  using Mma = threadblock::ImplicitGemmPipelined<
    ThreadblockShape,
    IteratorA,
    SmemIteratorA,
    IteratorB,
    SmemIteratorB,
    ElementC,
    LayoutC,
    MmaPolicy
  >;

  static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;

  // Define the epilogue
  using Epilogue = typename detail::DefaultConvEpilogue<
    ArchTag,
    ThreadblockShape,
    WarpMmaTensorOp,
    kPartitionsK,
    EpilogueOutputOp
  >::Epilogue;

  // Define the kernel
  using Kernel = cutlass::conv::kernel::ImplicitGemmConvolution<
    Mma,
    Epilogue,
    ThreadblockSwizzle,
    conv::Operator::kFprop,
    Conv2dProblemSize,
    GroupMode::kSingleGroup
  >;
};

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

} // namespace kernel
} // namespace conv
} // namespace cutlass

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