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/*! \file
    \brief Tests for device-wide CONV interface
*/

#include "cutlass_unit_test.h"

#include "cutlass/cutlass.h"
#include "cute/tensor.hpp"
#include "cute/atom/mma_atom.hpp"

#include "cutlass/numeric_types.h"

#include "cutlass/conv/device/conv_universal_adapter.hpp"
#include "cutlass/conv/kernel/conv_universal.hpp"
#include "cutlass/conv/collective/collective_builder.hpp"
#include "cutlass/epilogue/collective/collective_builder.hpp"

#include "../testbed_conv.hpp"
using namespace cute;

#if defined(CUTLASS_ARCH_MMA_SM100_SUPPORTED)

//////////////////////////////////////////////////////////////////////////////////////////////////
// Static cluster
//////////////////////////////////////////////////////////////////////////////////////////////////

//
// Cluster tile shape 64x64x64
// Cluster shape 1x1x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 64x64x64_1x1x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_64, _64, Shape<_64>>;
  using ClusterShape = Shape<_1,_1,_1>;
 
  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}

//
// Cluster tile shape 128x64x64
// Cluster shape 1x1x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 128x64x64_1x1x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_128, _64, Shape<_64>>;
  using ClusterShape = Shape<_1,_1,_1>;
 
  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}

//
// Cluster tile shape 128x128x64
// Cluster shape 1x2x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 128x128x64_1x2x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_128, _64, Shape<_64>>;
  using ClusterShape = Shape<_1,_2,_1>;

  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}

//
// Cluster tile shape 256x64x64
// Cluster shape 2x1x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 256x64x64_2x1x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_256, _64, Shape<_64>>;
  using ClusterShape = Shape<_2,_1,_1>;

  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}

//
// Cluster tile shape 256x128x64
// Cluster shape 2x2x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 256x128x64_2x2x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_256, _64, Shape<_64>>;
  using ClusterShape = Shape<_2,_2,_1>;
 
  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}

//////////////////////////////////////////////////////////////////////////////////////////////////
// Dynamic cluster
//////////////////////////////////////////////////////////////////////////////////////////////////

//
// CTA tile shape 64x64x64
// preferred cluster shape 2x4x1
// fallback cluster shape  2x2x1
//
TEST(SM100_device_conv3d_dgrad_implicitgemm_f8ndhwc_f8ndhwc_f8ndhwc_tensor_op_f32, 64x64x64_preferred_2x4x1_fallback_2x2x1) {
  using ElementAct     = cutlass::float_e4m3_t;
  using ElementFlt     = cutlass::float_e4m3_t;
  using ElementOut     = cutlass::float_e4m3_t;
  using ElementAcc     = float;
  using ElementCompute = float;
  using MmaTileShape = Shape<_64, _64, Shape<_64>>;
  using ClusterShape = decltype(make_shape(int(0), int(0), Int<1>{}));

  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      MmaTileShape, ClusterShape,
      cutlass::epilogue::collective::EpilogueTileAuto,
      ElementAcc, ElementCompute,
      ElementAct, cutlass::layout::TensorNDHWC, 128 / cutlass::sizeof_bits<ElementAct>::value,
      ElementOut, cutlass::layout::TensorNDHWC, 128 /  cutlass::sizeof_bits<ElementOut>::value,
      cutlass::epilogue::collective::EpilogueScheduleAuto
    >::CollectiveOp;

  using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
      cutlass::arch::Sm100, cutlass::arch::OpClassTensorOp,
      cutlass::conv::Operator::kDgrad,
      ElementAct, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementAct),
      ElementFlt, cutlass::layout::TensorNDHWC, 16 / sizeof(ElementFlt),
      ElementAcc,
      MmaTileShape, ClusterShape,
      cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
      cutlass::conv::collective::KernelScheduleAuto
    >::CollectiveOp;

  using ProblemShape=cutlass::conv::ConvProblemShape<CollectiveMainloop::DispatchPolicy::ConvOp, CollectiveMainloop::DispatchPolicy::NumSpatialDimensions>;
  using ConvKernel = cutlass::conv::kernel::ConvUniversal<
      ProblemShape,
      CollectiveMainloop,
      CollectiveEpilogue
    >;

  using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;

  EXPECT_TRUE(test::conv::device::TestAllConv<Conv>(1.0, 0.0, 0.0f, dim3(2,4,1), dim3(2,2,1)));
}

#endif // defined(CUTLASS_ARCH_MMA_SM100_SUPPORTED)
