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

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

#include "cutlass/conv/kernel/default_conv3d_dgrad.h"
#include "cutlass/conv/device/implicit_gemm_convolution.h"

#include "conv3d_testbed.h"

#if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)

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

TEST(SM80_Device_Conv3d_Dgrad_Analytic_ImplicitGemm_tf32ndhwc_tf32ndhwc_f32ndhwc_tensor_op_f32,
  128x128_32x3_64x64x32) {

  /// Conv operation element types for the Gemm equivalent (ImplicitGemm)
  using ElementA           = cutlass::tfloat32_t;
  using ElementB           = cutlass::tfloat32_t;
  using ElementC           = float;
  using ElementAccumulator = float;
  using ElementCompute     = float;

  /// Device-level Conv2d instance
  using Conv3dDgradKernel = typename cutlass::conv::kernel::DefaultConv3dDgrad<
    ElementA, cutlass::layout::TensorNDHWC,
    ElementB, cutlass::layout::TensorNDHWC,
    ElementC, cutlass::layout::TensorNDHWC,
    ElementAccumulator,
    cutlass::arch::OpClassTensorOp,
    cutlass::arch::Sm80,
    cutlass::gemm::GemmShape<128, 128, 16>,
    cutlass::gemm::GemmShape<64, 64, 16>,
    cutlass::gemm::GemmShape<16, 8, 8>,
    cutlass::epilogue::thread::LinearCombination<
      ElementC,
      128 / cutlass::sizeof_bits<ElementC>::value,
      ElementAccumulator,
      ElementCompute
    >,
    cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
    3,
    cutlass::arch::OpMultiplyAdd,
    cutlass::conv::IteratorAlgorithm::kAnalytic
  >::Kernel;

  using Conv3dDgrad = cutlass::conv::device::ImplicitGemmConvolution<Conv3dDgradKernel>;

  /// Run all unit test sizes with device-level Conv3d instance
  EXPECT_TRUE(test::conv::device::TestAllConv3d<Conv3dDgrad>());
}

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

TEST(SM80_Device_Conv3d_Dgrad_Optimized_ImplicitGemm_tf32ndhwc_tf32ndhwc_f32ndhwc_tensor_op_f32,
  128x128_32x3_64x64x32) {

  /// Conv operation element types for the Gemm equivalent (ImplicitGemm)
  using ElementA           = cutlass::tfloat32_t;
  using ElementB           = cutlass::tfloat32_t;
  using ElementC           = float;
  using ElementAccumulator = float;
  using ElementCompute     = float;

  /// Device-level Conv2d instance
  using Conv3dDgradKernel = typename cutlass::conv::kernel::DefaultConv3dDgrad<
    ElementA, cutlass::layout::TensorNDHWC,
    ElementB, cutlass::layout::TensorNDHWC,
    ElementC, cutlass::layout::TensorNDHWC,
    ElementAccumulator,
    cutlass::arch::OpClassTensorOp,
    cutlass::arch::Sm80,
    cutlass::gemm::GemmShape<128, 128, 16>,
    cutlass::gemm::GemmShape<64, 64, 16>,
    cutlass::gemm::GemmShape<16, 8, 8>,
    cutlass::epilogue::thread::LinearCombination<
      ElementC,
      128 / cutlass::sizeof_bits<ElementC>::value,
      ElementAccumulator,
      ElementCompute
    >,
    cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
    3,
    cutlass::arch::OpMultiplyAdd,
    cutlass::conv::IteratorAlgorithm::kOptimized,
    cutlass::conv::StrideSupport::kUnity
  >::Kernel;

  using Conv3dDgrad = cutlass::conv::device::ImplicitGemmConvolution<Conv3dDgradKernel>;

  /// Run all unit test sizes with device-level Conv3d instance
  EXPECT_TRUE(test::conv::device::TestAllConv3d<Conv3dDgrad>());
}
////////////////////////////////////////////////////////////////////////////////
#endif  // CUTLASS_ARCH_MMA_SM80_SUPPORTED
