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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_conv2d_wgrad.h"
#include "cutlass/conv/device/implicit_gemm_convolution.h"

#include "conv2d_testbed.h"

#if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)


////////////////////////////////////////////////////////////////////////////////
TEST(SM80_Device_Conv2d_Wgrad_Analytic_ImplicitGemm_cf32nhwc_cf32nhwc_cf32nhwc_simt_f32,
  128x128_8x4_32x64x8) {

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


  /// Device-level Conv2d instance
  using Conv2dWgradKernel = typename cutlass::conv::kernel::DefaultConv2dWgrad<
    ElementA, 
    cutlass::layout::TensorNHWC,
    ElementB, 
    cutlass::layout::TensorNHWC,
    ElementC, 
    cutlass::layout::TensorNHWC,
    ElementAccumulator,
    cutlass::arch::OpClassSimt,
    cutlass::arch::Sm80,
    cutlass::gemm::GemmShape<128, 128, 8>,
    cutlass::gemm::GemmShape<32, 64, 8>, 
    cutlass::gemm::GemmShape<1, 1, 1>,
    cutlass::epilogue::thread::LinearCombination<
      ElementC,
      1,
      ElementAccumulator,
      ElementCompute
    >,
    cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
    4,
    cutlass::arch::OpMultiplyAddComplex,
    cutlass::conv::IteratorAlgorithm::kAnalytic
  >::Kernel;

  using Conv2dWgrad = cutlass::conv::device::ImplicitGemmConvolution<Conv2dWgradKernel>;

  /// Run all unit test sizes with device-level Conv2d instance
  EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dWgrad>());

}

////////////////////////////////////////////////////////////////////////////////
TEST(SM80_Device_Conv2d_Wgrad_Optimized_ImplicitGemm_cf32nhwc_cf32nhwc_cf32nhwc_simt_f32,
  128x128_8x4_64x32x8) {

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


  /// Device-level Conv2d instance
  using Conv2dWgradKernel = typename cutlass::conv::kernel::DefaultConv2dWgrad<
    ElementA, 
    cutlass::layout::TensorNHWC,
    ElementB, 
    cutlass::layout::TensorNHWC,
    ElementC, 
    cutlass::layout::TensorNHWC,
    ElementAccumulator,
    cutlass::arch::OpClassSimt,
    cutlass::arch::Sm80,
    cutlass::gemm::GemmShape<128, 128, 8>,
    cutlass::gemm::GemmShape<64, 32, 8>, 
    cutlass::gemm::GemmShape<1, 1, 1>,
    cutlass::epilogue::thread::LinearCombination<
      ElementC,
      1,
      ElementAccumulator,
      ElementCompute
    >,
    cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
    4,
    cutlass::arch::OpMultiplyAddComplex,
    cutlass::conv::IteratorAlgorithm::kOptimized
  >::Kernel;

  using Conv2dWgrad = cutlass::conv::device::ImplicitGemmConvolution<Conv2dWgradKernel>;

  /// Run all unit test sizes with device-level Conv2d instance
  EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dWgrad>());

}

////////////////////////////////////////////////////////////////////////////////
#endif  // CUTLASS_ARCH_MMA_SM80_SUPPORTED
