[QST] Getting a template error trying to use cutlass's depthwise 2D convolution with pytorch

[ahmadsharif1]

My high level goal is to use one of cutlass' 2D depthwise convolution kernels with pytorch's tensors.

I am starting off with the SIMT kernel because that can work on older devices. So I am basically copying code from this example:

https://github.com/NVIDIA/cutlass/blob/affd1b693dfc121c51118cbc8583dfd308227ca6/examples/46_depthwise_simt_conv2dfprop/depthwise_simt_conv2dfprop.cu#L80

The tensors that I have have layout NCHW and use float so I used this snippet of code in the example:

// The code section below describes datatype for input, output tensors and computation between
// elements
using ElementAccumulator = float;      // Data type of accumulator
using ElementComputeEpilogue = float;  // Data type of epilogue computation (alpha, beta)
using ElementInputA = float;           // Data type of elements in input tensor
using ElementInputB = float;           // Data type of elements in input tensor
using ElementOutput = float;           // Data type of elements in output tensor

using LayoutInputA = cutlass::layout::TensorNCHW;
using LayoutInputB = cutlass::layout::TensorNCHW;
using LayoutOutput = cutlass::layout::TensorNCHW;

This throws an error with nvcc:

Building CUDA object examples/46_depthwise_simt_conv2dfprop/CMakeFiles/46_depthwise_simt_conv2dfprop.dir/depthwise_simt_conv2dfprop.cu.o
/home/ahmads/personal/cutlass/include/cutlass/conv/kernel/direct_convolution.h(95): error: incomplete type is not allowed
          detected during:
            instantiation of class "cutlass::conv::kernel::DirectConvolutionParams<Mma_, Epilogue_, ThreadblockSwizzle_, ConvOperator, Arguments_, ConvOutputIteratorParameter_, ConvProblemSize_, GroupMode_, ThreadBlockOutputShape_> [with Mma_=cutlass::conv::threadblock::DepthwiseFpropDirectConvMultipleStage<ThreadblockShape, cutlass::conv::threadblock::DepthwiseFpropActivationDirect2dConvTileAccessIteratorFixedStrideDilation<cutlass::MatrixShape<64, 64>, ThreadBlockOutputShape, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, ElementInputA, LayoutInputA, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<100, 64>, ElementInputA, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseFpropFilterDirectConvTileAccessIteratorOptimized<cutlass::MatrixShape<64, 9>, ElementInputB, LayoutInputB, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<9, 64>, ElementInputB, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseDirectConvMmaPolicy<cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::MatrixShape<0, 0>, cutlass::MatrixShape<0, 0>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, 1>, 4, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, bool>, Epilogue_=cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, ThreadblockSwizzle_=SwizzleThreadBlock, ConvOperator=cutlass::conv::Operator::kFprop, Arguments_=cutlass::conv::kernel::DirectConvolution<cutlass::conv::threadblock::DepthwiseFpropDirectConvMultipleStage<ThreadblockShape, cutlass::conv::threadblock::DepthwiseFpropActivationDirect2dConvTileAccessIteratorFixedStrideDilation<cutlass::MatrixShape<64, 64>, ThreadBlockOutputShape, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, ElementInputA, LayoutInputA, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<100, 64>, ElementInputA, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseFpropFilterDirectConvTileAccessIteratorOptimized<cutlass::MatrixShape<64, 9>, ElementInputB, LayoutInputB, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<9, 64>, ElementInputB, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseDirectConvMmaPolicy<cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::MatrixShape<0, 0>, cutlass::MatrixShape<0, 0>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, 1>, 4, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, bool>, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, SwizzleThreadBlock, cutlass::conv::Operator::kFprop, cutlass::conv::Conv2dProblemSize, cutlass::conv::GroupMode::kDepthwise, ThreadBlockOutputShape>::Arguments, ConvOutputIteratorParameter_=cutlass::epilogue::threadblock::ConvOutputIteratorParameter<LayoutInputA, cutlass::layout::RowMajor, cutlass::TensorRef<ElementInputA, LayoutInputA>, cutlass::conv::Operator::kFprop, cutlass::conv::Conv2dProblemSize>, ConvProblemSize_=cutlass::conv::Conv2dProblemSize, GroupMode_=cutlass::conv::GroupMode::kDepthwise, ThreadBlockOutputShape_=ThreadBlockOutputShape]" 
/home/ahmads/personal/cutlass/include/cutlass/conv/device/direct_convolution.h(96): here
            instantiation of class "cutlass::conv::device::DirectConvolution<DirectConvolutionKernel_> [with DirectConvolutionKernel_=DepthwiseDirect2dConv]" 
/home/ahmads/personal/cutlass/examples/46_depthwise_simt_conv2dfprop/depthwise_simt_conv2dfprop.cu(481): here

/home/ahmads/personal/cutlass/include/cutlass/conv/kernel/direct_convolution.h(97): error: incomplete type is not allowed
          detected during:
            instantiation of class "cutlass::conv::kernel::DirectConvolutionParams<Mma_, Epilogue_, ThreadblockSwizzle_, ConvOperator, Arguments_, ConvOutputIteratorParameter_, ConvProblemSize_, GroupMode_, ThreadBlockOutputShape_> [with Mma_=cutlass::conv::threadblock::DepthwiseFpropDirectConvMultipleStage<ThreadblockShape, cutlass::conv::threadblock::DepthwiseFpropActivationDirect2dConvTileAccessIteratorFixedStrideDilation<cutlass::MatrixShape<64, 64>, ThreadBlockOutputShape, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, ElementInputA, LayoutInputA, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<100, 64>, ElementInputA, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseFpropFilterDirectConvTileAccessIteratorOptimized<cutlass::MatrixShape<64, 9>, ElementInputB, LayoutInputB, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<9, 64>, ElementInputB, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseDirectConvMmaPolicy<cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::MatrixShape<0, 0>, cutlass::MatrixShape<0, 0>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, 1>, 4, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, bool>, Epilogue_=cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, ThreadblockSwizzle_=SwizzleThreadBlock, ConvOperator=cutlass::conv::Operator::kFprop, Arguments_=cutlass::conv::kernel::DirectConvolution<cutlass::conv::threadblock::DepthwiseFpropDirectConvMultipleStage<ThreadblockShape, cutlass::conv::threadblock::DepthwiseFpropActivationDirect2dConvTileAccessIteratorFixedStrideDilation<cutlass::MatrixShape<64, 64>, ThreadBlockOutputShape, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, ElementInputA, LayoutInputA, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<100, 64>, ElementInputA, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseFpropFilterDirectConvTileAccessIteratorOptimized<cutlass::MatrixShape<64, 9>, ElementInputB, LayoutInputB, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, cutlass::AlignedArray<ElementInputA, 4, 16>>, cutlass::transform::threadblock::RegularTileAccessIteratorDirectConv<cutlass::MatrixShape<9, 64>, ElementInputB, cutlass::layout::RowMajor, 0, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, false, 16>, cutlass::arch::CacheOperation::Global, cutlass::conv::threadblock::DepthwiseDirectConvMmaPolicy<cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::MatrixShape<0, 0>, cutlass::MatrixShape<0, 0>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 100>, 128, 4>, cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 9>, 128, 4>, 1>, 4, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, bool>, cutlass::epilogue::threadblock::EpilogueDepthwise<ThreadblockShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::warp::MmaDepthwiseDirectConvSimt<WarpShape, FilterShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, ElementInputA, cutlass::layout::RowMajor, ElementInputB, cutlass::layout::RowMajor, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>, cutlass::conv::IteratorAlgorithm::kFixedStrideDilation, StrideShape, DilationShape, cutlass::conv::TensorNHWCShape<1, 10, 10, 64>, 1, cutlass::ComplexTransform::kNone, cutlass::ComplexTransform::kNone, bool>, cutlass::epilogue::threadblock::PredicatedTileIteratorDirectConv<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementOutput, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape>, cutlass::epilogue::warp::FragmentIteratorSimt<WarpShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::warp::TileIteratorSimtDirect2dConv<WarpShape, cutlass::conv::TensorNHWCShape<1, 4, 4, 2>, ThreadBlockOutputShape, cutlass::conv::thread::DepthwiseDirectConvElementwiseInnerProduct<cutlass::gemm::GemmShape<16, 2, 1>, ElementInputA, ElementInputB, ElementAccumulator, cutlass::arch::OpMultiplyAdd, bool>, ElementAccumulator, cutlass::layout::RowMajor, cutlass::gemm::warp::MmaSimtPolicy<cutlass::MatrixShape<1, 32>, cutlass::layout::RowMajorInterleaved<1>, cutlass::gemm::GemmShape<2, 2, 1>>>, cutlass::epilogue::threadblock::SharedLoadIteratorPitchLinear<cutlass::transform::PitchLinearStripminedThreadMap<cutlass::PitchLinearShape<64, 64>, 128, 4>, ElementAccumulator, 16>, EpilogueOp, cutlass::MatrixShape<0, 0>>, SwizzleThreadBlock, cutlass::conv::Operator::kFprop, cutlass::conv::Conv2dProblemSize, cutlass::conv::GroupMode::kDepthwise, ThreadBlockOutputShape>::Arguments, ConvOutputIteratorParameter_=cutlass::epilogue::threadblock::ConvOutputIteratorParameter<LayoutInputA, cutlass::layout::RowMajor, cutlass::TensorRef<ElementInputA, LayoutInputA>, cutlass::conv::Operator::kFprop, cutlass::conv::Conv2dProblemSize>, ConvProblemSize_=cutlass::conv::Conv2dProblemSize, GroupMode_=cutlass::conv::GroupMode::kDepthwise, ThreadBlockOutputShape_=ThreadBlockOutputShape]" 
/home/ahmads/personal/cutlass/include/cutlass/conv/device/direct_convolution.h(96): here
            instantiation of class "cutlass::conv::device::DirectConvolution<DirectConvolutionKernel_> [with DirectConvolutionKernel_=DepthwiseDirect2dConv]" 
/home/ahmads/personal/cutlass/examples/46_depthwise_simt_conv2dfprop/depthwise_simt_conv2dfprop.cu(481): here

2 errors detected in the compilation of "/home/ahmads/personal/cutlass/examples/46_depthwise_simt_conv2dfprop/depthwise_simt_conv2dfprop.cu".
make[3]: *** [examples/46_depthwise_simt_conv2dfprop/CMakeFiles/46_depthwise_simt_conv2dfprop.dir/build.make:77: examples/46_depthwise_simt_conv2dfprop/CMakeFiles/46_depthwise_simt_conv2dfprop.dir/depthwise_simt_conv2dfprop.cu.o] Error 2
make[2]: *** [CMakeFiles/Makefile2:9244: examples/46_depthwise_simt_conv2dfprop/CMakeFiles/46_depthwise_simt_conv2dfprop.dir/all] Error 2
make[1]: *** [CMakeFiles/Makefile2:9251: examples/46_depthwise_simt_conv2dfprop/CMakeFiles/46_depthwise_simt_conv2dfprop.dir/rule] Error 2
make: *** [Makefile:3177: 46_depthwise_simt_conv2dfprop] Error 2

What is your question?

Questions:

1. How do I fix this error? Are convolutions on NCHW tensors even supported by Cutlass?
2. Basic question: How do I convert a pytorch tensor into a cutlass::TensorRef? I am currently using this snippet of code:

    auto makeDeviceRef = [](const Tensor &tensor) {
      auto tensorLayout = cutlass::layout::TensorNCHW::packed({tensor.stride(0), tensor.stride(1), tensor.stride(2), tensor.stride(3)});
      auto ret = cutlass::make_TensorRef(tensor.data_ptr<scalar_t*>(), tensorLayout);
      return ret;
    };

Does that look correct? 3. Can cutlass handle convolutions with variable filter sizes that are not known at compile time? It seems like templates need to be instantiated with concrete numbers so cutlass only works for known filter sizes. 4. How can I choose what cuda stream to run the kernel on? 5. Is it possible to build the kernel for all sm arches and dynamically choose the one latest one dependent on the what machine I am running on? It seems like that's not possible because the arch has to be passed down to cutlass at compile time to DefaultDepthwiseDirect2dConvFprop. 6. How do I choose meta variables like pipelines stages, groups per CTA, thread block output shape, etc. in an automated way (I am afraid I may choose variables that could slow down my kernel)? Do I have to tune everything by hand or is there a way to choose these variables based on the GPU I am using more automatically? If these are compile-time constants, I may have to use a look-up table to figure them out per GPU? 7. Depth-wise convolution 2D specific question: what is this tensor_b_transpose variable (https://github.com/NVIDIA/cutlass/blob/affd1b693dfc121c51118cbc8583dfd308227ca6/examples/46_depthwise_simt_conv2dfprop/depthwise_simt_conv2dfprop.cu#L424)? It seems like in the code this is not derived from tensor_b at all (I thought it was going to be the transpose of tensor_b, but it seems to not be initialized in the example. Is this just a temporary tensor that is filled by cutlass itself? I am wondering why this is required? Why can't cutlass allocate this tensor by itself?

[hwu36]

@Junkai-Wu

[Junkai-Wu]

@Ethan-Yan27 could you help answer some of the questions here? Thanks!

[Ethan-Yan27]

Q1.

For depthwise conv, it only supports NHWC.

Q3.

Yes. filter size need to be a compile time value as some computations inside kernel rely on the filter size.

Q4.

I think default cuda stream should be okay.

Q5.

Depthwise conv kernel is using cp_async_fill, please build with >=sm80

Q6.

Here is the explanation about depthwise directconv impl and how to set the template: https://github.com/NVIDIA/cutlass/issues/1133#issuecomment-1756668121. several notes:

1. stages, groups per CTA,thread block output shape would affect the smem usage, we should not exceed the HW SMEM limiation.
2. please do not forget use splitK feature to max the SM utilization to get a better perf: https://github.com/NVIDIA/cutlass/issues/1213#issuecomment-1833431916

Q7. kernel would use this temp buffer to reorder the filter tensor https://github.com/NVIDIA/cutlass/blob/main/include/cutlass/conv/kernel/direct_convolution.h#L171

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