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IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ /*! \file \brief Default kernel-level fused activation's scale+bias+relu and implicit GEMM convolution definitions that 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_filter_tile_access_iterator_analytic.h" #include "cutlass/conv/threadblock/conv2d_fprop_activation_tile_access_iterator_optimized.h" #include "cutlass/conv/threadblock/conv2d_fprop_filter_tile_access_iterator_optimized.h" #include "cutlass/conv/threadblock/predicated_scale_bias_vector_access_iterator.h" #include "cutlass/transform/threadblock/regular_scale_bias_vector_access_iterator.h" #include "cutlass/gemm/warp/scale_bias_tile_iterator.h" ///////////////////////////////////////////////////////////////////////////////////////////////// namespace cutlass { namespace conv { namespace kernel { ///////////////////////////////////////////////////////////////////////////////////////////////// /// Defines a kernel for fused batch norm and Conv2dFprop template < typename ElementA, typename LayoutA, typename ElementB, typename LayoutB, typename ElementScaleBias, typename LayoutScaleBias, 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::IteratorAlgorithm IteratorAlgorithm = IteratorAlgorithm::kOptimized, conv::StrideSupport StrideSupport = StrideSupport::kUnity > struct DefaultConv2dFpropFusion; ///////////////////////////////////////////////////////////////////////////////////////////////// // OpClassTensorOp convolutions ///////////////////////////////////////////////////////////////////////////////////////////////// /// Defines a kernel for Conv2dFprop specialization for Analytic IteratorAlgorithm and multistage /// pipeline. template < typename ElementA, typename LayoutA, typename ElementB, typename LayoutB, typename ElementScaleBias, typename LayoutScaleBias, typename ElementC, typename LayoutC, typename ElementAccumulator, typename ArchTag, typename ThreadblockShape, typename WarpShape, typename InstructionShape, typename EpilogueOutputOp, typename ThreadblockSwizzle, int Stages, typename MathOperatorTag > struct DefaultConv2dFpropFusion < ElementA, LayoutA, ElementB, LayoutB, ElementScaleBias, LayoutScaleBias, ElementC, LayoutC, ElementAccumulator, arch::OpClassTensorOp, ArchTag, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, Stages, MathOperatorTag, IteratorAlgorithm::kAnalytic > { // 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 IteratorA = cutlass::conv::threadblock::Conv2dFpropActivationTileAccessIteratorAnalytic< cutlass::MatrixShape, ElementA, LayoutA, ThreadMapA >; using SmemIteratorA = typename MmaCore::SmemIteratorA; // Define iterators over tiles from the B operand using ThreadMapB = typename MmaCore::IteratorThreadMapB; using IteratorB = cutlass::conv::threadblock::Conv2dFpropFilterTileAccessIteratorAnalytic< cutlass::MatrixShape, ElementB, LayoutB, ThreadMapB >; using SmemIteratorB = typename MmaCore::SmemIteratorB; /// Define iterators over tiles from scale/bias vectors using IteratorScaleBias = cutlass::conv::threadblock::PredicatedScaleBiasVectorAccessIterator< cutlass::MatrixShape<1, ThreadblockShape::kK>, ElementScaleBias, LayoutScaleBias>; using SmemIteratorScaleBias = cutlass::transform::threadblock::RegularScaleBiasVectorAccessIterator< cutlass::MatrixShape<1, ThreadblockShape::kK>, ElementScaleBias, LayoutScaleBias>; // Warp-level GEMM components using WarpMmaTensorOp = typename MmaCore::MmaTensorOp; using MmaPolicy = typename MmaCore::MmaPolicy; static int const kThreadCount = 32; // Warp-level iterators to load scale and bias vectors using WarpIteratorScaleBias = cutlass::gemm::warp::ScaleBiasTileIterator< MatrixShape, ElementScaleBias, LayoutScaleBias, MatrixShape, typename WarpMmaTensorOp::IteratorA::Base::Policy, kThreadCount, MmaCore::WarpCount::kK>; // Define the Mma using Mma = threadblock::ImplicitGemmFpropFusionMultistage< ThreadblockShape, IteratorA, SmemIteratorA, arch::CacheOperation::Always, IteratorB, SmemIteratorB, arch::CacheOperation::Global, IteratorScaleBias, SmemIteratorScaleBias, arch::CacheOperation::Always, MmaPolicy, WarpIteratorScaleBias, Stages >; // Define the epilogue using Epilogue = typename epilogue::threadblock::DefaultEpilogueTensorOp< ThreadblockShape, WarpMmaTensorOp, 1, EpilogueOutputOp, EpilogueOutputOp::kCount >::Epilogue; // Define the kernel using Kernel = cutlass::conv::kernel::ImplicitGemmConvolutionFusion< Mma, Epilogue, ThreadblockSwizzle, conv::Operator::kFprop >; }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Defines a kernel for Conv2dFprop specialization for Optimzed IteratorAlgorithm and /// multistage pipeline. template < typename ElementA, typename LayoutA, typename ElementB, typename LayoutB, typename ElementScaleBias, typename LayoutScaleBias, typename ElementC, typename LayoutC, typename ElementAccumulator, typename ArchTag, typename ThreadblockShape, typename WarpShape, typename InstructionShape, typename EpilogueOutputOp, typename ThreadblockSwizzle, int Stages, typename MathOperatorTag > struct DefaultConv2dFpropFusion < ElementA, LayoutA, ElementB, LayoutB, ElementScaleBias, LayoutScaleBias, ElementC, LayoutC, ElementAccumulator, arch::OpClassTensorOp, ArchTag, ThreadblockShape, WarpShape, InstructionShape, EpilogueOutputOp, ThreadblockSwizzle, Stages, MathOperatorTag, IteratorAlgorithm::kOptimized > { // 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 IteratorA = cutlass::conv::threadblock::Conv2dFpropActivationTileAccessIteratorOptimized< cutlass::MatrixShape, ElementA, LayoutA, ThreadMapA >; using SmemIteratorA = typename MmaCore::SmemIteratorA; // Define iterators over tiles from the B operand using ThreadMapB = typename MmaCore::IteratorThreadMapB; using IteratorB = cutlass::conv::threadblock::Conv2dFpropFilterTileAccessIteratorOptimized< cutlass::MatrixShape, ElementB, LayoutB, ThreadMapB >; using SmemIteratorB = typename MmaCore::SmemIteratorB; /// Define iterators over tiles from scale/bias vectors using IteratorScaleBias = cutlass::conv::threadblock::PredicatedScaleBiasVectorAccessIterator< cutlass::MatrixShape<1, ThreadblockShape::kK>, ElementScaleBias, LayoutScaleBias>; using SmemIteratorScaleBias = cutlass::transform::threadblock::RegularScaleBiasVectorAccessIterator< cutlass::MatrixShape<1, ThreadblockShape::kK>, ElementScaleBias, LayoutScaleBias>; // Warp-level GEMM components using WarpMmaTensorOp = typename MmaCore::MmaTensorOp; using MmaPolicy = typename MmaCore::MmaPolicy; static int const kThreadCount = 32; // Warp-level iterators to load scale and bias vectors using WarpIteratorScaleBias = cutlass::gemm::warp::ScaleBiasTileIterator< MatrixShape, ElementScaleBias, LayoutScaleBias, MatrixShape, typename WarpMmaTensorOp::IteratorA::Base::Policy, kThreadCount, MmaCore::WarpCount::kK>; // Define the Mma using Mma = threadblock::ImplicitGemmFpropFusionMultistage< ThreadblockShape, IteratorA, SmemIteratorA, arch::CacheOperation::Always, IteratorB, SmemIteratorB, arch::CacheOperation::Global, IteratorScaleBias, SmemIteratorScaleBias, arch::CacheOperation::Always, MmaPolicy, WarpIteratorScaleBias, Stages >; // Define the epilogue using Epilogue = typename epilogue::threadblock::DefaultEpilogueTensorOp< ThreadblockShape, WarpMmaTensorOp, 1, EpilogueOutputOp, EpilogueOutputOp::kCount >::Epilogue; // Define the kernel using Kernel = cutlass::conv::kernel::ImplicitGemmConvolutionFusion< Mma, Epilogue, ThreadblockSwizzle, conv::Operator::kFprop >; }; ///////////////////////////////////////////////////////////////////////////////////////////////// } // namespace kernel } // namespace conv } // namespace cutlass /////////////////////////////////////////////////////////////////////////////////////////////////