Enable convolution with fused epilogue for Volta Tensor Cores (#402)
* Enabled convolution with epilogue fusion for Volta Tensor Cores. * Compilation fixes * Disabled testing Volta on Ampere architectures.
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1e4703cbab
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@ -37,6 +37,10 @@
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#include "cutlass/epilogue/threadblock/default_epilogue_simt.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_simt.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_volta_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_volta_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_with_broadcast.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_with_reduction.h"
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#include "cutlass/conv/convolution.h"
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#include "cutlass/conv/convolution.h"
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#include "cutlass/conv/threadblock/conv2d_tile_iterator.h"
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#include "cutlass/conv/threadblock/conv2d_tile_iterator.h"
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#include "cutlass/conv/threadblock/implicit_gemm_pipelined.h"
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#include "cutlass/conv/threadblock/implicit_gemm_pipelined.h"
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@ -96,6 +100,122 @@ struct DefaultConvEpilogue<
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OutputOp::kCount
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OutputOp::kCount
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>::Epilogue;
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>::Epilogue;
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};
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <
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typename ArchTag,
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typename Shape,
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typename WarpMmaTensorOp,
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int PartitionsK,
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typename ElementOutput,
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typename ElementTensor,
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typename ElementVector,
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typename OutputOp,
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int ElementsPerAccess
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>
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struct DefaultConvEpilogueWithBroadcastTensorOp {
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using Epilogue = typename epilogue::threadblock::DefaultEpilogueWithBroadcastTensorOp<
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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ElementTensor,
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ElementVector,
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OutputOp,
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ElementsPerAccess
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>::Epilogue;
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};
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template <
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typename Shape,
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typename WarpMmaTensorOp,
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int PartitionsK,
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typename ElementOutput,
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typename ElementTensor,
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typename ElementVector,
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typename OutputOp,
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int ElementsPerAccess
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>
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struct DefaultConvEpilogueWithBroadcastTensorOp<
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arch::Sm70,
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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ElementTensor,
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ElementVector,
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OutputOp,
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ElementsPerAccess
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> {
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using Epilogue = typename epilogue::threadblock::DefaultEpilogueWithBroadcastVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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ElementTensor,
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ElementVector,
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OutputOp,
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ElementsPerAccess
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>::Epilogue;
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <
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typename ArchTag,
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typename Shape,
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typename WarpMmaTensorOp,
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int PartitionsK,
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typename ElementOutput,
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typename OutputOp,
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typename ReductionOp,
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int ElementsPerAccess
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>
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struct DefaultConvEpilogueWithReductionTensorOp {
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using Epilogue = typename epilogue::threadblock::DefaultEpilogueWithReductionTensorOp<
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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OutputOp,
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ReductionOp,
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ElementsPerAccess
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>::Epilogue;
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};
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template <
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typename Shape,
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typename WarpMmaTensorOp,
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int PartitionsK,
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typename ElementOutput,
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typename OutputOp,
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typename ReductionOp,
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int ElementsPerAccess
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>
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struct DefaultConvEpilogueWithReductionTensorOp<
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arch::Sm70,
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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OutputOp,
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ReductionOp,
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ElementsPerAccess
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> {
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using Epilogue = typename epilogue::threadblock::DefaultEpilogueWithReductionVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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PartitionsK,
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ElementOutput,
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OutputOp,
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ReductionOp,
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ElementsPerAccess
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>::Epilogue;
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// Defaults for strided Dgrad
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// Defaults for strided Dgrad
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@ -94,7 +94,8 @@ struct DefaultConv2dFpropWithBroadcast {
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>::Kernel;
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>::Kernel;
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// Replace epilogue
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// Replace epilogue
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueWithBroadcastTensorOp<
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using Epilogue = typename cutlass::conv::kernel::detail::DefaultConvEpilogueWithBroadcastTensorOp<
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ArchTag,
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typename ImplicitGemmBase::Epilogue::Shape,
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typename ImplicitGemmBase::Epilogue::Shape,
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typename ImplicitGemmBase::Epilogue::WarpMmaOperator,
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typename ImplicitGemmBase::Epilogue::WarpMmaOperator,
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ImplicitGemmBase::Epilogue::kPartitionsK,
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ImplicitGemmBase::Epilogue::kPartitionsK,
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@ -95,7 +95,8 @@ struct DefaultConv2dFpropWithReduction {
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>::Kernel;
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>::Kernel;
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// Replace epilogue
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// Replace epilogue
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueWithReductionTensorOp<
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using Epilogue = typename cutlass::conv::kernel::detail::DefaultConvEpilogueWithReductionTensorOp<
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ArchTag,
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typename ImplicitGemmBase::Epilogue::Shape,
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typename ImplicitGemmBase::Epilogue::Shape,
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typename ImplicitGemmBase::Epilogue::WarpMmaOperator,
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typename ImplicitGemmBase::Epilogue::WarpMmaOperator,
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ImplicitGemmBase::Epilogue::kPartitionsK,
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ImplicitGemmBase::Epilogue::kPartitionsK,
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@ -129,6 +129,7 @@ endif()
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cutlass_test_unit_add_executable(
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cutlass_test_unit_add_executable(
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cutlass_test_unit_conv_device_tensorop_f32_sm70
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cutlass_test_unit_conv_device_tensorop_f32_sm70
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conv2d_fprop_with_broadcast_sm70.cu
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conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm70.cu
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@ -76,6 +76,49 @@ TEST(SM70_Device_Conv2d_Fprop_Analytic_ImplicitGemm_f16nhwc_f16nhwc_f32nhwc_tens
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EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dFprop>());
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EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dFprop>());
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Device_Conv2d_Fprop_Optimized_ImplicitGemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32,
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128x128_32x2_64x64x32) {
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/// Conv operation element types for the Gemm equivalent (ImplicitGemm)
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = float;
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using ElementAccumulator = float;
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using ElementCompute = float;
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/// Device-level Conv2d instance
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using Conv2dFpropKernel = typename cutlass::conv::kernel::DefaultConv2dFprop<
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ElementA, cutlass::layout::TensorNHWC,
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ElementB, cutlass::layout::TensorNHWC,
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ElementC, cutlass::layout::TensorNHWC,
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ElementAccumulator,
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cutlass::arch::OpClassTensorOp,
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cutlass::arch::Sm70,
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cutlass::gemm::GemmShape<128, 128, 32>,
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cutlass::gemm::GemmShape<64, 64, 32>,
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cutlass::gemm::GemmShape<8, 8, 4>,
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cutlass::epilogue::thread::LinearCombination<
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ElementC,
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128 / cutlass::sizeof_bits<ElementC>::value,
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ElementAccumulator,
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ElementCompute
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>,
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cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
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2,
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cutlass::arch::OpMultiplyAdd,
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cutlass::conv::IteratorAlgorithm::kOptimized
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>::Kernel;
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using Conv2dFprop = cutlass::conv::device::ImplicitGemmConvolution<Conv2dFpropKernel>;
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/// Run all unit test sizes with device-level Conv2d instance
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EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dFprop>());
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}
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////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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#endif // CUTLASS_ARCH_MMA_SM70_SUPPORTED
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#endif // CUTLASS_ARCH_MMA_SM70_SUPPORTED
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121
test/unit/conv/device/conv2d_fprop_with_broadcast_sm70.cu
Normal file
121
test/unit/conv/device/conv2d_fprop_with_broadcast_sm70.cu
Normal file
@ -0,0 +1,121 @@
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/***************************************************************************************************
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* Copyright (c) 2017-2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/*! \file
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\brief Tests for device-wide Implicit GEMM interface
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*/
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#include "../../common/cutlass_unit_test.h"
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#include "cutlass/cutlass.h"
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#include "cutlass/array.h"
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#include "cutlass/epilogue/thread/linear_combination_bias_elementwise.h"
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#include "cutlass/epilogue/thread/linear_combination_residual_block.h"
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#include "cutlass/epilogue/thread/activation.h"
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#include "cutlass/conv/kernel/default_conv2d_fprop_with_broadcast.h"
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#include "cutlass/conv/device/implicit_gemm_convolution.h"
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#include "conv2d_with_broadcast_testbed.h"
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#if defined(CUTLASS_ARCH_MMA_SM70_SUPPORTED)
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// Test residual block fusion: UnaryOp(BinaryOp(ActivationOp(Conv2d(X) + bias), residual))
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// LinearCombinationResidualBlock does not support the split-k mode unless ActivationOp is Identity.
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// This is because the activation needs to be applied to the fully accumulated output of the Conv2d op,
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// which only the last thread block would have an access to, before applying BinaryOp.
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// The epilogue functor in the last thread block would have to be given three inputs, namely
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// partial outputs, bias, and residual, but this is not supported in the current interface.
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// Set TestSplitK = false to skip split-k tests with non-trivial ActivationOp.
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template <
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typename ElementAccumulator,
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template<typename T> class ActivationOp,
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template<typename T> class BinaryOp,
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template<typename T> class UnaryOp,
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bool TestSplitK = false
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>
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void TestResidaulBlock() {
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using ElementD = ElementC;
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using ElementCompute = ElementAccumulator;
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using EpilogueOutputOp = cutlass::epilogue::thread::LinearCombinationResidualBlock<
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ElementD,
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ElementAccumulator,
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ElementCompute,
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ElementC,
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8,
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ActivationOp,
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BinaryOp,
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UnaryOp
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>;
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using Conv2dFpropKernel = typename cutlass::conv::kernel::DefaultConv2dFpropWithBroadcast<
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ElementA, cutlass::layout::TensorNHWC,
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ElementB, cutlass::layout::TensorNHWC,
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ElementC, cutlass::layout::TensorNHWC,
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ElementAccumulator,
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cutlass::arch::OpClassTensorOp,
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cutlass::arch::Sm70,
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cutlass::gemm::GemmShape<128, 128, 32>,
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cutlass::gemm::GemmShape<64, 64, 32>,
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cutlass::gemm::GemmShape<8, 8, 4>,
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EpilogueOutputOp,
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cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
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2,
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cutlass::arch::OpMultiplyAdd,
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cutlass::conv::IteratorAlgorithm::kOptimized
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>::Kernel;
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using Conv2dFprop = cutlass::conv::device::ImplicitGemmConvolution<Conv2dFpropKernel>;
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struct ReferenceOp {
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using OutputOp = typename Conv2dFprop::EpilogueOutputOp;
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using ElementZ = typename OutputOp::ElementZ;
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ActivationOp<ElementCompute> activation;
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BinaryOp<ElementCompute> binary_op;
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UnaryOp<ElementCompute> unary_op;
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void operator()(ElementZ &Z, ElementZ&, ElementCompute conv2d, ElementCompute residual) {
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Z = ElementZ(unary_op(binary_op(activation(conv2d), residual)));
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}
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};
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bool passed = test::conv::device::TestAllConv2dWithBroadcast<Conv2dFprop, ReferenceOp, true, TestSplitK>();
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EXPECT_TRUE(passed);
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}
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TEST(SM70_Device_Conv2d_Fprop_With_Residual_Block_Plus_Optimized_ImplicitGemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32,
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128x128_32x2_64x64x32) {
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// Resnet
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TestResidaulBlock<float, cutlass::epilogue::thread::ReLu, cutlass::plus, cutlass::epilogue::thread::Identity>();
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}
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////////////////////////////////////////////////////////////////////////////////
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#endif // CUTLASS_ARCH_MMA_SM70_SUPPORTED
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////////////////////////////////////////////////////////////////////////////////
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