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https://github.com/ROCm/composable_kernel.git
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Add instances for grouped conv fwd 3d with ConvScale for bf8@fp8->fp8 (#1369)
* Add an example
* Add instances
* Add a client example
[ROCm/composable_kernel commit: 7a46a91c84]
This commit is contained in:
@@ -51,6 +51,10 @@ target_link_libraries(client_conv3d_fwd_convscale_bf8 PRIVATE composable_kernel:
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add_executable(client_conv3d_fwd_convscale_fp8_bf8
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grouped_convnd_fwd_convscale/conv3d_fwd_convscale_fp8_bf8.cpp)
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target_link_libraries(client_conv3d_fwd_convscale_fp8_bf8 PRIVATE composable_kernel::device_conv_operations)
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add_executable(client_conv3d_fwd_convscale_bf8_fp8
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grouped_convnd_fwd_convscale/conv3d_fwd_convscale_bf8_fp8.cpp)
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target_link_libraries(client_conv3d_fwd_convscale_bf8_fp8 PRIVATE composable_kernel::device_conv_operations)
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# Bwd data bilinear
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add_executable(client_grouped_convnd_bwd_data_bilinear_residual_fp16
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grouped_convnd_bwd_data_bilinear/grouped_conv_bwd_data_bilinear_residual_fp16.cpp)
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@@ -0,0 +1,50 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
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#include "common.hpp"
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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using InDataType = ck::bf8_t;
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using WeiDataType = ck::f8_t;
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using CShuffleDataType = float;
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using OutDataType = ck::f8_t;
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using AComputeDataType = ck::bf8_t;
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using BComputeDataType = ck::f8_t;
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using InLayout = ck::tensor_layout::convolution::NDHWGC;
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using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
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using OutLayout = ck::tensor_layout::convolution::NDHWGK;
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static constexpr ck::index_t NumDimSpatial = 3;
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static constexpr ck::index_t G = 1;
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static constexpr ck::index_t N = 64;
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static constexpr ck::index_t K = 128;
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static constexpr ck::index_t C = 64;
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static constexpr ck::index_t Z = 3;
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static constexpr ck::index_t Y = 3;
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static constexpr ck::index_t X = 3;
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static constexpr ck::index_t Di = 28;
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static constexpr ck::index_t Hi = 28;
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static constexpr ck::index_t Wi = 3;
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static constexpr ck::index_t Do = 28;
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static constexpr ck::index_t Ho = 28;
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static constexpr ck::index_t Wo = 3;
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int main()
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{
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return run_grouped_conv_fwd_convscale<NumDimSpatial,
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InDataType,
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WeiDataType,
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OutDataType,
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InLayout,
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WeiLayout,
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OutLayout,
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3,
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AComputeDataType,
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BComputeDataType>(
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{N, Di, Hi, Wi, G, C}, {G, K, Z, Y, X, C}, {N, Do, Ho, Wo, G, K})
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? EXIT_SUCCESS
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: EXIT_FAILURE;
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}
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@@ -12,6 +12,9 @@ foreach(gpu IN LISTS GPU_TARGETS)
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add_example_executable(example_convnd_fwd_xdl_convscale_fp8_bf8 convnd_fwd_xdl_convscale_fp8_bf8.cpp)
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add_example_dependencies(example_convnd_activ_xdl_convscale example_convnd_fwd_xdl_convscale_fp8_bf8)
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add_example_executable(example_convnd_fwd_xdl_convscale_bf8_fp8 convnd_fwd_xdl_convscale_bf8_fp8.cpp)
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add_example_dependencies(example_convnd_activ_xdl_convscale example_convnd_fwd_xdl_convscale_bf8_fp8)
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set(target 1)
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endif()
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endforeach()
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@@ -0,0 +1,88 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
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#include "convnd_fwd_convscale_common.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_xdl_cshuffle.hpp"
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#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
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using InDataType = ck::bf8_t;
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using WeiDataType = ck::f8_t;
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using AccDataType = float;
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using CShuffleDataType = float;
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using DsDataType = ck::Tuple<>;
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using OutDataType = ck::f8_t;
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using AComputeDataType = ck::bf8_t;
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using BComputeDataType = ck::f8_t;
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template <ck::index_t... Is>
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using S = ck::Sequence<Is...>;
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using InElementOp = PassThrough;
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using WeiElementOp = PassThrough;
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using OutElementOp = ConvScale;
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static constexpr auto ConvSpec =
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ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
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static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
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template <ck::index_t NDimSpatial,
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typename InLayout,
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typename WeiLayout,
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typename DsLayout,
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typename OutLayout>
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using DeviceGroupedConvNDFwdInstance =
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ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<
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NDimSpatial,
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InLayout,
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WeiLayout,
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DsLayout,
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OutLayout,
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InDataType,
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WeiDataType,
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AccDataType,
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CShuffleDataType,
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DsDataType,
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OutDataType,
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InElementOp,
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WeiElementOp,
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OutElementOp,
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ConvSpec, // ConvForwardSpecialization
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GemmSpec, // GemmSpecialization
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1, //
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256, // BlockSize
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128, // MPerBlock
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256, // NPerBlock
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32, // KPerBlock
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8, // AK1
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8, // BK1
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32, // MPerXdl
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32, // NPerXdl
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2, // MXdlPerWave
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4, // NXdlPerWave
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S<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
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S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
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S<1, 0, 2>, // ABlockTransferSrcAccessOrder
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2, // ABlockTransferSrcVectorDim
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8, // ABlockTransferSrcScalarPerVector
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8, // ABlockTransferDstScalarPerVector_AK1
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1, // ABlockLdsExtraM
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S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
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S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
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S<1, 0, 2>, // BBlockTransferSrcAccessOrder
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2, // BBlockTransferSrcVectorDim
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8, // BBlockTransferSrcScalarPerVector
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8, // BBlockTransferDstScalarPerVector_BK1
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1, // BBlockLdsExtraN
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1,
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1,
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S<1, 32, 1, 8>,
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8,
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AComputeDataType,
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BComputeDataType>;
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#include "run_convnd_fwd_convscale_example.inc"
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int main(int argc, char* argv[]) { return run_convnd_fwd_example(argc, argv) ? 0 : 1; }
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@@ -147,6 +147,43 @@ using device_grouped_conv_fwd_xdl_outelementop_f8_bf8_instances = std::tuple<
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// clang-format on
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>;
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template <index_t NDimSpatial,
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typename ALayout,
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typename BLayout,
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typename DsLayout,
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typename ELayout,
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ConvolutionForwardSpecialization ConvSpec,
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typename OutElementOp>
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using device_grouped_conv_fwd_xdl_outelementop_bf8_f8_instances = std::tuple<
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// clang-format off
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//########################################| NumDim| A| B| Ds| E| AData| BData| AccData| CShuffle| Ds| EData| A| B| CDE| ConvForward| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| Compute| Compute|
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//########################################| Spatial| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| DataType| Type| Elementwise| Elementwise| Elementwise| Specialization| Specialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector| TypeA| TypeB|
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//########################################| | | | | | | | | | | | Operation| Operation| Operation| | | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl| | |
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//########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
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#if defined(CK_ENABLE_FP8) && defined(CK_ENABLE_BF8)
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// generic instance
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, 1, 1, S<1, 16, 1, 4>, 1, BF8, F8>,
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// instances for small conv.K and conv.C
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 1, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 128, 128, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 128, 32, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8, BF8, F8>,
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DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<NDimSpatial,ALayout,BLayout, DsLayout,ELayout, BF8, F8, F32, F32, Tuple<>, F8, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmMNKPadding, 1, 64, 32, 64, 32, 8, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8, BF8, F8>
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#endif
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// clang-format on
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>;
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} // namespace instance
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} // namespace device
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} // namespace tensor_operation
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@@ -70,6 +70,22 @@ void add_device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_f8_bf8_ins
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ConvScale,
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F8,
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BF8>>>& instances);
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void add_device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_bf8_f8_instances(
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std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleABD<3,
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NDHWGC,
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GKZYXC,
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ck::Tuple<>,
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NDHWGK,
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BF8,
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F8,
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ck::Tuple<>,
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F8,
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PassThrough,
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PassThrough,
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ConvScale,
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BF8,
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F8>>>& instances);
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#endif
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template <ck::index_t NumDimSpatial,
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@@ -147,6 +163,14 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
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add_device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_f8_bf8_instances(
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op_ptrs);
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}
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if constexpr(is_same_v<InDataType, bf8_t> && is_same_v<WeiDataType, f8_t> &&
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is_same_v<OutDataType, f8_t> && is_same_v<AComputeType, bf8_t> &&
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is_same_v<BComputeType, f8_t>)
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{
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add_device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_bf8_f8_instances(
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op_ptrs);
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}
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#endif
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}
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return op_ptrs;
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@@ -2,6 +2,7 @@
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set(GROUPED_CONV3D_FWD_CONVSCALE
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xdl/device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_f8_instance.cpp
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xdl/device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_bf8_instance.cpp
|
||||
xdl/device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_f8_bf8_instance.cpp)
|
||||
xdl/device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_f8_bf8_instance.cpp
|
||||
xdl/device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_bf8_f8_instance.cpp)
|
||||
|
||||
add_instance_library(device_grouped_conv3d_fwd_convscale_instance ${GROUPED_CONV3D_FWD_CONVSCALE})
|
||||
|
||||
@@ -0,0 +1,62 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#include "ck/library/tensor_operation_instance/gpu/grouped_conv_fwd/device_grouped_conv_fwd_xdl_outelementop_instance.hpp"
|
||||
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace instance {
|
||||
|
||||
using ConvScale = ck::tensor_operation::element_wise::ConvScale;
|
||||
|
||||
void add_device_grouped_conv3d_fwd_xdl_convscale_ndhwgc_gkzyxc_ndhwgk_bf8_f8_instances(
|
||||
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleABD<3,
|
||||
NDHWGC,
|
||||
GKZYXC,
|
||||
ck::Tuple<>,
|
||||
NDHWGK,
|
||||
BF8,
|
||||
F8,
|
||||
ck::Tuple<>,
|
||||
F8,
|
||||
PassThrough,
|
||||
PassThrough,
|
||||
ConvScale,
|
||||
BF8,
|
||||
F8>>>& instances)
|
||||
{
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_grouped_conv_fwd_xdl_outelementop_bf8_f8_instances<3,
|
||||
NDHWGC,
|
||||
GKZYXC,
|
||||
ck::Tuple<>,
|
||||
NDHWGK,
|
||||
ConvFwdDefault,
|
||||
ConvScale>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_grouped_conv_fwd_xdl_outelementop_bf8_f8_instances<3,
|
||||
NDHWGC,
|
||||
GKZYXC,
|
||||
ck::Tuple<>,
|
||||
NDHWGK,
|
||||
ConvFwd1x1P0,
|
||||
ConvScale>{});
|
||||
add_device_operation_instances(
|
||||
instances,
|
||||
device_grouped_conv_fwd_xdl_outelementop_bf8_f8_instances<3,
|
||||
NDHWGC,
|
||||
GKZYXC,
|
||||
ck::Tuple<>,
|
||||
NDHWGK,
|
||||
ConvFwd1x1S1P0,
|
||||
ConvScale>{});
|
||||
}
|
||||
|
||||
} // namespace instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
Reference in New Issue
Block a user