mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-04-20 14:59:17 +00:00
Adding remaining conv, dynamic_op, and scaleadd_scaleadd_relu flavors for grouped conv fwd (#3529)
* Adding remaining flavors for grouped conv fwd As titled. Following variants are added: - grouped_conv2d_fwd_dynamic_op - grouped_conv3d_fwd_dynamic_op - grouped_conv3d_fwd_bilinear - grouped_conv3d_fwd_convscale - grouped_conv3d_fwd_convinvscale - grouped_conv3d_fwd_convscale_add - grouped_conv3d_fwd_convscale_relu - grouped_conv3d_fwd_scale - grouped_conv3d_fwd_combconvscale - grouped_conv3d_fwd_scaleadd_scaleadd_relu * Fix incomplete parsing of types from source names in add_instance_library() cmakelists function so we don't build f8 on RDNA3. * Do not build f8 / bf8 only flavor tests on RDNA3 * Make sure we have proper generic instances for all instance lists related to the post-ces extra flavors, with scalarPerVector = 1. Then disable all but one generic instance per instance list to reduce compile time. * Post rebase fix: Template parameters for Grouped Conv Fwd Device Impl got tweaked upstream. * adding int8 and fp16 overloads to the elementwise operations * fixed copilot nits * Addressing review comments: - removed unnecessary examples for dynamic op - removed unnecessary conv specalizations for all the flavors - removed spurious bilinear and scale source files * clang-format * reduced no of tests --------- Co-authored-by: Wojciech Laskowski <wojciech.laskowski@streamhpc.com>
This commit is contained in:
Kiefer van Teutem
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GitHub
GitHub
parent
6a6177a246
commit
2377a62837
@@ -5,4 +5,11 @@ if (NOT GPU_TARGETS MATCHES "gfx11")
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add_custom_target(example_convnd_activ_xdl_convinvscale)
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add_example_executable(example_convnd_fwd_xdl_convinvscale_fp8 convnd_fwd_xdl_convinvscale_fp8.cpp)
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add_example_dependencies(example_convnd_activ_xdl_convinvscale example_convnd_fwd_xdl_convinvscale_fp8)
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endif()
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endif()
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# WMMA
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if (GPU_TARGETS MATCHES "gfx12")
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add_custom_target(example_convnd_activ_wmma_convinvscale)
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add_example_executable(example_convnd_fwd_wmma_convinvscale_fp8 convnd_fwd_wmma_convinvscale_fp8.cpp)
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add_example_dependencies(example_convnd_activ_wmma_convinvscale example_convnd_fwd_wmma_convinvscale_fp8)
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endif()
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@@ -0,0 +1,98 @@
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include "convnd_fwd_convinvscale_common.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
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using InDataType = ck::f8_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::f8_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 = ConvInvscale;
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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_Wmma_CShuffle_V3<
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NDimSpatial, // NDimSpatial
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InLayout, // ALayout
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WeiLayout, // BLayout
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DsLayout, // DsLayout (empty tuple for ConvInvScale)
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OutLayout, // ELayout
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InDataType, // ADataType
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WeiDataType, // BDataType
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AccDataType, // AccDataType
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CShuffleDataType, // CShuffleDataType
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DsDataType, // DsDataType (empty tuple)
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OutDataType, // EDataType
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InElementOp, // AElementwiseOperation
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WeiElementOp, // BElementwiseOperation
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OutElementOp, // CDEElementwiseOperation
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ConvSpec, // ConvForwardSpecialization
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GemmSpec, // GemmSpecialization
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64, // BlockSize
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64, // MPerBlock
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64, // NPerBlock
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32, // KPerBlock
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8, // AK1
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8, // BK1
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16, // MPerWmma
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16, // NPerWmma
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4, // MRepeat
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2, // NRepeat
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S<4, 16, 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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1, // ABlockTransferSrcScalarPerVector
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8, // ABlockTransferDstScalarPerVector_AK1
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1, // ABlockLdsExtraM
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S<4, 16, 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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1, // BBlockTransferSrcScalarPerVector
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8, // BBlockTransferDstScalarPerVector_BK1
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1, // BBlockLdsExtraN
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1, // CShuffleMRepeatPerShuffle
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1, // CShuffleNRepeatPerShuffle
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S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
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1, // CDEBlockTransferScalarPerVector_NPerBlock
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ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
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ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
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true, // UseThreadTileTransfer
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AComputeDataType, // AComputeDataType
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BComputeDataType, // BComputeDataType
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1>; // NumGroupsToMerge
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#include "run_convnd_fwd_convinvscale_example.inc"
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int main(int argc, char* argv[])
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{
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if(!ck::is_gfx12_supported())
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{
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std::cout << "This kernel support gfx12 only" << std::endl;
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return 0;
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}
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return run_convnd_fwd_example(argc, argv) ? 0 : 1;
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}
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@@ -15,3 +15,19 @@ if (NOT GPU_TARGETS MATCHES "gfx11")
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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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endif()
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# WMMA
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if (GPU_TARGETS MATCHES "gfx12")
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add_custom_target(example_convnd_activ_wmma_convscale)
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add_example_executable(example_convnd_fwd_wmma_convscale_fp8 convnd_fwd_wmma_convscale_fp8.cpp)
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add_example_dependencies(example_convnd_activ_wmma_convscale example_convnd_fwd_wmma_convscale_fp8)
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add_example_executable(example_convnd_fwd_wmma_convscale_bf8 convnd_fwd_wmma_convscale_bf8.cpp)
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add_example_dependencies(example_convnd_activ_wmma_convscale example_convnd_fwd_wmma_convscale_bf8)
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add_example_executable(example_convnd_fwd_wmma_convscale_fp8_bf8 convnd_fwd_wmma_convscale_fp8_bf8.cpp)
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add_example_dependencies(example_convnd_activ_wmma_convscale example_convnd_fwd_wmma_convscale_fp8_bf8)
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add_example_executable(example_convnd_fwd_wmma_convscale_bf8_fp8 convnd_fwd_wmma_convscale_bf8_fp8.cpp)
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add_example_dependencies(example_convnd_activ_wmma_convscale example_convnd_fwd_wmma_convscale_bf8_fp8)
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endif()
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@@ -0,0 +1,98 @@
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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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_wmma_cshuffle_v3.hpp"
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using InDataType = ck::bf8_t;
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using WeiDataType = ck::bf8_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 = InDataType;
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using BComputeDataType = AComputeDataType;
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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_Wmma_CShuffle_V3<
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NDimSpatial, // NDimSpatial
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InLayout, // ALayout
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WeiLayout, // BLayout
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DsLayout, // DsLayout (empty tuple for ConvScale)
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OutLayout, // ELayout
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InDataType, // ADataType
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WeiDataType, // BDataType
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AccDataType, // AccDataType
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CShuffleDataType, // CShuffleDataType
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DsDataType, // DsDataType (empty tuple)
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OutDataType, // EDataType
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InElementOp, // AElementwiseOperation
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WeiElementOp, // BElementwiseOperation
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OutElementOp, // CDEElementwiseOperation
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ConvSpec, // ConvForwardSpecialization
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GemmSpec, // GemmSpecialization
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64, // BlockSize
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64, // MPerBlock
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64, // NPerBlock
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32, // KPerBlock
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8, // AK1
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8, // BK1
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16, // MPerWmma
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16, // NPerWmma
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4, // MRepeat
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2, // NRepeat
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S<4, 16, 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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1, // ABlockTransferSrcScalarPerVector
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8, // ABlockTransferDstScalarPerVector_AK1
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1, // ABlockLdsExtraM
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S<4, 16, 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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1, // BBlockTransferSrcScalarPerVector
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8, // BBlockTransferDstScalarPerVector_BK1
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1, // BBlockLdsExtraN
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1, // CShuffleMRepeatPerShuffle
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1, // CShuffleNRepeatPerShuffle
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S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
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1, // CDEBlockTransferScalarPerVector_NPerBlock
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ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
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ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
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true, // UseThreadTileTransfer
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AComputeDataType, // AComputeDataType
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BComputeDataType, // BComputeDataType
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1>; // NumGroupsToMerge
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#include "run_convnd_fwd_convscale_example.inc"
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int main(int argc, char* argv[])
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{
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if(!ck::is_gfx12_supported())
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{
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std::cout << "This kernel support gfx12 only" << std::endl;
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return 0;
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}
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return run_convnd_fwd_example(argc, argv) ? 0 : 1;
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}
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@@ -0,0 +1,98 @@
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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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_wmma_cshuffle_v3.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_Wmma_CShuffle_V3<
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NDimSpatial, // NDimSpatial
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InLayout, // ALayout
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WeiLayout, // BLayout
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DsLayout, // DsLayout (empty tuple for ConvScale)
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OutLayout, // ELayout
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InDataType, // ADataType
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WeiDataType, // BDataType
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AccDataType, // AccDataType
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CShuffleDataType, // CShuffleDataType
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DsDataType, // DsDataType (empty tuple)
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OutDataType, // EDataType
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InElementOp, // AElementwiseOperation
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WeiElementOp, // BElementwiseOperation
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OutElementOp, // CDEElementwiseOperation
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ConvSpec, // ConvForwardSpecialization
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GemmSpec, // GemmSpecialization
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64, // BlockSize
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64, // MPerBlock
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64, // NPerBlock
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32, // KPerBlock
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8, // AK1
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8, // BK1
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16, // MPerWmma
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16, // NPerWmma
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4, // MRepeat
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2, // NRepeat
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S<4, 16, 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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1, // ABlockTransferSrcScalarPerVector
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8, // ABlockTransferDstScalarPerVector_AK1
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1, // ABlockLdsExtraM
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S<4, 16, 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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1, // BBlockTransferSrcScalarPerVector
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8, // BBlockTransferDstScalarPerVector_BK1
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1, // BBlockLdsExtraN
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1, // CShuffleMRepeatPerShuffle
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1, // CShuffleNRepeatPerShuffle
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S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
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1, // CDEBlockTransferScalarPerVector_NPerBlock
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ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
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ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
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true, // UseThreadTileTransfer
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AComputeDataType, // AComputeDataType
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BComputeDataType, // BComputeDataType
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1>; // NumGroupsToMerge
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#include "run_convnd_fwd_convscale_example.inc"
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int main(int argc, char* argv[])
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{
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if(!ck::is_gfx12_supported())
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{
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std::cout << "This kernel support gfx12 only" << std::endl;
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return 0;
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}
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return run_convnd_fwd_example(argc, argv) ? 0 : 1;
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}
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@@ -0,0 +1,98 @@
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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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_wmma_cshuffle_v3.hpp"
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using InDataType = ck::f8_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::f8_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_Wmma_CShuffle_V3<
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NDimSpatial, // NDimSpatial
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InLayout, // ALayout
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WeiLayout, // BLayout
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DsLayout, // DsLayout (empty tuple for ConvScale)
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OutLayout, // ELayout
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InDataType, // ADataType
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WeiDataType, // BDataType
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AccDataType, // AccDataType
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CShuffleDataType, // CShuffleDataType
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DsDataType, // DsDataType (empty tuple)
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OutDataType, // EDataType
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InElementOp, // AElementwiseOperation
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WeiElementOp, // BElementwiseOperation
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OutElementOp, // CDEElementwiseOperation
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ConvSpec, // ConvForwardSpecialization
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GemmSpec, // GemmSpecialization
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64, // BlockSize
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64, // MPerBlock
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64, // NPerBlock
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32, // KPerBlock
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8, // AK1
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8, // BK1
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16, // MPerWmma
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16, // NPerWmma
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4, // MRepeat
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2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
#include "run_convnd_fwd_convscale_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
if(!ck::is_gfx12_supported())
|
||||
{
|
||||
std::cout << "This kernel support gfx12 only" << std::endl;
|
||||
|
||||
return 0;
|
||||
}
|
||||
return run_convnd_fwd_example(argc, argv) ? 0 : 1;
|
||||
}
|
||||
@@ -0,0 +1,98 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include "convnd_fwd_convscale_common.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
|
||||
|
||||
using InDataType = ck::f8_t;
|
||||
using WeiDataType = ck::bf8_t;
|
||||
using AccDataType = float;
|
||||
using CShuffleDataType = float;
|
||||
using DsDataType = ck::Tuple<>;
|
||||
using OutDataType = ck::f8_t;
|
||||
using AComputeDataType = ck::f8_t;
|
||||
using BComputeDataType = ck::bf8_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = PassThrough;
|
||||
using WeiElementOp = PassThrough;
|
||||
using OutElementOp = ConvScale;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
template <ck::index_t NDimSpatial,
|
||||
typename InLayout,
|
||||
typename WeiLayout,
|
||||
typename DsLayout,
|
||||
typename OutLayout>
|
||||
using DeviceGroupedConvNDFwdInstance =
|
||||
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3<
|
||||
NDimSpatial, // NDimSpatial
|
||||
InLayout, // ALayout
|
||||
WeiLayout, // BLayout
|
||||
DsLayout, // DsLayout (empty tuple for ConvScale)
|
||||
OutLayout, // ELayout
|
||||
InDataType, // ADataType
|
||||
WeiDataType, // BDataType
|
||||
AccDataType, // AccDataType
|
||||
CShuffleDataType, // CShuffleDataType
|
||||
DsDataType, // DsDataType (empty tuple)
|
||||
OutDataType, // EDataType
|
||||
InElementOp, // AElementwiseOperation
|
||||
WeiElementOp, // BElementwiseOperation
|
||||
OutElementOp, // CDEElementwiseOperation
|
||||
ConvSpec, // ConvForwardSpecialization
|
||||
GemmSpec, // GemmSpecialization
|
||||
64, // BlockSize
|
||||
64, // MPerBlock
|
||||
64, // NPerBlock
|
||||
32, // KPerBlock
|
||||
8, // AK1
|
||||
8, // BK1
|
||||
16, // MPerWmma
|
||||
16, // NPerWmma
|
||||
4, // MRepeat
|
||||
2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
#include "run_convnd_fwd_convscale_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
if(!ck::is_gfx12_supported())
|
||||
{
|
||||
std::cout << "This kernel support gfx12 only" << std::endl;
|
||||
|
||||
return 0;
|
||||
}
|
||||
return run_convnd_fwd_example(argc, argv) ? 0 : 1;
|
||||
}
|
||||
@@ -5,4 +5,11 @@ if (NOT GPU_TARGETS MATCHES "gfx11")
|
||||
add_custom_target(example_convnd_activ_xdl_convscale_add)
|
||||
add_example_executable(example_convnd_fwd_xdl_convscale_add_fp8 convnd_fwd_xdl_convscale_add_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_xdl_convscale_add example_convnd_fwd_xdl_convscale_add_fp8)
|
||||
endif()
|
||||
endif()
|
||||
|
||||
# WMMA
|
||||
if (GPU_TARGETS MATCHES "gfx12")
|
||||
add_custom_target(example_convnd_activ_wmma_convscale_add)
|
||||
add_example_executable(example_convnd_fwd_wmma_convscale_add_fp8 convnd_fwd_wmma_convscale_add_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_wmma_convscale_add example_convnd_fwd_wmma_convscale_add_fp8)
|
||||
endif()
|
||||
|
||||
@@ -0,0 +1,99 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include "ck/utility/tuple.hpp"
|
||||
#include "convnd_fwd_convscale_add_common.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
|
||||
|
||||
using InDataType = ck::f8_t;
|
||||
using WeiDataType = ck::f8_t;
|
||||
using AccDataType = float;
|
||||
using CShuffleDataType = float;
|
||||
using DsDataType = float;
|
||||
using OutDataType = ck::f8_t;
|
||||
using AComputeDataType = ck::f8_t;
|
||||
using BComputeDataType = ck::f8_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = PassThrough;
|
||||
using WeiElementOp = PassThrough;
|
||||
using OutElementOp = ConvScaleAdd;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
template <ck::index_t NDimSpatial,
|
||||
typename InLayout,
|
||||
typename WeiLayout,
|
||||
typename DsLayout,
|
||||
typename OutLayout>
|
||||
using DeviceGroupedConvNDFwdInstance =
|
||||
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3<
|
||||
NDimSpatial, // NDimSpatial
|
||||
InLayout, // ALayout
|
||||
WeiLayout, // BLayout
|
||||
ck::Tuple<DsLayout>, // DsLayout
|
||||
OutLayout, // ELayout
|
||||
InDataType, // ADataType
|
||||
WeiDataType, // BDataType
|
||||
AccDataType, // AccDataType
|
||||
CShuffleDataType, // CShuffleDataType
|
||||
ck::Tuple<DsDataType>, // DsDataType
|
||||
OutDataType, // EDataType
|
||||
InElementOp, // AElementwiseOperation
|
||||
WeiElementOp, // BElementwiseOperation
|
||||
OutElementOp, // CDEElementwiseOperation
|
||||
ConvSpec, // ConvForwardSpecialization
|
||||
GemmSpec, // GemmSpecialization
|
||||
64, // BlockSize
|
||||
64, // MPerBlock
|
||||
64, // NPerBlock
|
||||
32, // KPerBlock
|
||||
8, // AK1
|
||||
8, // BK1
|
||||
16, // MPerWmma
|
||||
16, // NPerWmma
|
||||
4, // MRepeat
|
||||
2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
#include "run_convnd_fwd_convscale_add_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
if(!ck::is_gfx12_supported())
|
||||
{
|
||||
std::cout << "This kernel support gfx12 only" << std::endl;
|
||||
|
||||
return 0;
|
||||
}
|
||||
return run_convnd_fwd_example(argc, argv) ? 0 : 1;
|
||||
}
|
||||
@@ -8,4 +8,11 @@ if (NOT GPU_TARGETS MATCHES "gfx11")
|
||||
|
||||
add_example_executable(example_convnd_fwd_xdl_convscale_amax_fp8 convnd_fwd_xdl_convscale_amax_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_xdl_convscale_reduce example_convnd_fwd_xdl_convscale_amax_fp8)
|
||||
endif()
|
||||
endif()
|
||||
|
||||
# WMMA
|
||||
if (GPU_TARGETS MATCHES "gfx12")
|
||||
add_custom_target(example_convnd_activ_wmma_convscale_reduce)
|
||||
add_example_executable(example_convnd_fwd_wmma_convscale_amax_fp8 convnd_fwd_wmma_convscale_amax_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_wmma_convscale_reduce example_convnd_fwd_wmma_convscale_amax_fp8)
|
||||
endif()
|
||||
|
||||
@@ -0,0 +1,94 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include "convnd_fwd_convscale_reduce_common.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
|
||||
|
||||
using InDataType = ck::f8_t;
|
||||
using WeiDataType = ck::f8_t;
|
||||
using AccDataType = float;
|
||||
using CShuffleDataType = float;
|
||||
using ConvOutDataType = float; // data type of convolution result
|
||||
using OutDataType = ck::f8_t; // data type of final result
|
||||
using AComputeDataType = ck::f8_t;
|
||||
using BComputeDataType = ck::f8_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = PassThrough;
|
||||
using WeiElementOp = PassThrough;
|
||||
using OutElementOp = ConvScale;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
template <ck::index_t NDimSpatial, typename InLayout, typename WeiLayout, typename OutLayout>
|
||||
using DeviceGroupedConvNDFwdInstance =
|
||||
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3<
|
||||
NDimSpatial, // NDimSpatial
|
||||
InLayout, // ALayout
|
||||
WeiLayout, // BLayout
|
||||
ck::Tuple<>, // DsLayout
|
||||
OutLayout, // ELayout
|
||||
InDataType, // ADataType
|
||||
WeiDataType, // BDataType
|
||||
AccDataType, // AccDataType
|
||||
CShuffleDataType, // CShuffleDataType
|
||||
ck::Tuple<>, // DsDataType
|
||||
ConvOutDataType, // EDataType
|
||||
InElementOp, // AElementwiseOperation
|
||||
WeiElementOp, // BElementwiseOperation
|
||||
OutElementOp, // CDEElementwiseOperation
|
||||
ConvSpec, // ConvForwardSpecialization
|
||||
GemmSpec, // GemmSpecialization
|
||||
64, // BlockSize
|
||||
64, // MPerBlock
|
||||
64, // NPerBlock
|
||||
32, // KPerBlock
|
||||
8, // AK1
|
||||
8, // BK1
|
||||
16, // MPerWmma
|
||||
16, // NPerWmma
|
||||
4, // MRepeat
|
||||
2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
#include "run_convnd_fwd_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
if(!ck::is_gfx12_supported())
|
||||
{
|
||||
std::cout << "This kernel support gfx12 only" << std::endl;
|
||||
|
||||
return 0;
|
||||
}
|
||||
return run_convnd_fwd_example(argc, argv) ? 0 : 1;
|
||||
}
|
||||
@@ -6,3 +6,10 @@ if (NOT GPU_TARGETS MATCHES "gfx11")
|
||||
add_example_executable(example_convnd_fwd_xdl_convscale_relu_fp8 convnd_fwd_xdl_convscale_relu_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_xdl_convscale_relu example_convnd_fwd_xdl_convscale_relu_fp8)
|
||||
endif()
|
||||
|
||||
# WMMA
|
||||
if (GPU_TARGETS MATCHES "gfx12")
|
||||
add_custom_target(example_convnd_activ_wmma_convscale_relu)
|
||||
add_example_executable(example_convnd_fwd_wmma_convscale_relu_fp8 convnd_fwd_wmma_convscale_relu_fp8.cpp)
|
||||
add_example_dependencies(example_convnd_activ_wmma_convscale_relu example_convnd_fwd_wmma_convscale_relu_fp8)
|
||||
endif()
|
||||
|
||||
@@ -0,0 +1,98 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include "convnd_fwd_convscale_relu_common.hpp"
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
|
||||
|
||||
using InDataType = ck::f8_t;
|
||||
using WeiDataType = ck::f8_t;
|
||||
using AccDataType = float;
|
||||
using CShuffleDataType = float;
|
||||
using DsDataType = ck::Tuple<>;
|
||||
using OutDataType = ck::f8_t;
|
||||
using AComputeDataType = ck::f8_t;
|
||||
using BComputeDataType = ck::f8_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = PassThrough;
|
||||
using WeiElementOp = PassThrough;
|
||||
using OutElementOp = ConvScaleRelu;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
template <ck::index_t NDimSpatial,
|
||||
typename InLayout,
|
||||
typename WeiLayout,
|
||||
typename DsLayout,
|
||||
typename OutLayout>
|
||||
using DeviceGroupedConvNDFwdInstance =
|
||||
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3<
|
||||
NDimSpatial, // NDimSpatial
|
||||
InLayout, // ALayout
|
||||
WeiLayout, // BLayout
|
||||
DsLayout, // DsLayout (empty tuple for ConvScaleRelu)
|
||||
OutLayout, // ELayout
|
||||
InDataType, // ADataType
|
||||
WeiDataType, // BDataType
|
||||
AccDataType, // AccDataType
|
||||
CShuffleDataType, // CShuffleDataType
|
||||
DsDataType, // DsDataType (empty tuple)
|
||||
OutDataType, // EDataType
|
||||
InElementOp, // AElementwiseOperation
|
||||
WeiElementOp, // BElementwiseOperation
|
||||
OutElementOp, // CDEElementwiseOperation
|
||||
ConvSpec, // ConvForwardSpecialization
|
||||
GemmSpec, // GemmSpecialization
|
||||
64, // BlockSize
|
||||
64, // MPerBlock
|
||||
64, // NPerBlock
|
||||
32, // KPerBlock
|
||||
8, // AK1
|
||||
8, // BK1
|
||||
16, // MPerWmma
|
||||
16, // NPerWmma
|
||||
4, // MRepeat
|
||||
2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
#include "run_convnd_fwd_convscale_relu_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
if(!ck::is_gfx12_supported())
|
||||
{
|
||||
std::cout << "This kernel support gfx12 only" << std::endl;
|
||||
|
||||
return 0;
|
||||
}
|
||||
return run_convnd_fwd_example(argc, argv) ? 0 : 1;
|
||||
}
|
||||
@@ -37,4 +37,10 @@ add_example_executable(example_convnd_fwd_xdl_dynamic_passthrough_fp16 convnd_fw
|
||||
add_example_dependencies(example_convnd_activ_dynamic_unary_xdl example_convnd_fwd_xdl_dynamic_passthrough_fp16)
|
||||
# Logistic
|
||||
add_example_executable(example_convnd_fwd_xdl_dynamic_logistic_fp16 convnd_fwd_xdl_dynamic_logistic_fp16.cpp)
|
||||
add_example_dependencies(example_convnd_activ_dynamic_unary_xdl example_convnd_fwd_xdl_dynamic_logistic_fp16)
|
||||
add_example_dependencies(example_convnd_activ_dynamic_unary_xdl example_convnd_fwd_xdl_dynamic_logistic_fp16)
|
||||
|
||||
# WMMA
|
||||
add_custom_target(example_convnd_activ_dynamic_unary_wmma)
|
||||
# PassThrough
|
||||
add_example_executable(example_convnd_fwd_wmma_dynamic_passthrough_fp16 convnd_fwd_wmma_dynamic_passthrough_fp16.cpp)
|
||||
add_example_dependencies(example_convnd_activ_dynamic_unary_wmma example_convnd_fwd_wmma_dynamic_passthrough_fp16)
|
||||
|
||||
@@ -0,0 +1,245 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <cstdlib>
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
#include <type_traits>
|
||||
|
||||
#include "ck/ck.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_wmma_cshuffle_v3.hpp"
|
||||
|
||||
#include "ck/library/utility/algorithm.hpp"
|
||||
#include "ck/library/utility/check_err.hpp"
|
||||
#include "ck/library/utility/device_memory.hpp"
|
||||
#include "ck/library/utility/host_tensor.hpp"
|
||||
#include "ck/library/utility/host_tensor_generator.hpp"
|
||||
#include "ck/library/utility/convolution_parameter.hpp"
|
||||
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
|
||||
#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
|
||||
#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
|
||||
|
||||
constexpr ck::index_t NDimSpatial = 3;
|
||||
using InDataType = ck::half_t;
|
||||
using WeiDataType = ck::half_t;
|
||||
using AccDataType = float;
|
||||
using CShuffleDataType = ck::half_t;
|
||||
using OutDataType = ck::half_t;
|
||||
using AComputeDataType = ck::half_t;
|
||||
using BComputeDataType = ck::half_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
// Use correct tensor layouts for WMMA (matching working tests)
|
||||
using InLayout = ck::tensor_layout::convolution::NDHWGC;
|
||||
using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
|
||||
using OutLayout = ck::tensor_layout::convolution::NDHWGK;
|
||||
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using DynamicElementOp = ck::tensor_operation::element_wise::DynamicUnaryOp;
|
||||
|
||||
static constexpr auto ConvSpec =
|
||||
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
|
||||
|
||||
static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
|
||||
|
||||
using DeviceGroupedConvNDActivInstance =
|
||||
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3<
|
||||
NDimSpatial, // NDimSpatial
|
||||
InLayout, // ALayout
|
||||
WeiLayout, // BLayout
|
||||
ck::Tuple<>, // DsLayout
|
||||
OutLayout, // ELayout
|
||||
InDataType, // ADataType
|
||||
WeiDataType, // BDataType
|
||||
AccDataType, // AccDataType
|
||||
CShuffleDataType, // CShuffleDataType
|
||||
ck::Tuple<>, // DsDataType
|
||||
OutDataType, // EDataType
|
||||
InElementOp, // AElementwiseOperation
|
||||
WeiElementOp, // BElementwiseOperation
|
||||
DynamicElementOp, // CDEElementwiseOperation
|
||||
ConvSpec, // ConvForwardSpecialization
|
||||
GemmSpec, // GemmSpecialization
|
||||
64, // BlockSize
|
||||
64, // MPerBlock
|
||||
64, // NPerBlock
|
||||
32, // KPerBlock
|
||||
8, // AK1
|
||||
8, // BK1
|
||||
16, // MPerWmma
|
||||
16, // NPerWmma
|
||||
4, // MRepeat
|
||||
2, // NRepeat
|
||||
S<4, 16, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
1, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_AK1
|
||||
1, // ABlockLdsExtraM
|
||||
S<4, 16, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
|
||||
S<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // BBlockTransferSrcAccessOrder
|
||||
2, // BBlockTransferSrcVectorDim
|
||||
1, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_BK1
|
||||
1, // BBlockLdsExtraN
|
||||
1, // CShuffleMRepeatPerShuffle
|
||||
1, // CShuffleNRepeatPerShuffle
|
||||
S<1, 16, 1, 4>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
1, // CDEBlockTransferScalarPerVector_NPerBlock
|
||||
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
|
||||
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
|
||||
true, // UseThreadTileTransfer
|
||||
AComputeDataType, // AComputeDataType
|
||||
BComputeDataType, // BComputeDataType
|
||||
1>; // NumGroupsToMerge
|
||||
|
||||
template <ck::index_t NDimSpatial,
|
||||
typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename InElementOp,
|
||||
typename WeiElementOp,
|
||||
typename OutElementOp,
|
||||
typename DeviceConvNDFwdInstance>
|
||||
bool run_grouped_conv(bool do_verification,
|
||||
int init_method,
|
||||
bool time_kernel,
|
||||
const ck::utils::conv::ConvParam& conv_param,
|
||||
const ck::HostTensorDescriptor& in_g_n_c_wis_desc,
|
||||
const ck::HostTensorDescriptor& wei_g_k_c_xs_desc,
|
||||
const ck::HostTensorDescriptor& out_g_n_k_wos_desc,
|
||||
const InElementOp& in_element_op,
|
||||
const WeiElementOp& wei_element_op,
|
||||
const OutElementOp& out_element_op)
|
||||
{
|
||||
ck::Tensor<InDataType> in(in_g_n_c_wis_desc);
|
||||
ck::Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
|
||||
ck::Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
|
||||
ck::Tensor<OutDataType> out_device(out_g_n_k_wos_desc);
|
||||
|
||||
std::cout << "in: " << in.mDesc << std::endl;
|
||||
std::cout << "wei: " << wei.mDesc << std::endl;
|
||||
std::cout << "out: " << out_host.mDesc << std::endl;
|
||||
|
||||
switch(init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 2});
|
||||
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
|
||||
break;
|
||||
default:
|
||||
in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
|
||||
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.05, 0.05});
|
||||
}
|
||||
|
||||
ck::DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
|
||||
ck::DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
|
||||
ck::DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
|
||||
|
||||
in_device_buf.ToDevice(in.mData.data());
|
||||
wei_device_buf.ToDevice(wei.mData.data());
|
||||
|
||||
std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_lengths{};
|
||||
std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_strides{};
|
||||
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
|
||||
std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
|
||||
std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_lengths{};
|
||||
std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_strides{};
|
||||
std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
|
||||
std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
|
||||
std::array<ck::index_t, NDimSpatial> input_left_pads{};
|
||||
std::array<ck::index_t, NDimSpatial> input_right_pads{};
|
||||
|
||||
auto copy = [](const auto& x, auto& y) { ck::ranges::copy(x, y.begin()); };
|
||||
|
||||
copy(in_g_n_c_wis_desc.GetLengths(), a_g_n_c_wis_lengths);
|
||||
copy(in_g_n_c_wis_desc.GetStrides(), a_g_n_c_wis_strides);
|
||||
copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
|
||||
copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
|
||||
copy(out_g_n_k_wos_desc.GetLengths(), e_g_n_k_wos_lengths);
|
||||
copy(out_g_n_k_wos_desc.GetStrides(), e_g_n_k_wos_strides);
|
||||
copy(conv_param.conv_filter_strides_, conv_filter_strides);
|
||||
copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
|
||||
copy(conv_param.input_left_pads_, input_left_pads);
|
||||
copy(conv_param.input_right_pads_, input_right_pads);
|
||||
|
||||
// do Conv
|
||||
auto conv = DeviceConvNDFwdInstance{};
|
||||
auto invoker = conv.MakeInvoker();
|
||||
auto argument = conv.MakeArgument(in_device_buf.GetDeviceBuffer(),
|
||||
wei_device_buf.GetDeviceBuffer(),
|
||||
std::array<const void*, 0>{},
|
||||
out_device_buf.GetDeviceBuffer(),
|
||||
a_g_n_c_wis_lengths,
|
||||
a_g_n_c_wis_strides,
|
||||
b_g_k_c_xs_lengths,
|
||||
b_g_k_c_xs_strides,
|
||||
std::array<std::array<ck::index_t, NDimSpatial + 3>, 0>{{}},
|
||||
std::array<std::array<ck::index_t, NDimSpatial + 3>, 0>{{}},
|
||||
e_g_n_k_wos_lengths,
|
||||
e_g_n_k_wos_strides,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op);
|
||||
|
||||
if(!conv.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error("The device op with the specified compilation parameters does "
|
||||
"not support this convolution problem.");
|
||||
}
|
||||
|
||||
float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
|
||||
|
||||
std::size_t flop = conv_param.GetFlops();
|
||||
std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>();
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / avg_time;
|
||||
float gb_per_sec = num_btype / 1.E6 / avg_time;
|
||||
std::cout << "Perf: " << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
|
||||
<< conv.GetTypeString() << std::endl;
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
|
||||
InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp>();
|
||||
|
||||
auto ref_invoker = ref_conv.MakeInvoker();
|
||||
auto ref_argument = ref_conv.MakeArgument(in,
|
||||
wei,
|
||||
out_host,
|
||||
conv_param.conv_filter_strides_,
|
||||
conv_param.conv_filter_dilations_,
|
||||
conv_param.input_left_pads_,
|
||||
conv_param.input_right_pads_,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op);
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
out_device_buf.FromDevice(out_device.mData.data());
|
||||
|
||||
return ck::utils::check_err(out_device, out_host, "Error: incorrect results!", 1e-3, 0.1);
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
@@ -0,0 +1,12 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
#include "convnd_fwd_activ_dynamic_unary_wmma_common.hpp"
|
||||
|
||||
#include "../run_convnd_activ_dynamic_example.inc"
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
ck::tensor_operation::element_wise::PassThrough out_element_op;
|
||||
return !run_convnd_example(argc, argv, out_element_op);
|
||||
}
|
||||
@@ -47,6 +47,12 @@ bool run_convnd_example(int argc, char* argv[], const OutElementOp& out_element_
|
||||
conv_param = ck::utils::conv::parse_conv_param(num_dim_spatial, 5, argv);
|
||||
}
|
||||
|
||||
if(std::is_same_v<OutElementOp, ck::tensor_operation::element_wise::SoftRelu> &&
|
||||
init_method != 2)
|
||||
{
|
||||
std::cout << "Running SoftRelu op with int initialization. Risk of overflow.\n\n";
|
||||
}
|
||||
|
||||
const auto in_element_op = InElementOp{};
|
||||
const auto wei_element_op = WeiElementOp{};
|
||||
|
||||
|
||||
Reference in New Issue
Block a user