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Merge branch 'develop' into normalization/splitK

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library/src/tensor_operation_instance/gpu/grouped_gemm/device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instance.cpp 0 → 100644
View file @ 0d6da13c
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_xdl_splitk_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using Empty_Tuple = ck::Tuple<>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// a[m, k] * b[n, k] = e[m, n]
using device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances = std::tuple<
// clang-format off
//################################| A| B| Ds| E| AData| BData| AccData| CShuffle| DsData| EData| A| B| C| 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|
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| 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|
//################################| | | | | | | | | | | 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|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 128, 128, 32, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 128, 32, 128, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmDefault, 1, 64, 32, 64, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>
// clang-format on
>;
void add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemm<Row,
Col,
Empty_Tuple,
Row,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances)
{
add_device_operation_instances(instances,
device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/grouped_gemm/device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_instance.cpp 0 → 100644
View file @ 0d6da13c
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_xdl_splitk_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using Empty_Tuple = ck::Tuple<>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
using device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_tile_instances = std::tuple<
// clang-format off
//################################| A| B| Ds| E| AData| BData| AccData| CShuffle| DsData| EData| A| B| C| 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|
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| 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|
//################################| | | | | | | | | | | 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|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 192, 64, 32, 8, 8, 32, 32, 3, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 64, 192, 32, 8, 8, 32, 32, 1, 3, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 48, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 192, 32, 32, 8, 8, 32, 32, 3, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
// DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 32, 192, 32, 8, 8, 32, 32, 1, 3, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 128, 32, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 32, 128, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 32, 256, 32, 8, 8, 32, 32, 1, 4, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 32, 64, 32, 8, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 64, 32, 32, 8, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 128, 64, 64, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedGemmXdlSplitKCShuffle< Row, Col, Empty_Tuple, Row, F16, F16, F32, F16, Empty_Tuple, F16, PassThrough, PassThrough, PassThrough, GemmMNKPadding, 1, 64, 32, 64, 32, 8, 8, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>
// clang-format on
>;
void add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_instances(
std::vector<std::unique_ptr<DeviceGroupedGemm<Row,
Col,
Empty_Tuple,
Row,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances)
{
add_device_operation_instances(
instances, device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_tile_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/conv2d_quantization_common.hpp
View file @ 0d6da13c
...@@ -19,9 +19,9 @@ using Empty_Tuple = ck::Tuple<>; ...@@ -19,9 +19,9 @@ using Empty_Tuple = ck::Tuple<>;
template <ck::index_t... Is> template <ck::index_t... Is>
using S = ck::Sequence<Is...>; using S = ck::Sequence<Is...>;
using GNHWC = ck::tensor_layout::convolution::GNHWC; using NHWGC = ck::tensor_layout::convolution::NHWGC;
using GKYXC = ck::tensor_layout::convolution::GKYXC; using GKYXC = ck::tensor_layout::convolution::GKYXC;
using GNHWK = ck::tensor_layout::convolution::GNHWK; using NHWGK = ck::tensor_layout::convolution::NHWGK;
using GK = ck::tensor_layout::convolution::G_K; using GK = ck::tensor_layout::convolution::G_K;
using PassThrough = ck::tensor_operation::element_wise::PassThrough; using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using Relu = ck::tensor_operation::element_wise::Relu; using Relu = ck::tensor_operation::element_wise::Relu;
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_bias_perchannel_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -23,19 +23,28 @@ void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances( ...@@ -23,19 +23,28 @@ void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
{ {
// dl // dl
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -44,10 +53,10 @@ void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances( ...@@ -44,10 +53,10 @@ void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -58,19 +67,28 @@ void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances( ...@@ -58,19 +67,28 @@ void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(
{ {
// dl // dl
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -79,10 +97,10 @@ void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances( ...@@ -79,10 +97,10 @@ void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances(
void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -93,19 +111,28 @@ void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances( ...@@ -93,19 +111,28 @@ void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances(
{ {
// dl // dl
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_bias_perlayer_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
Add_Mul_Clamp>>>& instances) Add_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -56,21 +65,30 @@ void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances( ...@@ -56,21 +65,30 @@ void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(
Add_Relu_Mul_Clamp>>>& instances) Add_Relu_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -79,10 +97,10 @@ void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances( ...@@ -79,10 +97,10 @@ void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances(
void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -92,21 +110,30 @@ void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances( ...@@ -92,21 +110,30 @@ void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances(
Add_Mul_TanH_Mul_Clamp>>>& instances) Add_Mul_TanH_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_int8_instance.hpp
View file @ 0d6da13c
...@@ -12,7 +12,10 @@ namespace device { ...@@ -12,7 +12,10 @@ namespace device {
namespace instance { namespace instance {
// clang-format off // clang-format off
template <typename DsLayout, template <typename InLayout,
typename WeiLayout,
typename DsLayout,
typename OutLayout,
typename DsDatatype, typename DsDatatype,
typename OutElementOp, typename OutElementOp,
ConvolutionForwardSpecialization ConvSpec, ConvolutionForwardSpecialization ConvSpec,
...@@ -23,7 +26,7 @@ using device_grouped_conv2d_dl_int8_instances = ...@@ -23,7 +26,7 @@ using device_grouped_conv2d_dl_int8_instances =
// ###########################################| Spatial| Type| Type| Type| Type| Type| | | Layout| | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector| // ###########################################| Spatial| Type| Type| Type| Type| Type| | | Layout| | Elementwise| Elementwise| Elementwise| Forward| Spacialization| Size| Block| Block| Block| | ThreadM111| ThreadN111| Thread| ClusterM110Xs| ClusterN110Xs| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| ThreadSliceLengths| ThreadClusterLengths| ThreadCluster| SrcAccess| SrcVectorTensor| SrcVectorTensor| DstVectorTensor| SrcDstAccess| SrcDstVectorDim| DstScalarPerVector|
// ###########################################| | | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | | // ###########################################| | | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | | | | | K0_M0_M1_K1| K0_M0_M1_K1| ArrangeOrder| Order| Lengths_K0_M0_M1_K1| ContiguousDimOrder| Lengths_K0_M0_M1_K1| K0_N0_N1_K1| K0_N0_N1_K1| ArrangeOrder| Order| Lengths_K0_N0_N1_K1| ContiguousDimOrder| Lengths_K0_N0_N1_K1| Order| | |
// ###########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | // ###########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK< NDimSpatial, int8_t, int8_t, DsDatatype, int8_t, int32_t, GNHWC, GKYXC, DsLayout, GNHWK, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 256, 128, 128, 16, 4, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<0, 1, 2, 3, 4, 5>, 5, DstScalarPerVector> DeviceGroupedConvFwdDlMultipleD_NHWC_KYXC_NHWK< NDimSpatial, int8_t, int8_t, DsDatatype, int8_t, int32_t, InLayout, WeiLayout, DsLayout, OutLayout, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 256, 128, 128, 16, 4, 4, 4, 1, S<8, 2>, S<8, 2>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<8, 1, 1, 4>, S<2, 1, 128, 1>, S<1, 2, 0, 3>, S<1, 2, 0, 3>, S<4, 1, 1, 4>, S<1, 2, 0, 3>, S<1, 1, 1, 4>, S<0, 1, 2, 3, 4, 5>, 5, DstScalarPerVector>
>; >;
// clang-format on // clang-format on
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_perchannel_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_dl_perchannel_quantization_int8_instances( void add_device_conv2d_dl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_perchannel_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_perchannel_quantization_int8_instances(
Mul2_Clamp>>>& instances) Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_perchannel_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_perchannel_quantization_int8_instances(
void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances( void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -56,19 +65,28 @@ void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances( ...@@ -56,19 +65,28 @@ void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(
Relu_Mul2_Clamp>>>& instances) Relu_Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<GK_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_dl_perlayer_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_dl_perlayer_quantization_int8_instances( void add_device_conv2d_dl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_perlayer_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_dl_perlayer_quantization_int8_instances(
Mul_Clamp>>>& instances) Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_perlayer_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_dl_perlayer_quantization_int8_instances(
void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances( void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -56,19 +65,28 @@ void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances( ...@@ -56,19 +65,28 @@ void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(
Relu_Mul_Clamp>>>& instances) Relu_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
4>{}); 4>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_dl_int8_instances<Empty_Tuple, device_grouped_conv2d_dl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_bias_perchannel_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
Add_Mul2_Clamp>>>& instances) Add_Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_Clamp, Add_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances( ...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(
Add_Relu_Mul2_Clamp>>>& instances) Add_Relu_Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Relu_Mul2_Clamp, Add_Relu_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -77,10 +95,10 @@ void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances( ...@@ -77,10 +95,10 @@ void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances(
void add_device_conv2d_xdl_bias_tanh_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_tanh_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_GK_Tuple, GK_GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_F32_Tuple, I32_F32_Tuple,
...@@ -90,19 +108,28 @@ void add_device_conv2d_xdl_bias_tanh_perchannel_quantization_int8_instances( ...@@ -90,19 +108,28 @@ void add_device_conv2d_xdl_bias_tanh_perchannel_quantization_int8_instances(
Add_Mul2_TanH_Mul_Clamp>>>& instances) Add_Mul2_TanH_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_GK_Tuple,
NHWGK,
I32_F32_Tuple, I32_F32_Tuple,
Add_Mul2_TanH_Mul_Clamp, Add_Mul2_TanH_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_bias_perlayer_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
Add_Mul_Clamp>>>& instances) Add_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_Clamp, Add_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -56,21 +65,30 @@ void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances( ...@@ -56,21 +65,30 @@ void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(
Add_Relu_Mul_Clamp>>>& instances) Add_Relu_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Relu_Mul_Clamp, Add_Relu_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -79,10 +97,10 @@ void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances( ...@@ -79,10 +97,10 @@ void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances(
void add_device_conv2d_xdl_bias_tanh_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_tanh_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -92,21 +110,30 @@ void add_device_conv2d_xdl_bias_tanh_perlayer_quantization_int8_instances( ...@@ -92,21 +110,30 @@ void add_device_conv2d_xdl_bias_tanh_perlayer_quantization_int8_instances(
Add_Mul_TanH_Mul_Clamp>>>& instances) Add_Mul_TanH_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
I32_Tuple, I32_Tuple,
Add_Mul_TanH_Mul_Clamp, Add_Mul_TanH_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_int8_instance.hpp
View file @ 0d6da13c
...@@ -12,30 +12,33 @@ namespace device { ...@@ -12,30 +12,33 @@ namespace device {
namespace instance { namespace instance {
// clang-format off // clang-format off
template <typename DsLayout, template <typename ALayout,
typename BLayout,
typename DsLayout,
typename ELayout,
typename DsDatatype, typename DsDatatype,
typename OutElementOp, typename OutElementOp,
ConvolutionForwardSpecialization ConvSpec, ConvolutionForwardSpecialization ConvSpec,
index_t DstScalarPerVector> index_t DstScalarPerVector>
using device_grouped_conv2d_xdl_int8_instances = using device_grouped_conv2d_xdl_int8_instances =
std::tuple < std::tuple <
//########################################| 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| //########################################| 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|
//########################################| 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| //########################################| 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|
//########################################| | | | | | | | | | | | 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| //########################################| | | | | | | | | | | | 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|
//########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | //########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 256, 64, 16, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 256, 64, 16, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 64, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 64, 128, 64, 16, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 64, 64, 16, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 64, 64, 16, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 128, 64, 64, 16, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 64, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 256, 64, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 128, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 64, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 32, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 128, 32, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 4>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>, DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 64, 32, 64, 16, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>,
DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, GNHWC, GKYXC, DsLayout, GNHWK, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 32, 64, 64, 16, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector> DeviceGroupedConvFwdMultipleD_Xdl_CShuffle<NDimSpatial, ALayout, BLayout, DsLayout, ELayout, int8_t, int8_t, int32_t, int32_t, DsDatatype, int8_t, PassThrough, PassThrough, OutElementOp, ConvSpec, GemmSpec, 1, 64, 32, 64, 64, 16, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, 1, 1, S<1, 32, 1, 2>, DstScalarPerVector>
>; >;
// clang-format on // clang-format on
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_perchannel_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_xdl_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_perchannel_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
Mul2_Clamp>>>& instances) Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Mul2_Clamp, Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_perchannel_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances( ...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_relu_perchannel_quantization_int8_instances(
Relu_Mul2_Clamp>>>& instances) Relu_Mul2_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwdDefault, ConvFwdDefault,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
8>{}); 8>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<GK_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
GK_Tuple,
NHWGK,
F32_Tuple, F32_Tuple,
Relu_Mul2_Clamp, Relu_Mul2_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
library/src/tensor_operation_instance/gpu/quantization/conv2d_fwd/device_conv2d_xdl_perlayer_quantization_int8_instance.cpp
View file @ 0d6da13c
...@@ -9,10 +9,10 @@ namespace device { ...@@ -9,10 +9,10 @@ namespace device {
namespace instance { namespace instance {
void add_device_conv2d_xdl_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_perlayer_quantization_int8_instances( ...@@ -22,19 +22,28 @@ void add_device_conv2d_xdl_perlayer_quantization_int8_instances(
Mul_Clamp>>>& instances) Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
16>{}); 16>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
16>{}); 16>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Mul_Clamp, Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_perlayer_quantization_int8_instances( ...@@ -43,10 +52,10 @@ void add_device_conv2d_xdl_perlayer_quantization_int8_instances(
void add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<NDimSpatial,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances( ...@@ -56,19 +65,28 @@ void add_device_conv2d_xdl_relu_perlayer_quantization_int8_instances(
Relu_Mul_Clamp>>>& instances) Relu_Mul_Clamp>>>& instances)
{ {
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwdDefault, ConvFwdDefault,
16>{}); 16>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwd1x1P0, ConvFwd1x1P0,
16>{}); 16>{});
add_device_operation_instances(instances, add_device_operation_instances(instances,
device_grouped_conv2d_xdl_int8_instances<Empty_Tuple, device_grouped_conv2d_xdl_int8_instances<NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
Empty_Tuple, Empty_Tuple,
Relu_Mul_Clamp, Relu_Mul_Clamp,
ConvFwd1x1S1P0, ConvFwd1x1S1P0,
......
profiler/include/profiler/profile_gemm_splitk_impl.hpp
View file @ 0d6da13c
...@@ -72,8 +72,8 @@ bool profile_gemm_splitk_impl(int do_verification, ...@@ -72,8 +72,8 @@ bool profile_gemm_splitk_impl(int do_verification,
{ {
case 0: break; case 0: break;
case 1: case 1:
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5}); a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-1, 2});
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}); b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-1, 2});
break; break;
default: default:
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}); a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
...@@ -94,7 +94,7 @@ bool profile_gemm_splitk_impl(int do_verification, ...@@ -94,7 +94,7 @@ bool profile_gemm_splitk_impl(int do_verification,
a_device_buf.ToDevice(a_m_k.mData.data()); a_device_buf.ToDevice(a_m_k.mData.data());
b_device_buf.ToDevice(b_k_n.mData.data()); b_device_buf.ToDevice(b_k_n.mData.data());
c_device_buf.ToDevice(c_m_n_device_result.mData.data()); c_device_buf.SetZero();
using DeviceOp = ck::tensor_operation::device::DeviceGemmSplitK<ALayout, using DeviceOp = ck::tensor_operation::device::DeviceGemmSplitK<ALayout,
BLayout, BLayout,
......
profiler/include/profiler/profile_grouped_gemm_impl.hpp
View file @ 0d6da13c
...@@ -8,6 +8,7 @@ ...@@ -8,6 +8,7 @@
#include "ck/ck.hpp" #include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp" #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm.hpp" #include "ck/tensor_operation/gpu/device/device_grouped_gemm.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_splitk.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/grouped_gemm.hpp" #include "ck/library/tensor_operation_instance/gpu/grouped_gemm.hpp"
...@@ -39,7 +40,8 @@ bool profile_grouped_gemm_impl(int do_verification, ...@@ -39,7 +40,8 @@ bool profile_grouped_gemm_impl(int do_verification,
const std::vector<int>& Ks, const std::vector<int>& Ks,
const std::vector<int>& StrideAs, const std::vector<int>& StrideAs,
const std::vector<int>& StrideBs, const std::vector<int>& StrideBs,
const std::vector<int>& StrideCs) const std::vector<int>& StrideCs,
int kbatch = 1)
{ {
bool pass = true; bool pass = true;
...@@ -96,8 +98,6 @@ bool profile_grouped_gemm_impl(int do_verification, ...@@ -96,8 +98,6 @@ bool profile_grouped_gemm_impl(int do_verification,
a_m_k[i].GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}, num_thread); a_m_k[i].GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}, num_thread);
b_k_n[i].GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}, num_thread); b_k_n[i].GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}, num_thread);
} }
c_m_n_device_results[i].GenerateTensorValue(GeneratorTensor_0<CDataType>{}, num_thread);
} }
using AElementOp = ck::tensor_operation::element_wise::PassThrough; using AElementOp = ck::tensor_operation::element_wise::PassThrough;
...@@ -132,13 +132,12 @@ bool profile_grouped_gemm_impl(int do_verification, ...@@ -132,13 +132,12 @@ bool profile_grouped_gemm_impl(int do_verification,
std::make_unique<DeviceMem>(sizeof(ADataType) * a_m_k[i].mDesc.GetElementSpaceSize())); std::make_unique<DeviceMem>(sizeof(ADataType) * a_m_k[i].mDesc.GetElementSpaceSize()));
b_device_buf.emplace_back( b_device_buf.emplace_back(
std::make_unique<DeviceMem>(sizeof(BDataType) * b_k_n[i].mDesc.GetElementSpaceSize())); std::make_unique<DeviceMem>(sizeof(BDataType) * b_k_n[i].mDesc.GetElementSpaceSize()));
c_device_buf.emplace_back(std::make_unique<DeviceMem>( c_device_buf.emplace_back(std::make_unique<DeviceMem>(
sizeof(CDataType) * c_m_n_device_results[i].mDesc.GetElementSpaceSize())); sizeof(CDataType) * c_m_n_device_results[i].mDesc.GetElementSpaceSize()));
a_device_buf[i]->ToDevice(a_m_k[i].mData.data()); a_device_buf[i]->ToDevice(a_m_k[i].mData.data());
b_device_buf[i]->ToDevice(b_k_n[i].mData.data()); b_device_buf[i]->ToDevice(b_k_n[i].mData.data());
c_device_buf[i]->ToDevice(c_m_n_device_results[i].mData.data()); c_device_buf[i]->SetZero();
gemm_descs.push_back({Ms[i], Ns[i], Ks[i], StrideAs[i], StrideBs[i], StrideCs[i], {}}); gemm_descs.push_back({Ms[i], Ns[i], Ks[i], StrideAs[i], StrideBs[i], StrideCs[i], {}});
...@@ -197,6 +196,28 @@ bool profile_grouped_gemm_impl(int do_verification, ...@@ -197,6 +196,28 @@ bool profile_grouped_gemm_impl(int do_verification,
{ {
std::string gemm_name = gemm_ptr->GetTypeString(); std::string gemm_name = gemm_ptr->GetTypeString();
if(kbatch > 1)
{
using DeviceOpSplitK =
ck::tensor_operation::device::DeviceGroupedGemmSplitK<ALayout,
BLayout,
ck::Tuple<>,
CLayout,
ADataType,
BDataType,
ck::Tuple<>,
CDataType,
AElementOp,
BElementOp,
CElementOp>;
if(dynamic_cast<DeviceOpSplitK*>(gemm_ptr.get()) != nullptr)
{
dynamic_cast<DeviceOpSplitK*>(gemm_ptr.get())
->SetKBatchSize(argument_ptr.get(), kbatch);
}
}
float ave_time = float ave_time =
invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel}); invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
......
profiler/src/profile_grouped_gemm.cpp
View file @ 0d6da13c
...@@ -52,20 +52,24 @@ std::vector<int> argToIntArray(char* input) ...@@ -52,20 +52,24 @@ std::vector<int> argToIntArray(char* input)
int profile_grouped_gemm(int argc, char* argv[]) int profile_grouped_gemm(int argc, char* argv[])
{ {
if(!(argc == 14)) if(argc < 14)
{ {
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"); std::cout
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n"); << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n"); << "arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n"
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n"); << "arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n"
printf(" 2: A[k, m] * B[k, n] = C[m, n];\n"); << " 1: A[m, k] * B[n, k] = C[m, n];\n"
printf(" 3: A[k, m] * B[n, k] = C[m, n])\n"); << " 2: A[k, m] * B[k, n] = C[m, n];\n"
printf("arg4: verification (0: no; 1: yes)\n"); << " 3: A[k, m] * B[n, k] = C[m, n])\n"
printf("arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n"); << "arg4: verification (0: no; 1: yes)\n"
printf("arg6: print tensor value (0: no; 1: yes)\n"); << "arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n"
printf("arg7: time kernel (0=n0, 1=yes)\n"); << "arg6: print tensor value (0: no; 1: yes)\n"
printf("arg8 to 13: Ms, Ns, Ks, StrideAs, StrideBs, StrideCs (e.g., 256,256 128,128 64,64 " << "arg7: time kernel (0=n0, 1=yes)\n"
"64,64 64,64 128,128)\n"); << "arg8 to 13: Ms, Ns, Ks, StrideAs, StrideBs, StrideCs (e.g., 256,256 128,128 64,64 "
"64,64 64,64 128,128)\n"
<< "arg15: kbatch value (default 4)\n"
<< std::endl;
exit(1); exit(1);
} }
...@@ -83,6 +87,7 @@ int profile_grouped_gemm(int argc, char* argv[]) ...@@ -83,6 +87,7 @@ int profile_grouped_gemm(int argc, char* argv[])
const auto StrideAs = argToIntArray(argv[11]); const auto StrideAs = argToIntArray(argv[11]);
const auto StrideBs = argToIntArray(argv[12]); const auto StrideBs = argToIntArray(argv[12]);
const auto StrideCs = argToIntArray(argv[13]); const auto StrideCs = argToIntArray(argv[13]);
const int kbatch = argc == 15 ? std::stoi(argv[14]) : 1;
if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN) if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN)
{ {
...@@ -101,7 +106,8 @@ int profile_grouped_gemm(int argc, char* argv[]) ...@@ -101,7 +106,8 @@ int profile_grouped_gemm(int argc, char* argv[])
Ks, Ks,
StrideAs, StrideAs,
StrideBs, StrideBs,
StrideCs); StrideCs,
kbatch);
} }
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_NK_MN) else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_NK_MN)
{ {
...@@ -120,7 +126,8 @@ int profile_grouped_gemm(int argc, char* argv[]) ...@@ -120,7 +126,8 @@ int profile_grouped_gemm(int argc, char* argv[])
Ks, Ks,
StrideAs, StrideAs,
StrideBs, StrideBs,
StrideCs); StrideCs,
kbatch);
} }
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_KN_MN) else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_KN_MN)
{ {
...@@ -139,7 +146,8 @@ int profile_grouped_gemm(int argc, char* argv[]) ...@@ -139,7 +146,8 @@ int profile_grouped_gemm(int argc, char* argv[])
Ks, Ks,
StrideAs, StrideAs,
StrideBs, StrideBs,
StrideCs); StrideCs,
kbatch);
} }
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_NK_MN) else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::KM_NK_MN)
{ {
...@@ -158,7 +166,8 @@ int profile_grouped_gemm(int argc, char* argv[]) ...@@ -158,7 +166,8 @@ int profile_grouped_gemm(int argc, char* argv[])
Ks, Ks,
StrideAs, StrideAs,
StrideBs, StrideBs,
StrideCs); StrideCs,
kbatch);
} }
else else
{ {
......
script/cmake-ck-dev.sh
View file @ 0d6da13c
...@@ -12,9 +12,8 @@ cmake ...@@ -12,9 +12,8 @@ cmake
-save-temps=$PWD" \ -save-temps=$PWD" \
-D CMAKE_BUILD_TYPE=Release \ -D CMAKE_BUILD_TYPE=Release \
-D BUILD_DEV=ON \ -D BUILD_DEV=ON \
-D GPU_TARGETS="gfx908;gfx90a" \ -D GPU_TARGETS="gfx908;gfx90a;gfx940" \
-D CMAKE_VERBOSE_MAKEFILE:BOOL=ON \ -D CMAKE_VERBOSE_MAKEFILE:BOOL=ON \
-D USE_BITINT_EXTENSION_INT4=OFF \ -D USE_BITINT_EXTENSION_INT4=OFF \
${MY_PROJECT_SOURCE} ${MY_PROJECT_SOURCE}
#-D AMDGPU_TARGETS=gfx90a;gfx908
script/cmake-ck-release.sh
View file @ 0d6da13c
...@@ -11,9 +11,8 @@ cmake ...@@ -11,9 +11,8 @@ cmake
-D CMAKE_CXX_FLAGS="-O3" \ -D CMAKE_CXX_FLAGS="-O3" \
-D CMAKE_BUILD_TYPE=Release \ -D CMAKE_BUILD_TYPE=Release \
-D BUILD_DEV=OFF \ -D BUILD_DEV=OFF \
-D GPU_TARGETS="gfx908;gfx90a" \ -D GPU_TARGETS="gfx908;gfx90a;gfx940" \
-D CMAKE_VERBOSE_MAKEFILE:BOOL=ON \ -D CMAKE_VERBOSE_MAKEFILE:BOOL=ON \
-D USE_BITINT_EXTENSION_INT4=OFF \ -D USE_BITINT_EXTENSION_INT4=OFF \
${MY_PROJECT_SOURCE} ${MY_PROJECT_SOURCE}
#-D AMDGPU_TARGETS=gfx90a;gfx908
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