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Commit ed3c27cc authored by Chao Liu's avatar Chao Liu
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update gemm and batch gemm with e permute

parent dfbb659a
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example/24_batched_gemm_c_permute/CMakeLists.txt deleted 100644 → 0
View file @ dfbb659a
add_example_executable(example_batched_gemm_c_permute_xdl_fp16 batched_gemm_c_permute_xdl_fp16.cpp)
example/24_batched_gemm_e_permute/CMakeLists.txt 0 → 100644
View file @ ed3c27cc
add_example_executable(example_batched_gemm_e_permute_xdl_fp16 batched_gemm_e_permute_xdl_fp16.cpp)
example/24_batched_gemm_c_permute/batched_gemm_c_permute_xdl_fp16.cpp → example/24_batched_gemm_e_permute/batched_gemm_e_permute_xdl_fp16.cpp
View file @ ed3c27cc
...@@ -6,7 +6,7 @@ ...@@ -6,7 +6,7 @@
#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/gemm_specialization.hpp" #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_c_permute_xdl.hpp" #include "ck/tensor_operation/gpu/device/device_batched_gemm_e_permute_xdl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp" #include "ck/library/utility/check_err.hpp"
...@@ -26,35 +26,35 @@ using Col = ck::tensor_layout::gemm::ColumnMajor; ...@@ -26,35 +26,35 @@ using Col = ck::tensor_layout::gemm::ColumnMajor;
using PassThrough = ck::tensor_operation::element_wise::PassThrough; using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ADataType = ck::half_t; using ADataType = ck::half_t;
using BDataType = ck::half_t; using BDataType = ck::half_t;
using CDataType = ck::half_t; using AccDataType = float;
using AccDataType = float; using CShuffleDataType = ck::half_t;
using EDataType = ck::half_t;
using ALayout = ck::tensor_layout::gemm::RowMajor; using ALayout = ck::tensor_layout::gemm::RowMajor;
using BLayout = ck::tensor_layout::gemm::ColumnMajor; using BLayout = ck::tensor_layout::gemm::ColumnMajor;
using CLayout = ck::tensor_layout::gemm::RowMajor;
using AElementOp = ck::tensor_operation::element_wise::PassThrough; using AElementOp = ck::tensor_operation::element_wise::PassThrough;
using BElementOp = ck::tensor_operation::element_wise::PassThrough; using BElementOp = ck::tensor_operation::element_wise::PassThrough;
using CElementOp = ck::tensor_operation::element_wise::PassThrough; using CDEElementOp = ck::tensor_operation::element_wise::PassThrough;
// static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default; // static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// static constexpr auto MNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding; // static constexpr auto MNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
static constexpr auto MNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding; static constexpr auto MNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// clang-format off // clang-format off
using DeviceGemmInstance = ck::tensor_operation::device::DeviceBatchedGemmCPermuteXdl using DeviceGemmInstance = ck::tensor_operation::device::DeviceBatchedGemmEPermuteXdl
//######| ALayout| BLayout| AData| BData| CData| AccData| A| B| C| GEMM| Num| 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| //######| ALayout| BLayout| AData| BData| AccData| CShuffle| EData| A| B| C| GEMM| Num| 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|
//######| | | Type| Type| 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| //######| | | Type| Type| Type| Data| 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| | | | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl| //######| | | | | | Type| | Operation| Operation| Operation| | | | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | //######| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// < Row, Col, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, MNPadding, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8>; // < Row, Col, F16, F16, F32, F16, F16, PassThrough, PassThrough, PassThrough, MNPadding, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8>;
< Row, Col, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, MNKPadding, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8>; < Row, Col, F16, F16, F32, F16, F16, PassThrough, PassThrough, PassThrough, MNKPadding, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8>;
// clang-format on // clang-format on
using ReferenceBatchedGemmInstance = ck::tensor_operation::host:: using ReferenceBatchedGemmInstance = ck::tensor_operation::host::
ReferenceBatchedGemm<ADataType, BDataType, CDataType, AElementOp, BElementOp, CElementOp>; ReferenceBatchedGemm<ADataType, BDataType, EDataType, AElementOp, BElementOp, CDEElementOp>;
int main(int argc, char* argv[]) int main(int argc, char* argv[])
{ {
...@@ -95,7 +95,7 @@ int main(int argc, char* argv[]) ...@@ -95,7 +95,7 @@ int main(int argc, char* argv[])
} }
// GEMM shape // GEMM shape
ck::tensor_operation::device::BatchedGemmCPermuteDesc batched_gemm_c_permute_desc{ ck::tensor_operation::device::BatchedGemmEPermuteDesc batched_gemm_e_permute_desc{
G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N}; G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N};
auto f_host_tensor_descriptor = [](std::size_t batch_count_, auto f_host_tensor_descriptor = [](std::size_t batch_count_,
...@@ -118,7 +118,7 @@ int main(int argc, char* argv[]) ...@@ -118,7 +118,7 @@ int main(int argc, char* argv[])
Tensor<ADataType> a_g_m_k(f_host_tensor_descriptor(batch_count, M, K, stride_A, ALayout{})); Tensor<ADataType> a_g_m_k(f_host_tensor_descriptor(batch_count, M, K, stride_A, ALayout{}));
Tensor<BDataType> b_g_k_n(f_host_tensor_descriptor(batch_count, K, N, stride_B, BLayout{})); Tensor<BDataType> b_g_k_n(f_host_tensor_descriptor(batch_count, K, N, stride_B, BLayout{}));
auto f_host_c_tensor_descriptor = [](std::size_t G0_, auto f_host_e_tensor_descriptor = [](std::size_t G0_,
std::size_t G1_, std::size_t G1_,
std::size_t M_, std::size_t M_,
std::size_t N_, std::size_t N_,
...@@ -131,15 +131,15 @@ int main(int argc, char* argv[]) ...@@ -131,15 +131,15 @@ int main(int argc, char* argv[])
std::vector<std::size_t>({stride_G0_, stride_G1_, stride_M_, stride_N_})); std::vector<std::size_t>({stride_G0_, stride_G1_, stride_M_, stride_N_}));
}; };
Tensor<CDataType> c_g0_g1_m_n_host_result( Tensor<EDataType> e_g0_g1_m_n_host_result(
f_host_c_tensor_descriptor(G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N)); f_host_e_tensor_descriptor(G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N));
Tensor<CDataType> c_g0_g1_m_n_device_result( Tensor<EDataType> e_g0_g1_m_n_device_result(
f_host_c_tensor_descriptor(G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N)); f_host_e_tensor_descriptor(G0, G1, M, N, stride_G0, stride_G1, stride_M, stride_N));
std::cout << "a_g_m_k: " << a_g_m_k.mDesc << std::endl; std::cout << "a_g_m_k: " << a_g_m_k.mDesc << std::endl;
std::cout << "b_g_k_n: " << b_g_k_n.mDesc << std::endl; std::cout << "b_g_k_n: " << b_g_k_n.mDesc << std::endl;
std::cout << "c_g0_g1_m_n: " << c_g0_g1_m_n_host_result.mDesc << std::endl; std::cout << "e_g0_g1_m_n: " << e_g0_g1_m_n_host_result.mDesc << std::endl;
switch(init_method) switch(init_method)
{ {
...@@ -156,15 +156,15 @@ int main(int argc, char* argv[]) ...@@ -156,15 +156,15 @@ int main(int argc, char* argv[])
DeviceMem a_device_buf(sizeof(ADataType) * a_g_m_k.mDesc.GetElementSpaceSize()); DeviceMem a_device_buf(sizeof(ADataType) * a_g_m_k.mDesc.GetElementSpaceSize());
DeviceMem b_device_buf(sizeof(BDataType) * b_g_k_n.mDesc.GetElementSpaceSize()); DeviceMem b_device_buf(sizeof(BDataType) * b_g_k_n.mDesc.GetElementSpaceSize());
DeviceMem c_device_buf(sizeof(CDataType) * DeviceMem e_device_buf(sizeof(EDataType) *
c_g0_g1_m_n_device_result.mDesc.GetElementSpaceSize()); e_g0_g1_m_n_device_result.mDesc.GetElementSpaceSize());
a_device_buf.ToDevice(a_g_m_k.mData.data()); a_device_buf.ToDevice(a_g_m_k.mData.data());
b_device_buf.ToDevice(b_g_k_n.mData.data()); b_device_buf.ToDevice(b_g_k_n.mData.data());
auto a_element_op = AElementOp{}; auto a_element_op = AElementOp{};
auto b_element_op = BElementOp{}; auto b_element_op = BElementOp{};
auto c_element_op = CElementOp{}; auto cde_element_op = CDEElementOp{};
auto gemm = DeviceGemmInstance{}; auto gemm = DeviceGemmInstance{};
auto invoker = gemm.MakeInvoker(); auto invoker = gemm.MakeInvoker();
...@@ -172,16 +172,16 @@ int main(int argc, char* argv[]) ...@@ -172,16 +172,16 @@ int main(int argc, char* argv[])
// do GEMM // do GEMM
auto argument = gemm.MakeArgument(static_cast<ADataType*>(a_device_buf.GetDeviceBuffer()), auto argument = gemm.MakeArgument(static_cast<ADataType*>(a_device_buf.GetDeviceBuffer()),
static_cast<BDataType*>(b_device_buf.GetDeviceBuffer()), static_cast<BDataType*>(b_device_buf.GetDeviceBuffer()),
static_cast<CDataType*>(c_device_buf.GetDeviceBuffer()), static_cast<EDataType*>(e_device_buf.GetDeviceBuffer()),
M, M,
N, N,
K, K,
stride_A, stride_A,
stride_B, stride_B,
batched_gemm_c_permute_desc, batched_gemm_e_permute_desc,
a_element_op, a_element_op,
b_element_op, b_element_op,
c_element_op, cde_element_op,
batch_count); batch_count);
if(!gemm.IsSupportedArgument(argument)) if(!gemm.IsSupportedArgument(argument))
...@@ -196,7 +196,7 @@ int main(int argc, char* argv[]) ...@@ -196,7 +196,7 @@ int main(int argc, char* argv[])
std::size_t flop = std::size_t(2) * batch_count * M * N * K; std::size_t flop = std::size_t(2) * batch_count * M * N * K;
std::size_t num_btype = sizeof(ADataType) * batch_count * M * K + std::size_t num_btype = sizeof(ADataType) * batch_count * M * K +
sizeof(BDataType) * batch_count * K * N + sizeof(BDataType) * batch_count * K * N +
sizeof(CDataType) * batch_count * M * N; sizeof(EDataType) * batch_count * M * N;
float tflops = static_cast<float>(flop) / 1.E9 / ave_time; float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
...@@ -209,16 +209,16 @@ int main(int argc, char* argv[]) ...@@ -209,16 +209,16 @@ int main(int argc, char* argv[])
if(do_verification) if(do_verification)
{ {
c_device_buf.FromDevice(c_g0_g1_m_n_device_result.mData.data()); e_device_buf.FromDevice(e_g0_g1_m_n_device_result.mData.data());
auto ref_batched_gemm = ReferenceBatchedGemmInstance{}; auto ref_batched_gemm = ReferenceBatchedGemmInstance{};
auto ref_invoker = ref_batched_gemm.MakeInvoker(); auto ref_invoker = ref_batched_gemm.MakeInvoker();
Tensor<CDataType> c_g_m_n_host_result = HostTensorDescriptor( Tensor<EDataType> c_g_m_n_host_result = HostTensorDescriptor(
std::vector<std::size_t>({batch_count, M, N}), std::vector<std::size_t>({M * N, N, 1})); std::vector<std::size_t>({batch_count, M, N}), std::vector<std::size_t>({M * N, N, 1}));
auto ref_argument = ref_batched_gemm.MakeArgument( auto ref_argument = ref_batched_gemm.MakeArgument(
a_g_m_k, b_g_k_n, c_g_m_n_host_result, a_element_op, b_element_op, c_element_op); a_g_m_k, b_g_k_n, c_g_m_n_host_result, a_element_op, b_element_op, cde_element_op);
ref_invoker.Run(ref_argument); ref_invoker.Run(ref_argument);
...@@ -230,15 +230,16 @@ int main(int argc, char* argv[]) ...@@ -230,15 +230,16 @@ int main(int argc, char* argv[])
{ {
for(int n = 0; n < N; n++) for(int n = 0; n < N; n++)
{ {
int g = g0 * G1 + g1; int g = g0 * G1 + g1;
c_g0_g1_m_n_host_result(g0, g1, m, n) = c_g_m_n_host_result(g, m, n);
e_g0_g1_m_n_host_result(g0, g1, m, n) = c_g_m_n_host_result(g, m, n);
} }
} }
} }
} }
pass = ck::utils::check_err(c_g0_g1_m_n_host_result.mData, pass = ck::utils::check_err(e_g0_g1_m_n_host_result.mData,
c_g0_g1_m_n_device_result.mData, e_g0_g1_m_n_device_result.mData,
"Error: Incorrect results c"); "Error: Incorrect results c");
} }
......
example/25_gemm_bias_c_permute/CMakeLists.txt deleted 100644 → 0
View file @ dfbb659a
add_example_executable(example_gemm_bias_c_permute_xdl_fp16 gemm_bias_c_permute_xdl_fp16.cpp)
example/25_gemm_bias_e_permute/CMakeLists.txt 0 → 100644
View file @ ed3c27cc
add_example_executable(example_gemm_bias_e_permute_xdl_fp16 gemm_bias_e_permute_xdl_fp16.cpp)
example/25_gemm_bias_c_permute/gemm_bias_c_permute_xdl_fp16.cpp → example/25_gemm_bias_e_permute/gemm_bias_e_permute_xdl_fp16.cpp
View file @ ed3c27cc
...@@ -9,7 +9,7 @@ ...@@ -9,7 +9,7 @@
#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/gemm_specialization.hpp" #include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm_bias_c_permute_xdl.hpp" #include "ck/tensor_operation/gpu/device/device_gemm_bias_e_permute_xdl.hpp"
#include "ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp"
#include "ck/library/utility/device_memory.hpp" #include "ck/library/utility/device_memory.hpp"
...@@ -49,7 +49,7 @@ using CDEElementOp = Add; ...@@ -49,7 +49,7 @@ using CDEElementOp = Add;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default; static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// clang-format off // clang-format off
using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmBiasCPermute_Xdl using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmBiasEPermute_Xdl
//######| ALayout| BLayout| ELayout| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| 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| //######| ALayout| BLayout| ELayout| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| 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|
//######| | | | 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| //######| | | | 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| //######| | | | | | | | | | 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|
......
example/CMakeLists.txt
View file @ ed3c27cc
...@@ -38,8 +38,8 @@ add_subdirectory(20_convnd_bwd_weight) ...@@ -38,8 +38,8 @@ add_subdirectory(20_convnd_bwd_weight)
add_subdirectory(21_gemm_layernorm) add_subdirectory(21_gemm_layernorm)
add_subdirectory(22_cgemm) add_subdirectory(22_cgemm)
add_subdirectory(23_softmax) add_subdirectory(23_softmax)
add_subdirectory(24_batched_gemm_c_permute) add_subdirectory(24_batched_gemm_e_permute)
add_subdirectory(25_gemm_bias_c_permute) add_subdirectory(25_gemm_bias_e_permute)
add_subdirectory(26_contraction) add_subdirectory(26_contraction)
add_subdirectory(27_layernorm) add_subdirectory(27_layernorm)
add_subdirectory(28_group_convnd_fwd_bias_relu) add_subdirectory(28_group_convnd_fwd_bias_relu)
include/ck/tensor_operation/gpu/device/device_batched_gemm_c_permute.hpp → include/ck/tensor_operation/gpu/device/device_batched_gemm_e_permute.hpp
View file @ ed3c27cc
...@@ -8,7 +8,7 @@ namespace ck { ...@@ -8,7 +8,7 @@ namespace ck {
namespace tensor_operation { namespace tensor_operation {
namespace device { namespace device {
struct BatchedGemmCPermuteDesc struct BatchedGemmEPermuteDesc
{ {
ck::index_t G0_, G1_, M_, N_; ck::index_t G0_, G1_, M_, N_;
ck::index_t stride_G0_, stride_G1_, stride_M_, stride_N_; ck::index_t stride_G0_, stride_G1_, stride_M_, stride_N_;
...@@ -16,33 +16,27 @@ struct BatchedGemmCPermuteDesc ...@@ -16,33 +16,27 @@ struct BatchedGemmCPermuteDesc
template <typename AElementwiseOperation, template <typename AElementwiseOperation,
typename BElementwiseOperation, typename BElementwiseOperation,
typename CElementwiseOperation> typename CDEElementwiseOperation>
struct DeviceBatchedGemmCPermute : public BaseOperator struct DeviceBatchedGemmEPermute : public BaseOperator
{ {
virtual std::unique_ptr<BaseArgument> virtual std::unique_ptr<BaseArgument>
MakeArgumentPointer(const void* p_a, MakeArgumentPointer(const void* p_a,
const void* p_b, const void* p_b,
void* p_c, void* p_e,
index_t M, index_t M,
index_t N, index_t N,
index_t K, index_t K,
index_t stride_A, index_t stride_A,
index_t stride_B, index_t stride_B,
BatchedGemmCPermuteDesc batched_gemm_c_permute_desc, BatchedGemmEPermuteDesc batched_gemm_e_permute_desc,
AElementwiseOperation a_element_op, AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op, BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op, CDEElementwiseOperation cde_element_op,
ck::index_t BatchCount) = 0; ck::index_t BatchCount) = 0;
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0; virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
}; };
template <typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation>
using DeviceBatchedGemmCPermutePtr = std::unique_ptr<
DeviceBatchedGemmCPermute<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
} // namespace device } // namespace device
} // namespace tensor_operation } // namespace tensor_operation
} // namespace ck } // namespace ck
include/ck/tensor_operation/gpu/device/device_gemm_bias_c_permute.hpp → include/ck/tensor_operation/gpu/device/device_gemm_bias_e_permute.hpp
View file @ ed3c27cc
...@@ -46,12 +46,6 @@ struct DeviceGemmBiasCPermute : public BaseOperator ...@@ -46,12 +46,6 @@ struct DeviceGemmBiasCPermute : public BaseOperator
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0; virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
}; };
template <typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation>
using DeviceGemmBiasCPermutePtr = std::unique_ptr<
DeviceGemmBiasCPermute<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
} // namespace device } // namespace device
} // namespace tensor_operation } // namespace tensor_operation
} // namespace ck } // namespace ck
include/ck/tensor_operation/gpu/device/device_gemm_multiple_d_xdl_cshuffle.hpp
View file @ ed3c27cc
...@@ -205,12 +205,12 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout, ...@@ -205,12 +205,12 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
static auto MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE) static auto MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE)
{ {
const auto e_grid_desc_mraw_nraw = [&]() { const auto e_grid_desc_mraw_nraw = [&]() {
if constexpr(is_same<tensor_layout::gemm::RowMajor, ELayout>::value) if constexpr(is_same<tensor_layout::gemm::RowMajor, ELay>::value)
{ {
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw), return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
make_tuple(StrideE, I1)); make_tuple(StrideE, I1));
} }
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, ELayout>::value) else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, ELay>::value)
{ {
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw), return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
make_tuple(I1, StrideE)); make_tuple(I1, StrideE));
...@@ -329,7 +329,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout, ...@@ -329,7 +329,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
b_element_op_{b_element_op}, b_element_op_{b_element_op},
cde_element_op_{cde_element_op} cde_element_op_{cde_element_op}
{ {
// populate pointer, batch stride, desc for Ds // populate pointer, desc for Ds
static_for<0, NumDTensor, 1>{}([&](auto i) { static_for<0, NumDTensor, 1>{}([&](auto i) {
using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>; using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>; using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
......
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