Skip to content

GitLab

Commit 8820cf9f authored by Po-Yen, Chen's avatar Po-Yen, Chen
Browse files

Merge branch 'develop' into feature/integrage-karg-simplification-pr

parents cb46ef7a 4feebedd
Hide whitespace changes
Inline Side-by-side
Showing with 563 additions and 106 deletions
include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v2r4.hpp
View file @ 8820cf9f
...@@ -42,7 +42,8 @@ __global__ void ...@@ -42,7 +42,8 @@ __global__ void
const CElementwiseOperation c_element_op, const CElementwiseOperation c_element_op,
const CBlockClusterAdaptor c_block_cluster_adaptor) const CBlockClusterAdaptor c_block_cluster_adaptor)
{ {
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__)) #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx940__))
constexpr index_t shared_block_size = constexpr index_t shared_block_size =
GridwiseGemm::GetSharedMemoryNumberOfByte() / sizeof(FloatAB); GridwiseGemm::GetSharedMemoryNumberOfByte() / sizeof(FloatAB);
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v2r4r2.hpp
View file @ 8820cf9f
...@@ -15,26 +15,32 @@ ...@@ -15,26 +15,32 @@
#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp" #include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp" #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_pipeline_selector.hpp"
namespace ck { namespace ck {
template <typename GridwiseGemm, template <typename GridwiseGemm,
bool HasMainKBlockLoop, bool HasMainKBlockLoop,
InMemoryDataOperationEnum CGlobalMemoryDataOperation> InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename Block2CTileMap>
__global__ void __global__ void
#if CK_USE_LAUNCH_BOUNDS #if CK_USE_LAUNCH_BOUNDS
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU) __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
#endif #endif
kernel_gemm_xdlops_v2r4r2_simplified(typename GridwiseGemm::Argument karg) kernel_gemm_xdlops_v2r4r2_simplified(typename GridwiseGemm::Argument karg,
const Block2CTileMap& b2c_map)
{ {
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__)) #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx940__))
constexpr index_t shared_size = GridwiseGemm::GetSharedMemoryNumberOfByte(); constexpr index_t shared_size = GridwiseGemm::GetSharedMemoryNumberOfByte();
__shared__ uint8_t p_shared[shared_size]; __shared__ uint8_t p_shared[shared_size];
GridwiseGemm::template Run<HasMainKBlockLoop, CGlobalMemoryDataOperation>( GridwiseGemm::template Run<HasMainKBlockLoop, CGlobalMemoryDataOperation>(
karg, static_cast<void*>(p_shared)); karg, static_cast<void*>(p_shared), b2c_map);
#else #else
ignore = karg; ignore = karg;
ignore = b2c_map;
#endif // end of if (defined(__gfx908__) || defined(__gfx90a__)) #endif // end of if (defined(__gfx908__) || defined(__gfx90a__))
} }
...@@ -478,8 +484,21 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -478,8 +484,21 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
Number<CShuffleNRepeatPerShuffle * NWave * NPerXDL>{})); Number<CShuffleNRepeatPerShuffle * NWave * NPerXDL>{}));
} }
template <bool HasMainKBlockLoop, InMemoryDataOperationEnum CGlobalMemoryDataOperation> // return block_id to C matrix tile idx (m0, n0, k_split) mapping
__device__ static void Run(const Argument& karg, void* __restrict__ p_shared_block) __host__ __device__ static constexpr auto MakeDefaultBlock2CTileMap()
{
return BlockToCTileMap_3DGrid_KSplit<MPerBlock, NPerBlock>();
}
using CGridDesc_M_N = remove_cvref_t<decltype(MakeCGridDescriptor_M_N(1, 1, 1, 1, 1))>;
using DefaultBlock2CTileMap = remove_cvref_t<decltype(MakeDefaultBlock2CTileMap())>;
template <bool HasMainKBlockLoop,
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename Block2CTileMap>
__device__ static void Run(const Argument& karg,
void* __restrict__ p_shared_block,
const Block2CTileMap& block_2_ctile_map)
{ {
const FloatAB* p_a_grid = karg.p_a_grid; const FloatAB* p_a_grid = karg.p_a_grid;
const FloatAB* p_b_grid = karg.p_b_grid; const FloatAB* p_b_grid = karg.p_b_grid;
...@@ -504,11 +523,21 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -504,11 +523,21 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>( auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize()); p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
const auto K0 = a_b_k0_m_k1_grid_desc.GetLength(I1); // divide block work by [KBatch, M, N]
const auto block_work_idx =
block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
const index_t block_m_id = __builtin_amdgcn_readfirstlane(blockIdx.y); if(!block_2_ctile_map.ValidCTileIndex(
const index_t block_n_id = __builtin_amdgcn_readfirstlane(blockIdx.x); block_work_idx,
const index_t k_batch_id = __builtin_amdgcn_readfirstlane(blockIdx.z); make_tuple(c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
{
return;
}
const index_t block_m_id = __builtin_amdgcn_readfirstlane(block_work_idx[I1]);
const index_t block_n_id = __builtin_amdgcn_readfirstlane(block_work_idx[I2]);
const index_t k_batch_id = __builtin_amdgcn_readfirstlane(block_work_idx[I0]);
// HACK: this force m/n_block_data_idx_on_grid into SGPR // HACK: this force m/n_block_data_idx_on_grid into SGPR
const index_t m_block_data_idx_on_grid = const index_t m_block_data_idx_on_grid =
...@@ -651,6 +680,7 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -651,6 +680,7 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
// c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in // c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
// register // register
// sanity check // sanity check
#if 1
auto blockwise_gemm = auto blockwise_gemm =
BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize, BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
FloatAB, FloatAB,
...@@ -662,6 +692,20 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -662,6 +692,20 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
MRepeat, MRepeat,
NRepeat, NRepeat,
K1>{}; K1>{};
#else
auto blockwise_gemm = BlockwiseGemmXdlopsInterwave_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<
BlockSize,
FloatAB,
FloatAcc,
decltype(a_k0_m_k1_block_desc),
decltype(b_k0_n_k1_block_desc),
MPerXDL,
NPerXDL,
MRepeat,
NRepeat,
K1>{};
#endif
auto c_thread_buf = blockwise_gemm.GetCThreadBuffer(); auto c_thread_buf = blockwise_gemm.GetCThreadBuffer();
...@@ -680,6 +724,7 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -680,6 +724,7 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>( auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
p_b_block, b_k0_n_k1_block_desc.GetElementSpaceSize()); p_b_block, b_k0_n_k1_block_desc.GetElementSpaceSize());
#if 0
// preload data into LDS // preload data into LDS
{ {
a_blockwise_copy.RunRead(a_b_k0_m_k1_grid_desc, a_grid_buf); a_blockwise_copy.RunRead(a_b_k0_m_k1_grid_desc, a_grid_buf);
...@@ -725,6 +770,31 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 ...@@ -725,6 +770,31 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
blockwise_gemm.Run(a_block_buf, b_block_buf, c_thread_buf); blockwise_gemm.Run(a_block_buf, b_block_buf, c_thread_buf);
} }
#else
// gridwise GEMM pipeline
const auto gridwise_gemm_pipeline =
GridwiseGemmPipeline_Selector<PipelineVersion::v2, 1, LoopScheduler::Default>();
const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
(a_b_k0_m_k1_grid_desc.GetLength(I1) * a_b_k0_m_k1_grid_desc.GetLength(I3)) /
(K0PerBlock * K1));
gridwise_gemm_pipeline.template Run<HasMainKBlockLoop>(a_b_k0_m_k1_grid_desc,
a_b_k0_m_k1_block_desc,
a_blockwise_copy,
a_grid_buf,
a_block_buf,
a_block_slice_copy_step,
b_b_k0_n_k1_grid_desc,
b_b_k0_n_k1_block_desc,
b_blockwise_copy,
b_grid_buf,
b_block_buf,
b_block_slice_copy_step,
blockwise_gemm,
c_thread_buf,
num_k_block_main_loop);
#endif
// output: register to global memory // output: register to global memory
{ {
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v3r1.hpp
View file @ 8820cf9f
...@@ -46,7 +46,8 @@ __global__ void ...@@ -46,7 +46,8 @@ __global__ void
const CElementwiseOperation c_element_op, const CElementwiseOperation c_element_op,
const Block2CTileMap block_2_ctile_map) const Block2CTileMap block_2_ctile_map)
{ {
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__)) #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx940__))
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()]; __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
GridwiseGemm::template Run<HasMainK0BlockLoop>( GridwiseGemm::template Run<HasMainK0BlockLoop>(
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v3r2.hpp
View file @ 8820cf9f
...@@ -49,7 +49,8 @@ __global__ void ...@@ -49,7 +49,8 @@ __global__ void
const CElementwiseOperation c_element_op, const CElementwiseOperation c_element_op,
const Block2CTileMap block_2_ctile_map) const Block2CTileMap block_2_ctile_map)
{ {
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__)) #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx940__))
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()]; __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
GridwiseGemm::template Run<HasMainKBlockLoop>( GridwiseGemm::template Run<HasMainKBlockLoop>(
......
include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v3r3.hpp
View file @ 8820cf9f
...@@ -53,7 +53,8 @@ __global__ void ...@@ -53,7 +53,8 @@ __global__ void
const CElementwiseOperation c_element_op, const CElementwiseOperation c_element_op,
const Block2CTileMap block_2_ctile_map) const Block2CTileMap block_2_ctile_map)
{ {
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__)) #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
defined(__gfx940__))
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()]; __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
GridwiseGemm::template Run<HasMainKBlockLoop>( GridwiseGemm::template Run<HasMainKBlockLoop>(
......
include/ck/tensor_operation/gpu/warp/xdlops_gemm.hpp
View file @ 8820cf9f
...@@ -27,6 +27,8 @@ enum struct MfmaInstr ...@@ -27,6 +27,8 @@ enum struct MfmaInstr
mfma_f32_16x16x8bf16, mfma_f32_16x16x8bf16,
mfma_i32_32x32x8i8, mfma_i32_32x32x8i8,
mfma_i32_16x16x16i8, mfma_i32_16x16x16i8,
mfma_i32_32x32x16i8,
mfma_i32_16x16x32i8,
mfma_f64_16x16x4f64 mfma_f64_16x16x4f64
}; };
...@@ -386,6 +388,50 @@ struct mfma_type<MfmaInstr::mfma_i32_16x16x16i8> ...@@ -386,6 +388,50 @@ struct mfma_type<MfmaInstr::mfma_i32_16x16x16i8>
} }
}; };
template <>
struct mfma_type<MfmaInstr::mfma_i32_32x32x16i8>
{
static constexpr index_t group_size = 4;
static constexpr index_t num_groups_per_blk = 4;
static constexpr index_t num_regs_per_blk = 16;
static constexpr index_t num_threads_per_blk = 32;
static constexpr index_t wave_size = 64;
static constexpr index_t num_input_blks = 2;
static constexpr index_t num_output_blks = 1;
static constexpr index_t m_per_blk = 32;
static constexpr index_t n_per_blk = 32;
static constexpr index_t k_per_blk = 8;
static constexpr bool is_k_reduction = true;
template <index_t MPerXdlops, index_t NPerXdlops, class FloatA, class FloatB, class FloatC>
__device__ void run(const FloatA& a, const FloatB& b, FloatC& reg_c) const
{
intrin_mfma_i32_32x32x16i8<MPerXdlops, NPerXdlops>::Run(a, b, reg_c);
}
};
template <>
struct mfma_type<MfmaInstr::mfma_i32_16x16x32i8>
{
static constexpr index_t group_size = 4;
static constexpr index_t num_groups_per_blk = 1;
static constexpr index_t num_regs_per_blk = 4;
static constexpr index_t num_threads_per_blk = 16;
static constexpr index_t wave_size = 64;
static constexpr index_t num_input_blks = 4;
static constexpr index_t num_output_blks = 1;
static constexpr index_t m_per_blk = 16;
static constexpr index_t n_per_blk = 16;
static constexpr index_t k_per_blk = 8;
static constexpr bool is_k_reduction = true;
template <index_t MPerXdlops, index_t NPerXdlops, class FloatA, class FloatB, class FloatC>
__device__ void run(const FloatA& a, const FloatB& b, FloatC& reg_c) const
{
intrin_mfma_i32_16x16x32i8<MPerXdlops, NPerXdlops>::Run(a, b, reg_c);
}
};
template <> template <>
struct mfma_type<MfmaInstr::mfma_f64_16x16x4f64> struct mfma_type<MfmaInstr::mfma_f64_16x16x4f64>
{ {
...@@ -524,17 +570,29 @@ struct MfmaSelector ...@@ -524,17 +570,29 @@ struct MfmaSelector
#endif #endif
} }
#if defined(CK_USE_AMD_MFMA_GFX940)
template <>
static constexpr auto GetMfma<int8_t, 32, 32>()
{
return MfmaInstr::mfma_i32_32x32x16i8;
}
template <>
static constexpr auto GetMfma<int8_t, 16, 16>()
{
return MfmaInstr::mfma_i32_16x16x32i8;
}
#else
template <> template <>
static constexpr auto GetMfma<int8_t, 32, 32>() static constexpr auto GetMfma<int8_t, 32, 32>()
{ {
return MfmaInstr::mfma_i32_32x32x8i8; return MfmaInstr::mfma_i32_32x32x8i8;
} }
template <> template <>
static constexpr auto GetMfma<int8_t, 16, 16>() static constexpr auto GetMfma<int8_t, 16, 16>()
{ {
return MfmaInstr::mfma_i32_16x16x16i8; return MfmaInstr::mfma_i32_16x16x16i8;
} }
#endif
static constexpr auto selected_mfma = mfma_type<GetMfma<base_type, MPerXdlops, NPerXdlops>()>{}; static constexpr auto selected_mfma = mfma_type<GetMfma<base_type, MPerXdlops, NPerXdlops>()>{};
......
include/ck/utility/amd_xdlops.hpp
View file @ 8820cf9f
...@@ -297,6 +297,44 @@ struct intrin_mfma_i32_16x16x16i8<16, 16> ...@@ -297,6 +297,44 @@ struct intrin_mfma_i32_16x16x16i8<16, 16>
} }
}; };
template <index_t MPerWave, index_t NPerWave>
struct intrin_mfma_i32_32x32x16i8;
template <>
struct intrin_mfma_i32_32x32x16i8<32, 32>
{
template <class FloatC>
__device__ static void Run(const int8x8_t& reg_a, const int8x8_t& reg_b, FloatC& reg_c)
{
reg_c.template AsType<int32x16_t>()(Number<0>{}) =
__builtin_amdgcn_mfma_i32_32x32x16_i8(bit_cast<int64_t>(reg_a),
bit_cast<int64_t>(reg_b),
reg_c.template AsType<int32x16_t>()[Number<0>{}],
0,
0,
0);
}
};
template <index_t MPerWave, index_t NPerWave>
struct intrin_mfma_i32_16x16x32i8;
template <>
struct intrin_mfma_i32_16x16x32i8<16, 16>
{
template <class FloatC>
__device__ static void Run(const int8x8_t& reg_a, const int8x8_t& reg_b, FloatC& reg_c)
{
reg_c.template AsType<int32x4_t>()(Number<0>{}) =
__builtin_amdgcn_mfma_i32_16x16x32i8(bit_cast<int64_t>(reg_a),
bit_cast<int64_t>(reg_b),
reg_c.template AsType<int32x4_t>()[Number<0>{}],
0,
0,
0);
}
};
template <index_t MPerWave, index_t NPerWave> template <index_t MPerWave, index_t NPerWave>
struct intrin_mfma_f64_16x16x4f64; struct intrin_mfma_f64_16x16x4f64;
...@@ -306,7 +344,7 @@ struct intrin_mfma_f64_16x16x4f64<16, 16> ...@@ -306,7 +344,7 @@ struct intrin_mfma_f64_16x16x4f64<16, 16>
template <class FloatC> template <class FloatC>
__device__ static void Run(const double& reg_a, const double& reg_b, FloatC& reg_c) __device__ static void Run(const double& reg_a, const double& reg_b, FloatC& reg_c)
{ {
#ifdef __gfx90a__ #if defined(__gfx90a__) || defined(__gfx940__)
reg_c.template AsType<double4_t>()(Number<0>{}) = __builtin_amdgcn_mfma_f64_16x16x4f64( reg_c.template AsType<double4_t>()(Number<0>{}) = __builtin_amdgcn_mfma_f64_16x16x4f64(
reg_a, reg_b, reg_c.template AsType<double4_t>()[Number<0>{}], 0, 0, 0); reg_a, reg_b, reg_c.template AsType<double4_t>()[Number<0>{}], 0, 0, 0);
#else #else
......
include/ck/utility/data_type.hpp
View file @ 8820cf9f
...@@ -898,6 +898,8 @@ struct vector_type<T, 256> ...@@ -898,6 +898,8 @@ struct vector_type<T, 256>
} }
}; };
using int64_t = long;
// fp64 // fp64
using double2_t = typename vector_type<double, 2>::type; using double2_t = typename vector_type<double, 2>::type;
using double4_t = typename vector_type<double, 4>::type; using double4_t = typename vector_type<double, 4>::type;
......
include/ck/utility/math.hpp
View file @ 8820cf9f
...@@ -168,6 +168,10 @@ __device__ double exp<double>(double x) ...@@ -168,6 +168,10 @@ __device__ double exp<double>(double x)
return exp(x); return exp(x);
} }
static inline __host__ float exp(float x) { return std::expf(x); }
static inline __host__ double exp(double x) { return std::exp(x); }
// greatest common divisor, aka highest common factor // greatest common divisor, aka highest common factor
__host__ __device__ constexpr index_t gcd(index_t x, index_t y) __host__ __device__ constexpr index_t gcd(index_t x, index_t y)
{ {
......
library/include/ck/library/tensor_operation_instance/device_operation_instance_factory.hpp
View file @ 8820cf9f
...@@ -26,6 +26,7 @@ using Empty_Tuple = ck::Tuple<>; ...@@ -26,6 +26,7 @@ using Empty_Tuple = ck::Tuple<>;
using F16_Tuple = ck::Tuple<F16>; using F16_Tuple = ck::Tuple<F16>;
using F16_F16_Tuple = ck::Tuple<F16, F16>; using F16_F16_Tuple = ck::Tuple<F16, F16>;
using F64_Tuple = ck::Tuple<F64>;
using F32_Tuple = ck::Tuple<F32>; using F32_Tuple = ck::Tuple<F32>;
using I32_Tuple = ck::Tuple<I32>; using I32_Tuple = ck::Tuple<I32>;
using I32_F32_Tuple = ck::Tuple<I32, F32>; using I32_F32_Tuple = ck::Tuple<I32, F32>;
...@@ -95,6 +96,7 @@ using FastGelu = ck::tensor_operation::element_wise::FastGelu; ...@@ -95,6 +96,7 @@ using FastGelu = ck::tensor_operation::element_wise::FastGelu;
using AddMultiply = ck::tensor_operation::element_wise::AddMultiply; using AddMultiply = ck::tensor_operation::element_wise::AddMultiply;
using ScaleAdd = ck::tensor_operation::element_wise::ScaleAdd; using ScaleAdd = ck::tensor_operation::element_wise::ScaleAdd;
using Gelu = ck::tensor_operation::element_wise::Gelu; using Gelu = ck::tensor_operation::element_wise::Gelu;
using Swish = ck::tensor_operation::element_wise::Swish;
template <typename Activation> template <typename Activation>
using Activation_Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Activation>; using Activation_Mul_Clamp = ck::tensor_operation::element_wise::Activation_Mul_Clamp<Activation>;
......
library/include/ck/library/tensor_operation_instance/gpu/contraction_bilinear.hpp
View file @ 8820cf9f
...@@ -19,6 +19,7 @@ namespace tensor_operation { ...@@ -19,6 +19,7 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// float
void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_kknn_instance( void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_kknn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2, 2,
...@@ -67,6 +68,55 @@ void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn ...@@ -67,6 +68,55 @@ void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn
PassThrough, PassThrough,
Bilinear>>>& instances); Bilinear>>>& instances);
// double
void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_kknn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
F64_Tuple,
F64,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_knnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
F64_Tuple,
F64,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mknn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
F64_Tuple,
F64,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mnnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
F64_Tuple,
F64,
PassThrough,
PassThrough,
Bilinear>>>& instances);
// Contraction + Bilinear // Contraction + Bilinear
template <index_t NumDimM, template <index_t NumDimM,
index_t NumDimN, index_t NumDimN,
...@@ -118,6 +168,22 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceContra ...@@ -118,6 +168,22 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceContra
} }
} }
if constexpr(is_same_v<ADataType, double> && is_same_v<BDataType, double> &&
is_same_v<DDataType, double> && is_same_v<EDataType, double>)
{
if constexpr(NumDimM == 2 && NumDimN == 2 && NumDimK == 2)
{
add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_kknn_instance(
op_ptrs);
add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_knnn_instance(
op_ptrs);
add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mnnn_instance(
op_ptrs);
add_device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mknn_instance(
op_ptrs);
}
}
return op_ptrs; return op_ptrs;
} }
}; };
......
library/include/ck/library/tensor_operation_instance/gpu/contraction_scale.hpp
View file @ 8820cf9f
...@@ -19,6 +19,7 @@ namespace tensor_operation { ...@@ -19,6 +19,7 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// float
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_kkn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2, 2,
...@@ -67,6 +68,55 @@ void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instanc ...@@ -67,6 +68,55 @@ void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instanc
PassThrough, PassThrough,
Scale>>>& instances); Scale>>>& instances);
// double
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
Empty_Tuple,
F64,
PassThrough,
PassThrough,
Scale>>>& instances);
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
Empty_Tuple,
F64,
PassThrough,
PassThrough,
Scale>>>& instances);
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
Empty_Tuple,
F64,
PassThrough,
PassThrough,
Scale>>>& instances);
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
2,
2,
F64,
F64,
Empty_Tuple,
F64,
PassThrough,
PassThrough,
Scale>>>& instances);
// Contraction + Scale // Contraction + Scale
template <index_t NumDimM, template <index_t NumDimM,
index_t NumDimN, index_t NumDimN,
...@@ -117,6 +167,22 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceContra ...@@ -117,6 +167,22 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceContra
} }
} }
if constexpr(is_same_v<ADataType, double> && is_same_v<BDataType, double> &&
is_same_v<EDataType, double>)
{
if constexpr(NumDimM == 2 && NumDimN == 2 && NumDimK == 2)
{
add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance(
op_ptrs);
add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance(
op_ptrs);
add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance(
op_ptrs);
add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance(
op_ptrs);
}
}
return op_ptrs; return op_ptrs;
} }
}; };
......
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_forward.hpp
View file @ 8820cf9f
...@@ -117,20 +117,6 @@ void add_device_grouped_conv2d_fwd_xdl_gnhwc_gkyxc_gnhwk_f32_instances( ...@@ -117,20 +117,6 @@ void add_device_grouped_conv2d_fwd_xdl_gnhwc_gkyxc_gnhwk_f32_instances(
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
void add_device_grouped_conv2d_fwd_xdl_gnhwc_gkyxc_gnhwk_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC,
GKYXC,
Empty_Tuple,
GNHWK,
int8_t,
int8_t,
Empty_Tuple,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_f16_instances( void add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_f16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, GNHWC,
...@@ -159,20 +145,21 @@ void add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_f32_instances( ...@@ -159,20 +145,21 @@ void add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_f32_instances(
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
void add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_int8_instances( // grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, BF16,
int8_t, BF16,
Empty_Tuple, Empty_Tuple,
int8_t, BF16,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
// grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f16_instances( void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
NHWGC, NHWGC,
...@@ -187,6 +174,20 @@ void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f16_instances( ...@@ -187,6 +174,20 @@ void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f16_instances(
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
void add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f32_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
NHWGC,
GKYXC,
Empty_Tuple,
NHWGK,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
PassThrough>>>& instances);
// grouped conv3d forward, GNDHWC/GKZYXC/GNDHWK // grouped conv3d forward, GNDHWC/GKZYXC/GNDHWK
void add_device_grouped_conv3d_fwd_xdl_gndhwc_gkzyxc_gndhwk_bf16_instances( void add_device_grouped_conv3d_fwd_xdl_gndhwc_gkzyxc_gndhwk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<3, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<3,
...@@ -385,12 +386,6 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -385,12 +386,6 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
add_device_grouped_conv1d_fwd_xdl_gnhwc_gkyxc_gnhwk_bf16_instances(op_ptrs); add_device_grouped_conv1d_fwd_xdl_gnhwc_gkyxc_gnhwk_bf16_instances(op_ptrs);
} }
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_grouped_conv2d_fwd_xdl_gnhwc_gkyxc_gnhwk_int8_instances(op_ptrs);
add_device_grouped_conv2d_fwd_dl_gnhwc_gkyxc_gnhwk_int8_instances(op_ptrs);
}
} }
else if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> && else if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<OutLayout, NHWGK>) is_same_v<WeiLayout, GKYXC> && is_same_v<OutLayout, NHWGK>)
...@@ -398,7 +393,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -398,7 +393,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>) is_same_v<OutDataType, float>)
{ {
// no instance add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_f32_instances(op_ptrs);
} }
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
...@@ -409,12 +404,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -409,12 +404,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<WeiDataType, ck::bhalf_t> && is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t>) is_same_v<OutDataType, ck::bhalf_t>)
{ {
// no instance add_device_grouped_conv2d_fwd_xdl_nhwgc_gkyxc_nhwgk_bf16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
// no instance
} }
} }
else if constexpr(NumDimSpatial == 3 && is_same_v<InLayout, GNDHWC> && else if constexpr(NumDimSpatial == 3 && is_same_v<InLayout, GNDHWC> &&
......
library/include/ck/library/tensor_operation_instance/gpu/grouped_gemm.hpp
View file @ 8820cf9f
...@@ -68,6 +68,58 @@ void add_device_grouped_gemm_xdl_f16_f16_f16_km_nk_mn_instances( ...@@ -68,6 +68,58 @@ void add_device_grouped_gemm_xdl_f16_f16_f16_km_nk_mn_instances(
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
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);
void add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemm<Row,
Row,
Empty_Tuple,
Row,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
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);
void add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_irregular_instances(
std::vector<std::unique_ptr<DeviceGroupedGemm<Row,
Row,
Empty_Tuple,
Row,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
template <typename ALayout, template <typename ALayout,
typename BLayout, typename BLayout,
typename ELayout, typename ELayout,
...@@ -109,11 +161,17 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -109,11 +161,17 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
is_same_v<ELayout, Row>) is_same_v<ELayout, Row>)
{ {
add_device_grouped_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(op_ptrs); add_device_grouped_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_irregular_instances(
op_ptrs);
} }
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> && else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
is_same_v<ELayout, Row>) is_same_v<ELayout, Row>)
{ {
add_device_grouped_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(op_ptrs); add_device_grouped_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
add_device_grouped_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_instances(
op_ptrs);
} }
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> && else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
is_same_v<ELayout, Row>) is_same_v<ELayout, Row>)
......
library/include/ck/library/tensor_operation_instance/gpu/normalization_swish.hpp 0 → 100644
View file @ 8820cf9f
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_normalization.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// FP16
void add_device_normalization_rank_5_3_swish_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F32, F16, Swish, 5, 3>>>&);
// FP32
void add_device_normalization_rank_5_3_swish_f32_instances(
std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Swish, 5, 3>>>&);
// [x, gamma, beta, y] = [f16, f32, f32, f16]
void add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(
std::vector<std::unique_ptr<DeviceNormalization<F16, F32, F32, F32, F16, Swish, 5, 3>>>&);
template <typename XDataType,
typename GammaDataType,
typename BetaDataType,
typename YDataType,
index_t Rank,
index_t NumReduceDim>
struct DeviceOperationInstanceFactory<
ck::tensor_operation::device::DeviceNormalization<XDataType,
GammaDataType,
BetaDataType,
F32,
YDataType,
ck::tensor_operation::element_wise::Swish,
Rank,
NumReduceDim>>
{
using DeviceOp = DeviceNormalization<XDataType,
GammaDataType,
BetaDataType,
F32,
YDataType,
ck::tensor_operation::element_wise::Swish,
Rank,
NumReduceDim>;
static auto GetInstances()
{
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F16> &&
is_same_v<BetaDataType, F16> && is_same_v<YDataType, F16>)
{
if constexpr(Rank == 5 && NumReduceDim == 3)
{
add_device_normalization_rank_5_3_swish_f16_instances(op_ptrs);
}
}
else if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> &&
is_same_v<BetaDataType, F32> && is_same_v<YDataType, F32>)
{
if constexpr(Rank == 5 && NumReduceDim == 3)
{
add_device_normalization_rank_5_3_swish_f32_instances(op_ptrs);
}
}
else if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F32> &&
is_same_v<BetaDataType, F32> && is_same_v<YDataType, F16>)
{
if constexpr(Rank == 5 && NumReduceDim == 3)
{
add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(op_ptrs);
}
}
return op_ptrs;
}
};
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_bias_forward_perchannel_quantization.hpp
View file @ 8820cf9f
...@@ -17,14 +17,14 @@ namespace tensor_operation { ...@@ -17,14 +17,14 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances( void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -36,10 +36,10 @@ void add_device_conv2d_dl_bias_perchannel_quantization_int8_instances( ...@@ -36,10 +36,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -52,10 +52,10 @@ void add_device_conv2d_dl_bias_relu_perchannel_quantization_int8_instances( ...@@ -52,10 +52,10 @@ 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::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -68,10 +68,10 @@ void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances( ...@@ -68,10 +68,10 @@ void add_device_conv2d_dl_bias_tanh_perchannel_quantization_int8_instances(
void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -83,10 +83,10 @@ void add_device_conv2d_xdl_bias_perchannel_quantization_int8_instances( ...@@ -83,10 +83,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -99,10 +99,10 @@ void add_device_conv2d_xdl_bias_relu_perchannel_quantization_int8_instances( ...@@ -99,10 +99,10 @@ 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::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
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,
...@@ -154,9 +154,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -154,9 +154,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_GK_Tuple> && is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_GK_Tuple> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>)
...@@ -220,9 +220,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -220,9 +220,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_GK_Tuple> && is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_GK_Tuple> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_F32_Tuple> && is_same_v<OutDataType, int8_t>)
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_bias_forward_perlayer_quantization.hpp
View file @ 8820cf9f
...@@ -17,14 +17,14 @@ namespace tensor_operation { ...@@ -17,14 +17,14 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances( void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -36,10 +36,10 @@ void add_device_conv2d_dl_bias_perlayer_quantization_int8_instances( ...@@ -36,10 +36,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -51,10 +51,10 @@ void add_device_conv2d_dl_bias_relu_perlayer_quantization_int8_instances( ...@@ -51,10 +51,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -67,10 +67,10 @@ void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances( ...@@ -67,10 +67,10 @@ void add_device_conv2d_dl_bias_tanh_perlayer_quantization_int8_instances(
void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances(
std::vector< std::vector<
std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -82,10 +82,10 @@ void add_device_conv2d_xdl_bias_perlayer_quantization_int8_instances( ...@@ -82,10 +82,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -97,10 +97,10 @@ void add_device_conv2d_xdl_bias_relu_perlayer_quantization_int8_instances( ...@@ -97,10 +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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
I32_Tuple, I32_Tuple,
...@@ -152,9 +152,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -152,9 +152,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> && is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>)
...@@ -218,9 +218,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -218,9 +218,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> && is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>) is_same_v<DsDataType, I32_Tuple> && is_same_v<OutDataType, int8_t>)
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_forward_perchannel_quantization.hpp
View file @ 8820cf9f
...@@ -17,13 +17,13 @@ namespace tensor_operation { ...@@ -17,13 +17,13 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_conv2d_dl_perchannel_quantization_int8_instances( void add_device_conv2d_dl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -35,10 +35,10 @@ void add_device_conv2d_dl_perchannel_quantization_int8_instances( ...@@ -35,10 +35,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -50,10 +50,10 @@ void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances( ...@@ -50,10 +50,10 @@ void add_device_conv2d_dl_relu_perchannel_quantization_int8_instances(
void add_device_conv2d_xdl_perchannel_quantization_int8_instances( void add_device_conv2d_xdl_perchannel_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -65,10 +65,10 @@ void add_device_conv2d_xdl_perchannel_quantization_int8_instances( ...@@ -65,10 +65,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
GK_Tuple, GK_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
F32_Tuple, F32_Tuple,
...@@ -119,9 +119,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -119,9 +119,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> && is_same_v<WeiLayout, GKYXC> && is_same_v<DsLayout, GK_Tuple> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>) is_same_v<OutDataType, int8_t>)
......
library/include/ck/library/tensor_operation_instance/gpu/quantization/grouped_convolution_forward_perlayer_quantization.hpp
View file @ 8820cf9f
...@@ -17,13 +17,13 @@ namespace tensor_operation { ...@@ -17,13 +17,13 @@ namespace tensor_operation {
namespace device { namespace device {
namespace instance { namespace instance {
// grouped conv2d forward, GNHWC/GKYXC/GNHWK // grouped conv2d forward, NHWGC/GKYXC/NHWGK
void add_device_conv2d_dl_perlayer_quantization_int8_instances( void add_device_conv2d_dl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -35,10 +35,10 @@ void add_device_conv2d_dl_perlayer_quantization_int8_instances( ...@@ -35,10 +35,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -50,10 +50,10 @@ void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances( ...@@ -50,10 +50,10 @@ void add_device_conv2d_dl_relu_perlayer_quantization_int8_instances(
void add_device_conv2d_xdl_perlayer_quantization_int8_instances( void add_device_conv2d_xdl_perlayer_quantization_int8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -65,10 +65,10 @@ void add_device_conv2d_xdl_perlayer_quantization_int8_instances( ...@@ -65,10 +65,10 @@ 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<2, std::vector<std::unique_ptr<DeviceGroupedConvFwdMultipleD<2,
GNHWC, NHWGC,
GKYXC, GKYXC,
Empty_Tuple, Empty_Tuple,
GNHWK, NHWGK,
int8_t, int8_t,
int8_t, int8_t,
Empty_Tuple, Empty_Tuple,
...@@ -117,8 +117,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -117,8 +117,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
{ {
std::vector<std::unique_ptr<DeviceOp>> op_ptrs; std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, GNHWC> && if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWGC> &&
is_same_v<WeiLayout, GKYXC> && is_same_v<OutLayout, GNHWK>) is_same_v<WeiLayout, GKYXC> && is_same_v<OutLayout, NHWGK>)
{ {
if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> && if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>) is_same_v<OutDataType, int8_t>)
......
library/src/tensor_operation_instance/gpu/contraction_bilinear/CMakeLists.txt
View file @ 8820cf9f
add_instance_library(device_contraction_bilinear_instance add_instance_library(device_contraction_bilinear_instance
#float
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_kknn_instance.cpp device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_kknn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_knnn_instance.cpp device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_knnn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mknn_instance.cpp device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mknn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn_instance.cpp device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn_instance.cpp
#double
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_kknn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_knnn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mknn_instance.cpp
device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mnnn_instance.cpp
) )
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment