Skip to content

GitLab

"src/include/blockwise_gemm.hpp" did not exist on "7a251a0922e1ec7e27b2612e4136b5f5849c89ca"
Unverified Commit cea992b8 authored by zjing14's avatar zjing14 Committed by GitHub
Browse files

Merge branch 'develop' into aosewski/gemm_tile_loop

parents e7a53782 c8a8385f
Show whitespace changes
Inline Side-by-side
Showing with 83 additions and 44 deletions
library/src/tensor_operation_instance/gpu/gemm/device_gemm_dl_i8_i8_i8_mk_kn_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_dl.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_dl_i8_i8_i8_mk_kn_mn_irregular_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_dl.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_dl_i8_i8_i8_mk_nk_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_dl.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_dl_i8_i8_i8_mk_nk_mn_irregular_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_dl.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instance.cpp
View file @ cea992b8
......@@ -8,7 +8,7 @@
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#ifdef __int8__
#ifdef CK_ENABLE_INT8
namespace ck {
namespace tensor_operation {
namespace device {
......
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instance.cpp
View file @ cea992b8
......@@ -29,6 +29,17 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
using device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_generic_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| Block| MPer| NPer| K0Per| K1| 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|Specialization| 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_MXdlPerWave_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_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 16, 1, 8>, 2>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 64, 32, 32, 4, 8, 32, 32, 1, 1, S<1, 2, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 16, 1, 4>, 2>
// clang-format on
>;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances = std::tuple<
// clang-format off
......@@ -74,7 +85,6 @@ using device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances = std::tuple<
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F16, PipelineVersion::v2>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F16, PipelineVersion::v2>
// clang-format on
// clang-format on
>;
void add_device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(
......@@ -82,6 +92,8 @@ void add_device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(
DeviceGemmSplitK<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_generic_instances{});
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances{});
}
......
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instance.cpp
View file @ cea992b8
......@@ -28,6 +28,17 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
using device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_generic_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| Block| MPer| NPer| K0Per| K1| 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|Specialization| 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_MXdlPerWave_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_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 1, 8, true, 1, 1, S<1, 32, 1, 8>, 2, F16, PipelineVersion::v1>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 2, F16, PipelineVersion::v1>
// clang-format on
>;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances = std::tuple<
// clang-format off
......@@ -72,6 +83,8 @@ void add_device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances(
DeviceGemmSplitK<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_generic_instances{});
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances{});
}
......
library/src/tensor_operation_instance/gpu/gemm_streamk/device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_instance.cpp
View file @ cea992b8
......@@ -29,6 +29,16 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// static constexpr auto GemmMNPadding =
// ck::tensor_operation::device::GemmSpecialization::MNPadding;
using device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_generic_instances = std::tuple<
// clang-format off
//##################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| 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| 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_MXdlPerWave_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_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//##################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlStreamK< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 16, 1, 8>, 2>,
DeviceGemmXdlStreamK< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 128, 32, 64, 4, 8, 32, 32, 1, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 16, 1, 8>, 2>
// clang-format on
>;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_instances = std::tuple<
......@@ -61,6 +71,8 @@ void add_device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_instances(
DeviceGemmStreamK<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_generic_instances{});
add_device_operation_instances(instances,
device_gemm_xdl_streamk_f16_f16_f16_mk_kn_mn_instances{});
}
......
profiler/include/profiler/profile_gemm_streamk_impl.hpp
View file @ cea992b8
......@@ -170,6 +170,25 @@ bool profile_gemm_streamk_impl(int do_verification,
// re-init C to zero before profiling next kernel
c_device_buf.SetZero();
invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
if(do_verification)
{
c_device_buf.FromDevice(c_m_n_device_result.mData.data());
pass = pass & ck::utils::check_err(c_m_n_device_result, c_m_n_host_result);
if(do_log)
{
LogRangeAsType<float>(std::cout << "a : ", a_m_k.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "b: ", b_k_n.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_host : ", c_m_n_host_result.mData, ",")
<< std::endl;
LogRangeAsType<float>(std::cout << "c_device: ", c_m_n_device_result.mData, ",")
<< std::endl;
}
}
std::string op_name = op_ptr->GetTypeString();
float ave_time =
......@@ -194,23 +213,6 @@ bool profile_gemm_streamk_impl(int do_verification,
best_ave_time = ave_time;
best_gb_per_sec = gb_per_sec;
}
if(do_verification)
{
c_device_buf.FromDevice(c_m_n_device_result.mData.data());
pass = pass & ck::utils::check_err(c_m_n_device_result, c_m_n_host_result);
if(do_log)
{
LogRangeAsType<float>(std::cout << "a : ", a_m_k.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "b: ", b_k_n.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_host : ", c_m_n_host_result.mData, ",")
<< std::endl;
LogRangeAsType<float>(std::cout << "c_device: ", c_m_n_device_result.mData, ",")
<< std::endl;
}
}
}
else
{
......
profiler/src/profile_batched_gemm_multi_d.cpp
View file @ cea992b8
......@@ -71,7 +71,7 @@ int profile_batched_gemm_multi_d(int argc, char* argv[])
const int BatchCount = std::stoi(argv[17]);
using F16 = ck::half_t;
#ifdef __int8__
#ifdef CK_ENABLE_INT8
using INT8 = int8_t;
#endif
......@@ -165,7 +165,7 @@ int profile_batched_gemm_multi_d(int argc, char* argv[])
{
return profile(F16{}, F16{}, F16{}, Col{}, Col{}, Row{});
}
#ifdef __int8__
#ifdef CK_ENABLE_INT8
else if(data_type == GemmDataType::INT8_INT8_INT8 && layout == GemmMatrixLayout::MK_KN_MN)
{
return profile(INT8{}, INT8{}, INT8{}, Row{}, Row{}, Row{});
......
profiler/src/profile_conv_bwd_data.cpp
View file @ cea992b8
......@@ -77,7 +77,7 @@ int profile_conv_bwd_data(int argc, char* argv[])
using F32 = float;
using F16 = ck::half_t;
using BF16 = ck::bhalf_t;
#ifdef __int8__
#ifdef CK_ENABLE_INT8
using INT8 = int8_t;
#endif
......@@ -140,7 +140,7 @@ int profile_conv_bwd_data(int argc, char* argv[])
{
return profile(I1, NWC{}, KXC{}, NWK{}, BF16{}, BF16{}, BF16{});
}
#ifdef __int8__
#ifdef CK_ENABLE_INT8
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I1, NWC{}, KXC{}, NWK{}, INT8{}, INT8{}, INT8{});
......@@ -161,7 +161,7 @@ int profile_conv_bwd_data(int argc, char* argv[])
{
return profile(I2, NHWC{}, KYXC{}, NHWK{}, BF16{}, BF16{}, BF16{});
}
#ifdef __int8__
#ifdef CK_ENABLE_INT8
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I2, NHWC{}, KYXC{}, NHWK{}, INT8{}, INT8{}, INT8{});
......@@ -182,7 +182,7 @@ int profile_conv_bwd_data(int argc, char* argv[])
{
return profile(I3, NDHWC{}, KZYXC{}, NDHWK{}, BF16{}, BF16{}, BF16{});
}
#ifdef __int8__
#ifdef CK_ENABLE_INT8
else if(data_type == ConvDataType::INT8_INT8_INT8)
{
return profile(I3, NDHWC{}, KZYXC{}, NDHWK{}, INT8{}, INT8{}, INT8{});
......
profiler/src/profile_gemm.cpp
View file @ cea992b8
......@@ -69,10 +69,10 @@ int profile_gemm(int argc, char* argv[])
using F32 = float;
using F16 = ck::half_t;
#ifdef __bf16__
#ifdef CK_ENABLE_BF16
using BF16 = ck::bhalf_t;
#endif
#ifdef __int8__
#ifdef CK_ENABLE_INT8
using INT8 = int8_t;
using INT32 = int32_t;
#endif
......@@ -123,7 +123,7 @@ int profile_gemm(int argc, char* argv[])
if(false)
;
#ifdef __fp32__
#ifdef CK_ENABLE_FP32
else if(data_type == GemmDataType::F32_F32_F32 && layout == GemmMatrixLayout::MK_KN_MN)
{
return profile(Row{}, Row{}, Row{}, F32{}, F32{}, F32{}, F32{});
......@@ -141,7 +141,7 @@ int profile_gemm(int argc, char* argv[])
return profile(Col{}, Col{}, Row{}, F32{}, F32{}, F32{}, F32{});
}
#endif
#ifdef __fp16__
#ifdef CK_ENABLE_FP16
else if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN)
{
return profile(Row{}, Row{}, Row{}, F16{}, F16{}, F32{}, F16{});
......@@ -159,7 +159,7 @@ int profile_gemm(int argc, char* argv[])
return profile(Col{}, Col{}, Row{}, F16{}, F16{}, F32{}, F16{});
}
#endif
#ifdef __bf16__
#ifdef CK_ENABLE_BF16
else if(data_type == GemmDataType::BF16_BF16_BF16 && layout == GemmMatrixLayout::MK_KN_MN)
{
return profile(Row{}, Row{}, Row{}, BF16{}, BF16{}, F32{}, BF16{});
......@@ -177,7 +177,7 @@ int profile_gemm(int argc, char* argv[])
return profile(Col{}, Col{}, Row{}, BF16{}, BF16{}, F32{}, BF16{});
}
#endif
#ifdef __int8__
#ifdef CK_ENABLE_INT8
else if(data_type == GemmDataType::INT8_INT8_INT8 && layout == GemmMatrixLayout::MK_KN_MN)
{
return profile(Row{}, Row{}, Row{}, INT8{}, INT8{}, INT32{}, INT8{});
......
profiler/src/profile_grouped_gemm.cpp
View file @ cea992b8
......@@ -88,7 +88,7 @@ int profile_grouped_gemm(int argc, char* argv[])
const auto StrideBs = argToIntArray(argv[12]);
const auto StrideCs = argToIntArray(argv[13]);
const int kbatch = argc == 15 ? std::stoi(argv[14]) : 1;
#ifdef __fp16__
#ifdef CK_ENABLE_FP16
if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN)
{
ck::profiler::profile_grouped_gemm_impl<ck::half_t,
......
script/clang-format-overwrite.sh
View file @ cea992b8
#find . -name deps -prune -o -name build -prune -o -iname '*.h' -o -iname '*.hpp' -o -iname '*.cpp' -o -iname '*.h.in' -o -iname '*.hpp.in' -o -iname '*.cpp.in' -o -iname '*.cl' -o -iname '*.cuh' -o -iname '*.cu' -o -iname '*.inc' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-10 -i -style=file {}'
git status --porcelain | awk '$1 != "D" && (match($2, "\\.cpp|hpp|inc")) {print $2}' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-10 -i -style=file {}'
#find . -name deps -prune -o -name build -prune -o -iname '*.h' -o -iname '*.hpp' -o -iname '*.cpp' -o -iname '*.h.in' -o -iname '*.hpp.in' -o -iname '*.cpp.in' -o -iname '*.cl' -o -iname '*.cuh' -o -iname '*.cu' -o -iname '*.inc' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-12 -i -style=file {}'
git status --porcelain | awk '$1 != "D" && (match($2, "\\.cpp|hpp|inc")) {print $2}' | xargs -n 1 -P 16 -I{} -t sh -c 'clang-format-12 -i -style=file {}'
script/install_precommit.sh
View file @ cea992b8
......@@ -11,7 +11,7 @@ run_and_check() {
}
echo "I: Installing tools required for pre-commit checks..."
run_and_check apt install clang-format-10
run_and_check apt install clang-format-12
echo "I: Installing pre-commit itself..."
run_and_check pip3 install pre-commit
......
test/batched_gemm_multi_d/test_batched_gemm_multi_d.cpp
View file @ cea992b8
......@@ -71,6 +71,6 @@ TYPED_TEST_SUITE(TestBatchedGemmMultiD, KernelTypes);
#ifdef __fp16
TYPED_TEST(TestBatchedGemmMultiD, f16) { this->template Run<F16>(); }
#endif
#ifdef __int8__
#ifdef CK_ENABLE_INT8
TYPED_TEST(TestBatchedGemmMultiD, int8) { this->template Run<int8_t>(); }
#endif
test/pool_fwd/test_avg_pool3d_fwd.cpp
View file @ cea992b8
......@@ -43,7 +43,7 @@ class TestAvgPool3dFwd : public ::testing::Test
}
}
};
#ifdef __fp16__
#ifdef CK_ENABLE_FP16
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
#else
......
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