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Use ""_uz to simplify example code

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This commit is contained in:
Po-Yen, Chen
2022-08-19 11:54:51 -04:00
parent 3e2371c554
commit 4d4a659cd6
2 changed files with 14 additions and 12 deletions
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13
example/01_gemm/gemm_dl_int4.cpp
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@@ -20,6 +20,7 @@
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/literals.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
template <ck::index_t... Is>
@@ -62,6 +63,8 @@ using ReferenceGemmInstance = ck::tensor_operation::host::
int main(int argc, char* argv[])
{
using namespace ck::literals;
bool do_verification = true;
int init_method = 1;
bool time_kernel = false;
@@ -111,15 +114,13 @@ int main(int argc, char* argv[])
auto f_host_tensor_descriptor =
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
if constexpr(std::is_same_v<decltype(layout), ck::tensor_layout::gemm::RowMajor>)
{
return HostTensorDescriptor(std::vector<std::size_t>({row, col}),
std::vector<std::size_t>({stride, 1}));
return HostTensorDescriptor({row, col}, {stride, 1_uz});
}
else
{
return HostTensorDescriptor(std::vector<std::size_t>({row, col}),
std::vector<std::size_t>({1, stride}));
return HostTensorDescriptor({row, col}, {1_uz, stride});
}
};
@@ -189,7 +190,7 @@ int main(int argc, char* argv[])
float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
std::size_t flop = std::size_t(2) * M * N * K;
std::size_t flop = 2_uz * M * N * K;
std::size_t num_btype = sizeof(KernelADataType) * M * K + sizeof(KernelBDataType) * K * N +
sizeof(KernelCDataType) * M * N;

13
example/01_gemm/gemm_xdl_int4.cpp
View File

@@ -21,6 +21,7 @@
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/literals.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
template <ck::index_t... Is>
@@ -64,6 +65,8 @@ using ReferenceGemmInstance = ck::tensor_operation::host::
int main(int argc, char* argv[])
{
using namespace ck::literals;
bool do_verification = true;
int init_method = 1;
bool time_kernel = false;
@@ -109,15 +112,13 @@ int main(int argc, char* argv[])
auto f_host_tensor_descriptor =
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
if(std::is_same<decltype(layout), ck::tensor_layout::gemm::RowMajor>::value)
if constexpr(std::is_same_v<decltype(layout), ck::tensor_layout::gemm::RowMajor>)
{
return HostTensorDescriptor(std::vector<std::size_t>({row, col}),
std::vector<std::size_t>({stride, 1}));
return HostTensorDescriptor({row, col}, {stride, 1_uz});
}
else
{
return HostTensorDescriptor(std::vector<std::size_t>({row, col}),
std::vector<std::size_t>({1, stride}));
return HostTensorDescriptor({row, col}, {1_uz, stride});
}
};
@@ -183,7 +184,7 @@ int main(int argc, char* argv[])
float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
std::size_t flop = std::size_t(2) * M * N * K;
std::size_t flop = 2_uz * M * N * K;
std::size_t num_btype = sizeof(KernelADataType) * M * K + sizeof(KernelBDataType) * K * N +
sizeof(KernelCDataType) * M * N;