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Commit 4ecec24c authored by illsilin's avatar illsilin
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fix clang format

parent 3c5717df
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Inline Side-by-side
Showing with 42 additions and 38 deletions
example/ck_tile/03_gemm/run_gemm_example.inc
View file @ 4ecec24c
......@@ -30,8 +30,13 @@ auto calculate_rtol_atol(const ck_tile::index_t K,
return ck_tile::make_tuple(std::max(rtol, rtol_split_k), std::max(atol, atol_split_k));
}
template <typename ADataType, typename BDataType, typename AccDataType, typename CDataType,
typename ALayout, typename BLayout, typename CLayout>
template <typename ADataType,
typename BDataType,
typename AccDataType,
typename CDataType,
typename ALayout,
typename BLayout,
typename CLayout>
float invoke_gemm(ck_tile::DeviceMem& a_m_k_dev_buf,
ck_tile::DeviceMem& b_k_n_dev_buf,
ck_tile::DeviceMem& c_m_n_dev_buf,
......@@ -57,9 +62,9 @@ float invoke_gemm(ck_tile::DeviceMem& a_m_k_dev_buf,
args.stride_B = stride_B;
args.stride_C = stride_C;
float ave_time = gemm_calc<ADataType, BDataType, AccDataType, CDataType,
ALayout, BLayout, CLayout>(
args, ck_tile::stream_config{nullptr, true, 1, n_warmup, n_repeat});
float ave_time =
gemm_calc<ADataType, BDataType, AccDataType, CDataType, ALayout, BLayout, CLayout>(
args, ck_tile::stream_config{nullptr, true, 1, n_warmup, n_repeat});
std::size_t flop = std::size_t(2) * M * N * K;
std::size_t num_byte =
......@@ -69,14 +74,11 @@ float invoke_gemm(ck_tile::DeviceMem& a_m_k_dev_buf,
std::cout << "Run Gemm kernel with M =" << M << " N =" << N << " K =" << K
<< " StrideA =" << stride_A << " StrideB =" << stride_B << " StrideC =" << stride_C
<< " A_Layout =" << ALayout::name
<< " B_Layout =" << BLayout::name
<< " C_Layout =" << CLayout::name
<< " A Type = " << DataTypeTraits<ADataType>::name
<< " B Type = " << DataTypeTraits<BDataType>::name
<< " C Type = " << DataTypeTraits<CDataType>::name
<< " : " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
<< std::endl;
<< " A_Layout =" << ALayout::name << " B_Layout =" << BLayout::name
<< " C_Layout =" << CLayout::name << " A Type = " << DataTypeTraits<ADataType>::name
<< " B Type = " << DataTypeTraits<BDataType>::name
<< " C Type = " << DataTypeTraits<CDataType>::name << " : " << ave_time << " ms, "
<< tflops << " TFlops, " << gb_per_sec << " GB/s, " << std::endl;
return ave_time;
}
......@@ -92,10 +94,10 @@ int run_gemm_example_with_layouts(int argc,
if(!result)
return -1;
using ADataType = typename GemmBasicTypeConfig<PrecType>::ADataType;
using BDataType = typename GemmBasicTypeConfig<PrecType>::BDataType;
using CDataType = typename GemmBasicTypeConfig<PrecType>::CDataType;
using AccDataType = typename GemmBasicTypeConfig<PrecType>::AccDataType;
using ADataType = typename GemmBasicTypeConfig<PrecType>::ADataType;
using BDataType = typename GemmBasicTypeConfig<PrecType>::BDataType;
using CDataType = typename GemmBasicTypeConfig<PrecType>::CDataType;
using AccDataType = typename GemmBasicTypeConfig<PrecType>::AccDataType;
ck_tile::index_t M = arg_parser.get_int("m");
ck_tile::index_t N = arg_parser.get_int("n");
......@@ -133,19 +135,19 @@ int run_gemm_example_with_layouts(int argc,
c_m_n_dev_buf.SetZero();
c_m_n_dev_result.SetZero();
invoke_gemm<ADataType, BDataType, AccDataType, CDataType,
ALayout, BLayout, CLayout>(a_m_k_dev_buf,
b_k_n_dev_buf,
c_m_n_dev_buf,
M,
N,
K,
stride_A,
stride_B,
stride_C,
kbatch,
n_warmup,
n_repeat);
invoke_gemm<ADataType, BDataType, AccDataType, CDataType, ALayout, BLayout, CLayout>(
a_m_k_dev_buf,
b_k_n_dev_buf,
c_m_n_dev_buf,
M,
N,
K,
stride_A,
stride_B,
stride_C,
kbatch,
n_warmup,
n_repeat);
c_m_n_dev_buf.FromDevice(c_m_n_dev_result.data());
bool pass = true;
......@@ -160,9 +162,9 @@ int run_gemm_example_with_layouts(int argc,
a_m_k, b_k_n, c_m_n_host_ref);
const float max_accumulated_value =
*std::max_element(c_m_n_host_ref.mData.begin(), c_m_n_host_ref.mData.end());
const auto rtol_atol = calculate_rtol_atol<ADataType, BDataType, AccDataType, CDataType>
(K, kbatch, max_accumulated_value);
pass = ck_tile::check_err(c_m_n_dev_result,
const auto rtol_atol = calculate_rtol_atol<ADataType, BDataType, AccDataType, CDataType>(
K, kbatch, max_accumulated_value);
pass = ck_tile::check_err(c_m_n_dev_result,
c_m_n_host_ref,
"Error: Incorrect results!",
rtol_atol.at(ck_tile::number<0>{}),
......@@ -218,9 +220,9 @@ int run_gemm_example_with_layouts(int argc,
c_m_n_gpu_buf_ref.FromDevice(c_m_n_gpu_ref.data());
const float max_accumulated_value =
*std::max_element(c_m_n_gpu_ref.mData.begin(), c_m_n_gpu_ref.mData.end());
const auto rtol_atol = calculate_rtol_atol<ADataType, BDataType, AccDataType, CDataType>
(K, kbatch, max_accumulated_value);
pass = ck_tile::check_err(c_m_n_dev_result,
const auto rtol_atol = calculate_rtol_atol<ADataType, BDataType, AccDataType, CDataType>(
K, kbatch, max_accumulated_value);
pass = ck_tile::check_err(c_m_n_dev_result,
c_m_n_gpu_ref,
"Error: Incorrect results!",
rtol_atol.at(ck_tile::number<0>{}),
......
include/ck/tensor_operation/gpu/device/impl/device_batched_gemm_multiple_d_gemm_multiple_d_xdl_cshuffle.hpp
View file @ 4ecec24c
......@@ -827,8 +827,10 @@ struct DeviceBatchedGemmMultipleDGemmMultipleD_Xdl_CShuffle
is_same_v<tensor_layout::gemm::ColumnMajor, B0Layout> &&
CheckDLayout<tensor_layout::gemm::RowMajor, D0sLayout, NumD0Tensor>() &&
(is_same_v<tensor_layout::gemm::RowMajor, B1Layout> ||
is_same_v<tensor_layout::gemm::ColumnMajor, B1Layout>) &&
CheckDLayout<tensor_layout::gemm::RowMajor, D1sLayout, NumD1Tensor>() &&
is_same_v<tensor_layout::gemm::ColumnMajor,
B1Layout>)&&CheckDLayout<tensor_layout::gemm::RowMajor,
D1sLayout,
NumD1Tensor>() &&
is_same_v<tensor_layout::gemm::RowMajor, E1Layout>))
{
return false;
......
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