Unverified Commit 0394f8a7 authored by ltqin's avatar ltqin Committed by GitHub
Browse files

update layernorm (#1570)

* port layernorm

* change warp_welford.hpp

* Update warpshuffle

* 1. Add save mean and save std back
2. Move construction of tensor_view and tile_window to operator()

* refine welford max count calculation

* unify layernorm api

* Rename file

* Remove save mean and inv std

* Revert "refine welford max count calculation"

This reverts commit 02236580

.

* Fix order of parameter

* refine welford max count calculation again

* Remove fp32 instances

* Fix bug of padding

* refactor api

* Support bf16

* Extract common function

* Refine arg of operator()

* Add kMThreadPerBlock to template parameter

* clang format

* Refine variable name

* Refine file name

* remove redundant line

* refactor layernorm2d pipeline and add block-per-block utility

* fix name

* rename more

* add more block-per-tile instance

* remove duplicated define

* update instance for 2048, 1024 case

* support up to 2048 now

* opt loading

* add n1536

* Add two pass pipeline

* format

* Fix incorrect type

* parallel compilation

* Use smaller N

* fix 2p pass

* Support Repeat_M in distribution

* Refine nameing

* Add reduce example

---------
Co-authored-by: default avatarletaoqin <letaoqin@amd.com>
Co-authored-by: default avataraska-0096 <haocwang@amd.com>
Co-authored-by: default avatarrocking <ChunYu.Lai@amd.com>
Co-authored-by: default avatarcarlushuang <carlus.huang@amd.com>
parent 3f710930
...@@ -127,44 +127,47 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -127,44 +127,47 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
switch(init_method) switch(init_method)
{ {
case 0: break; case 0: break;
case 1: case 1:
a_ms_ks_re.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5}); a_ms_ks_re.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
b_ns_ks_re.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}); b_ns_ks_re.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
d_ms_ns_re.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}); d_ms_ns_re.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
a_ms_ks_img.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5}); a_ms_ks_img.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
b_ns_ks_img.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}); b_ns_ks_img.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
d_ms_ns_img.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}); d_ms_ns_img.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
break; break;
default: default:
a_ms_ks_re.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}); a_ms_ks_re.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
b_ns_ks_re.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}); b_ns_ks_re.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
d_ms_ns_re.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}); d_ms_ns_re.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
a_ms_ks_img.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}); a_ms_ks_img.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
b_ns_ks_img.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}); b_ns_ks_img.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
d_ms_ns_img.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}); d_ms_ns_img.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
break; break;
} }
DeviceMem a_device_buf_re(sizeof(ADataType) * a_ms_ks_re.mDesc.GetElementSpaceSize()); DeviceMem a_device_buf_re(sizeof(ADataType) * a_ms_ks_re.mDesc.GetElementSpaceSize());
DeviceMem b_device_buf_re(sizeof(BDataType) * b_ns_ks_re.mDesc.GetElementSpaceSize()); DeviceMem b_device_buf_re(sizeof(BDataType) * b_ns_ks_re.mDesc.GetElementSpaceSize());
DeviceMem d_device_buf_re(sizeof(DDataType) * d_ms_ns_re.mDesc.GetElementSpaceSize()); DeviceMem d_device_buf_re(sizeof(DDataType) * d_ms_ns_re.mDesc.GetElementSpaceSize());
DeviceMem e_device_buf_re(sizeof(EDataType) * e_ms_ns_device_result_re.mDesc.GetElementSpaceSize()); DeviceMem e_device_buf_re(sizeof(EDataType) *
e_ms_ns_device_result_re.mDesc.GetElementSpaceSize());
DeviceMem a_device_buf_img(sizeof(ADataType) * a_ms_ks_img.mDesc.GetElementSpaceSize()); DeviceMem a_device_buf_img(sizeof(ADataType) * a_ms_ks_img.mDesc.GetElementSpaceSize());
DeviceMem b_device_buf_img(sizeof(BDataType) * b_ns_ks_img.mDesc.GetElementSpaceSize()); DeviceMem b_device_buf_img(sizeof(BDataType) * b_ns_ks_img.mDesc.GetElementSpaceSize());
DeviceMem d_device_buf_img(sizeof(DDataType) * d_ms_ns_img.mDesc.GetElementSpaceSize()); DeviceMem d_device_buf_img(sizeof(DDataType) * d_ms_ns_img.mDesc.GetElementSpaceSize());
DeviceMem e_device_buf_img(sizeof(EDataType) * e_ms_ns_device_result_img.mDesc.GetElementSpaceSize()); DeviceMem e_device_buf_img(sizeof(EDataType) *
e_ms_ns_device_result_img.mDesc.GetElementSpaceSize());
// Intermediate Value For E Real and Img // Intermediate Value For E Real and Img
DeviceMem e_device_buf_re1(sizeof(EDataType) * e_ms_ns_device_result_re.mDesc.GetElementSpaceSize()); DeviceMem e_device_buf_re1(sizeof(EDataType) *
DeviceMem e_device_buf_img1(sizeof(EDataType) * e_ms_ns_device_result_img.mDesc.GetElementSpaceSize()); e_ms_ns_device_result_re.mDesc.GetElementSpaceSize());
DeviceMem e_device_buf_img1(sizeof(EDataType) *
e_ms_ns_device_result_img.mDesc.GetElementSpaceSize());
a_device_buf_re.ToDevice(a_ms_ks_re.mData.data()); a_device_buf_re.ToDevice(a_ms_ks_re.mData.data());
b_device_buf_re.ToDevice(b_ns_ks_re.mData.data()); b_device_buf_re.ToDevice(b_ns_ks_re.mData.data());
...@@ -181,7 +184,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -181,7 +184,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
// set zero for intermediate values // set zero for intermediate values
e_device_buf_re1.SetZero(); e_device_buf_re1.SetZero();
e_device_buf_img1.SetZero(); e_device_buf_img1.SetZero();
auto a_element_op = AElementOp{}; auto a_element_op = AElementOp{};
auto b_element_op = BElementOp{}; auto b_element_op = BElementOp{};
auto cde_element_op = CDEElementOp{alpha, beta}; auto cde_element_op = CDEElementOp{alpha, beta};
...@@ -189,23 +192,24 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -189,23 +192,24 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
// device operation // device operation
// For real Intermediate Value re_1 // For real Intermediate Value re_1
auto op = DeviceOpInstance{}; auto op = DeviceOpInstance{};
auto invoker = op.MakeInvoker(); auto invoker = op.MakeInvoker();
auto argument_re1 = op.MakeArgument(a_device_buf_re.GetDeviceBuffer(), auto argument_re1 =
b_device_buf_re.GetDeviceBuffer(), op.MakeArgument(a_device_buf_re.GetDeviceBuffer(),
std::array<const void*, 1>{d_device_buf_re.GetDeviceBuffer()}, b_device_buf_re.GetDeviceBuffer(),
e_device_buf_re1.GetDeviceBuffer(), std::array<const void*, 1>{d_device_buf_re.GetDeviceBuffer()},
a_ms_ks_lengths, e_device_buf_re1.GetDeviceBuffer(),
a_ms_ks_strides, a_ms_ks_lengths,
b_ns_ks_lengths, a_ms_ks_strides,
b_ns_ks_strides, b_ns_ks_lengths,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths}, b_ns_ks_strides,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides}, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths},
e_ms_ns_lengths, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides},
e_ms_ns_strides, e_ms_ns_lengths,
a_element_op, e_ms_ns_strides,
b_element_op, a_element_op,
cde_element_op); b_element_op,
cde_element_op);
if(!op.IsSupportedArgument(argument_re1)) if(!op.IsSupportedArgument(argument_re1))
{ {
...@@ -216,7 +220,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -216,7 +220,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
float ave_time_re1 = invoker.Run(argument_re1, StreamConfig{nullptr, time_kernel}); float ave_time_re1 = invoker.Run(argument_re1, StreamConfig{nullptr, time_kernel});
alpha = -1.f; alpha = -1.f;
beta = 1.f; beta = 1.f;
...@@ -228,21 +231,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -228,21 +231,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
// For real Intermediate Value re_2 // For real Intermediate Value re_2
// auto op = DeviceOpInstance{}; // auto op = DeviceOpInstance{};
// auto invoker = op.MakeInvoker(); // auto invoker = op.MakeInvoker();
auto argument_re2 = op.MakeArgument(a_device_buf_img.GetDeviceBuffer(), auto argument_re2 =
b_device_buf_img.GetDeviceBuffer(), op.MakeArgument(a_device_buf_img.GetDeviceBuffer(),
std::array<const void*, 1>{e_device_buf_re1.GetDeviceBuffer()}, b_device_buf_img.GetDeviceBuffer(),
e_device_buf_re.GetDeviceBuffer(), std::array<const void*, 1>{e_device_buf_re1.GetDeviceBuffer()},
a_ms_ks_lengths, e_device_buf_re.GetDeviceBuffer(),
a_ms_ks_strides, a_ms_ks_lengths,
b_ns_ks_lengths, a_ms_ks_strides,
b_ns_ks_strides, b_ns_ks_lengths,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths}, b_ns_ks_strides,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides}, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths},
e_ms_ns_lengths, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides},
e_ms_ns_strides, e_ms_ns_lengths,
a_element_op, e_ms_ns_strides,
b_element_op, a_element_op,
cde_element_op); b_element_op,
cde_element_op);
if(!op.IsSupportedArgument(argument_re2)) if(!op.IsSupportedArgument(argument_re2))
{ {
...@@ -253,7 +257,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -253,7 +257,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
float ave_time_re2 = invoker.Run(argument_re2, StreamConfig{nullptr, time_kernel}); float ave_time_re2 = invoker.Run(argument_re2, StreamConfig{nullptr, time_kernel});
alpha = 1.f; alpha = 1.f;
beta = 1.f; beta = 1.f;
...@@ -261,22 +264,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -261,22 +264,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
b_element_op = BElementOp{}; b_element_op = BElementOp{};
cde_element_op = CDEElementOp{alpha, beta}; cde_element_op = CDEElementOp{alpha, beta};
auto argument_img1 = op.MakeArgument(a_device_buf_re.GetDeviceBuffer(), auto argument_img1 =
b_device_buf_img.GetDeviceBuffer(), op.MakeArgument(a_device_buf_re.GetDeviceBuffer(),
std::array<const void*, 1>{d_device_buf_img.GetDeviceBuffer()}, b_device_buf_img.GetDeviceBuffer(),
e_device_buf_img1.GetDeviceBuffer(), std::array<const void*, 1>{d_device_buf_img.GetDeviceBuffer()},
a_ms_ks_lengths, e_device_buf_img1.GetDeviceBuffer(),
a_ms_ks_strides, a_ms_ks_lengths,
b_ns_ks_lengths, a_ms_ks_strides,
b_ns_ks_strides, b_ns_ks_lengths,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths}, b_ns_ks_strides,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides}, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths},
e_ms_ns_lengths, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides},
e_ms_ns_strides, e_ms_ns_lengths,
a_element_op, e_ms_ns_strides,
b_element_op, a_element_op,
cde_element_op); b_element_op,
cde_element_op);
if(!op.IsSupportedArgument(argument_img1)) if(!op.IsSupportedArgument(argument_img1))
{ {
...@@ -290,23 +293,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -290,23 +293,22 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
alpha = 1.f; alpha = 1.f;
beta = 1.f; beta = 1.f;
auto argument_img2 = op.MakeArgument(a_device_buf_img.GetDeviceBuffer(), auto argument_img2 =
b_device_buf_re.GetDeviceBuffer(), op.MakeArgument(a_device_buf_img.GetDeviceBuffer(),
std::array<const void*, 1>{e_device_buf_img1.GetDeviceBuffer()}, b_device_buf_re.GetDeviceBuffer(),
e_device_buf_img.GetDeviceBuffer(), std::array<const void*, 1>{e_device_buf_img1.GetDeviceBuffer()},
a_ms_ks_lengths, e_device_buf_img.GetDeviceBuffer(),
a_ms_ks_strides, a_ms_ks_lengths,
b_ns_ks_lengths, a_ms_ks_strides,
b_ns_ks_strides, b_ns_ks_lengths,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths}, b_ns_ks_strides,
std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides}, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_lengths},
e_ms_ns_lengths, std::array<std::vector<ck::index_t>, 1>{d_ms_ns_strides},
e_ms_ns_strides, e_ms_ns_lengths,
a_element_op, e_ms_ns_strides,
b_element_op, a_element_op,
cde_element_op); b_element_op,
cde_element_op);
if(!op.IsSupportedArgument(argument_img2)) if(!op.IsSupportedArgument(argument_img2))
{ {
...@@ -317,7 +319,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -317,7 +319,6 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
float ave_time_img2 = invoker.Run(argument_img2, StreamConfig{nullptr, time_kernel}); float ave_time_img2 = invoker.Run(argument_img2, StreamConfig{nullptr, time_kernel});
ck::index_t M = ck::index_t M =
ck::accumulate_n<ck::index_t>(e_ms_ns_lengths.begin(), NumDimM, 1, std::multiplies<>{}); ck::accumulate_n<ck::index_t>(e_ms_ns_lengths.begin(), NumDimM, 1, std::multiplies<>{});
...@@ -331,9 +332,9 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -331,9 +332,9 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
std::size_t num_btype = sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + std::size_t num_btype = sizeof(ADataType) * M * K + sizeof(BDataType) * K * N +
sizeof(DDataType) * M * N + sizeof(EDataType) * M * N * 2; sizeof(DDataType) * M * N + sizeof(EDataType) * M * N * 2;
float ave_time = ave_time_img2 + ave_time_img1 + ave_time_re2 + ave_time_re1 ; float ave_time = ave_time_img2 + ave_time_img1 + ave_time_re2 + ave_time_re1;
float tflops = static_cast<float>(flop) / 1.E9 / ave_time; float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
float gb_per_sec = num_btype / 1.E6 / ave_time; float gb_per_sec = num_btype / 1.E6 / ave_time;
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
...@@ -343,7 +344,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -343,7 +344,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
e_device_buf_img.FromDevice(e_ms_ns_device_result_img.mData.data()); e_device_buf_img.FromDevice(e_ms_ns_device_result_img.mData.data());
auto isRealOk = 0; auto isRealOk = 0;
auto isImgOk = 0; auto isImgOk = 0;
if(do_verification) if(do_verification)
{ {
...@@ -366,17 +367,16 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -366,17 +367,16 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
auto ref_op = ReferenceOpInstance{}; auto ref_op = ReferenceOpInstance{};
auto ref_invoker = ref_op.MakeInvoker(); auto ref_invoker = ref_op.MakeInvoker();
auto ref_argument_re = auto ref_argument_re = ref_op.MakeArgument(
ref_op.MakeArgument(a_ms_ks_re, b_ns_ks_re, c_ms_ns_host_result_re, a_element_op, b_element_op); a_ms_ks_re, b_ns_ks_re, c_ms_ns_host_result_re, a_element_op, b_element_op);
ref_invoker.Run(ref_argument_re); ref_invoker.Run(ref_argument_re);
alpha = 1.f; alpha = 1.f;
beta = 1.f; beta = 1.f;
cde_element_op = CDEElementOp{alpha, beta}; cde_element_op = CDEElementOp{alpha, beta};
for(size_t m0 = 0; m0 < e_ms_ns_host_result_re.mDesc.GetLengths()[0]; ++m0) for(size_t m0 = 0; m0 < e_ms_ns_host_result_re.mDesc.GetLengths()[0]; ++m0)
{ {
for(size_t m1 = 0; m1 < e_ms_ns_host_result_re.mDesc.GetLengths()[1]; ++m1) for(size_t m1 = 0; m1 < e_ms_ns_host_result_re.mDesc.GetLengths()[1]; ++m1)
...@@ -395,11 +395,11 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -395,11 +395,11 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
alpha = 1.f; alpha = 1.f;
beta = -1.f; beta = -1.f;
cde_element_op = CDEElementOp{alpha, beta}; cde_element_op = CDEElementOp{alpha, beta};
auto ref_argument_re1 = auto ref_argument_re1 = ref_op.MakeArgument(
ref_op.MakeArgument(a_ms_ks_img, b_ns_ks_img, c_ms_ns_host_result_re1, a_element_op, b_element_op); a_ms_ks_img, b_ns_ks_img, c_ms_ns_host_result_re1, a_element_op, b_element_op);
ref_invoker.Run(ref_argument_re1); ref_invoker.Run(ref_argument_re1);
...@@ -419,23 +419,20 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -419,23 +419,20 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
} }
} }
isRealOk = ck::utils::check_err(e_ms_ns_device_result_re, e_ms_ns_host_result_re) ? 0 : 1; isRealOk = ck::utils::check_err(e_ms_ns_device_result_re, e_ms_ns_host_result_re) ? 0 : 1;
// Img Part Verification // Img Part Verification
Tensor<CShuffleDataType> c_ms_ns_host_result_img(e_ms_ns_lengths, e_ms_ns_strides); Tensor<CShuffleDataType> c_ms_ns_host_result_img(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<CShuffleDataType> c_ms_ns_host_result_img1(e_ms_ns_lengths, e_ms_ns_strides); Tensor<CShuffleDataType> c_ms_ns_host_result_img1(e_ms_ns_lengths, e_ms_ns_strides);
auto ref_argument_img = auto ref_argument_img = ref_op.MakeArgument(
ref_op.MakeArgument(a_ms_ks_re, b_ns_ks_img, c_ms_ns_host_result_img, a_element_op, b_element_op); a_ms_ks_re, b_ns_ks_img, c_ms_ns_host_result_img, a_element_op, b_element_op);
ref_invoker.Run(ref_argument_img); ref_invoker.Run(ref_argument_img);
alpha = 1.f; alpha = 1.f;
beta = 1.f; beta = 1.f;
cde_element_op = CDEElementOp{alpha, beta}; cde_element_op = CDEElementOp{alpha, beta};
for(size_t m0 = 0; m0 < e_ms_ns_host_result_img.mDesc.GetLengths()[0]; ++m0) for(size_t m0 = 0; m0 < e_ms_ns_host_result_img.mDesc.GetLengths()[0]; ++m0)
...@@ -454,9 +451,9 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -454,9 +451,9 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
} }
} }
auto ref_argument_img1 = auto ref_argument_img1 = ref_op.MakeArgument(
ref_op.MakeArgument(a_ms_ks_img, b_ns_ks_re, c_ms_ns_host_result_img1, a_element_op, b_element_op); a_ms_ks_img, b_ns_ks_re, c_ms_ns_host_result_img1, a_element_op, b_element_op);
ref_invoker.Run(ref_argument_img1); ref_invoker.Run(ref_argument_img1);
for(size_t m0 = 0; m0 < e_ms_ns_host_result_img.mDesc.GetLengths()[0]; ++m0) for(size_t m0 = 0; m0 < e_ms_ns_host_result_img.mDesc.GetLengths()[0]; ++m0)
...@@ -475,7 +472,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[]) ...@@ -475,7 +472,7 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
} }
} }
isImgOk = ck::utils::check_err(e_ms_ns_device_result_re, e_ms_ns_host_result_re) ? 0 : 1; isImgOk = ck::utils::check_err(e_ms_ns_device_result_re, e_ms_ns_host_result_re) ? 0 : 1;
return (isRealOk && isImgOk); return (isRealOk && isImgOk);
} }
......
set(EXAMPLE_LAYERNORM2D_FWD "tile_example_layernorm2d_fwd")
# not using add_example_executable() to add this target, since we don't want this to have # not using add_example_executable() to add this target, since we don't want this to have
# to be included in "make all/install/check" # to be included in "make all/install/check"
add_executable(tile_example_layernorm2d_fwd EXCLUDE_FROM_ALL layernorm2d_fwd.cpp) message("adding example ${EXAMPLE_LAYERNORM2D_FWD}")
target_compile_options(tile_example_layernorm2d_fwd PRIVATE -DSAVE_MEAN_INV_STD) file(GLOB INSTANCE_SRCS instances/*.cpp)
\ No newline at end of file add_executable(${EXAMPLE_LAYERNORM2D_FWD} EXCLUDE_FROM_ALL layernorm2d_fwd.cpp)
target_include_directories(${EXAMPLE_LAYERNORM2D_FWD} PRIVATE ${CMAKE_CURRENT_LIST_DIR})
target_sources(${EXAMPLE_LAYERNORM2D_FWD} PRIVATE ${INSTANCE_SRCS})
set(EXAMPLE_LAYERNORM2D_FWD_COMPILE_OPTIONS)
# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
list(APPEND EXAMPLE_LAYERNORM2D_FWD_COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
target_compile_options(${EXAMPLE_LAYERNORM2D_FWD} PRIVATE ${EXAMPLE_LAYERNORM2D_FWD_COMPILE_OPTIONS})
# TODO: we have to turn off this global prop, otherwise the progress bar generated
# by cmake will print too many files, execvp: /bin/sh: Argument list too long
# however, this property may affect global
# TODO: consider codegen a makefile by us
set_property(GLOBAL PROPERTY RULE_MESSAGES OFF)
...@@ -6,8 +6,7 @@ This folder contains example for Layernorm2D forward using ck_tile tile-programm ...@@ -6,8 +6,7 @@ This folder contains example for Layernorm2D forward using ck_tile tile-programm
``` ```
# in the root of ck_tile # in the root of ck_tile
mkdir build && cd build mkdir build && cd build
# you can replace <arch> with the appropriate architecture (for example gfx90a or gfx942) or leave it blank sh ../script/cmake-ck-dev.sh ../ <arch> # you can replace this <arch> to gfx90a, gfx942...
sh ../script/cmake-ck-dev.sh ../ <arch>
make tile_example_layernorm2d_fwd -j make tile_example_layernorm2d_fwd -j
``` ```
This will result in an executable `build/bin/tile_example_layernorm2d_fwd` This will result in an executable `build/bin/tile_example_layernorm2d_fwd`
...@@ -20,4 +19,4 @@ args: ...@@ -20,4 +19,4 @@ args:
-e epsilon (default:1e-5) -e epsilon (default:1e-5)
-v cpu validation or not (default:1) -v cpu validation or not (default:1)
-prec precision (default:fp16) -prec precision (default:fp16)
``` ```
\ No newline at end of file
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "layernorm2d_fwd.hpp"
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t Repeat_N_, // each thread repeat along N
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
ck_tile::index_t Vector_N_, // vector size along N
bool kPadN_,
bool kSaveMeanInvStd_,
bool kTwoPass_>
using trait_ = layernorm2d_fwd_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kSaveMeanInvStd_,
kTwoPass_>;
template <typename data_type>
float layernorm2d_fwd_b16_(layernorm2d_fwd_traits /*t*/,
layernorm2d_fwd_args a,
const ck_tile::stream_config& s)
{
#if 1
float r = -1;
// clang-format off
// rm rn tm tn vn pd mv 2p
if(a.n <= 64) {
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 128) {
if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 256) {
if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 512) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 8, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 768) {
if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 6, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1,12, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 1024) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 2, 128, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 2, 128, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 2, 128, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 1536) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 2, 128, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 1, 256, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 6, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 2048) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 8, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 3072) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 1, 128, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 6, 1, 256, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 3, 1, 1024, 1, true, false, false>>(s, a);
}
else if(a.n <= 4096) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 1, 1024, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 1024, 1, true, false, false>>(s, a);
}
else if(a.n > 4096) {
if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 8, true, false, true>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 4, true, false, true>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 1, 1024, 2, true, false, true>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 1, 1024, 1, true, false, true>>(s, a);
}
return r;
#else
return layernorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 4, true, false, false>>(s, a);
#endif
// clang-format on
}
float layernorm2d_fwd(layernorm2d_fwd_traits t,
layernorm2d_fwd_args a,
const ck_tile::stream_config& s)
{
float r = -1;
if(t.data_type.compare("fp16") == 0)
{
return layernorm2d_fwd_b16_<ck_tile::fp16_t>(t, a, s);
}
else if(t.data_type.compare("bf16") == 0)
{
return layernorm2d_fwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
throw std::runtime_error("Without supported instances!");
return r;
}
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
#if 0
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
#endif
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 2, 128, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 2, 128, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 2, 128, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 2, 128, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 128, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, false, true>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, false, true>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, false, true>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, false, true>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 12, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
#if 0
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
#endif
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 2, 128, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 2, 128, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 2, 128, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 2, 128, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 128, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 8, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 4, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 1024, 2, true, false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on
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