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dummycoderfe
2024-10-27 15:05:52 +00:00
parent 5c9cba82a8
commit 7db609fe32
18 changed files with 579 additions and 47 deletions
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4
CMakeLists.txt
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@@ -495,10 +495,6 @@ include_directories(BEFORE
)
SET(BUILD_DEV ON CACHE BOOL "BUILD_DEV")
if(BUILD_DEV)
add_compile_options(-Werror)
add_compile_options(-Weverything)
endif()
message("CMAKE_CXX_FLAGS: ${CMAKE_CXX_FLAGS}")
if("${CMAKE_CXX_COMPILER_ID}" MATCHES "Clang")

1
cmake/EnableCompilerWarnings.cmake
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@@ -66,7 +66,6 @@ else()
-Wunreachable-code
-Wunused
-Wno-reserved-identifier
-Werror
-Wno-option-ignored
-Wsign-compare
-Wno-extra-semi-stmt

21
example/ck_tile/06_layernorm2d_bwd/CMakeLists.txt Normal file
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@@ -0,0 +1,21 @@
set(EXAMPLE_LAYERNORM2D_BWD "tile_example_layernorm2d_bwd")
# 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"
message("adding example ${EXAMPLE_LAYERNORM2D_BWD}")
file(GLOB INSTANCE_SRCS instances/*.cpp)
add_executable(${EXAMPLE_LAYERNORM2D_BWD} EXCLUDE_FROM_ALL layernorm2d_bwd.cpp)
target_include_directories(${EXAMPLE_LAYERNORM2D_BWD} PRIVATE ${CMAKE_CURRENT_LIST_DIR})
target_sources(${EXAMPLE_LAYERNORM2D_BWD} PRIVATE ${INSTANCE_SRCS})
set(EXAMPLE_layernorm2d_bwd_COMPILE_OPTIONS)
# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
list(APPEND EXAMPLE_layernorm2d_bwd_COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
target_compile_options(${EXAMPLE_LAYERNORM2D_BWD} PRIVATE ${EXAMPLE_layernorm2d_bwd_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)

22
example/ck_tile/06_layernorm2d_bwd/README.md Normal file
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@@ -0,0 +1,22 @@
# Layernorm2D forward
This folder contains example for Layernorm2D forward using ck_tile tile-programming implementation.
## build
```
# in the root of ck_tile
mkdir build && cd build
sh ../script/cmake-ck-dev.sh ../ <arch> # you can replace this <arch> to gfx90a, gfx942...
make tile_example_layernorm2d_bwd -j
```
This will result in an executable `build/bin/tile_example_layernorm2d_bwd`
## example
```
args:
-m m dimension (default:3328)
-n m dimension (default:4096)
-e epsilon (default:1e-5)
-v cpu validation or not (default:1)
-prec precision (default:fp16)
```

44
example/ck_tile/06_layernorm2d_bwd/instances/layernorm2d_bwd_api.cpp Normal file
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@@ -0,0 +1,44 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "layernorm2d_bwd.hpp"
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
bool kPadN_>
using trait_ = layernorm2d_bwd_traits_<DataType_,
Repeat_M_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
kPadN_>;
template <typename data_type>
float layernorm2d_bwd_b16_(layernorm2d_bwd_traits /*t*/,
layernorm2d_bwd_args a,
const ck_tile::stream_config& s)
{
return layernorm2d_bwd_<trait_<data_type, 1, 1, 64, true>>(s, a);
}
float layernorm2d_bwd(layernorm2d_bwd_traits t,
layernorm2d_bwd_args a,
const ck_tile::stream_config& s)
{
float r = -1;
if(t.data_type.compare("fp16") == 0)
{
return layernorm2d_bwd_b16_<ck_tile::fp16_t>(t, a, s);
}
else if(t.data_type.compare("bf16") == 0)
{
return layernorm2d_bwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
throw std::runtime_error("Without supported instances!");
return r;
}

11
example/ck_tile/06_layernorm2d_bwd/instances/layernorm2d_bwd_bf16_n64_n128_instance.cpp Normal file
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@@ -0,0 +1,11 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_bwd_instance_common.hpp"
// clang-format off
// rm tm tn pd
template float layernorm2d_bwd_<trait_<ck_tile::bf16_t, 1, 1, 64, true>>(const S&, A);
template float layernorm2d_bwd_<trait_<ck_tile::fp16_t, 1, 1, 64, true>>(const S&, A);
// clang-format on

55
example/ck_tile/06_layernorm2d_bwd/instances/layernorm2d_bwd_instance_common.hpp Normal file
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@@ -0,0 +1,55 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "layernorm2d_bwd.hpp"
#include <iostream>
#pragma once
using S = ck_tile::stream_config;
using A = layernorm2d_bwd_args;
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
bool kPadN_>
using trait_ = layernorm2d_bwd_traits_<DataType_,
Repeat_M_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
kPadN_>;
template <typename Traits_>
float layernorm2d_bwd_(const S& s, A a)
{
using DataType = typename Traits_::DataType;
using PipelineProblem = ck_tile::Layernorm2dBwdGammaBetaPipelineProblem<
typename LayerNormTypeConfig<DataType>::XDataType,
typename LayerNormTypeConfig<DataType>::GammaDataType,
typename LayerNormTypeConfig<DataType>::BetaDataType,
typename LayerNormTypeConfig<DataType>::ComputeDataType,
typename LayerNormTypeConfig<DataType>::YDataType,
typename LayerNormTypeConfig<DataType>::MeanDataType,
typename LayerNormTypeConfig<DataType>::InvStdDataType,
typename Traits_::Shape,
Traits_::kPadN>;
using Pipeline = ck_tile::Layernorm2dBwdGammaBetaPipeline<PipelineProblem>;
using Kernel = ck_tile::Layernorm2dBwdGammaBeta<Pipeline>;
const dim3 grids = Kernel::GridSize(a);
constexpr dim3 blocks = Kernel::BlockSize();
constexpr ck_tile::index_t kBlockPerCu = 1;
auto kargs = Kernel::MakeKargs(a);
if(s.log_level_ > 0)
std::cout << ", " << Kernel::GetName() << std::flush;
return ck_tile::launch_kernel(
s, ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
}

179
example/ck_tile/06_layernorm2d_bwd/layernorm2d_bwd.cpp Normal file
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@@ -0,0 +1,179 @@
#include "ck_tile/host.hpp"
#include "layernorm2d_bwd.hpp"
#include <cstring>
// different threshold for different dtype
template <typename DataType>
auto get_elimit()
{
double rtol = 1e-2;
double atol = 1e-2;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::bf16_t>()
{
double rtol = 1e-2;
double atol = 1e-2;
return ck_tile::make_tuple(rtol, atol);
}
auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("m", "3328", "m dimension")
.insert("n", "4096", "n dimension")
.insert("stride", "-1", "stride per row, if -1 then equal to n")
.insert("v", "1", "cpu validation or not")
.insert("kname", "1", "print kernel name or not")
.insert("prec", "fp16", "precision")
.insert("warmup", "5", "cold iter")
.insert("repeat", "20", "hot iter");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
template <typename DataType>
bool run(const ck_tile::ArgParser& arg_parser)
{
ck_tile::index_t m = arg_parser.get_int("m");
ck_tile::index_t n = arg_parser.get_int("n");
ck_tile::index_t stride = arg_parser.get_int("stride");
if(stride < 0)
stride = n;
std::string data_type = arg_parser.get_str("prec");
int kname = arg_parser.get_int("kname");
int do_validation = arg_parser.get_int("v");
int warmup = arg_parser.get_int("warmup");
int repeat = arg_parser.get_int("repeat");
assert(stride >= n);
using TypeConfig = LayerNormTypeConfig<DataType>;
using XDataType = typename TypeConfig::XDataType;
using YDataType = typename TypeConfig::YDataType;
using GammaDataType = typename TypeConfig::GammaDataType;
using BetaDataType = typename TypeConfig::BetaDataType;
using MeanDataType = typename TypeConfig::MeanDataType;
using InvStdDataType = typename TypeConfig::InvStdDataType;
using ComputeDataType = typename TypeConfig::ComputeDataType;
// host verify
ck_tile::HostTensor<YDataType> dy_host({m, n}, {stride, 1});
ck_tile::HostTensor<MeanDataType> mean_host({m});
ck_tile::HostTensor<InvStdDataType> invStd_host({m});
ck_tile::HostTensor<GammaDataType> dgamma_host_dev({n});
ck_tile::HostTensor<BetaDataType> dbeta_host_dev({n});
ck_tile::HostTensor<GammaDataType> dgamma_host_ref({n});
ck_tile::HostTensor<BetaDataType> dbeta_host_ref({n});
ck_tile::FillUniformDistribution<YDataType>{-.5f, .5f}(dy_host);
// ck_tile::FillUniformDistribution<MeanDataType>{-.5f, .5f}(mean_host);
ck_tile::FillMonotonicSeq<MeanDataType>{}(mean_host);
ck_tile::FillUniformDistribution<InvStdDataType>{-.5f, .5f}(invStd_host);
ck_tile::DeviceMem dy_buf(dy_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem mean_buf(mean_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem invStd_buf(invStd_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem dgamma_buf(dgamma_host_dev.get_element_space_size_in_bytes());
ck_tile::DeviceMem dbeta_buf(dbeta_host_dev.get_element_space_size_in_bytes());
dy_buf.ToDevice(dy_host.data());
mean_buf.ToDevice(mean_host.data());
invStd_buf.ToDevice(invStd_host.data());
std::cout << "[" << data_type << "]"
<< " m:" << m << ", n:" << n << ", stride:" << stride << std::flush;
layernorm2d_bwd_traits traits{data_type};
layernorm2d_bwd_args args{dy_buf.GetDeviceBuffer(),
mean_buf.GetDeviceBuffer(),
invStd_buf.GetDeviceBuffer(),
dgamma_buf.GetDeviceBuffer(),
dbeta_buf.GetDeviceBuffer(),
nullptr,
m,
n,
stride};
float ave_time = layernorm2d_bwd(
traits, args, ck_tile::stream_config{nullptr, true, kname ? 1 : 0, warmup, repeat});
std::size_t num_byte = sizeof(XDataType) * m * n + sizeof(GammaDataType) * n +
sizeof(BetaDataType) * n + sizeof(YDataType) * m * n;
float gb_per_sec = num_byte / 1.E6 / ave_time;
std::cout << sizeof(ComputeDataType) << ", " << ave_time * 1.E3 << " us, " << gb_per_sec << " GB/s" << std::flush;
bool pass = true;
if(do_validation)
{
// // reference
// ck_tile::reference_layernorm2d_bwd<XDataType,
// GammaDataType,
// BetaDataType,
// ComputeDataType,
// YDataType,
// MeanDataType,
// InvStdDataType>(
// x_host, gamma_host, beta_host, y_host_ref, mean_host_ref, invStd_host_ref, epsilon);
// y_buf.FromDevice(y_host_dev.data());
// auto [rtol, atol] = get_elimit<DataType>();
// if(stride == n)
// {
// pass = ck_tile::check_err(
// y_host_dev, y_host_ref, std::string("OUT Error: Incorrect results!"), rtol, atol);
// }
// else
// {
// for(int i_r = 0; i_r < m; i_r++)
// {
// std::vector<YDataType> y_host_dev_row(y_host_dev.begin() + i_r * stride,
// y_host_dev.begin() + i_r * stride + n);
// std::vector<YDataType> y_host_ref_row(y_host_ref.begin() + i_r * stride,
// y_host_ref.begin() + i_r * stride + n);
// pass &= ck_tile::check_err(y_host_dev_row,
// y_host_ref_row,
// std::string("OUT[") + std::to_string(i_r) +
// std::string("] Error: Incorrect results!"),
// rtol,
// atol);
// }
// }
std::cout << ", valid:" << (pass ? "y" : "n") << std::flush << std::endl;
}
return pass;
}
int main(int argc, char* argv[])
{
auto [result, arg_parser] = create_args(argc, argv);
if(!result)
return -1;
const std::string data_type = arg_parser.get_str("prec");
if(data_type == "fp16")
{
return run<ck_tile::half_t>(arg_parser) ? 0 : -2;
}
else if(data_type == "bf16")
{
return run<ck_tile::bf16_t>(arg_parser) ? 0 : -2;
}
return -3;
}

113
example/ck_tile/06_layernorm2d_bwd/layernorm2d_bwd.hpp Normal file
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@@ -0,0 +1,113 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/layernorm2d.hpp"
#include <string>
template <typename DataType>
struct LayerNormTypeConfig;
template <>
struct LayerNormTypeConfig<ck_tile::half_t>
{
using XDataType = ck_tile::half_t;
using YDataType = ck_tile::half_t;
using GammaDataType = ck_tile::half_t;
using BetaDataType = ck_tile::half_t;
using MeanDataType = ck_tile::half_t;
using InvStdDataType = ck_tile::half_t;
using ComputeDataType = float;
};
template <>
struct LayerNormTypeConfig<ck_tile::bf16_t>
{
using XDataType = ck_tile::bf16_t;
using YDataType = ck_tile::bf16_t;
using GammaDataType = ck_tile::bf16_t;
using BetaDataType = ck_tile::bf16_t;
using MeanDataType = ck_tile::bf16_t;
using InvStdDataType = ck_tile::bf16_t;
using ComputeDataType = float;
};
// runtime args
struct layernorm2d_bwd_args : public ck_tile::Layernorm2dBwdGammaBetaHostArgs
{
};
// this is used to pattern-match internl kernel implementation, not to instantiate kernel
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
bool kPadN_>
struct layernorm2d_bwd_traits_
{
using DataType = ck_tile::remove_cvref_t<DataType_>;
static constexpr bool is_warp_per_row = ThreadPerBlock_N_ <= warpSize;
static_assert((ThreadPerBlock_M_ * ThreadPerBlock_N_) % warpSize == 0);
static constexpr ck_tile::index_t total_warps =
(ThreadPerBlock_M_ * ThreadPerBlock_N_) / warpSize;
// num of warps along m
static constexpr ck_tile::index_t BlockWarps_M = []() {
if constexpr(is_warp_per_row)
{
static_assert(warpSize % ThreadPerBlock_N_ == 0);
return total_warps * (warpSize / ThreadPerBlock_N_);
}
else
{
// static_assert(warpSize % ThreadPerBlock_M_ == 0);
return total_warps / (ThreadPerBlock_N_ / warpSize);
}
}();
// num of warps along n
static constexpr ck_tile::index_t BlockWarps_N = []() {
if constexpr(is_warp_per_row)
{
static_assert(warpSize % ThreadPerBlock_N_ == 0);
return 1;
}
else
{
static_assert(ThreadPerBlock_N_ % warpSize == 0);
return ThreadPerBlock_N_ / warpSize;
}
}();
static constexpr ck_tile::index_t Repeat_M = Repeat_M_;
static constexpr ck_tile::index_t Block_M = Repeat_M_ * ThreadPerBlock_M_;
static constexpr ck_tile::index_t Block_N = ThreadPerBlock_N_;
static constexpr ck_tile::index_t Warp_M = ThreadPerBlock_M_ / BlockWarps_M;
static constexpr ck_tile::index_t Warp_N = ThreadPerBlock_N_ / BlockWarps_N;
using BlockTile = ck_tile::sequence<Block_M, Block_N>;
using BlockWarps = ck_tile::sequence<BlockWarps_M, BlockWarps_N>;
using WarpTile = ck_tile::sequence<Warp_M, Warp_N>;
using Vector = ck_tile::sequence<1, 1>;
using Shape = ck_tile::Layernorm2dShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
};
template <typename Traits_>
float layernorm2d_bwd_(const ck_tile::stream_config& s, layernorm2d_bwd_args a);
// This is the public API, will be generated by script
struct layernorm2d_bwd_traits
{
std::string data_type;
};
float layernorm2d_bwd(layernorm2d_bwd_traits, layernorm2d_bwd_args, const ck_tile::stream_config&);

38
example/ck_tile/06_layernorm2d_bwd/script/perf_test.sh Executable file
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@@ -0,0 +1,38 @@
# run from top of ck folder
EXE=build/bin/tile_example_layernorm2d_bwd
$EXE -m=1 -n=1 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=128 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=144 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=168 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=184 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=256 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=288 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=344 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=376 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=448 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=512 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=924 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1024 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1078 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1996 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=4080 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=128 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=144 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=168 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=184 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=256 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=288 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=344 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=376 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=448 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=512 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=924 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1024 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1078 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1996 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=4080 -e=1e-12 -v=1 -prec=fp16 -repeat=1000

31
example/ck_tile/06_layernorm2d_bwd/script/smoke_test.sh Executable file
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@@ -0,0 +1,31 @@
#!/bin/sh
# call from top of CK folder
EXE=./build/bin/tile_example_layernorm2d_bwd
for pr_i in "fp16" "bf16" ; do
$EXE -prec=$pr_i -m=99 -n=13
$EXE -prec=$pr_i -m=17 -n=16
$EXE -prec=$pr_i -m=1 -n=100
$EXE -prec=$pr_i -m=4 -n=128
$EXE -prec=$pr_i -m=80 -n=127
$EXE -prec=$pr_i -m=22 -n=255 -stride=256
$EXE -prec=$pr_i -m=7 -n=599
$EXE -prec=$pr_i -m=19 -n=512
$EXE -prec=$pr_i -m=33 -n=313 -stride=1000
$EXE -prec=$pr_i -m=11 -n=510
$EXE -prec=$pr_i -m=171 -n=676 -stride=818
$EXE -prec=$pr_i -m=91 -n=636
$EXE -prec=$pr_i -m=12 -n=768 -stride=800
$EXE -prec=$pr_i -m=100 -n=766 -stride=812
$EXE -prec=$pr_i -m=31 -n=1024
$EXE -prec=$pr_i -m=64 -n=1000 -stride=1004
$EXE -prec=$pr_i -m=8 -n=1501
$EXE -prec=$pr_i -m=3 -n=1826
$EXE -prec=$pr_i -m=5 -n=2040
$EXE -prec=$pr_i -m=7 -n=2734
$EXE -prec=$pr_i -m=1 -n=3182
$EXE -prec=$pr_i -m=9 -n=4096
$EXE -prec=$pr_i -m=3 -n=8192
$EXE -prec=$pr_i -m=1 -n=10547
$EXE -prec=$pr_i -m=3 -n=17134
done

1
example/ck_tile/CMakeLists.txt
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@@ -7,3 +7,4 @@ add_subdirectory(02_layernorm2d)
add_subdirectory(03_gemm)
add_subdirectory(04_img2col)
add_subdirectory(05_reduce)
add_subdirectory(06_layernorm2d_bwd)

7
include/ck_tile/ops/layernorm2d.hpp
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@@ -9,4 +9,11 @@
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_one_pass.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_problem.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_two_pass.hpp"
#include "ck_tile/ops/layernorm2d/kernel/layernorm2d_bwd_gamma_beta_kernel.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_default_policy.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_gamma_beta.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_problem.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"

6
include/ck_tile/ops/layernorm2d/kernel/layernorm2d_bwd_gamma_beta_kernel.hpp
View File

@@ -104,15 +104,13 @@ struct Layernorm2dBwdGammaBeta
auto surfix = [&] () {
std::string n;
if (kPadN) n += "_pn";
if (kSaveMeanInvStd) n += "_mv";
if (kTwoPass) n += "_2p";
return n; }();
#define _SS_ std::string
#define _TS_ std::to_string
return _SS_("layernorm2d_fwd_") + _SS_(t2s<XDataType>::name) + "_" +
return _SS_("layernorm2d_bwd_") + _SS_(t2s<XDataType>::name) + "_" +
_TS_(S_::Block_M) + "x" + _TS_(S_::Block_N) + "_" + _TS_(S_::WarpPerBlock_M) + "x" + _TS_(S_::WarpPerBlock_N) + "_" +
_TS_(S_::Warp_M) + "x" + _TS_(S_::Warp_N) + "_" + _TS_(S_::Vector_M) + "x" + _TS_(S_::Vector_N) + "_" +
_TS_(S_::Warp_M) + "x" + _TS_(S_::Warp_N) + "_" + _TS_(S_::Vector_M) + "x" + _TS_(1) + "_" +
_SS_(Pipeline::name) + surfix;
#undef _SS_
#undef _TS_

16
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_default_policy.hpp
View File

@@ -4,8 +4,6 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/welford/block/block_welford_problem.hpp"
#include "ck_tile/ops/welford/block/block_welford.hpp"
namespace ck_tile {
@@ -41,6 +39,20 @@ struct Layernorm2dBwdGammaBetaPipelineDefaultPolicy
sequence<0>>{});
}
// template <typename Problem>
// CK_TILE_DEVICE static constexpr auto MakeGammaBetaBlockTileDistribution()
// {
// using S = typename Problem::BlockShape;
// return make_static_tile_distribution(
// tile_distribution_encoding<
// sequence<S::Repeat_M, S::WarpPerBlock_M, S::ThreadPerWarp_M>,
// tuple<sequence<S::WarpPerBlock_N, S::ThreadPerWarp_N>>,
// tuple<sequence<0, 1>, sequence<0, 1>>,
// tuple<sequence<1, 0>, sequence<2, 1>>,
// sequence<0>,
// sequence<0>>{});
// }
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{

44
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_gamma_beta.hpp → include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_gamma_beta.hpp
View File

@@ -4,7 +4,7 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_default_policy.hpp"
#include "ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_default_policy.hpp"
#include <string>
#include <type_traits>
@@ -28,14 +28,32 @@ struct Layernorm2dBwdGammaBetaPipeline
static constexpr bool kPadN = Problem::kPadN;
static constexpr const char* name = []() {
return "bwd_gamma_beta"
return "bwd_gamma_beta";
}();
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
// template <typename DumpTensor_>
// CK_TILE_DEVICE void dump(const DumpTensor_& x) const
// {
// constexpr auto I0 = number<0>{};
// constexpr auto I1 = number<1>{};
// constexpr auto spans = DumpTensor_::get_distributed_spans();
// sweep_tile_span(spans[I1], [&](auto i1) {
// sweep_tile_span(spans[I0], [&](auto i0) {
// constexpr auto in_dstr_idx = make_tuple(i0, i1);
// auto v = ck_tile::type_convert<float>(x[in_dstr_idx]);
// index_t tid =
// (threadIdx.z * (blockDim.x * blockDim.y)) + (threadIdx.y * blockDim.x) + threadIdx.x;
// printf("%d %f\n", tid, v);
// });
// });
// }
template <typename DYWindow,
typename MeanWindow,
typename InvStdWindow,
@@ -49,10 +67,12 @@ struct Layernorm2dBwdGammaBetaPipeline
ck_tile::index_t row_size,
void* smem) const
{
const auto dy_window =
make_tile_window(dy_window_, Policy::template MakeDyBlockTileDistribution<Problem>());
const auto dy_window = make_tile_window(dy_window_,
Policy::template MakeDyBlockTileDistribution<Problem>());
const auto mean_window = make_tile_window(
mean_window_, Policy::template MakeMeanBlockTileDistribution<Problem>());
const auto inv_std_window = make_tile_window(
inv_std_window_, Policy::template MakeMeanBlockTileDistribution<Problem>());
// const auto gamma_window = make_tile_window(
// gamma_window_, Policy::template MakeGammaBetaBlockTileDistribution<Problem>());
// const auto beta_window = make_tile_window(
@@ -60,7 +80,23 @@ struct Layernorm2dBwdGammaBetaPipeline
const auto dy = load_tile(dy_window);
const auto mean = load_tile(mean_window);
const auto inv_std = load_tile(inv_std_window);
// auto y = make_static_distributed_tensor<YDataType>(dy.get_tile_distribution());
sweep_tile(mean, [&](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
// constexpr auto j_idx = make_tuple(idx[number<1>{}]);
index_t tid = (threadIdx.y * blockDim.x) + threadIdx.x;
const auto m = type_convert<float>(mean[i_idx]);
if(blockIdx.x == 0 && blockIdx.y == 0)
printf("%d %f\n", tid, m);
});
// dump(dy);
// dump(mean);
// dump(inv_std);
*reinterpret_cast<char *>(smem) = row_size;
// layernorm computation
// auto y = make_static_distributed_tensor<YDataType>(x.get_tile_distribution());

4
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_bwd_pipeline_problem.hpp
View File

@@ -15,9 +15,7 @@ template <typename XDataType_,
typename MeanDataType_,
typename InvStdDataType_,
typename BlockShape_,
bool kPadN_,
bool kSaveMeanInvStd_,
bool kTwoPass_>
bool kPadN_>
struct Layernorm2dBwdGammaBetaPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;

29
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_problem.hpp
View File

@@ -37,33 +37,4 @@ struct Layernorm2dFwdPipelineProblem
static constexpr bool kTwoPass = kTwoPass_;
};
template <typename XDataType_,
typename GammaDataType_,
typename BetaDataType_,
typename ComputeDataType_,
typename YDataType_,
typename MeanDataType_,
typename InvStdDataType_,
typename BlockShape_,
bool kPadN_,
bool kSaveMeanInvStd_,
bool kTwoPass_>
struct Layernorm2dFwdPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using BetaDataType = remove_cvref_t<BetaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using MeanDataType = remove_cvref_t<MeanDataType_>;
using InvStdDataType = remove_cvref_t<InvStdDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveMeanInvStd = kSaveMeanInvStd_;
static constexpr bool kTwoPass = kTwoPass_;
};
} // namespace ck_tile