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[CK-tile] remove old ck-tile transpose test (#2591)

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* remove old ck-tile transpose test

* rename test exe for consistency

* replace batched transpose regression test
This commit is contained in:
Max Podkorytov
2025-08-01 14:50:09 -07:00
committed by GitHub
parent e5b79b26fa
commit f36cb5b2aa
8 changed files with 3 additions and 478 deletions
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30
test/ck_tile/batched_transpose/CMakeLists.txt
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@@ -1,33 +1,7 @@
# Currently ck_tile is only built on gfx9
if(GPU_TARGETS MATCHES "gfx9")
function (add_batched_transpose_test TARGET_NAME MAIN_SRC)
message(DEBUG "adding ${TARGET_NAME}")
add_test_executable(${TARGET_NAME} ${MAIN_SRC} batched_transpose_api.cpp)
target_include_directories(${TARGET_NAME} PRIVATE ${CMAKE_CURRENT_LIST_DIR})
# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
list(APPEND EXAMPLE_BATCHED_TRANSPOSE_COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
# list(APPEND EXAMPLE_BATCHED_TRANSPOSE_COMPILE_OPTIONS -v --save-temps -Wno-gnu-line-marker)
target_compile_options(${TARGET_NAME} PRIVATE ${EXAMPLE_BATCHED_TRANSPOSE_COMPILE_OPTIONS})
endfunction(add_batched_transpose_test TARGET_NAME MAIN_SRC)
set(CUSTOM_TARGET_NAME test_ck_tile_batched_transpose)
add_custom_target(${CUSTOM_TARGET_NAME})
add_batched_transpose_test(test_ck_tile_batched_transpose_fp16 batched_transpose_fp16.cpp)
add_dependencies(${CUSTOM_TARGET_NAME} test_ck_tile_batched_transpose_fp16)
add_batched_transpose_test(test_ck_tile_batched_transpose_fp8 batched_transpose_fp8.cpp)
add_dependencies(${CUSTOM_TARGET_NAME} test_ck_tile_batched_transpose_fp8)
add_batched_transpose_test(test_ck_tile_batched_transpose_bf16 batched_transpose_bf16.cpp)
add_dependencies(${CUSTOM_TARGET_NAME} test_ck_tile_batched_transpose_bf16)
add_gtest_executable(test_batched_transpose test_batched_transpose.cpp)
set_property(TARGET test_batched_transpose PROPERTY CXX_STANDARD 20)
add_gtest_executable(test_ck_tile_batched_transpose test_batched_transpose.cpp)
set_property(TARGET test_ck_tile_batched_transpose PROPERTY CXX_STANDARD 20)
else()
message(DEBUG "Skipping ck_tile batched_transpose tests for current target")
endif()

25
test/ck_tile/batched_transpose/batched_transpose.hpp
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@@ -1,25 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "ck_tile/core.hpp"
#include "ck_tile/host.hpp"
#include "ck_tile/ops/reduce.hpp"
#include "ck_tile/ops/batched_transpose.hpp"
#include <vector>
#include <string>
#pragma once
struct batched_transpose_trait
{
std::string type;
std::string layout;
};
struct batched_transpose_kargs : public ck_tile::BatchedTransposeHostArgs
{
};
float batched_transpose(batched_transpose_trait t,
batched_transpose_kargs a,
ck_tile::stream_config s);

283
test/ck_tile/batched_transpose/batched_transpose.inc
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@@ -1,283 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <vector>
#include <iostream>
#include <numeric>
#include <cassert>
#include <cstdlib>
#include <iostream>
#include <time.h>
#include <unordered_set>
#include "batched_transpose.hpp"
// different threshold for different dtype
template <typename DataType>
auto get_elimit(std::string /*init_method*/)
{
double rtol = 1e-3;
double atol = 1e-3;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::bf16_t>(std::string /*init_method*/)
{
double rtol = 1e-2;
double atol = 1e-2;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::fp8_t>(std::string init_method)
{
if(init_method == "ui" || init_method == "ni")
{
unsigned max_rounding_point_distance = 0;
double atol = 2e-3;
return ck_tile::make_tuple(max_rounding_point_distance, atol);
}
else
{
unsigned max_rounding_point_distance = 1;
double atol = 0.0625;
return ck_tile::make_tuple(max_rounding_point_distance, atol);
}
}
auto create_args(int argc, char* argv[], int index = 0)
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("v", "1", "whether do CPU validation or not")
.insert("pr", "fp16", "input data type. fp16/fp32 (representing 8/16/32 bit data)")
.insert("N", "1", "input batch size. ")
.insert("C", "64", "input channel size.")
.insert("H", "18", "input height size.")
.insert("W", "64", "input width size. ")
.insert("layout_in", "NCHW", "input tensor data layout - NCHW by default")
.insert("layout_out", "NHWC", "output tensor data layout - NHWC by default ")
.insert("warmup", "50", "number of iterations before benchmark the kernel")
.insert("repeat", "100", "number of iterations to benchmark the kernel")
.insert("seed", "-1", "seed to be used, -1 means random every time")
.insert("kname", "0", "t to 1 will print kernel name");
bool result = arg_parser.parse(argc, argv, index);
return std::make_tuple(result, arg_parser);
}
template <typename Type>
bool run_batched_transpose(ck_tile::ArgParser args)
{
int validate = args.get_int("v");
std::string prec = args.get_str("pr");
int N = args.get_int("N");
int C = args.get_int("C");
int H = args.get_int("H");
int W = args.get_int("W");
int n_warmup = args.get_int("warmup");
int n_repeat = args.get_int("repeat");
std::string layout_in = args.get_str("layout_in");
std::string layout_out = args.get_str("layout_out");
int seed = args.get_int("seed");
int dim_in[4], dim_out[4];
int stride_dim_in[4], stride_dim_out[4];
bool nchw2nhwc = layout_in == "NCHW" && layout_out == "NHWC";
bool nhwc2nchw = layout_in == "NHWC" && layout_out == "NCHW";
assert(nchw2nhwc != nhwc2nchw);
(void)nhwc2nchw;
dim_in[0] = N;
dim_in[1] = nchw2nhwc ? C : H;
dim_in[2] = nchw2nhwc ? H : W;
dim_in[3] = nchw2nhwc ? W : C;
dim_out[0] = N;
dim_out[1] = nchw2nhwc ? H : C;
dim_out[2] = nchw2nhwc ? W : H;
dim_out[3] = nchw2nhwc ? C : W;
stride_dim_in[0] = C * H * W;
stride_dim_in[1] = nchw2nhwc ? H * W : C * W;
stride_dim_in[2] = nchw2nhwc ? W : C;
stride_dim_in[3] = 1;
stride_dim_out[0] = C * H * W;
stride_dim_out[1] = nchw2nhwc ? C * W : H * W;
stride_dim_out[2] = nchw2nhwc ? C : W;
stride_dim_out[3] = 1;
if(seed < 0)
{
seed = std::time(nullptr);
}
ck_tile::HostTensor<Type> x_host(
{dim_in[0], dim_in[1], dim_in[2], dim_in[3]},
{stride_dim_in[0], stride_dim_in[1], stride_dim_in[2], stride_dim_in[3]});
ck_tile::HostTensor<Type> y_host(
{dim_out[0], dim_out[1], dim_out[2], dim_out[3]},
{stride_dim_out[0], stride_dim_out[1], stride_dim_out[2], stride_dim_out[3]});
ck_tile::FillUniformDistribution<Type>{-.5f, .5f}(x_host);
ck_tile::DeviceMem x_dev(x_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem y_dev(y_host.get_element_space_size_in_bytes());
x_dev.ToDevice(x_host.data());
auto trait = batched_transpose_trait{prec, layout_in};
uint32_t height = nchw2nhwc ? C : H * W;
uint32_t width = nchw2nhwc ? H * W : C;
batched_transpose_kargs karg = [&]() {
batched_transpose_kargs a_;
a_.p_input = x_dev.GetDeviceBuffer();
a_.p_output = y_dev.GetDeviceBuffer();
a_.batch = N;
a_.height = height;
a_.width = width;
return a_;
}();
ck_tile::stream_config sc{nullptr, true, n_warmup, n_repeat};
auto ms = batched_transpose(trait, karg, sc);
std::size_t num_operations = N * C * H * (W - 1);
std::size_t num_bytes = N * C * H * W * sizeof(Type);
float ave_time = ms * 1E-3;
float gb_per_sec = num_bytes / ms * 1.E-6;
float tflops = static_cast<float>(num_operations) / ms * 1.E-6;
std::cout << "Run Batched Transpose kernel with N=" << N << ", C=" << C << ", H=" << H
<< ", W=" << W << ", layout_in=" << layout_in << ", layout_out=" << layout_out
<< " : " << ms << " ms (" << ave_time << " ave_time), " << tflops << " TFlops"
<< gb_per_sec << " GB/s, " << std::endl;
printf("[%s]N:%d, C:%d, H:%d, W:%d, layout_in:%s, %f\n",
prec.c_str(),
N,
C,
H,
W,
layout_in.c_str(),
ms);
if(ms < 0)
printf("------------------------------------not "
"supported-------------------------------------\n");
fflush(stdout);
if(ms < 0)
{
return false;
}
y_dev.FromDevice(y_host.data());
bool rtn = true;
if(validate)
{
// this host buffer will not copy to GPU, so no need use stride
ck_tile::HostTensor<Type> y_ref(
{dim_out[0], dim_out[1], dim_out[2], dim_out[3]},
{stride_dim_out[0], stride_dim_out[1], stride_dim_out[2], stride_dim_out[3]});
ck_tile::reference_batched_transpose<Type>(x_host, y_ref, layout_in, layout_out);
auto [rtol, atol] = get_elimit<Type>("");
rtn &= ck_tile::check_err(
y_host, y_ref, std::string("y Error: Incorrect results!"), rtol, atol);
}
printf("-----------------------------------------------------------------------valid:%s--------"
"--------------------------------------------------------------------\n",
rtn ? "y" : "n");
fflush(stdout);
return rtn;
}
template <typename PrecType>
bool run_test_case(int argc, char** argv)
{
auto [result, args] = create_args(argc, argv);
if(!result)
return false;
return run_batched_transpose<PrecType>(args);
}
template <typename PrecType>
bool run_test_cases(std::vector<std::vector<std::string>>& test_cases)
{
bool valid = true;
for(std::size_t test_idx = 0; test_idx < test_cases.size(); ++test_idx)
{
constexpr int num_args = 7;
char* argv[num_args];
assert(test_cases[test_idx].size() == num_args &&
"invalid number of arguments in test case");
for(std::size_t idx = 0; idx < test_cases[test_idx].size(); ++idx)
{
argv[idx] = test_cases[test_idx][idx].data();
}
valid = valid && run_test_case<PrecType>(num_args, argv);
if(!valid)
break;
}
return valid;
}
std::vector<std::vector<std::string>> generate_test_cases(const std::string prec)
{
return {
{"-pr=" + prec, "-N=1", "-C=32", "-H=1", "-W=32", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=1", "-C=64", "-H=1", "-W=64", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=2", "-C=12", "-H=1", "-W=32", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec, "-N=3", "-C=1334", "-H=1", "-W=37", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec, "-N=4", "-C=27", "-H=1", "-W=32", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=5", "-C=1234", "-H=1", "-W=12", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=1", "-C=1", "-H=1", "-W=1", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=1", "-C=1", "-H=1", "-W=1", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec,
"-N=128",
"-C=1024",
"-H=64",
"-W=64",
"-layout_in=NCHW",
"-layout_out=NHWC"},
{"-pr=" + prec,
"-N=128",
"-C=1024",
"-H=64",
"-W=64",
"-layout_in=NHWC",
"-layout_out=NCHW"},
{"-pr=" + prec, "-N=16", "-C=64", "-H=32", "-W=128", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=16", "-C=64", "-H=128", "-W=32", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec, "-N=1", "-C=2048", "-H=1", "-W=1", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=1", "-C=2048", "-H=1", "-W=1", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec,
"-N=1",
"-C=1",
"-H=1024",
"-W=1024",
"-layout_in=NCHW",
"-layout_out=NHWC"},
{"-pr=" + prec,
"-N=1",
"-C=1",
"-H=1024",
"-W=1024",
"-layout_in=NHWC",
"-layout_out=NCHW"},
{"-pr=" + prec, "-N=8", "-C=16", "-H=8", "-W=16", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=8", "-C=16", "-H=8", "-W=16", "-layout_in=NHWC", "-layout_out=NCHW"},
{"-pr=" + prec, "-N=1", "-C=64", "-H=1", "-W=1024", "-layout_in=NCHW", "-layout_out=NHWC"},
{"-pr=" + prec, "-N=1", "-C=64", "-H=1024", "-W=1", "-layout_in=NHWC", "-layout_out=NCHW"}};
}

109
test/ck_tile/batched_transpose/batched_transpose_api.cpp
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@@ -1,109 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "batched_transpose.hpp"
template <typename ts_type,
ck_tile::index_t block_x,
ck_tile::index_t block_y,
ck_tile::index_t warp_x,
ck_tile::index_t warp_y,
bool kPadM,
bool kPadN>
float batched_transpose_dispatch(batched_transpose_kargs& a, ck_tile::stream_config& s)
{
uint32_t dim_stride = a.height * a.width;
a.dim_stride = dim_stride;
a.dim_block_h = block_y;
a.dim_block_w = block_x;
using block_tile = ck_tile::sequence<block_x, block_y>;
using warp_layout = ck_tile::sequence<warp_x, warp_y>;
using ts_problem =
ck_tile::BatchedTransposeProblem<ts_type, block_tile, warp_layout, kPadM, kPadN>;
using ts_pipeline = ck_tile::BatchedTransposePipeline<ts_problem>;
using kernel = ck_tile::BatchedTransposeKernel<ts_pipeline>;
auto kargs = kernel::MakeKargs(a);
const dim3 grids = kernel::GridSize(a);
constexpr dim3 blocks = kernel::BlockSize();
printf("Grid: %u %u %u\n", grids.x, grids.y, grids.z);
printf("Block: %u %u %u\n", blocks.x, blocks.y, blocks.z);
printf("kargs: kargs.batch %d kargs.height %d kargs.width %d kargs.dim_strid %d\n",
kargs.batch,
kargs.height,
kargs.width,
kargs.dim_stride);
printf("Launching Kernel...\n");
float ave_time = ck_tile::launch_kernel(
s, ck_tile::make_kernel<blocks.x, 1>(kernel{}, grids, blocks, 0, kargs));
printf("Kernel finished...\n");
return ave_time;
}
// Param Comb: type_size, block_x & y, warp_x & y, thread_x & y
#define FOREACH_TRANSPOSE_PARAM(F) \
F(fp8, ck_tile::fp8_t, 64, 64, 1, 1, true, true) \
F(fp8, ck_tile::fp8_t, 64, 64, 1, 1, false, false) \
F(fp16, ck_tile::fp16_t, 64, 64, 1, 1, true, true) \
F(fp16, ck_tile::fp16_t, 64, 64, 1, 1, false, false) \
F(bf16, ck_tile::bf16_t, 64, 64, 1, 1, true, true) \
F(bf16, ck_tile::bf16_t, 64, 64, 1, 1, false, false)
// Macro that defines one static function per line
#define GEN_TRANSPOSE_FN(SHORT_NAME, REAL_TYPE, BX, BY, WX, WY, PADM, PADN) \
static float transpose_fn_##SHORT_NAME##_##BX##_##BY##_##WX##_##WY##_##PADM##_##PADN( \
batched_transpose_kargs& a, ck_tile::stream_config& s) \
{ \
return batched_transpose_dispatch<REAL_TYPE, BX, BY, WX, WY, PADM, PADN>(a, s); \
}
FOREACH_TRANSPOSE_PARAM(GEN_TRANSPOSE_FN)
float batched_transpose(batched_transpose_trait t,
batched_transpose_kargs a,
ck_tile::stream_config s)
{
if(t.type == "fp8")
{
if(a.height % 64 == 0 && a.width % 64 == 0)
{
return transpose_fn_fp8_64_64_1_1_false_false(a, s);
}
else
{
return transpose_fn_fp8_64_64_1_1_true_true(a, s);
}
}
else if(t.type == "fp16")
{
if(a.height % 64 == 0 && a.width % 64 == 0)
{
return transpose_fn_fp16_64_64_1_1_false_false(a, s);
}
else
{
return transpose_fn_fp16_64_64_1_1_true_true(a, s);
}
}
else if(t.type == "bf16")
{
if(a.height % 64 == 0 && a.width % 64 == 0)
{
return transpose_fn_bf16_64_64_1_1_false_false(a, s);
}
else
{
return transpose_fn_bf16_64_64_1_1_true_true(a, s);
}
}
return -1;
}

10
test/ck_tile/batched_transpose/batched_transpose_bf16.cpp
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@@ -1,10 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "batched_transpose.inc"
int main()
{
std::vector<std::vector<std::string>> test_cases = generate_test_cases("bf16");
return !run_test_cases<ck_tile::bf16_t>(test_cases);
}

10
test/ck_tile/batched_transpose/batched_transpose_fp16.cpp
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@@ -1,10 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "batched_transpose.inc"
int main()
{
std::vector<std::vector<std::string>> test_cases = generate_test_cases("fp16");
return !run_test_cases<ck_tile::fp16_t>(test_cases);
}

10
test/ck_tile/batched_transpose/batched_transpose_fp8.cpp
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@@ -1,10 +0,0 @@
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "batched_transpose.inc"
int main()
{
std::vector<std::vector<std::string>> test_cases = generate_test_cases("fp8");
return !run_test_cases<ck_tile::fp8_t>(test_cases);
}