mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-04-19 22:39:03 +00:00
* Implement hiprtc for codegen tests
* Introduce gemm_softmax_gemm to codegen.
* Fix codegen build issues.
* Address PR comments.
* Separate ck_host lib and gemm_softmax_gemm into different PR.
* Fix cmake.
* Replace ENV variable with CMake option for toggling hipRTC in codegen
tests.
* Address PR comments.
* fix clang format
* Add missing header in magic_division.hpp
* - Workaround for hipRTC content wrapper
- Move descriptor for gemm_softmax_gemm to different branch
* Fix formatting.
* Revert "Fix formatting."
This reverts commit b5209eaef4.
* formatting fix
* fixed header guard issues
* updated header guards
* updated data_type for new types
* fixed redefinition error
* Add codegen test for batched_gemm_softmax_gemm.
Signed-off-by: Mirza Halilcevic <mirza.halilcevic@amd.com>
* formatting fix
---------
Signed-off-by: Mirza Halilcevic <mirza.halilcevic@amd.com>
Co-authored-by: Dino Musić <dino.music@htecgroup.com>
Co-authored-by: Mirza Halilcevic <mirza.halilcevic@htecgroup.com>
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
Co-authored-by: arai713 <67439843+arai713@users.noreply.github.com>
Co-authored-by: Astha Rai <astha.rai713@gmail.com>
Co-authored-by: Mirza Halilcevic <mirza.halilcevic@amd.com>
This commit is contained in:
@@ -6,134 +6,24 @@
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#include "ck/host/headers.hpp"
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#include "ck/host/stringutils.hpp"
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#include "ck/host/utils.hpp"
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#include <algorithm>
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#include <cmath>
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#include <iterator>
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#include <random>
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#include <test.hpp>
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#include "common.hpp"
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#include <rtc/compile_kernel.hpp>
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#include <rtc/hip.hpp>
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#include <test.hpp>
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#include <algorithm>
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#include <cmath>
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#include <fstream>
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#include <iterator>
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#include <random>
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using half = _Float16;
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// using half = __fp16;
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std::vector<rtc::src_file> get_headers_for_test()
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{
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std::vector<rtc::src_file> result;
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auto hs = ck::host::GetHeaders();
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std::transform(
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hs.begin(), hs.end(), std::back_inserter(result), [&](const auto& p) -> rtc::src_file {
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return {p.first, p.second};
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});
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return result;
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}
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template <class T>
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rtc::buffer<T> generate_buffer(std::size_t n, std::size_t seed = 0)
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{
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rtc::buffer<T> result(n);
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std::mt19937 gen(seed);
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std::uniform_real_distribution<double> dis(-1.0);
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std::generate(result.begin(), result.end(), [&] { return dis(gen); });
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return result;
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}
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template <class T, class U>
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bool allclose(const T& a, const U& b, double atol = 0.01, double rtol = 0.01)
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{
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return std::equal(a.begin(), a.end(), b.begin(), b.end(), [&](double x, double y) {
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return fabs(x - y) < atol + rtol * fabs(y);
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});
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}
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std::string classify(double x)
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{
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switch(std::fpclassify(x))
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{
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case FP_INFINITE: return "inf";
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case FP_NAN: return "nan";
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case FP_NORMAL: return "normal";
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case FP_SUBNORMAL: return "subnormal";
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case FP_ZERO: return "zero";
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default: return "unknown";
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}
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}
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template <class Buffer>
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void print_classification(const Buffer& x)
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{
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std::unordered_set<std::string> result;
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for(const auto& i : x)
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result.insert(classify(i));
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for(const auto& c : result)
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std::cout << c << ", ";
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std::cout << std::endl;
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}
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template <class Buffer>
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void print_statistics(const Buffer& x)
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{
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std::cout << "Min value: " << *std::min_element(x.begin(), x.end()) << ", ";
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std::cout << "Max value: " << *std::max_element(x.begin(), x.end()) << ", ";
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double num_elements = x.size();
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auto mean =
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std::accumulate(x.begin(), x.end(), double{0.0}, std::plus<double>{}) / num_elements;
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auto stddev = std::sqrt(
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std::accumulate(x.begin(),
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x.end(),
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double{0.0},
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[&](double r, double v) { return r + std::pow((v - mean), 2.0); }) /
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num_elements);
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std::cout << "Mean: " << mean << ", ";
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std::cout << "StdDev: " << stddev << "\n";
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}
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template <class Buffer>
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void print_preview(const Buffer& x)
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{
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if(x.size() <= 10)
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{
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std::for_each(x.begin(), x.end(), [&](double i) { std::cout << i << ", "; });
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}
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else
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{
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std::for_each(x.begin(), x.begin() + 5, [&](double i) { std::cout << i << ", "; });
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std::cout << "..., ";
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std::for_each(x.end() - 5, x.end(), [&](double i) { std::cout << i << ", "; });
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}
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std::cout << std::endl;
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}
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template <class T>
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struct check_all
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{
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rtc::buffer<T> data{};
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bool operator()(const rtc::buffer<T>& x)
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{
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if(data.empty())
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{
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data = x;
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return true;
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}
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if(std::any_of(x.begin(), x.end(), [](double y) { return std::isnan(y); }))
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return false;
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return allclose(data, x);
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}
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};
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template <class Solution>
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auto report(const Solution& solution, bool pass)
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{
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return test::make_predicate(solution.ToTemplateString(), [=] { return pass; });
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}
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const std::string gemm_compile_check = R"__ck__(
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#include <${include}>
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extern "C" __global__ void f(const ck::half_t* a, const ck::half_t* b, ck::half_t* c) {
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using G = ${template};
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constexpr auto desc = ${template}::make_descriptor(ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${k})),
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constexpr auto desc = G::make_descriptor(ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${k})),
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ck::make_naive_tensor_descriptor(ck::make_tuple(${n}, ${k}), ck::make_tuple(1, ${n})),
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ck::make_tuple(),
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ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${n})));
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@@ -166,15 +56,19 @@ TEST_CASE(test_problem_kernel)
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std::string epilogue = "";
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std::string prologue = "";
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for(auto solution : prob.GetSolutions("gfx90a", prologue, epilogue))
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auto solutions = prob.GetSolutions("gfx90a", prologue, epilogue);
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std::cout << "Num solutions: " << solutions.size() << std::endl;
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for(auto i = 0; i < solutions.size(); ++i)
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{
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auto src = ck::host::InterpolateString(gemm_compile_check,
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std::cout << "Testing solution " << std::to_string(i + 1) << std::endl;
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auto&& solution = solutions[i];
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auto src = ck::host::InterpolateString(gemm_compile_check,
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{{"include", prob.GetIncludeHeader()},
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{"template", solution.ToTemplateString()},
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{"m", std::to_string(prob.M)},
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{"n", std::to_string(prob.N)},
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{"k", std::to_string(prob.K)}});
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auto srcs = get_headers_for_test();
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auto srcs = get_headers_for_test();
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srcs.push_back({"main.cpp", src});
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rtc::compile_options options;
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options.kernel_name = "f";
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