mirror of
https://github.com/ROCm/composable_kernel.git
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155 lines
4.2 KiB
C++
155 lines
4.2 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include "ck/host/headers.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 <iterator>
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#include <numeric>
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#include <random>
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#include <unordered_set>
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inline std::vector<rtc::src_file> create_headers_for_test()
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{
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auto ck_headers = ck::host::GetHeaders();
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std::vector<rtc::src_file> result;
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std::transform(ck_headers.begin(), ck_headers.end(), std::back_inserter(result), [](auto& p) {
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std::string content;
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content.reserve(p.second.size() + 1);
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content.push_back(' '); // We need a whitespace before the content for hipRTC to work
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content.append(p.second.data(), p.second.size());
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return rtc::src_file{p.first, std::move(content)};
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});
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return result;
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}
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inline const std::vector<rtc::src_file>& get_headers_for_test()
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{
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static const std::vector<rtc::src_file> headers = create_headers_for_test();
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return headers;
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}
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template <typename V>
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std::size_t GetSize(V mLens, V mStrides)
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{
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std::size_t space = 1;
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for(std::size_t i = 0; i < mLens.Size(); ++i)
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{
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if(mLens[i] == 0)
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continue;
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space += (mLens[i] - 1) * mStrides[i];
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}
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return space;
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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, typename V>
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std::enable_if_t<!std::is_integral_v<V>, rtc::buffer<T>>
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generate_buffer(V mLens, V mStrides, std::size_t seed = 0)
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{
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std::size_t space = GetSize(mLens, mStrides);
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return generate_buffer<T>(space, seed);
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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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inline 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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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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