Fabio
c36510c21e
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86 lines
2.8 KiB
C++
86 lines
2.8 KiB
C++
#include "engine/framework/audio/dsp.h"
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#include "engine/framework/audio/wav_reader.h"
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#include <chrono>
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#include <cmath>
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#include <filesystem>
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#include <iostream>
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#include <stdexcept>
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#include <string>
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#include <vector>
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namespace {
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std::vector<float> make_hann_window(int64_t win_length) {
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std::vector<float> window(static_cast<size_t>(win_length), 0.0f);
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if (win_length == 1) {
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window[0] = 1.0f;
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return window;
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}
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constexpr long double kPi = 3.14159265358979323846264338327950288L;
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for (int64_t i = 0; i < win_length; ++i) {
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window[static_cast<size_t>(i)] =
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0.5f - 0.5f * std::cos(2.0L * kPi * static_cast<long double>(i) /
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static_cast<long double>(win_length - 1));
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}
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return window;
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}
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} // namespace
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int main(int argc, char ** argv) {
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if (argc != 7) {
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std::cerr << "Usage: stft_bench <wav> <kind:stft> <iters> <n_fft> <hop_length> <win_length>\n";
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return 1;
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}
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const std::filesystem::path wav_path(argv[1]);
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const std::string kind(argv[2]);
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const int iters = std::stoi(argv[3]);
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const int64_t n_fft = std::stoll(argv[4]);
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const int64_t hop_length = std::stoll(argv[5]);
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const int64_t win_length = std::stoll(argv[6]);
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auto wav = engine::audio::read_wav_f32(wav_path);
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if (wav.channels != 1) {
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throw std::runtime_error("stft_bench requires mono WAV");
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}
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if (iters <= 0) {
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throw std::runtime_error("iters must be > 0");
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}
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const engine::audio::STFTConfig config{
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n_fft,
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hop_length,
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win_length,
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true,
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engine::audio::STFTPadMode::Constant,
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};
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const auto window = make_hann_window(win_length);
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double total_ms = 0.0;
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size_t output_size = 0;
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for (int i = 0; i < iters; ++i) {
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const auto started = std::chrono::steady_clock::now();
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engine::audio::AudioTensor tensor;
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if (kind == "stft") {
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tensor = engine::audio::STFT().compute_complex(
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wav.samples, window, 1, static_cast<int64_t>(wav.samples.size()), config);
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} else {
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throw std::runtime_error("kind must be 'stft'");
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}
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const auto ended = std::chrono::steady_clock::now();
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total_ms += std::chrono::duration<double, std::milli>(ended - started).count();
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output_size = tensor.values.size();
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}
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std::cout << "kind=" << kind << "\n";
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std::cout << "iters=" << iters << "\n";
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std::cout << "n_fft=" << n_fft << "\n";
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std::cout << "hop_length=" << hop_length << "\n";
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std::cout << "win_length=" << win_length << "\n";
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std::cout << "output_size=" << output_size << "\n";
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std::cout << "total_ms=" << total_ms << "\n";
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std::cout << "avg_ms=" << (total_ms / static_cast<double>(iters)) << "\n";
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return 0;
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}
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