Skip to content

llama-tts : precompute irFFT theta #12514

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

llama-tts : precompute irFFT theta #12514

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
49 changes: 48 additions & 1 deletion examples/tts/tts.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -128,6 +128,34 @@ static void twiddle(float * real, float * imag, int k, int N) {
*imag = sin(angle);
}

struct theta {
theta() : cosine(0.0f), sine(0.0f) {}

void reset(int k, int N) {
twiddle(&cosine, &sine, k, N);
}

const float & get_cos() const {return cosine;}
const float & get_sin() const {return sine;}

private:
float cosine;
float sine;
};

static std::vector<theta> thetas;

static void fill_thetas(int N) {
thetas.resize(N);
for (int k = 0; k < N; ++k) {
thetas[k].reset(k, N);
}
}

static const theta& get_theta(int k) {
return thetas[k % thetas.size()];
}

static void irfft(int n, const float * inp_cplx, float * out_real) {
int N = n / 2 + 1;

Expand Down Expand Up @@ -160,6 +188,19 @@ static void irfft(int n, const float * inp_cplx, float * out_real) {
}
}

static void irfft_2(int n, const float * inp_cplx, float * out_real) {
int N = n / 2 + 1;

for (int k = 0; k < n; ++k) {
out_real[k] = 0.0f;
for (int m = 0; m < N; ++m) {
const theta & t = get_theta(k * m);
out_real[k] += inp_cplx[2 * m] * t.get_cos() - inp_cplx[2 * m + 1] * t.get_sin();
}
out_real[k] /= N;
}
}

//
// y = torch.nn.functional.fold(
// data, output_size=(1, output_size), kernel_size=(1, self.win_length), stride=(1, self.hop_length),
Expand Down Expand Up @@ -207,6 +248,8 @@ static std::vector<float> embd_to_audio(
const int n_pad = (n_win - n_hop)/2;
const int n_out = (n_codes - 1)*n_hop + n_win;

fill_thetas(n_fft);

std::vector<float> hann(n_fft);

fill_hann_window(hann.size(), true, hann.data());
Expand Down Expand Up @@ -248,11 +291,13 @@ static std::vector<float> embd_to_audio(
std::vector<float> res (n_codes*n_fft);
std::vector<float> hann2(n_codes*n_fft);

const auto t_irfft_start = ggml_time_us();

std::vector<std::thread> workers(n_thread);
for (int i = 0; i < n_thread; ++i) {
workers[i] = std::thread([&, i]() {
for (int l = i; l < n_codes; l += n_thread) {
irfft(n_fft, ST.data() + l*n_embd, res.data() + l*n_fft);
irfft_2(n_fft, ST.data() + l*n_embd, res.data() + l*n_fft);
for (int j = 0; j < n_fft; ++j) {
res [l*n_fft + j] *= hann[j];
hann2[l*n_fft + j] = hann[j] * hann[j];
Expand All @@ -264,6 +309,8 @@ static std::vector<float> embd_to_audio(
workers[i].join();
}

LOG_INF("%s: time irfft: %.3f ms\n", __func__, (ggml_time_us() - t_irfft_start) / 1000.0f);

std::vector<float> audio;
std::vector<float> env;

Expand Down
Loading