Re-organize the wasm examples (#231)

* Move the whisper example.

* More renaming.

* Add llama2 as a new wasm example.

* Live generation.

* More of the llama wasm example.

* Formatting.

candle-wasm-examples/whisper/src/audio.rs

@@ -0,0 +1,217 @@
+// Audio processing code, adapted from whisper.cpp
+// https://github.com/ggerganov/whisper.cpp
+use super::worker;
+
+pub trait Float: num_traits::Float + num_traits::FloatConst + num_traits::NumAssign {}
+
+impl Float for f32 {}
+impl Float for f64 {}
+
+// https://github.com/ggerganov/whisper.cpp/blob/4774d2feb01a772a15de81ffc34b34a1f294f020/whisper.cpp#L2357
+fn fft<T: Float>(inp: &[T]) -> Vec<T> {
+    let n = inp.len();
+    let zero = T::zero();
+    if n == 1 {
+        return vec![inp[0], zero];
+    }
+    if n % 2 == 1 {
+        return dft(inp);
+    }
+    let mut out = vec![zero; n * 2];
+
+    let mut even = vec![];
+    even.reserve(n / 2);
+    let mut odd = vec![];
+    odd.reserve(n / 2);
+
+    for (i, &inp) in inp.iter().enumerate() {
+        if i % 2 == 0 {
+            even.push(inp)
+        } else {
+            odd.push(inp);
+        }
+    }
+
+    let even_fft = fft(&even);
+    let odd_fft = fft(&odd);
+
+    let two_pi = T::PI() + T::PI();
+    let n_t = T::from(n).unwrap();
+    for k in 0..n / 2 {
+        let k_t = T::from(k).unwrap();
+        let theta = two_pi * k_t / n_t;
+        let re = theta.cos();
+        let im = -theta.sin();
+
+        let re_odd = odd_fft[2 * k];
+        let im_odd = odd_fft[2 * k + 1];
+
+        out[2 * k] = even_fft[2 * k] + re * re_odd - im * im_odd;
+        out[2 * k + 1] = even_fft[2 * k + 1] + re * im_odd + im * re_odd;
+
+        out[2 * (k + n / 2)] = even_fft[2 * k] - re * re_odd + im * im_odd;
+        out[2 * (k + n / 2) + 1] = even_fft[2 * k + 1] - re * im_odd - im * re_odd;
+    }
+    out
+}
+
+// https://github.com/ggerganov/whisper.cpp/blob/4774d2feb01a772a15de81ffc34b34a1f294f020/whisper.cpp#L2337
+fn dft<T: Float>(inp: &[T]) -> Vec<T> {
+    let zero = T::zero();
+    let n = inp.len();
+    let two_pi = T::PI() + T::PI();
+
+    let mut out = Vec::new();
+    out.reserve(2 * n);
+    let n_t = T::from(n).unwrap();
+    for k in 0..n {
+        let k_t = T::from(k).unwrap();
+        let mut re = zero;
+        let mut im = zero;
+
+        for (j, &inp) in inp.iter().enumerate() {
+            let j_t = T::from(j).unwrap();
+            let angle = two_pi * k_t * j_t / n_t;
+            re += inp * angle.cos();
+            im -= inp * angle.sin();
+        }
+
+        out.push(re);
+        out.push(im);
+    }
+    out
+}
+
+#[allow(clippy::too_many_arguments)]
+// https://github.com/ggerganov/whisper.cpp/blob/4774d2feb01a772a15de81ffc34b34a1f294f020/whisper.cpp#L2414
+fn log_mel_spectrogram_w<T: Float>(
+    ith: usize,
+    hann: &[T],
+    samples: &[T],
+    filters: &[T],
+    fft_size: usize,
+    fft_step: usize,
+    speed_up: bool,
+    n_len: usize,
+    n_mel: usize,
+    n_threads: usize,
+) -> Vec<T> {
+    let n_fft = if speed_up {
+        1 + fft_size / 4
+    } else {
+        1 + fft_size / 2
+    };
+
+    let zero = T::zero();
+    let half = T::from(0.5).unwrap();
+    let mut fft_in = vec![zero; fft_size];
+    let mut mel = vec![zero; n_len * n_mel];
+
+    for i in (ith..n_len).step_by(n_threads) {
+        let offset = i * fft_step;
+
+        // apply Hanning window
+        for j in 0..fft_size {
+            fft_in[j] = if offset + j < samples.len() {
+                hann[j] * samples[offset + j]
+            } else {
+                zero
+            }
+        }
+
+        // FFT -> mag^2
+        let mut fft_out: Vec<T> = fft(&fft_in);
+
+        for j in 0..fft_size {
+            fft_out[j] = fft_out[2 * j] * fft_out[2 * j] + fft_out[2 * j + 1] * fft_out[2 * j + 1];
+        }
+        for j in 1..fft_size / 2 {
+            let v = fft_out[fft_size - j];
+            fft_out[j] += v;
+        }
+
+        if speed_up {
+            // scale down in the frequency domain results in a speed up in the time domain
+            for j in 0..n_fft {
+                fft_out[j] = half * (fft_out[2 * j] + fft_out[2 * j + 1]);
+            }
+        }
+
+        // mel spectrogram
+        for j in 0..n_mel {
+            let mut sum = zero;
+            for k in 0..n_fft {
+                sum += fft_out[k] * filters[j * n_fft + k];
+            }
+            mel[j * n_len + i] = T::max(sum, T::from(1e-10).unwrap()).log10();
+        }
+    }
+    mel
+}
+
+fn log_mel_spectrogram_<T: Float + std::fmt::Display>(
+    samples: &[T],
+    filters: &[T],
+    fft_size: usize,
+    fft_step: usize,
+    n_mel: usize,
+    speed_up: bool,
+) -> Vec<T> {
+    let zero = T::zero();
+    let two_pi = T::PI() + T::PI();
+    let half = T::from(0.5).unwrap();
+    let one = T::from(1.0).unwrap();
+    let four = T::from(4.0).unwrap();
+    let fft_size_t = T::from(fft_size).unwrap();
+
+    let hann: Vec<T> = (0..fft_size)
+        .map(|i| half * (one - ((two_pi * T::from(i).unwrap()) / fft_size_t).cos()))
+        .collect();
+    let n_len = samples.len() / fft_step;
+
+    // pad audio with at least one extra chunk of zeros
+    let pad = 100 * worker::CHUNK_LENGTH / 2;
+    let n_len = if n_len % pad != 0 {
+        (n_len / pad + 1) * pad
+    } else {
+        n_len
+    };
+    let n_len = n_len + pad;
+    let samples = {
+        let mut samples_padded = samples.to_vec();
+        let to_add = n_len * fft_step - samples.len();
+        samples_padded.extend(std::iter::repeat(zero).take(to_add));
+        samples_padded
+    };
+
+    // Use a single thread for now.
+    let mut mel = log_mel_spectrogram_w(
+        0, &hann, &samples, filters, fft_size, fft_step, speed_up, n_len, n_mel, 1,
+    );
+    let mmax = mel
+        .iter()
+        .max_by(|&u, &v| u.partial_cmp(v).unwrap_or(std::cmp::Ordering::Greater))
+        .copied()
+        .unwrap_or(zero)
+        - T::from(8).unwrap();
+    for m in mel.iter_mut() {
+        let v = T::max(*m, mmax);
+        *m = v / four + one
+    }
+    mel
+}
+
+pub fn pcm_to_mel<T: Float + std::fmt::Display>(
+    samples: &[T],
+    filters: &[T],
+) -> anyhow::Result<Vec<T>> {
+    let mel = log_mel_spectrogram_(
+        samples,
+        filters,
+        worker::N_FFT,
+        worker::HOP_LENGTH,
+        worker::N_MELS,
+        false,
+    );
+    Ok(mel)
+}