Read wav files.

This commit is contained in:
laurent
2023-07-05 11:53:58 +01:00
parent 26d1a7803f
commit 95f378ebb4
3 changed files with 61 additions and 41 deletions

View File

@ -21,6 +21,7 @@ clap = { version = "4.2.4", features = ["derive"] }
rand = "0.8.5"
tokenizers = { version = "0.13.3", default-features=false, features=["onig"] }
tokio = { version = "1.28.2", features = ["macros", "rt-multi-thread"] }
wav = "1.0.0"
[features]
default = ["cuda"]

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@ -1,13 +1,16 @@
// Audio processing code, adapted from whisper.cpp
// https://github.com/ggerganov/whisper.cpp
const WHISPER_SAMPLE_RATE: usize = 16000;
const WHISPER_N_FFT: usize = 400;
const WHISPER_N_MEL: usize = 80;
const WHISPER_HOP_LENGTH: usize = 160;
const WHISPER_CHUNK_SIZE: usize = 30;
pub const WHISPER_SAMPLE_RATE: usize = 16000;
pub const WHISPER_N_FFT: usize = 400;
pub const WHISPER_N_MEL: usize = 80;
pub const WHISPER_HOP_LENGTH: usize = 160;
pub const WHISPER_CHUNK_SIZE: usize = 30;
trait Float: num_traits::Float + num_traits::FloatConst + num_traits::NumAssign {}
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> {
@ -203,7 +206,7 @@ fn log_mel_spectrogram_<T: Float>(
mel
}
fn pcm_to_mel<T: Float>(samples: &[T], filters: &[T]) -> anyhow::Result<Vec<T>> {
pub fn pcm_to_mel<T: Float>(samples: &[T], filters: &[T]) -> anyhow::Result<Vec<T>> {
if filters.len() != WHISPER_N_MEL * WHISPER_N_FFT {
anyhow::bail!(
"unexpected filter length {} (n_mel: {}, n_fft: {})",

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@ -40,33 +40,6 @@ const EOT_TOKEN: u32 = 50256;
const NO_SPEECH_TOKEN: u32 = 50361;
const NO_TIMESTAMP_TOKEN: u32 = 50362;
#[derive(Parser, Debug)]
#[command(author, version, about, long_about = None)]
struct Args {
/// Run on CPU rather than on GPU.
#[arg(long)]
cpu: bool,
#[arg(long)]
weights: String,
#[arg(long)]
input: String,
#[arg(long)]
tokenizer_config: String,
/// The seed to use when generating random samples.
#[arg(long, default_value_t = 299792458)]
seed: u64,
#[arg(
long,
default_value = "candle-examples/examples/whisper/mel_filters.safetensors"
)]
filters: String,
}
#[derive(Debug, Clone)]
struct DecodingResult {
tokens: Vec<u32>,
@ -184,6 +157,35 @@ impl Decode {
}
}
#[derive(Parser, Debug)]
#[command(author, version, about, long_about = None)]
struct Args {
/// Run on CPU rather than on GPU.
#[arg(long)]
cpu: bool,
#[arg(long)]
weights: String,
/// The input to be processed, in wav formats.
#[arg(long)]
input: String,
#[arg(long)]
tokenizer_config: String,
/// The seed to use when generating random samples.
#[arg(long, default_value_t = 299792458)]
seed: u64,
/// The mel filters in safetensors format.
#[arg(
long,
default_value = "candle-examples/examples/whisper/mel_filters.safetensors"
)]
filters: String,
}
fn main() -> Result<()> {
let args = Args::parse();
let device = if args.cpu {
@ -195,14 +197,28 @@ fn main() -> Result<()> {
let tokenizer = Tokenizer::from_file(args.tokenizer_config).map_err(E::msg)?;
let filters = unsafe { candle::safetensors::MmapedFile::new(args.filters)? };
let filters = filters.deserialize()?;
let filters = filters.tensor("mel_80", &device)?;
println!("loaded mel filters {:?}", filters.shape());
let mel_filters = unsafe { candle::safetensors::MmapedFile::new(args.filters)? };
let mel_filters = mel_filters.deserialize()?;
let mel_filters = mel_filters.tensor("mel_80", &device)?;
println!("loaded mel filters {:?}", mel_filters.shape());
let mel_filters = mel_filters.flatten_all()?.to_vec1::<f32>()?;
let input = unsafe { candle::safetensors::MmapedFile::new(args.input)? };
let input = input.deserialize()?;
let mel = input.tensor("mel", &device)?;
let mut input = std::fs::File::open(args.input)?;
let (header, data) = wav::read(&mut input)?;
println!("loaded wav data: {header:?}");
if header.sampling_rate != audio::WHISPER_SAMPLE_RATE as u32 {
anyhow::bail!(
"wav file must have a {} sampling rate",
audio::WHISPER_SAMPLE_RATE
)
}
let data = data.as_sixteen().expect("expected 16 bit wav file");
let pcm_data: Vec<_> = data[..data.len() / header.channel_count as usize]
.iter()
.map(|v| *v as f32 / 32768.)
.collect();
let mel = audio::pcm_to_mel(&pcm_data, &mel_filters)?;
let mel = Tensor::new(&mel[..], &device)?;
println!("loaded mel: {:?}", mel.dims());
let weights = unsafe { candle::safetensors::MmapedFile::new(args.weights)? };