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use crate::utils;
use ndarray::{Array, Array1, Array2, ArrayBase, ArrayD, Dim, IxDynImpl, OwnedRepr};
use ort::session::Session;
use ort::value::Value;
use std::mem::take;
use std::path::Path;
#[derive(Debug)]
pub struct Silero {
session: Session,
sample_rate: ArrayBase<OwnedRepr<i64>, Dim<[usize; 1]>>,
state: ArrayBase<OwnedRepr<f32>, Dim<IxDynImpl>>,
context: Array1<f32>,
context_size: usize,
}
impl Silero {
pub fn new(
sample_rate: utils::SampleRate,
model_path: impl AsRef<Path>,
) -> Result<Self, ort::Error> {
let session = Session::builder()?.commit_from_file(model_path)?;
let state = ArrayD::<f32>::zeros([2, 1, 128].as_slice());
let sample_rate_val: i64 = sample_rate.into();
let context_size = if sample_rate_val == 16000 { 64 } else { 32 };
let context = Array1::<f32>::zeros(context_size);
let sample_rate = Array::from_shape_vec([1], vec![sample_rate_val]).unwrap();
Ok(Self {
session,
sample_rate,
state,
context,
context_size,
})
}
pub fn reset(&mut self) {
self.state = ArrayD::<f32>::zeros([2, 1, 128].as_slice());
self.context = Array1::<f32>::zeros(self.context_size);
}
pub fn calc_level(&mut self, audio_frame: &[i16]) -> Result<f32, ort::Error> {
let data = audio_frame
.iter()
.map(|x| (*x as f32) / (i16::MAX as f32))
.collect::<Vec<_>>();
// Concatenate context with input
let mut input_with_context = Vec::with_capacity(self.context_size + data.len());
input_with_context.extend_from_slice(self.context.as_slice().unwrap());
input_with_context.extend_from_slice(&data);
let frame =
Array2::<f32>::from_shape_vec([1, input_with_context.len()], input_with_context)
.unwrap();
let frame_value = Value::from_array(frame)?;
let state_value = Value::from_array(take(&mut self.state))?;
let sr_value = Value::from_array(self.sample_rate.clone())?;
let res = self.session.run([
(&frame_value).into(),
(&state_value).into(),
(&sr_value).into(),
])?;
let (shape, state_data) = res["stateN"].try_extract_tensor::<f32>()?;
let shape_usize: Vec<usize> = shape.as_ref().iter().map(|&d| d as usize).collect();
self.state = ArrayD::from_shape_vec(shape_usize.as_slice(), state_data.to_vec()).unwrap();
// Update context with last context_size samples from the input
if data.len() >= self.context_size {
self.context = Array1::from_vec(data[data.len() - self.context_size..].to_vec());
}
let prob = *res["output"]
.try_extract_tensor::<f32>()
.unwrap()
.1
.first()
.unwrap();
Ok(prob)
}
}