Struct FastLearnedFftModel 

pub struct FastLearnedFftModel {
    pub n_fft: usize,
    pub n_mels: usize,
    pub sample_rate: f32,
    pub twiddles: Vec<f32>,
    pub gates: Vec<f32>,
    pub freq_mask: Vec<f32>,
    pub denoiser: SpectrumDenoiser,
    pub use_q8: bool,
    pub hard_gate_threshold: Option<f32>,
    /* private fields */
}

End-to-end learned spectral model for fast inference paths.

Fields

n_fft: usize

n_mels: usize

sample_rate: f32

twiddles: Vec<f32>

gates: Vec<f32>

freq_mask: Vec<f32>

Per complex-bin mask (learnable), init 1.

denoiser: SpectrumDenoiser

use_q8: bool

hard_gate_threshold: Option<f32>

When set, inference uses hard gates (0/1) at this threshold.

Implementations

impl FastLearnedFftModel

pub fn new(cfg: &FftLearnConfig, n_mels: usize, sample_rate: f32) -> Self

pub fn with_hard_gates(self, threshold: f32) -> Self

pub fn mel_filters(&self) -> &[f32]

pub fn with_q8(self) -> Self

pub fn sync_q8(&mut self)

pub fn twiddles_for_forward(&self) -> Vec<f32>

pub fn spectrum_batch_raw( &self, signal: &[f32], batch: usize, ) -> Result<Vec<f32>>

pub fn spectrum_batch(&self, signal: &[f32], batch: usize) -> Result<Vec<f32>>

pub fn log_mel_batch(&self, signal: &[f32], batch: usize) -> Result<Vec<f32>>

pub fn welch_psd_batch( &self, signal: &[f32], batch: usize, params: WelchParams, ) -> Result<Vec<f32>>

pub fn welch_peaks_batch( &self, signal: &[f32], batch: usize, params: WelchPeakParams, ) -> Result<Vec<f32>>

Fast Welch path (few segments) → top-K (bin, power) spikes only.

pub fn mean_gate(&self) -> f32

pub fn active_gates(&self, threshold: f32) -> usize

Trait Implementations

impl Clone for FastLearnedFftModel

fn clone(&self) -> FastLearnedFftModel

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FastLearnedFftModel

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.