sonora-agc2 0.1.0

Automatic Gain Control 2 (AGC2) with RNN VAD for WebRTC Audio Processing
Documentation 
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//! Neural network weight tables for the RNN VAD.
//!
//! Ported from `webrtc/third_party/rnnoise/src/rnn_vad_weights.cc`.

/// Weights scaling factor.
pub(crate) const WEIGHTS_SCALE: f32 = 1.0 / 256.0;

// Input layer (dense).
pub(crate) const INPUT_LAYER_INPUT_SIZE: usize = 42;
pub(crate) const INPUT_LAYER_OUTPUT_SIZE: usize = 24;

pub(crate) const INPUT_DENSE_WEIGHTS: [i8; INPUT_LAYER_INPUT_SIZE * INPUT_LAYER_OUTPUT_SIZE] = [
    -10, 0, -3, 1, -8, -6, 3, -13, 1, 0, -3, -7, -5, -3, 6, -1, -6, 0, -6, -4, -1, -2, 1, 1, -7, 2,
    21, 10, -5, -20, 24, 23, 37, 8, -2, 33, -6, 22, 13, -2, 50, 8, 13, 1, -15, 30, -10, 30, 0, 3,
    5, 27, 1, 4, -3, 41, 56, 35, -2, 49, -13, 11, 13, -2, -47, 5, -16, -60, -15, 77, -17, 26, -3,
    14, -21, 19, -5, -19, -13, 0, 10, 14, 9, 31, -13, -41, -10, 4, 22, 18, -48, -6, -10, 62, -3,
    -18, -14, 12, 26, -28, 3, 14, 25, -13, -19, 6, 5, 36, -3, -65, -12, 0, 31, -7, -9, 101, -4, 26,
    16, 17, -12, -12, 14, -36, -3, 5, -15, 21, 2, 30, -3, 38, -4, 1, -6, 7, -7, 14, 38, -22, -30,
    -3, -7, 3, -39, -70, -126, 25, 34, 94, -67, -22, -33, 83, -47, -118, 4, 70, 33, 25, 62, -128,
    -76, -118, -113, 49, -12, -100, -18, -114, -33, 43, 32, 61, 40, -9, -106, 2, 36, -100, -40, -5,
    20, -75, 61, -51, -9, 126, -27, -52, 5, -24, -21, -126, -114, -12, 15, 106, -2, 73, -125, 50,
    13, -120, 35, 35, 4, -61, 29, -124, 6, -53, -69, -125, 64, -89, 36, -107, -103, -7, 27, 121,
    69, 77, -35, 35, 95, -125, -49, 97, -45, -43, -23, 23, -28, -65, -118, 2, 8, -126, 27, -97, 92,
    5, 55, 82, 17, -57, -115, 37, 8, -106, -46, 41, -2, 21, -44, 8, -73, -58, -39, 34, 89, -95, 95,
    -117, 120, -58, 31, 123, 1, -32, -109, -110, 60, -120, -43, -74, 5, 91, 26, 21, 114, 82, -83,
    -126, 123, 22, -16, -67, 25, -83, 46, 48, -34, -121, -124, -63, -35, -9, 31, 82, 123, 6, -3,
    117, 93, -2, -13, -36, 124, -112, -6, -102, -5, -33, -15, 44, -69, -127, -23, -40, -34, -85,
    68, 83, -1, 40, 8, 84, 118, -58, -55, -102, 123, -55, -14, -123, 44, -63, -14, 21, 35, 16, 24,
    -126, -13, -114, 35, 20, -36, 61, -9, 97, 34, 19, -32, -109, 76, -104, 99, -119, 45, -125, -51,
    -28, -8, -69, -8, 125, -45, -93, 113, 103, -41, -82, 52, 7, 126, 0, -40, 104, 55, -58, 17,
    -124, -93, -58, 8, -45, 1, 56, -123, 108, -47, -23, 115, 127, 17, -68, -13, 116, -82, -44, 45,
    67, -120, -101, -15, -125, 120, -113, 17, -48, -73, 126, -64, -86, -118, -19, 112, -1, -66,
    -27, -62, 121, -86, -58, 50, 89, -38, -75, 95, -111, 12, -113, 2, -68, 2, -94, -121, 91, -5, 0,
    79, 43, -7, -18, 79, 35, -38, 47, 1, -45, 83, -50, 102, 32, 55, -96, 15, -122, -69, 45, -27,
    91, -62, -30, 46, -95, 22, -72, -97, -1, 14, -122, 28, 127, 61, -126, 121, 9, 68, -120, 49,
    -60, 90, 3, 43, 68, 54, 34, -10, 28, 21, -24, -54, 22, -113, -12, 82, -2, -17, -9, 127, 8, 116,
    -92, 0, -70, -33, 123, 66, 116, -74, -4, 74, -72, -22, -47, 1, -83, -60, -124, 1, 122, -57,
    -43, 49, 40, -126, -128, -8, -29, 28, -24, -123, -121, -70, -93, -37, -126, 11, -125, -37, 11,
    -31, -51, -124, 116, -128, 8, -25, 109, 75, -12, 7, 8, 10, 117, 124, -128, -128, 29, -26, 101,
    21, -128, 87, 8, -39, 23, -128, 127, -127, 74, -55, 74, 112, 127, 4, 55, 44, -92, 123, 34, -93,
    47, -21, -92, 17, 49, -121, 92, 7, -126, -125, 124, -74, 3, -59, 18, -91, 3, -9, 9, 56, 116, 7,
    -29, 33, 87, -21, -128, -13, 57, 74, 9, -29, -61, -97, -21, -95, -12, -114, 16, 82, 125, -7,
    10, -24, 9, 77, -128, -102, -25, 3, -126, 10, 13, -18, 51, 26, 127, -79, 35, 51, 12, -50, -24,
    1, -7, 22, 81, 65, 120, -30, -38, 85, 122, -4, -106, -11, 27, 53, 41, 8, -104, -66, -38, -124,
    10, 12, 76, 117, -109, 9, 11, 2, -18, 3, 113, -16, -79, -39, -123, -20, -128, 2, 13, -33, -58,
    10, 84, -104, 13, 64, 109, 1, 54, -12, 28, 24, 63, -126, 118, -82, 46, -12, -15, 14, -43, 60,
    22, -32, -19, -46, 91, -107, 24, -94, 26, -47, 125, 6, 58, -15, -75, -26, -38, -35, 103, -16,
    -17, -13, 63, -2, 45, -45, -73, -23, 70, -87, 51, -17, 53, 76, 14, -18, -31, -14, 103, 8, 21,
    -28, -33, -20, -47, 6, 39, 40, -30, 7, -76, 55, 31, -20, -21, -59, 1, 25, -11, 17, 5, -13, -39,
    0, -76, 50, -33, -29, -50, -16, -11, -12, -1, -46, 40, -10, 65, -19, 21, -41, -32, -83, -19,
    -4, 49, -60, 118, -24, -46, 9, 102, -20, 8, -19, 25, 31, -3, -37, 0, 25, 7, 29, 2, -39, 127,
    -64, -20, 64, 115, -30, 36, 100, 35, 122, 127, 127, -127, 127, -127, 19, 127, -89, -79, -32,
    39, -127, 125, -80, 126, -127, 26, 8, 98, -8, -57, -90, -50, 126, 61, 127, -126, 40, -106, -68,
    104, -125, -119, 11, 10, -127, 66, -56, -12, -126, -104, 27, 75, 38, -124, -126, -125, 84,
    -123, -45, -114, -128, 127, 103, -101, -124, 127, -11, -23, -123, 92, -123, 24, 126, 41, -2,
    -39, -27, -94, 40, -112, -48, 127, 58, 14, 38, -75, -64, 73, 117, 100, -119, -11, 6, 32, -126,
    -14, 35, 121, -10, 54, -60, 89, -3, 69, -25, -20, 43, -86, -34, 24, 27, 7, -81, -99, -23, -16,
    -26, 13, 35, -97, 80, -29, -13, -121, -12, -65, -94, 70, -89, -126, -95, 88, 33, 96, 29, -90,
    69, 114, -78, 65, 90, -47, -47, 89, 1, -12, 3, 8, 30, 5, 2, -30, -1, 6, -7, 10, -4, 46, -27,
    -40, 22, -6, -17, 45, 24, -9, 23, -14, -63, -26, -12, -57, 27, 25, 55, -76, -47, 21, 34, 33,
    26, 17, 14, 6, 9, 26, 25, -25, -25, -18,
];

pub(crate) const INPUT_DENSE_BIAS: [i8; INPUT_LAYER_OUTPUT_SIZE] = [
    38, -6, 127, 127, 127, -43, -127, 78, 127, 5, 127, 123, 127, 127, -128, -76, -126, 28, 127,
    125, -30, 127, -89, -20,
];

// Hidden layer (GRU).
pub(crate) const HIDDEN_LAYER_OUTPUT_SIZE: usize = 24;

pub(crate) const HIDDEN_GRU_WEIGHTS: [i8; 3 * HIDDEN_LAYER_OUTPUT_SIZE * HIDDEN_LAYER_OUTPUT_SIZE] =
    include!("weights_hidden_gru.inc");

pub(crate) const HIDDEN_GRU_RECURRENT_WEIGHTS: [i8; 3
    * HIDDEN_LAYER_OUTPUT_SIZE
    * HIDDEN_LAYER_OUTPUT_SIZE] = include!("weights_hidden_gru_recurrent.inc");

pub(crate) const HIDDEN_GRU_BIAS: [i8; 3 * HIDDEN_LAYER_OUTPUT_SIZE] = [
    124, 125, -57, -126, 53, 123, 127, -75, 68, 102, -2, 116, 124, 127, 124, 125, 126, 123, -16,
    48, 125, 126, 78, 85, 11, 126, -30, -30, -64, -3, -105, -29, -17, 69, 63, 2, -32, -10, -62,
    113, -52, 112, -109, 112, 7, -40, 73, 53, 62, 6, -2, 0, 0, 100, -16, 26, -24, 56, 26, -10, -33,
    41, 70, 109, -29, 127, 34, -66, 49, 53, 27, 62,
];

// Output layer (dense).
pub(crate) const OUTPUT_LAYER_OUTPUT_SIZE: usize = 1;

pub(crate) const OUTPUT_DENSE_WEIGHTS: [i8; HIDDEN_LAYER_OUTPUT_SIZE * OUTPUT_LAYER_OUTPUT_SIZE] = [
    127, 127, 127, 127, 127, 20, 127, -126, -126, -54, 14, 125, -126, -126, 127, -125, -126, 127,
    -127, -127, -57, -30, 127, 80,
];

pub(crate) const OUTPUT_DENSE_BIAS: [i8; OUTPUT_LAYER_OUTPUT_SIZE] = [-50];