opus1 0.3.0

//! The RDOVAE decoder of deep redundancy (DRED): its layers and the constants
//! of its C header.
//!
//! Generated by `tools/dnn-gen` from libopus 1.6.1 `dnn/dred_rdovae_dec_data.h`
//! and `dnn/dred_rdovae_dec_data.c` (`init_rdovaedec`). Do not edit: change the
//! generator and run it again (`tools/dnn-gen/README.md`).

use crate::Error;
use super::{Layer, LayerSpec, LinearSpec};
use crate::dnn::nnet::LinearLayer;
use crate::dnn::weights::WeightList;

/// The file of this model's weights in `dnn-weights/`.
pub const BLOB_FILE: &str = "dred_rdovae_dec.bin";

// The constants of `dnn/dred_rdovae_dec_data.h`, in the same order.

/// `DEC_DENSE1_OUT_SIZE`.
pub const DEC_DENSE1_OUT_SIZE: usize = 96;

/// `DEC_GLU1_OUT_SIZE`.
pub const DEC_GLU1_OUT_SIZE: usize = 64;

/// `DEC_GLU2_OUT_SIZE`.
pub const DEC_GLU2_OUT_SIZE: usize = 64;

/// `DEC_GLU3_OUT_SIZE`.
pub const DEC_GLU3_OUT_SIZE: usize = 64;

/// `DEC_GLU4_OUT_SIZE`.
pub const DEC_GLU4_OUT_SIZE: usize = 64;

/// `DEC_GLU5_OUT_SIZE`.
pub const DEC_GLU5_OUT_SIZE: usize = 64;

/// `DEC_HIDDEN_INIT_OUT_SIZE`.
pub const DEC_HIDDEN_INIT_OUT_SIZE: usize = 128;

/// `DEC_OUTPUT_OUT_SIZE`.
pub const DEC_OUTPUT_OUT_SIZE: usize = 80;

/// `DEC_CONV_DENSE1_OUT_SIZE`.
pub const DEC_CONV_DENSE1_OUT_SIZE: usize = 32;

/// `DEC_CONV_DENSE2_OUT_SIZE`.
pub const DEC_CONV_DENSE2_OUT_SIZE: usize = 32;

/// `DEC_CONV_DENSE3_OUT_SIZE`.
pub const DEC_CONV_DENSE3_OUT_SIZE: usize = 32;

/// `DEC_CONV_DENSE4_OUT_SIZE`.
pub const DEC_CONV_DENSE4_OUT_SIZE: usize = 32;

/// `DEC_CONV_DENSE5_OUT_SIZE`.
pub const DEC_CONV_DENSE5_OUT_SIZE: usize = 32;

/// `DEC_GRU_INIT_OUT_SIZE`.
pub const DEC_GRU_INIT_OUT_SIZE: usize = 320;

/// `DEC_GRU1_OUT_SIZE`.
pub const DEC_GRU1_OUT_SIZE: usize = 64;

/// `DEC_GRU1_STATE_SIZE`.
pub const DEC_GRU1_STATE_SIZE: usize = 64;

/// `DEC_GRU2_OUT_SIZE`.
pub const DEC_GRU2_OUT_SIZE: usize = 64;

/// `DEC_GRU2_STATE_SIZE`.
pub const DEC_GRU2_STATE_SIZE: usize = 64;

/// `DEC_GRU3_OUT_SIZE`.
pub const DEC_GRU3_OUT_SIZE: usize = 64;

/// `DEC_GRU3_STATE_SIZE`.
pub const DEC_GRU3_STATE_SIZE: usize = 64;

/// `DEC_GRU4_OUT_SIZE`.
pub const DEC_GRU4_OUT_SIZE: usize = 64;

/// `DEC_GRU4_STATE_SIZE`.
pub const DEC_GRU4_STATE_SIZE: usize = 64;

/// `DEC_GRU5_OUT_SIZE`.
pub const DEC_GRU5_OUT_SIZE: usize = 64;

/// `DEC_GRU5_STATE_SIZE`.
pub const DEC_GRU5_STATE_SIZE: usize = 64;

/// `DEC_CONV1_OUT_SIZE`.
pub const DEC_CONV1_OUT_SIZE: usize = 32;

/// `DEC_CONV1_IN_SIZE`.
pub const DEC_CONV1_IN_SIZE: usize = 32;

/// `DEC_CONV1_STATE_SIZE`, `(32 * (1))` in C.
pub const DEC_CONV1_STATE_SIZE: usize = 32;

/// `DEC_CONV2_OUT_SIZE`.
pub const DEC_CONV2_OUT_SIZE: usize = 32;

/// `DEC_CONV2_IN_SIZE`.
pub const DEC_CONV2_IN_SIZE: usize = 32;

/// `DEC_CONV2_STATE_SIZE`, `(32 * (1))` in C.
pub const DEC_CONV2_STATE_SIZE: usize = 32;

/// `DEC_CONV3_OUT_SIZE`.
pub const DEC_CONV3_OUT_SIZE: usize = 32;

/// `DEC_CONV3_IN_SIZE`.
pub const DEC_CONV3_IN_SIZE: usize = 32;

/// `DEC_CONV3_STATE_SIZE`, `(32 * (1))` in C.
pub const DEC_CONV3_STATE_SIZE: usize = 32;

/// `DEC_CONV4_OUT_SIZE`.
pub const DEC_CONV4_OUT_SIZE: usize = 32;

/// `DEC_CONV4_IN_SIZE`.
pub const DEC_CONV4_IN_SIZE: usize = 32;

/// `DEC_CONV4_STATE_SIZE`, `(32 * (1))` in C.
pub const DEC_CONV4_STATE_SIZE: usize = 32;

/// `DEC_CONV5_OUT_SIZE`.
pub const DEC_CONV5_OUT_SIZE: usize = 32;

/// `DEC_CONV5_IN_SIZE`.
pub const DEC_CONV5_IN_SIZE: usize = 32;

/// `DEC_CONV5_STATE_SIZE`, `(32 * (1))` in C.
pub const DEC_CONV5_STATE_SIZE: usize = 32;

/// The layers in the order of `init_rdovaedec`: the arrays that each one reads,
/// and its shape. The names are the array names of the blob.
pub const LAYERS: [LayerSpec; 29] = [
    LayerSpec::Linear(LinearSpec {
        name: "dec_dense1",
        bias: Some("dec_dense1_bias"),
        subias: None,
        weights: None,
        float_weights: Some("dec_dense1_weights_float"),
        weights_idx: None,
        diag: None,
        scale: None,
        nb_inputs: 26,
        nb_outputs: 96,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_glu1",
        bias: Some("dec_glu1_bias"),
        subias: Some("dec_glu1_subias"),
        weights: Some("dec_glu1_weights_int8"),
        float_weights: Some("dec_glu1_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_glu1_scale"),
        nb_inputs: 64,
        nb_outputs: 64,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_glu2",
        bias: Some("dec_glu2_bias"),
        subias: Some("dec_glu2_subias"),
        weights: Some("dec_glu2_weights_int8"),
        float_weights: Some("dec_glu2_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_glu2_scale"),
        nb_inputs: 64,
        nb_outputs: 64,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_glu3",
        bias: Some("dec_glu3_bias"),
        subias: Some("dec_glu3_subias"),
        weights: Some("dec_glu3_weights_int8"),
        float_weights: Some("dec_glu3_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_glu3_scale"),
        nb_inputs: 64,
        nb_outputs: 64,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_glu4",
        bias: Some("dec_glu4_bias"),
        subias: Some("dec_glu4_subias"),
        weights: Some("dec_glu4_weights_int8"),
        float_weights: Some("dec_glu4_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_glu4_scale"),
        nb_inputs: 64,
        nb_outputs: 64,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_glu5",
        bias: Some("dec_glu5_bias"),
        subias: Some("dec_glu5_subias"),
        weights: Some("dec_glu5_weights_int8"),
        float_weights: Some("dec_glu5_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_glu5_scale"),
        nb_inputs: 64,
        nb_outputs: 64,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_hidden_init",
        bias: Some("dec_hidden_init_bias"),
        subias: None,
        weights: None,
        float_weights: Some("dec_hidden_init_weights_float"),
        weights_idx: None,
        diag: None,
        scale: None,
        nb_inputs: 50,
        nb_outputs: 128,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_output",
        bias: Some("dec_output_bias"),
        subias: Some("dec_output_subias"),
        weights: Some("dec_output_weights_int8"),
        float_weights: Some("dec_output_weights_float"),
        weights_idx: Some("dec_output_weights_idx"),
        diag: None,
        scale: Some("dec_output_scale"),
        nb_inputs: 576,
        nb_outputs: 80,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv_dense1",
        bias: Some("dec_conv_dense1_bias"),
        subias: Some("dec_conv_dense1_subias"),
        weights: Some("dec_conv_dense1_weights_int8"),
        float_weights: Some("dec_conv_dense1_weights_float"),
        weights_idx: Some("dec_conv_dense1_weights_idx"),
        diag: None,
        scale: Some("dec_conv_dense1_scale"),
        nb_inputs: 160,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv_dense2",
        bias: Some("dec_conv_dense2_bias"),
        subias: Some("dec_conv_dense2_subias"),
        weights: Some("dec_conv_dense2_weights_int8"),
        float_weights: Some("dec_conv_dense2_weights_float"),
        weights_idx: Some("dec_conv_dense2_weights_idx"),
        diag: None,
        scale: Some("dec_conv_dense2_scale"),
        nb_inputs: 256,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv_dense3",
        bias: Some("dec_conv_dense3_bias"),
        subias: Some("dec_conv_dense3_subias"),
        weights: Some("dec_conv_dense3_weights_int8"),
        float_weights: Some("dec_conv_dense3_weights_float"),
        weights_idx: Some("dec_conv_dense3_weights_idx"),
        diag: None,
        scale: Some("dec_conv_dense3_scale"),
        nb_inputs: 352,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv_dense4",
        bias: Some("dec_conv_dense4_bias"),
        subias: Some("dec_conv_dense4_subias"),
        weights: Some("dec_conv_dense4_weights_int8"),
        float_weights: Some("dec_conv_dense4_weights_float"),
        weights_idx: Some("dec_conv_dense4_weights_idx"),
        diag: None,
        scale: Some("dec_conv_dense4_scale"),
        nb_inputs: 448,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv_dense5",
        bias: Some("dec_conv_dense5_bias"),
        subias: Some("dec_conv_dense5_subias"),
        weights: Some("dec_conv_dense5_weights_int8"),
        float_weights: Some("dec_conv_dense5_weights_float"),
        weights_idx: Some("dec_conv_dense5_weights_idx"),
        diag: None,
        scale: Some("dec_conv_dense5_scale"),
        nb_inputs: 544,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru_init",
        bias: Some("dec_gru_init_bias"),
        subias: Some("dec_gru_init_subias"),
        weights: Some("dec_gru_init_weights_int8"),
        float_weights: Some("dec_gru_init_weights_float"),
        weights_idx: Some("dec_gru_init_weights_idx"),
        diag: None,
        scale: Some("dec_gru_init_scale"),
        nb_inputs: 128,
        nb_outputs: 320,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru1_input",
        bias: Some("dec_gru1_input_bias"),
        subias: Some("dec_gru1_input_subias"),
        weights: Some("dec_gru1_input_weights_int8"),
        float_weights: Some("dec_gru1_input_weights_float"),
        weights_idx: Some("dec_gru1_input_weights_idx"),
        diag: None,
        scale: Some("dec_gru1_input_scale"),
        nb_inputs: 96,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru1_recurrent",
        bias: Some("dec_gru1_recurrent_bias"),
        subias: Some("dec_gru1_recurrent_subias"),
        weights: Some("dec_gru1_recurrent_weights_int8"),
        float_weights: Some("dec_gru1_recurrent_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_gru1_recurrent_scale"),
        nb_inputs: 64,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru2_input",
        bias: Some("dec_gru2_input_bias"),
        subias: Some("dec_gru2_input_subias"),
        weights: Some("dec_gru2_input_weights_int8"),
        float_weights: Some("dec_gru2_input_weights_float"),
        weights_idx: Some("dec_gru2_input_weights_idx"),
        diag: None,
        scale: Some("dec_gru2_input_scale"),
        nb_inputs: 192,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru2_recurrent",
        bias: Some("dec_gru2_recurrent_bias"),
        subias: Some("dec_gru2_recurrent_subias"),
        weights: Some("dec_gru2_recurrent_weights_int8"),
        float_weights: Some("dec_gru2_recurrent_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_gru2_recurrent_scale"),
        nb_inputs: 64,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru3_input",
        bias: Some("dec_gru3_input_bias"),
        subias: Some("dec_gru3_input_subias"),
        weights: Some("dec_gru3_input_weights_int8"),
        float_weights: Some("dec_gru3_input_weights_float"),
        weights_idx: Some("dec_gru3_input_weights_idx"),
        diag: None,
        scale: Some("dec_gru3_input_scale"),
        nb_inputs: 288,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru3_recurrent",
        bias: Some("dec_gru3_recurrent_bias"),
        subias: Some("dec_gru3_recurrent_subias"),
        weights: Some("dec_gru3_recurrent_weights_int8"),
        float_weights: Some("dec_gru3_recurrent_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_gru3_recurrent_scale"),
        nb_inputs: 64,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru4_input",
        bias: Some("dec_gru4_input_bias"),
        subias: Some("dec_gru4_input_subias"),
        weights: Some("dec_gru4_input_weights_int8"),
        float_weights: Some("dec_gru4_input_weights_float"),
        weights_idx: Some("dec_gru4_input_weights_idx"),
        diag: None,
        scale: Some("dec_gru4_input_scale"),
        nb_inputs: 384,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru4_recurrent",
        bias: Some("dec_gru4_recurrent_bias"),
        subias: Some("dec_gru4_recurrent_subias"),
        weights: Some("dec_gru4_recurrent_weights_int8"),
        float_weights: Some("dec_gru4_recurrent_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_gru4_recurrent_scale"),
        nb_inputs: 64,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru5_input",
        bias: Some("dec_gru5_input_bias"),
        subias: Some("dec_gru5_input_subias"),
        weights: Some("dec_gru5_input_weights_int8"),
        float_weights: Some("dec_gru5_input_weights_float"),
        weights_idx: Some("dec_gru5_input_weights_idx"),
        diag: None,
        scale: Some("dec_gru5_input_scale"),
        nb_inputs: 480,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_gru5_recurrent",
        bias: Some("dec_gru5_recurrent_bias"),
        subias: Some("dec_gru5_recurrent_subias"),
        weights: Some("dec_gru5_recurrent_weights_int8"),
        float_weights: Some("dec_gru5_recurrent_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_gru5_recurrent_scale"),
        nb_inputs: 64,
        nb_outputs: 192,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv1",
        bias: Some("dec_conv1_bias"),
        subias: Some("dec_conv1_subias"),
        weights: Some("dec_conv1_weights_int8"),
        float_weights: Some("dec_conv1_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_conv1_scale"),
        nb_inputs: 64,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv2",
        bias: Some("dec_conv2_bias"),
        subias: Some("dec_conv2_subias"),
        weights: Some("dec_conv2_weights_int8"),
        float_weights: Some("dec_conv2_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_conv2_scale"),
        nb_inputs: 64,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv3",
        bias: Some("dec_conv3_bias"),
        subias: Some("dec_conv3_subias"),
        weights: Some("dec_conv3_weights_int8"),
        float_weights: Some("dec_conv3_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_conv3_scale"),
        nb_inputs: 64,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv4",
        bias: Some("dec_conv4_bias"),
        subias: Some("dec_conv4_subias"),
        weights: Some("dec_conv4_weights_int8"),
        float_weights: Some("dec_conv4_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_conv4_scale"),
        nb_inputs: 64,
        nb_outputs: 32,
    }),
    LayerSpec::Linear(LinearSpec {
        name: "dec_conv5",
        bias: Some("dec_conv5_bias"),
        subias: Some("dec_conv5_subias"),
        weights: Some("dec_conv5_weights_int8"),
        float_weights: Some("dec_conv5_weights_float"),
        weights_idx: None,
        diag: None,
        scale: Some("dec_conv5_scale"),
        nb_inputs: 64,
        nb_outputs: 32,
    }),
];

/// libopus `RDOVAEDec` (`dnn/dred_rdovae_dec_data.h`): the layers of the model,
/// in the order of the C struct. Each layer borrows its arrays from a weight
/// list.
#[derive(Clone, Copy, Default)]
pub struct RdovaeDec<'w> {
    /// `dec_dense1`: float weights, 26 inputs, 96 outputs.
    pub dec_dense1: LinearLayer<'w>,
    /// `dec_glu1`: int8 weights, 64 inputs, 64 outputs.
    pub dec_glu1: LinearLayer<'w>,
    /// `dec_glu2`: int8 weights, 64 inputs, 64 outputs.
    pub dec_glu2: LinearLayer<'w>,
    /// `dec_glu3`: int8 weights, 64 inputs, 64 outputs.
    pub dec_glu3: LinearLayer<'w>,
    /// `dec_glu4`: int8 weights, 64 inputs, 64 outputs.
    pub dec_glu4: LinearLayer<'w>,
    /// `dec_glu5`: int8 weights, 64 inputs, 64 outputs.
    pub dec_glu5: LinearLayer<'w>,
    /// `dec_hidden_init`: float weights, 50 inputs, 128 outputs.
    pub dec_hidden_init: LinearLayer<'w>,
    /// `dec_output`: int8 sparse weights, 576 inputs, 80 outputs.
    pub dec_output: LinearLayer<'w>,
    /// `dec_conv_dense1`: int8 sparse weights, 160 inputs, 32 outputs.
    pub dec_conv_dense1: LinearLayer<'w>,
    /// `dec_conv_dense2`: int8 sparse weights, 256 inputs, 32 outputs.
    pub dec_conv_dense2: LinearLayer<'w>,
    /// `dec_conv_dense3`: int8 sparse weights, 352 inputs, 32 outputs.
    pub dec_conv_dense3: LinearLayer<'w>,
    /// `dec_conv_dense4`: int8 sparse weights, 448 inputs, 32 outputs.
    pub dec_conv_dense4: LinearLayer<'w>,
    /// `dec_conv_dense5`: int8 sparse weights, 544 inputs, 32 outputs.
    pub dec_conv_dense5: LinearLayer<'w>,
    /// `dec_gru_init`: int8 sparse weights, 128 inputs, 320 outputs.
    pub dec_gru_init: LinearLayer<'w>,
    /// `dec_gru1_input`: int8 sparse weights, 96 inputs, 192 outputs.
    pub dec_gru1_input: LinearLayer<'w>,
    /// `dec_gru1_recurrent`: int8 weights, 64 inputs, 192 outputs.
    pub dec_gru1_recurrent: LinearLayer<'w>,
    /// `dec_gru2_input`: int8 sparse weights, 192 inputs, 192 outputs.
    pub dec_gru2_input: LinearLayer<'w>,
    /// `dec_gru2_recurrent`: int8 weights, 64 inputs, 192 outputs.
    pub dec_gru2_recurrent: LinearLayer<'w>,
    /// `dec_gru3_input`: int8 sparse weights, 288 inputs, 192 outputs.
    pub dec_gru3_input: LinearLayer<'w>,
    /// `dec_gru3_recurrent`: int8 weights, 64 inputs, 192 outputs.
    pub dec_gru3_recurrent: LinearLayer<'w>,
    /// `dec_gru4_input`: int8 sparse weights, 384 inputs, 192 outputs.
    pub dec_gru4_input: LinearLayer<'w>,
    /// `dec_gru4_recurrent`: int8 weights, 64 inputs, 192 outputs.
    pub dec_gru4_recurrent: LinearLayer<'w>,
    /// `dec_gru5_input`: int8 sparse weights, 480 inputs, 192 outputs.
    pub dec_gru5_input: LinearLayer<'w>,
    /// `dec_gru5_recurrent`: int8 weights, 64 inputs, 192 outputs.
    pub dec_gru5_recurrent: LinearLayer<'w>,
    /// `dec_conv1`: int8 weights, 64 inputs, 32 outputs.
    pub dec_conv1: LinearLayer<'w>,
    /// `dec_conv2`: int8 weights, 64 inputs, 32 outputs.
    pub dec_conv2: LinearLayer<'w>,
    /// `dec_conv3`: int8 weights, 64 inputs, 32 outputs.
    pub dec_conv3: LinearLayer<'w>,
    /// `dec_conv4`: int8 weights, 64 inputs, 32 outputs.
    pub dec_conv4: LinearLayer<'w>,
    /// `dec_conv5`: int8 weights, 64 inputs, 32 outputs.
    pub dec_conv5: LinearLayer<'w>,
}

impl<'w> RdovaeDec<'w> {
    /// libopus `init_rdovaedec`: builds every layer from the arrays of `list`,
    /// in the order of `LAYERS`. Fails at the first layer whose arrays are
    /// missing, have the wrong size or are malformed; then nothing is built.
    pub fn init(list: &WeightList<'w>) -> Result<Self, Error> {
        Ok(RdovaeDec {
            dec_dense1: LAYERS[0].linear(list)?,
            dec_glu1: LAYERS[1].linear(list)?,
            dec_glu2: LAYERS[2].linear(list)?,
            dec_glu3: LAYERS[3].linear(list)?,
            dec_glu4: LAYERS[4].linear(list)?,
            dec_glu5: LAYERS[5].linear(list)?,
            dec_hidden_init: LAYERS[6].linear(list)?,
            dec_output: LAYERS[7].linear(list)?,
            dec_conv_dense1: LAYERS[8].linear(list)?,
            dec_conv_dense2: LAYERS[9].linear(list)?,
            dec_conv_dense3: LAYERS[10].linear(list)?,
            dec_conv_dense4: LAYERS[11].linear(list)?,
            dec_conv_dense5: LAYERS[12].linear(list)?,
            dec_gru_init: LAYERS[13].linear(list)?,
            dec_gru1_input: LAYERS[14].linear(list)?,
            dec_gru1_recurrent: LAYERS[15].linear(list)?,
            dec_gru2_input: LAYERS[16].linear(list)?,
            dec_gru2_recurrent: LAYERS[17].linear(list)?,
            dec_gru3_input: LAYERS[18].linear(list)?,
            dec_gru3_recurrent: LAYERS[19].linear(list)?,
            dec_gru4_input: LAYERS[20].linear(list)?,
            dec_gru4_recurrent: LAYERS[21].linear(list)?,
            dec_gru5_input: LAYERS[22].linear(list)?,
            dec_gru5_recurrent: LAYERS[23].linear(list)?,
            dec_conv1: LAYERS[24].linear(list)?,
            dec_conv2: LAYERS[25].linear(list)?,
            dec_conv3: LAYERS[26].linear(list)?,
            dec_conv4: LAYERS[27].linear(list)?,
            dec_conv5: LAYERS[28].linear(list)?,
        })
    }

    /// Every layer, in the order of `LAYERS`.
    pub fn layers(&self) -> [Layer<'_, 'w>; 29] {
        [
            Layer::Linear(&self.dec_dense1),
            Layer::Linear(&self.dec_glu1),
            Layer::Linear(&self.dec_glu2),
            Layer::Linear(&self.dec_glu3),
            Layer::Linear(&self.dec_glu4),
            Layer::Linear(&self.dec_glu5),
            Layer::Linear(&self.dec_hidden_init),
            Layer::Linear(&self.dec_output),
            Layer::Linear(&self.dec_conv_dense1),
            Layer::Linear(&self.dec_conv_dense2),
            Layer::Linear(&self.dec_conv_dense3),
            Layer::Linear(&self.dec_conv_dense4),
            Layer::Linear(&self.dec_conv_dense5),
            Layer::Linear(&self.dec_gru_init),
            Layer::Linear(&self.dec_gru1_input),
            Layer::Linear(&self.dec_gru1_recurrent),
            Layer::Linear(&self.dec_gru2_input),
            Layer::Linear(&self.dec_gru2_recurrent),
            Layer::Linear(&self.dec_gru3_input),
            Layer::Linear(&self.dec_gru3_recurrent),
            Layer::Linear(&self.dec_gru4_input),
            Layer::Linear(&self.dec_gru4_recurrent),
            Layer::Linear(&self.dec_gru5_input),
            Layer::Linear(&self.dec_gru5_recurrent),
            Layer::Linear(&self.dec_conv1),
            Layer::Linear(&self.dec_conv2),
            Layer::Linear(&self.dec_conv3),
            Layer::Linear(&self.dec_conv4),
            Layer::Linear(&self.dec_conv5),
        ]
    }
}