Struct burn_core::nn::transformer::TransformerEncoderConfig

pub struct TransformerEncoderConfig {
    pub d_model: usize,
    pub d_ff: usize,
    pub n_heads: usize,
    pub n_layers: usize,
    pub dropout: f64,
    pub norm_first: bool,
    pub quiet_softmax: bool,
    pub initializer: Initializer,
}

Configuration to create a Transformer Encoder layer.

Fields

d_model: usize

The size of the model.

d_ff: usize

The size of the position-wise feed-forward network.

n_heads: usize

The number of attention heads.

n_layers: usize

The number of layers.

dropout: f64

The dropout rate. Default: 0.1

norm_first: bool

Layer norm will be applied first instead of after the other modules.

quiet_softmax: bool

Use “quiet softmax” instead of regular softmax.

• Usage may improve performance by allowing attention heads to deposit no information (if the sequence contains no information relevant to that head).
• Usage may reduce the entropy of weights in the model, enhancing quantization and compression.

Reference: https://www.evanmiller.org/attention-is-off-by-one.html

initializer: Initializer

The type of function used to initialize neural network parameters

Implementations

impl TransformerEncoderConfig

pub fn new(d_model: usize, d_ff: usize, n_heads: usize, n_layers: usize) -> Self

Create a new instance of the config.

impl TransformerEncoderConfig

pub fn with_dropout(self, dropout: f64) -> Self

The dropout rate. Default: 0.1

pub fn with_norm_first(self, norm_first: bool) -> Self

Layer norm will be applied first instead of after the other modules.

pub fn with_quiet_softmax(self, quiet_softmax: bool) -> Self

Use “quiet softmax” instead of regular softmax.

pub fn with_initializer(self, initializer: Initializer) -> Self

The type of function used to initialize neural network parameters

impl TransformerEncoderConfig

pub fn init<B: Backend>(&self) -> TransformerEncoder<B>

Initialize a new transformer encoder module.

pub fn init_with<B: Backend>( &self, record: TransformerEncoderRecord<B> ) -> TransformerEncoder<B>

Initialize a new transformer encoder module with a record.

Trait Implementations

impl Clone for TransformerEncoderConfig

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Config for TransformerEncoderConfig

fn save<P: AsRef<Path>>(&self, file: P) -> Result<()>

Saves the configuration to a file.

fn load<P: AsRef<Path>>(file: P) -> Result<Self, ConfigError>

Loads the configuration from a file.

fn load_binary(data: &[u8]) -> Result<Self, ConfigError>

Loads the configuration from a binary buffer.

impl<'de> Deserialize<'de> for TransformerEncoderConfig

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for TransformerEncoderConfig

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

Formats the value using the given formatter.

impl Serialize for TransformerEncoderConfig

fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>where S: Serializer,

Serialize this value into the given Serde serializer.