pub struct LayerNorm {
pub n_features: usize,
pub gamma: Vec<f64>,
pub beta: Vec<f64>,
pub epsilon: f64,
}Expand description
Layer normalisation applied to each time step independently.
Normalises a feature vector of length n_features to zero mean and unit
variance, then applies learnable scale (gamma) and bias (beta).
Fields§
§n_features: usizeNumber of features.
gamma: Vec<f64>Learnable scale parameter.
beta: Vec<f64>Learnable shift parameter.
epsilon: f64Numerical stability constant.
Implementations§
Trait Implementations§
Auto Trait Implementations§
impl Freeze for LayerNorm
impl RefUnwindSafe for LayerNorm
impl Send for LayerNorm
impl Sync for LayerNorm
impl Unpin for LayerNorm
impl UnsafeUnpin for LayerNorm
impl UnwindSafe for LayerNorm
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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
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