LayerNormalization class

A Layer Normalization layer for 2D Matrix data.

This layer normalizes its inputs across the feature dimension for each individual data sample (row) in a batch. It is a critical component in the Transformer architecture.

Inheritance

• Object
• Layer
• LayerNormalization

Constructors

LayerNormalization({double epsilon = 1e-5})

Properties

beta ↔ Tensor<Vector>

getter/setter pair

epsilon ↔ double

getter/setter pair

gamma ↔ Tensor<Vector>

getter/setter pair

hashCode → int

The hash code for this object.

no setter, inherited

name ↔ String

A user-friendly name for the layer (e.g., 'dense', 'lstm').

getter/setter pair, override-getter

parameters → List<Tensor>

A list of all trainable tensors (weights and biases) in the layer.

no setter, override

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

build(Tensor input) → void

Initializes the layer's parameters based on the shape of the first input.

override

call(Tensor input) → Tensor

The public, callable interface for the layer.

inherited

forward(Tensor input) → Tensor<Matrix>

The core logic of the layer's transformation.

override

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited