TransformerEncoderBlock class

Implements a single Transformer Encoder Block.

This is the main repeating component of the Transformer's encoder. It consists of two primary sub-layers: a Multi-Head Self-Attention mechanism and a position-wise Feed-Forward Network. Each sub-layer is followed by a residual connection and a layer normalization step.

By stacking these blocks, the model can build an increasingly deep and context-aware representation of the input sequence.

Inheritance

• Object
• Layer
• TransformerEncoderBlock

Constructors

TransformerEncoderBlock(int dModel, int numHeads, int dff)

Properties

dff ↔ int

getter/setter pair

dModel ↔ int

getter/setter pair

ffn ↔ SNetwork

getter/setter pair

hashCode → int

The hash code for this object.

no setter, inherited

layerNorm1 ↔ LayerNormalization

getter/setter pair

layerNorm2 ↔ LayerNormalization

getter/setter pair

mha ↔ MultiHeadAttention

getter/setter pair

name ↔ String

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

getter/setter pair, override-getter

numHeads ↔ int

getter/setter pair

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