EmbeddingLayer class

A layer that turns a 1D vector of integer indices into a 2D matrix of dense vectors.

This layer is the standard first step for processing a single sequence of text for a Natural Language Processing (NLP) task.

• Input: A Tensor<Vector> where the vector contains integer indices representing a single sequence of words.
• Output: A Tensor<Matrix> representing the sequence of embedding vectors, with a shape of [sequence_length, embeddingDimension].

Inheritance

• Object
• Layer
• EmbeddingLayer

Constructors

EmbeddingLayer(int vocabularySize, int embeddingDimension)

Properties

embeddingDimension ↔ int

getter/setter pair

embeddings ↔ Tensor<Matrix>

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

vocabularySize ↔ int

getter/setter pair

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