DenseLayer class

A standard, fully-connected neural network layer for 1D Vector data.

A DenseLayer implements the operation: activation(weights @ input + biases). It is the most common layer for processing flat feature vectors.

• Input: A Tensor<Vector> of shape [input_size].
• Output: A Tensor<Vector> of shape [output_size].

Inheritance

• Object
• Layer
• DenseLayer

Constructors

DenseLayer(int outputSize, {ActivationFunction? activation})

Properties

activation ↔ ActivationFunction?

getter/setter pair

biases ↔ 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

outputSize ↔ 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

weights ↔ Tensor<Matrix>

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<Vector>

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