Class ActivationLayer<T>

java.lang.Object

org.episteme.core.mathematics.ml.neural.layers.ActivationLayer<T>

Type Parameters:

T - data type

All Implemented Interfaces:

Serializable, Layer<T>

Direct Known Subclasses:

ReLU

public class ActivationLayer<T>
extends Object
implements Layer<T>

Generic activation layer that applies a specified ActivationFunction.

Since:

2.0

Author:

Silvere Martin-Michiellot, Gemini AI (Google DeepMind)

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
ActivationLayer(String functionName)
ActivationLayer(ActivationFunction function)

Method Summary

Modifier and Type	Method	Description
GraphNode<T>	forward(GraphNode<T> input)	Performs a forward pass using explicit autograd nodes.
ActivationFunction	getFunction()
Map<String, GraphNode<T>>	getParameters()	Returns the learnable parameters of this layer.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface Layer

forward, getGradients, setTraining

Constructor Details

ActivationLayer

public ActivationLayer(ActivationFunction function)

ActivationLayer

public ActivationLayer(String functionName)

Method Details

forward

public GraphNode<T> forward(GraphNode<T> input)

Description copied from interface: Layer

Performs a forward pass using explicit autograd nodes.

Specified by:

forward in interface Layer<T>

Parameters:

input - the input node.

Returns:

the transformed output node.

getParameters

public Map<String, GraphNode<T>> getParameters()

Description copied from interface: Layer

Returns the learnable parameters of this layer. Keys should be unique within the layer (e.g., "weights", "bias").

Specified by:

getParameters in interface Layer<T>

Returns:

a map of parameter graph nodes.

getFunction

public ActivationFunction getFunction()