NNFS
Neural network library from scratch
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NNFS::ReLU Class Reference

ReLU activation function. More...

#include <ReLU.hpp>

Inheritance diagram for NNFS::ReLU:
[legend]

Public Member Functions

 ReLU ()
 Construct a new ReLU object.
 
void forward (Eigen::MatrixXd &out, const Eigen::MatrixXd &x) override
 Forward pass of the ReLU activation function.
 
void backward (Eigen::MatrixXd &out, const Eigen::MatrixXd &dx) override
 Backward pass of the ReLU activation function.
 
- Public Member Functions inherited from NNFS::Activation
 Activation (ActivationType activation_type)
 Construct a new Activation object.
 
- Public Member Functions inherited from NNFS::Layer
 Layer (LayerType type)
 Construct a new Layer object.
 
virtual ~Layer ()=default
 Basic destructor.
 
virtual void forward (Eigen::MatrixXd &out, const Eigen::MatrixXd &x)=0
 Forward pass of the layer.
 
virtual void backward (Eigen::MatrixXd &out, const Eigen::MatrixXd &dx)=0
 Backward pass of the layer.
 

Additional Inherited Members

- Public Attributes inherited from NNFS::Activation
ActivationType activation_type
 
- Public Attributes inherited from NNFS::Layer
LayerType type
 
- Protected Attributes inherited from NNFS::Activation
Eigen::MatrixXd _forward_input
 

Detailed Description

ReLU activation function.

This class implements the ReLU activation function.

Constructor & Destructor Documentation

◆ ReLU()

NNFS::ReLU::ReLU ( )
inline

Construct a new ReLU object.

Member Function Documentation

◆ backward()

void NNFS::ReLU::backward ( Eigen::MatrixXd &  out,
const Eigen::MatrixXd &  dx 
)
inlineoverridevirtual

Backward pass of the ReLU activation function.

Parameters
[out]outInput gradient
[in]dxOutput gradient

Implements NNFS::Layer.

◆ forward()

void NNFS::ReLU::forward ( Eigen::MatrixXd &  out,
const Eigen::MatrixXd &  x 
)
inlineoverridevirtual

Forward pass of the ReLU activation function.

Parameters
[out]outOutput of the ReLU activation function
[in]xInput to the ReLU activation function

Implements NNFS::Layer.


The documentation for this class was generated from the following file: