NNFS::RMSProp Class Reference

Root Mean Square Propagation optimizer. More...

#include <RMSProp.hpp>

Inheritance diagram for NNFS::RMSProp:

Public Member Functions
	RMSProp (double lr=1e-3, double decay=1e-3, double epsilon=1e-7, double rho=.9)
	Construct a new RMSProp object.
void	update_params (std::shared_ptr< Dense > &layer)
	Update the parameters of the layer.
Public Member Functions inherited from NNFS::Optimizer
	Optimizer (double lr, double decay)
	Construct a new Optimizer object.
virtual	~Optimizer ()=default
	Basic destructor.
virtual void	update_params (std::shared_ptr< Dense > &layer)=0
	Update the parameters of the layer.
void	pre_update_params ()
	Pre-update parameters (e.g. learning rate decay)
void	post_update_params ()
	Post-update parameters (e.g. increase iteration count)
double &	current_lr ()
	Get the current learning rate.
int &	iterations ()
	Get current iteration count.

Additional Inherited Members
Protected Attributes inherited from NNFS::Optimizer
const double	_lr
double	_current_lr
int	_iterations
double	_decay

Detailed Description

Root Mean Square Propagation optimizer.

This class implements the Root Mean Square Propagation (RMSProp) optimizer.

Constructor & Destructor Documentation

RMSProp()

NNFS::RMSProp::RMSProp ( double  lr = 1e-3, double  decay = 1e-3, double  epsilon = 1e-7, double  rho = .9  )

inline

Construct a new RMSProp object.

Parameters

lr	Learning rate (default: 1e-3)
decay	Learning rate decay (default: 1e-3)
epsilon	Epsilon - to avoid division by zero (default: 1e-7)
rho	RMSProp uses "rho" to calculate an exponentially weighted average over the square of the gradients. (default: .9)

Member Function Documentation

update_params()

void NNFS::RMSProp::update_params ( std::shared_ptr< Dense > &  layer )

inlinevirtual

Update the parameters of the layer.

Parameters

[in,out]

layer

Layer to update

Implements NNFS::Optimizer.

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

• include/NNFS/Optimizer/RMSProp.hpp