bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType > Struct Template Reference

#include <stochastic_gradient_descent.h>

Inheritance diagram for bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >:

Collaboration diagram for bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >:

Public Types
using	value_type = bc::traits::conditional_detected_t< bc::traits::query_value_type, ValueType, ValueType >

Public Member Functions
template<class... Args>
	Optimizer (Args &&...)
template<class TensorX , class Gradients >
void	update (TensorX &tensor, Gradients &&delta)
void	set_learning_rate (value_type lr)
Public Member Functions inherited from bc::nn::Optimizer_Base
void	save (Layer_Loader &loader, std::string name) const
void	load (Layer_Loader &loader, std::string name)

Public Attributes
value_type	learning_rate = 0.003

Member Typedef Documentation

value_type

template<class ValueType >

using bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >::value_type = bc::traits::conditional_detected_t< bc::traits::query_value_type, ValueType, ValueType>

Constructor & Destructor Documentation

Optimizer()

template<class ValueType >

template<class... Args>

bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >::Optimizer ( Args &&  ... )

inline

Member Function Documentation

set_learning_rate()

template<class ValueType >

void bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >::set_learning_rate ( value_type  lr )

inline

update()

template<class ValueType >

template<class TensorX , class Gradients >

void bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >::update ( TensorX &  tensor, Gradients &&  delta  )

inline

Member Data Documentation

learning_rate

template<class ValueType >

value_type bc::nn::Stochastic_Gradient_Descent::Optimizer< ValueType >::learning_rate = 0.003

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

• blackcat/neural_networks/optimzers/stochastic_gradient_descent.h