tiny_dnn::sequential Class Reference

single-input, single-output feedforward network More...

#include <nodes.h>

Inheritance diagram for tiny_dnn::sequential:

Collaboration diagram for tiny_dnn::sequential:

Public Member Functions
void	backward (const std::vector< tensor_t > &first) override
	propagate gradient
std::vector< tensor_t >	forward (const std::vector< tensor_t > &first) override
template<typename T >
void	add (T &&layer)
void	check_connectivity ()
template<typename InputArchive >
void	load_connections (InputArchive &ia)
template<typename OutputArchive >
void	save_connections (OutputArchive &) const
Public Member Functions inherited from tiny_dnn::nodes
virtual void	update_weights (optimizer *opt, int batch_size)
	update weights and clear all gradients
virtual void	setup (bool reset_weight)
	setup all weights, must be called before forward/backward
void	clear_grads ()
size_t	size () const
iterator	begin ()
iterator	end ()
const_iterator	begin () const
const_iterator	end () const
layer *	operator[] (size_t index)
const layer *	operator[] (size_t index) const
serial_size_t	in_data_size () const
serial_size_t	out_data_size () const
template<typename T >
const T &	at (size_t index) const
template<typename T >
T &	at (size_t index)
virtual float_t	target_value_min (int out_channel=0) const
virtual float_t	target_value_max (int out_channel=0) const
void	save (std::ostream &os) const
void	load (std::istream &is)
virtual void	load (const std::vector< float_t > &vec)
void	label2vec (const label_t *t, serial_size_t num, std::vector< vec_t > *vec) const
template<typename OutputArchive >
void	save_model (OutputArchive &oa) const
template<typename InputArchive >
void	load_model (InputArchive &ia)
template<typename OutputArchive >
void	save_weights (OutputArchive &oa) const
template<typename InputArchive >
void	load_weights (InputArchive &ia)

Friends
class	nodes

Additional Inherited Members
Public Types inherited from tiny_dnn::nodes
typedef std::vector< layerptr_t >::iterator	iterator
typedef std::vector< layerptr_t >::const_iterator	const_iterator
Protected Member Functions inherited from tiny_dnn::nodes
template<typename T >
void	push_back (T &&node)
template<typename T >
void	push_back (std::shared_ptr< T > node)
std::vector< tensor_t >	reorder_for_layerwise_processing (const std::vector< tensor_t > &input)
template<typename T >
void	push_back_impl (T &&node, std::true_type)
template<typename T >
void	push_back_impl (T &&node, std::false_type)
Protected Attributes inherited from tiny_dnn::nodes
std::vector< std::shared_ptr< layer > >	own_nodes_
std::vector< layerptr_t >	nodes_

Detailed Description

single-input, single-output feedforward network

Member Function Documentation

backward()

void tiny_dnn::sequential::backward ( const std::vector< tensor_t > &  first )

inlineoverridevirtual

propagate gradient

Parameters

first	: gradient of cost function(dE/dy)
worker_index	: id of worker-task

Implements tiny_dnn::nodes.

forward()

std::vector< tensor_t > tiny_dnn::sequential::forward ( const std::vector< tensor_t > &  first )

inlineoverridevirtual

Parameters

first	input : data vectors
worker_index	: id of worker-task

Implements tiny_dnn::nodes.

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

• tiny_dnn/nodes.h