tiny_dnn  1.0.0
A header only, dependency-free deep learning framework in C++11
Public Member Functions | Friends | List of all members
tiny_dnn::sequential Class Reference

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

#include <nodes.h>

Inheritance diagram for tiny_dnn::sequential:
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Public Member Functions

void backward (const std::vector< tensor_t > &first) override
 propagate gradient More...
 
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
 
layeroperator[] (size_t index)
 
const layeroperator[] (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_tnodes_
 

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
firstinput : data vectors
worker_index: id of worker-task

Implements tiny_dnn::nodes.


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