tiny_dnn 1.0.0
A header only, dependency-free deep learning framework in C++11
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single-input, single-output feedforward network More...
#include <nodes.h>
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 |
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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 | |
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typedef std::vector< layerptr_t >::iterator | iterator |
typedef std::vector< layerptr_t >::const_iterator | const_iterator |
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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) |
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std::vector< std::shared_ptr< layer > > | own_nodes_ |
std::vector< layerptr_t > | nodes_ |
single-input, single-output feedforward network
propagate gradient
first | : gradient of cost function(dE/dy) |
worker_index | : id of worker-task |
Implements tiny_dnn::nodes.
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inlineoverridevirtual |
first | input : data vectors |
worker_index | : id of worker-task |
Implements tiny_dnn::nodes.