bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor > Struct Template Reference

#include <layer_base.h>

Inheritance diagram for bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >:

Collaboration diagram for bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >:

Public Types
using	value_type = typename InputTensorDescriptor::value_type
using	system_tag = typename InputTensorDescriptor::system_tag
using	allocator_type = typename InputTensorDescriptor::allocator_type
using	input_tensor_dim = typename InputTensorDescriptor::tensor_dim
using	shape_type = bc::Dim< input_tensor_dim::value >
using	input_tensor_type = typename InputTensorDescriptor::type
using	batched_input_tensor_type = typename InputTensorDescriptor::batched_type
using	output_value_type = typename OutputTensorDescriptor::value_type
using	output_system_tag = typename OutputTensorDescriptor::system_tag
using	output_allocator_type = typename OutputTensorDescriptor::allocator_type
using	output_tensor_dim = typename OutputTensorDescriptor::tensor_dim
using	output_shape_type = bc::Dim< output_tensor_dim::value >
using	output_tensor_type = typename OutputTensorDescriptor::type
using	batched_output_tensor_type = typename OutputTensorDescriptor::batched_type
Public Types inherited from bc::nn::Layer_Output_Base< OutputTensorDescriptor >
using	output_value_type = typename OutputTensorDescriptor::value_type
using	output_system_tag = typename OutputTensorDescriptor::system_tag
using	output_allocator_type = typename OutputTensorDescriptor::allocator_type
using	output_tensor_dim = typename OutputTensorDescriptor::tensor_dim
using	output_shape_type = bc::Dim< output_tensor_dim::value >
using	output_tensor_type = typename OutputTensorDescriptor::type
using	batched_output_tensor_type = typename OutputTensorDescriptor::batched_type
using	next_layer_type = Layer_Input_Base< OutputTensorDescriptor >
using	output_value_type = typename OutputTensorDescriptor::value_type
using	output_system_tag = typename OutputTensorDescriptor::system_tag
using	output_allocator_type = typename OutputTensorDescriptor::allocator_type
using	output_tensor_dim = typename OutputTensorDescriptor::tensor_dim
using	output_shape_type = typename OutputTensorDescriptor::shape_type
using	output_tensor_type = typename OutputTensorDescriptor::tensor_type
using	batched_output_tensor_type = typename OutputTensorDescriptor::batched_type
using	next_layer_type = Layer_Input_Base< OutputTensorDescriptor >

Public Member Functions
	Layer_Base (std::string classname, shape_type input_shape, output_shape_type output_shape)
	m_classname should be initialized by supplying __func__ to the first argument of the Layer_Base. More...
	Layer_Base (std::string classname, shape_type input_shape)
virtual	~Layer_Base ()
virtual output_shape_type	get_output_shape () const
virtual shape_type	get_input_shape () const
auto	get_batched_input_shape () const
auto	get_batched_output_shape () const
bc::size_t	input_size () const
bc::size_t	output_size () const
bc::size_t	batch_size () const
bc::size_t	batched_input_size () const
bc::size_t	batched_output_size () const
void	set_batch_size (int batch_size)
virtual void	set_batch_size_hook (int batch_size)
void	set_learning_rate (value_type learning_rate)
virtual void	set_learning_rate_hook (value_type learning_rate)
auto	get_learning_rate () const
auto	get_batched_learning_rate () const
virtual void	save (Layer_Loader &) const
virtual void	save_from_cache (Layer_Loader &, const Cache &) const
virtual void	load (Layer_Loader &)
virtual void	load_to_cache (Layer_Loader &, const Cache &)
void	copy_training_data_to_single_predict (Cache &, int batch_index)
void	update_weights ()
void	clear_bp_storage (Cache &)
const std::string &	classname () const
	Returns the derived_classes class namepse. More...
template<int ADL = 0>
std::string	get_string_architecture () const
virtual std::string	get_string_architecture_hook () const
auto	default_input_tensor_factory () const
auto	default_output_tensor_factory () const
auto	default_batched_input_tensor_factory () const
auto	default_batched_output_tensor_factory () const
Public Member Functions inherited from bc::nn::Layer_Input_Base< InputTensorDescriptor >
void	set_prev (prev_layer_type &prev)
input_shape_type	input_shape () const
const prev_layer_type &	prev_layer () const
prev_layer_type &	prev_layer ()
virtual	~Layer_Input_Base ()
void	set_prev (prev_layer_type &prev)
input_shape_type	input_shape () const
const prev_layer_type &	prev_layer () const
prev_layer_type &	prev_layer ()
virtual	~Layer_Input_Base ()
Public Member Functions inherited from bc::nn::Layer_Output_Base< OutputTensorDescriptor >
void	set_next (next_layer_type &next)
output_shape_type	output_shape () const
const next_layer_type &	next_layer () const
next_layer_type &	next_layer ()
virtual	~Layer_Output_Base ()
void	set_next (next_layer_type &next)
output_shape_type	output_shape () const
const next_layer_type &	next_layer () const
next_layer_type &	next_layer ()
virtual	~Layer_Output_Base ()

Static Public Member Functions
static std::string	parse_classname (std::string classname)

Static Public Attributes
static constexpr value_type	default_learning_rate = .01

Protected Attributes
shape_type	m_input_shape
output_shape_type	m_output_shape
Protected Attributes inherited from bc::nn::Layer_Input_Base< InputTensorDescriptor >
prev_layer_type *	m_prev_layer
input_shape_type	m_input_shape
Protected Attributes inherited from bc::nn::Layer_Output_Base< OutputTensorDescriptor >
next_layer_type *	m_next_layer = nullptr
bc::Dim< output_tensor_dim::value >	m_output_shape

Member Typedef Documentation

allocator_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::allocator_type = typename InputTensorDescriptor::allocator_type

batched_input_tensor_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::batched_input_tensor_type = typename InputTensorDescriptor::batched_type

batched_output_tensor_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::batched_output_tensor_type = typename OutputTensorDescriptor::batched_type

input_tensor_dim

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::input_tensor_dim = typename InputTensorDescriptor::tensor_dim

input_tensor_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::input_tensor_type = typename InputTensorDescriptor::type

output_allocator_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_allocator_type = typename OutputTensorDescriptor::allocator_type

output_shape_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_shape_type = bc::Dim<output_tensor_dim::value>

output_system_tag

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_system_tag = typename OutputTensorDescriptor::system_tag

output_tensor_dim

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_tensor_dim = typename OutputTensorDescriptor::tensor_dim

output_tensor_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_tensor_type = typename OutputTensorDescriptor::type

output_value_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_value_type = typename OutputTensorDescriptor::value_type

shape_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::shape_type = bc::Dim<input_tensor_dim::value>

system_tag

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::system_tag = typename InputTensorDescriptor::system_tag

value_type

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

using bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::value_type = typename InputTensorDescriptor::value_type

Constructor & Destructor Documentation

Layer_Base() [1/2]

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::Layer_Base ( std::string  classname, shape_type  input_shape, output_shape_type  output_shape  )

inline

m_classname should be initialized by supplying __func__ to the first argument of the Layer_Base.

parse_classname() will normalize the string as __func__ is compiler dependent.

Layer_Base() [2/2]

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::Layer_Base ( std::string  classname, shape_type  input_shape  )

inline

~Layer_Base()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::~Layer_Base ( )

inlinevirtual

Member Function Documentation

batch_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::size_t bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::batch_size ( ) const

inline

batched_input_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::size_t bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::batched_input_size ( ) const

inline

batched_output_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::size_t bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::batched_output_size ( ) const

inline

classname()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

const std::string& bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::classname ( ) const

inline

Returns the derived_classes class namepse.

Note: Architecture dependent

clear_bp_storage()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::clear_bp_storage ( Cache &  )

inline

copy_training_data_to_single_predict()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::copy_training_data_to_single_predict ( Cache &  , int  batch_index  )

inline

default_batched_input_tensor_factory()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::default_batched_input_tensor_factory ( ) const

inline

default_batched_output_tensor_factory()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::default_batched_output_tensor_factory ( ) const

inline

default_input_tensor_factory()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::default_input_tensor_factory ( ) const

inline

default_output_tensor_factory()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::default_output_tensor_factory ( ) const

inline

get_batched_input_shape()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_batched_input_shape ( ) const

inline

get_batched_learning_rate()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_batched_learning_rate ( ) const

inline

get_batched_output_shape()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_batched_output_shape ( ) const

inline

get_input_shape()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual shape_type bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_input_shape ( ) const

inlinevirtual

get_learning_rate()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

auto bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_learning_rate ( ) const

inline

get_output_shape()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual output_shape_type bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_output_shape ( ) const

inlinevirtual

get_string_architecture()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

template<int ADL = 0>

std::string bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_string_architecture ( ) const

inline

get_string_architecture_hook()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual std::string bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::get_string_architecture_hook ( ) const

inlinevirtual

input_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::size_t bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::input_size ( ) const

inline

load()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::load ( Layer_Loader &  )

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >, bc::nn::Convolution< SystemTag, ValueType, Optimizer >, bc::nn::Recurrent< SystemTag, ValueType, RecurrentNonLinearity >, and bc::nn::FeedForward< SystemTag, ValueType, Optimizer >.

load_to_cache()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::load_to_cache ( Layer_Loader &  , const Cache &    )

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >.

output_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

bc::size_t bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::output_size ( ) const

inline

parse_classname()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

static std::string bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::parse_classname ( std::string  classname )

inlinestatic

save()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::save ( Layer_Loader &  ) const

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >, bc::nn::Convolution< SystemTag, ValueType, Optimizer >, bc::nn::Recurrent< SystemTag, ValueType, RecurrentNonLinearity >, and bc::nn::FeedForward< SystemTag, ValueType, Optimizer >.

save_from_cache()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::save_from_cache ( Layer_Loader &  , const Cache &    ) const

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >.

set_batch_size()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::set_batch_size ( int  batch_size )

inline

set_batch_size_hook()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::set_batch_size_hook ( int  batch_size )

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >, bc::nn::Recurrent< SystemTag, ValueType, RecurrentNonLinearity >, and bc::nn::SoftMax< SystemTag, ValueType >.

set_learning_rate()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::set_learning_rate ( value_type  learning_rate )

inline

set_learning_rate_hook()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

virtual void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::set_learning_rate_hook ( value_type  learning_rate )

inlinevirtual

Reimplemented in bc::nn::LSTM< SystemTag, ValueType, Optimizer, ForgetGateNonlinearity, WriteGateNonlinearity, InputGateNonlinearity, OutputGateNonlinearity, CellStateNonLinearity >, and bc::nn::FeedForward< SystemTag, ValueType, Optimizer >.

update_weights()

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

void bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::update_weights ( )

inline

Member Data Documentation

default_learning_rate

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

constexpr value_type bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::default_learning_rate = .01

static

m_input_shape

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

shape_type bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::m_input_shape

protected

m_output_shape

template<class DerivedLayer, class InputTensorDescriptor, class OutputTensorDescriptor = InputTensorDescriptor>

output_shape_type bc::nn::Layer_Base< DerivedLayer, InputTensorDescriptor, OutputTensorDescriptor >::m_output_shape

protected

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

• blackcat/neural_networks/layers/layer_base.h