Fully-connected layer with configurable activation, optional batch normalization and dropout. More...

#include <dense_layer.h>

Inheritance diagram for opennn::Dense:

Public Member Functions
	Dense (const Shape &={}, const Shape &={}, const string &="Tanh", bool=false, const string &="dense_layer")
	Constructs a dense layer with the given input/output shapes, activation, and batch-norm flag.

Shape	get_output_shape () const override
	Returns the layer output shape, derived from input shape and configured output features.

Index	get_input_features () const

Index	get_sequence_length () const

const ActivationOp::Function &	get_activation_function () const

ActivationOp::Function	get_output_activation () const override
	Returns the layer's output activation (Identity for most layers; overridden by Dense/Bounding).

bool	get_batch_normalization () const

float	get_momentum () const

vector< TensorSpec >	get_forward_specs (Index batch_size) const override
	Returns the tensor specs of intermediate forward buffers for a given batch size.

void	set (const Shape &={}, const Shape &={}, const string &="Tanh", bool=false, const string &="dense_layer")
	Reconfigures the layer with new shapes, activation, batch-normalization flag and label.

void	set_input_shape (const Shape &) override
	Sets the input shape; subclasses override to derive dependent dimensions.

void	set_output_shape (const Shape &) override
	Sets the output shape; subclasses override when the output is user-configurable.

void	on_compute_dtype_changed () override
	Subclass hook invoked when the compute dtype changes; default is no-op.

void	set_activation_function (const string &)
	Sets the activation function from its string name (e.g. "Tanh", "Logistic", "Linear").

void	set_batch_normalization (bool enable)
	Enables or disables batch normalization on the layer combination output.

void	set_dropout_rate (float new_dropout_rate)

void	set_momentum (float new_momentum)
	Sets the running-statistics momentum used by batch normalization.

void	read_JSON_body (const Json *) override
	Subclass hook reading the body section of the layer's JSON node.

string	write_expression (const vector< string > &input_names, const vector< string > &output_names) const override
	Returns a human-readable mathematical expression for this layer (empty by default).

Public Member Functions inherited from opennn::Layer
virtual	~Layer ()=default

const string &	get_label () const

const string &	get_name () const

LayerType	get_type () const

void	set_label (string new_label)

Index	get_parameters_number () const
	Returns the total number of trainable parameters owned by this layer.

const vector< Operator * > &	get_operators () const

virtual vector< TensorSpec >	get_parameter_specs () const
	Returns the tensor specs of trainable parameters; subclasses override.

virtual vector< TensorSpec >	get_state_specs () const
	Returns the tensor specs of persistent state (e.g. running mean/variance).

virtual vector< TensorSpec >	get_backward_specs (Index batch_size) const
	Returns the tensor specs of the backward workspace; empty for non-trainable layers.

virtual Shape	get_input_shape () const
	Returns the input shape stored by the layer.

Index	get_inputs_number () const

Index	get_outputs_number () const

virtual void	forward_propagate (ForwardPropagation &fp, size_t layer, bool is_training) noexcept
	Runs the forward pass by chaining the layer's operators in order.

virtual void	back_propagate (ForwardPropagation &fp, BackPropagation &bp, size_t i) const noexcept
	Runs the backward pass by chaining the layer's operators in reverse order.

virtual void	from_JSON (const JsonDocument &document)
	Restores layer configuration and parameters from a JSON document.

virtual void	load_state_from_JSON (const JsonDocument &document)
	Restores persistent state (e.g. running statistics) from a JSON document.

virtual void	to_JSON (JsonWriter &writer) const
	Serializes layer configuration and parameters to a JSON writer.

virtual void	write_JSON_body (JsonWriter &) const
	Subclass hook writing the body section of the layer's JSON node.

virtual void	print () const
	Prints a human-readable summary of the layer to standard output.

bool	get_is_trainable () const

Type	get_compute_dtype () const

void	set_compute_dtype (Type new_compute_dtype)
	Sets the compute dtype and notifies subclasses via on_compute_dtype_changed().

virtual float *	link_states (float *pointer)
	Binds the persistent-state region of the shared buffer to operator views.

float *	link_gradients (float *pointer, vector< TensorView > &gradient_views)
	Binds the gradient slice of the shared buffer to operator gradient views.

vector< TensorView > &	get_parameter_views ()

const vector< TensorView > &	get_parameter_views () const

void	redistribute_parameters_to_operators ()
	Re-binds operator parameter views after the parameter buffer has been resized or moved.

Additional Inherited Members
Protected Types inherited from opennn::Layer
enum	Forward { Input , Output }

enum	Backward { OutputDelta , InputDelta }

Protected Member Functions inherited from opennn::Layer
	Layer ()=default

	Layer (LayerType t, bool trainable=true)

float *	link_views_to_operators (vector< TensorView > &views, float pointer, vector< TensorSpec >(Operator::specs_fn)() const, void(Operator::*link_fn)(span< const TensorView >))

Protected Attributes inherited from opennn::Layer
string	label = "my_layer"

LayerType	layer_type = LayerType::Dense

bool	is_trainable = true

Shape	input_shape

Type	compute_dtype = Type::FP32

vector< TensorView >	parameters

vector< TensorView >	states

vector< Operator * >	operators

Detailed Description

Fully-connected layer with configurable activation, optional batch normalization and dropout.

Constructor & Destructor Documentation

◆ Dense()

opennn::Dense::Dense	(	const Shape &	= {},
		const Shape &	= {},
		const string &	= "Tanh",
		bool	= false,
		const string &	= "dense_layer" )

Constructs a dense layer with the given input/output shapes, activation, and batch-norm flag.

Member Function Documentation

◆ get_activation_function()

const ActivationOp::Function & opennn::Dense::get_activation_function ( ) const

inline

◆ get_batch_normalization()

bool opennn::Dense::get_batch_normalization ( ) const

inline

◆ get_forward_specs()

vector< TensorSpec > opennn::Dense::get_forward_specs ( Index batch_size ) const

overridevirtual

Returns the tensor specs of intermediate forward buffers for a given batch size.

Reimplemented from opennn::Layer.

◆ get_input_features()

Index opennn::Dense::get_input_features ( ) const

inline

◆ get_momentum()

float opennn::Dense::get_momentum ( ) const

inline

◆ get_output_activation()

ActivationOp::Function opennn::Dense::get_output_activation ( ) const

inlineoverridevirtual

Returns the layer's output activation (Identity for most layers; overridden by Dense/Bounding).

Reimplemented from opennn::Layer.

◆ get_output_shape()

Shape opennn::Dense::get_output_shape ( ) const

overridevirtual

Returns the layer output shape, derived from input shape and configured output features.

Implements opennn::Layer.

◆ get_sequence_length()

Index opennn::Dense::get_sequence_length ( ) const

inline

◆ on_compute_dtype_changed()

void opennn::Dense::on_compute_dtype_changed ( )

inlineoverridevirtual

Subclass hook invoked when the compute dtype changes; default is no-op.

Reimplemented from opennn::Layer.

◆ read_JSON_body()

void opennn::Dense::read_JSON_body ( const Json * )

overridevirtual

Subclass hook reading the body section of the layer's JSON node.

Reimplemented from opennn::Layer.

◆ set()

void opennn::Dense::set	(	const Shape &	= {},
		const Shape &	= {},
		const string &	= "Tanh",
		bool	= false,
		const string &	= "dense_layer" )

Reconfigures the layer with new shapes, activation, batch-normalization flag and label.

◆ set_activation_function()

void opennn::Dense::set_activation_function ( const string & )

Sets the activation function from its string name (e.g. "Tanh", "Logistic", "Linear").

◆ set_batch_normalization()

void opennn::Dense::set_batch_normalization ( bool enable )

Enables or disables batch normalization on the layer combination output.

◆ set_dropout_rate()

void opennn::Dense::set_dropout_rate ( float new_dropout_rate )

inline

◆ set_input_shape()

void opennn::Dense::set_input_shape ( const Shape & )

overridevirtual

Sets the input shape; subclasses override to derive dependent dimensions.

Reimplemented from opennn::Layer.

◆ set_momentum()

void opennn::Dense::set_momentum ( float new_momentum )

Sets the running-statistics momentum used by batch normalization.

◆ set_output_shape()

void opennn::Dense::set_output_shape ( const Shape & )

overridevirtual

Sets the output shape; subclasses override when the output is user-configurable.

Reimplemented from opennn::Layer.

◆ write_expression()

string opennn::Dense::write_expression	(	const vector< string > &	input_names,
		const vector< string > &	output_names ) const

overridevirtual

Returns a human-readable mathematical expression for this layer (empty by default).

Parameters

input_names	Names assigned to the inputs.
output_names	Names assigned to the outputs.

Reimplemented from opennn::Layer.

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Dense()

Member Function Documentation

◆ get_activation_function()

◆ get_batch_normalization()

◆ get_forward_specs()

◆ get_input_features()

◆ get_momentum()

◆ get_output_activation()

◆ get_output_shape()

◆ get_sequence_length()

◆ on_compute_dtype_changed()

◆ read_JSON_body()

◆ set()

◆ set_activation_function()

◆ set_batch_normalization()

◆ set_dropout_rate()

◆ set_input_shape()

◆ set_momentum()

◆ set_output_shape()

◆ write_expression()