Element-wise addition layer that sums two input tensors of identical shape (residual connections). More...

#include <addition_layer.h>

Inheritance diagram for opennn::Addition:

Public Member Functions
	Addition (const Shape &={}, const string &="")
	Constructs an addition layer for the given input shape and label.

Shape	get_output_shape () const override
	Returns the output shape; subclasses must implement this to expose their geometry.

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

void	set (const Shape &, const string &)
	Reconfigures the layer with a new input shape and label.

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

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

const string &	get_label () const

const string &	get_name () const

LayerType	get_type () const

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

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_forward_specs (Index batch_size) const
	Returns the tensor specs of the forward workspace; defaults to a single output tensor.

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

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

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

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

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

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

Element-wise addition layer that sums two input tensors of identical shape (residual connections).

Constructor & Destructor Documentation

◆ Addition()

opennn::Addition::Addition	(	const Shape &	= {},
		const string &	= "" )

Constructs an addition layer for the given input shape and label.

Member Function Documentation

◆ get_backward_specs()

vector< TensorSpec > opennn::Addition::get_backward_specs ( Index batch_size ) const

overridevirtual

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

Reimplemented from opennn::Layer.

◆ get_output_shape()

Shape opennn::Addition::get_output_shape ( ) const

inlineoverridevirtual

Returns the output shape; subclasses must implement this to expose their geometry.

Implements opennn::Layer.

◆ set()

void opennn::Addition::set	(	const Shape &	,
		const string &	)

Reconfigures the layer with a new input shape and label.

◆ set_input_shape()

void opennn::Addition::set_input_shape ( const Shape & shape )