Sequence-pooling layer for rank-2 inputs (sequence_length, features). More...

#include <pooling_layer_3d.h>

Inheritance diagram for opennn::Pooling3d:

Public Member Functions
	Pooling3d (const Shape &input_shape={0, 0}, const PoolingMethod &pooling_method=PoolingMethod::MaxPooling, const string &label="sequence_pooling_layer")
	Constructs a Pooling3d layer.

Shape	get_input_shape () const override
	Returns the per-sample input shape (sequence_length, features).

Shape	get_output_shape () const override
	Returns the per-sample output shape.

Index	get_sequence_length () const
	Sequence (time) length of the input.

Index	get_input_features () const
	Number of features per time step.

PoolingMethod	get_pooling_method () const
	Configured pooling reduction method.

string	write_pooling_method () const
	Returns the canonical string name of the pooling method.

vector< Operator * >	get_operators () override
	Returns the single Pool3d operator that implements this layer.

vector< pair< Shape, Type > >	get_forward_specs (Index batch_size) const override
	Specifications of the forward intermediate buffers.

void	set (const Shape &input_shape, const PoolingMethod &pooling_method, const string &label)
	Re-initializes the layer.

void	set_input_shape (const Shape &new_input_shape) override
	Updates the input shape (sequence_length, features).

void	set_pooling_method (const PoolingMethod &new_pooling_method)
	Sets the pooling method directly.

void	set_pooling_method (const string &)
	Sets the pooling method by name.

void	back_propagate (ForwardPropagation &, BackPropagation &, size_t) const noexcept override
	Routes output gradients back to the corresponding sequence positions in InputDelta.

void	read_JSON_body (const Json *) override
	Reads the layer-specific JSON body (input shape and method).

void	write_JSON_body (JsonWriter &) const override
	Writes the layer-specific JSON body (input shape and method).

Public Member Functions inherited from opennn::Layer
virtual	~Layer ()=default
	Virtual destructor; subclasses are owned via unique_ptr<Layer>.

const string &	get_label () const
	Returns the user-assigned label of this layer.

const string &	get_name () const
	Returns the canonical type name of this layer.

LayerType	get_type () const
	Returns the LayerType enumerator for this layer.

virtual void	set_output_shape (const Shape &)
	Sets the per-sample output shape of this layer.

void	set_label (string new_label)
	Sets the human-readable label of this layer.

Index	get_parameters_number () const
	Total number of trainable parameters in this layer.

virtual vector< pair< Shape, Type > >	get_parameter_specs () const
	Specifications of the trainable parameter tensors owned by this layer.

virtual vector< pair< Shape, Type > >	get_state_specs () const
	Specifications of the persistent state tensors of this layer.

virtual vector< pair< Shape, Type > >	get_backward_specs (Index batch_size) const
	Specifications of the backward intermediate buffers for one batch.

vector< Shape >	get_parameter_shapes () const
	Shape-only view of get_parameter_specs().

vector< Shape >	get_state_shapes () const
	Shape-only view of get_state_specs().

vector< Shape >	get_forward_shapes (Index b) const
	Shape-only view of get_forward_specs() for batch size `b`.

vector< Shape >	get_backward_shapes (Index b) const
	Shape-only view of get_backward_specs() for batch size `b`.

vector< Type >	get_parameter_dtypes () const
	Dtype-only view of get_parameter_specs().

vector< Type >	get_forward_dtypes (Index b) const
	Dtype-only view of get_forward_specs() for batch size `b`.

vector< Type >	get_backward_dtypes (Index b) const
	Dtype-only view of get_backward_specs() for batch size `b`.

virtual Activation::Function	get_output_activation () const
	Activation function fused at the end of this layer, if any.

Index	get_inputs_number () const
	Total number of scalar inputs per sample (product of input dims).

Index	get_outputs_number () const
	Total number of scalar outputs per sample (product of output dims).

virtual void	forward_propagate (ForwardPropagation &fp, size_t layer, bool is_training) noexcept
	Forward pass: reads inputs from `fp` and writes outputs into `fp`.

virtual void	from_JSON (const JsonDocument &document)
	Loads the layer configuration (hyperparameters) from JSON.

virtual void	load_state_from_JSON (const JsonDocument &document)
	Loads parameter and state tensors from a JSON document.

virtual void	to_JSON (JsonWriter &writer) const
	Writes the layer configuration to JSON.

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

bool	get_is_trainable () const
	Whether this layer has trainable parameters.

Type	get_compute_dtype () const
	Numerical type used for forward/backward computation.

void	set_compute_dtype (Type new_compute_dtype)
	Sets the compute dtype and triggers on_compute_dtype_changed().

virtual void	on_compute_dtype_changed ()
	Hook invoked after set_compute_dtype() mutates the dtype.

virtual float *	link_parameters (float *pointer)
	Wires this layer's parameter TensorViews onto an external buffer.

virtual float *	link_states (float *pointer)
	Wires this layer's state TensorViews onto an external buffer.

vector< TensorView > &	get_parameter_views ()
	Mutable access to this layer's parameter TensorViews.

const vector< TensorView > &	get_parameter_views () const
	Read-only access to this layer's parameter TensorViews.

vector< TensorView > &	get_state_views ()
	Mutable access to this layer's state TensorViews.

const vector< TensorView > &	get_state_views () const
	Read-only access to this layer's state TensorViews.

void	redistribute_parameters_to_operators ()
	Forwards the current parameter views down to each composing Operator.

void	redistribute_parameter_gradients_to_operators (vector< TensorView > &gradient_views)
	Forwards externally provided gradient views down to each Operator.

void	redistribute_states_to_operators ()
	Forwards the current state views down to each composing Operator.

Additional Inherited Members
Protected Member Functions inherited from opennn::Layer
	Layer ()=default
	Default constructor; only invoked by subclasses.

float *	link_views (float pointer, const vector< Shape > &shapes, vector< TensorView > &views, const char tag) const
	Builds `views` over a contiguous float buffer using `shapes`.

void	distribute_to_operators (vector< TensorView > &views, void(Operator::link)(const vector< TensorView > &), vector< pair< Shape, Type > >(Operator::specs)() const)
	Generic helper used by the redistribute_*_to_operators() routines.

Protected Attributes inherited from opennn::Layer
string	label = "my_layer"
	User-visible label for this layer instance (default "my_layer").

string	name = "layer"
	Canonical type name set by the subclass (e.g. "dense").

LayerType	layer_type = LayerType::Dense
	Layer type tag set by the subclass.

bool	is_trainable = true
	True if the layer has parameters that participate in training.

bool	is_first_layer = false
	True if this layer is the network's input layer.

Type	compute_dtype = Type::FP32
	Numerical type used for forward and backward computation.

vector< TensorView >	parameters
	Parameter TensorViews bound to the network's parameter arena.

vector< TensorView >	states
	State TensorViews bound to the network's state arena.

vector< unique_ptr< Layer > >	layers
	Sub-layers, when this layer is itself a composite.

Detailed Description

Sequence-pooling layer for rank-2 inputs (sequence_length, features).

Reduces along the sequence axis using either max or average pooling and outputs a single feature vector per sample. Reuses PoolingMethod from pooling_layer.h.

Constructor & Destructor Documentation

◆ Pooling3d()

opennn::Pooling3d::Pooling3d	(	const Shape &	input_shape = {0, 0},
		const PoolingMethod &	pooling_method = PoolingMethod::MaxPooling,
		const string &	label = "sequence_pooling_layer" )

Constructs a Pooling3d layer.

Parameters

input_shape	Per-sample input shape (sequence_length, features).
pooling_method	Reduction method applied along the sequence axis.
label	Human-readable label assigned to this layer.

Member Function Documentation

◆ back_propagate()

void opennn::Pooling3d::back_propagate	(	ForwardPropagation &	,
		BackPropagation &	,
		size_t	) const

overridevirtualnoexcept

Routes output gradients back to the corresponding sequence positions in InputDelta.

Receives the forward intermediates, the BackPropagation buffer and this layer's index inside the network.

Reimplemented from opennn::Layer.

◆ get_forward_specs()

vector< pair< Shape, Type > > opennn::Pooling3d::get_forward_specs ( Index batch_size ) const

overridevirtual

Specifications of the forward intermediate buffers.

Parameters

batch_size Batch size used for sizing.

Returns: Specs for Input, MaximalIndices and Output slots.

Reimplemented from opennn::Layer.

◆ get_input_features()

Index opennn::Pooling3d::get_input_features ( ) const

inline

Number of features per time step.

◆ get_input_shape()

Shape opennn::Pooling3d::get_input_shape ( ) const

inlineoverridevirtual

Returns the per-sample input shape (sequence_length, features).

Implements opennn::Layer.

◆ get_operators()

vector< Operator * > opennn::Pooling3d::get_operators ( )

inlineoverridevirtual

Returns the single Pool3d operator that implements this layer.

Reimplemented from opennn::Layer.

◆ get_output_shape()

Shape opennn::Pooling3d::get_output_shape ( ) const

overridevirtual

Returns the per-sample output shape.

Returns: Shape with a single feature axis (sequence reduced away).

Implements opennn::Layer.

◆ get_pooling_method()

PoolingMethod opennn::Pooling3d::get_pooling_method ( ) const

inline

Configured pooling reduction method.

◆ get_sequence_length()

Index opennn::Pooling3d::get_sequence_length ( ) const

inline

Sequence (time) length of the input.

◆ read_JSON_body()

void opennn::Pooling3d::read_JSON_body ( const Json * )

overridevirtual

Reads the layer-specific JSON body (input shape and method).

Reimplemented from opennn::Layer.

◆ set()

void opennn::Pooling3d::set	(	const Shape &	input_shape,
		const PoolingMethod &	pooling_method,
		const string &	label )

Re-initializes the layer.

Parameters

input_shape	Per-sample input shape (sequence_length, features).
pooling_method	Reduction method.
label	Human-readable label.

◆ set_input_shape()

void opennn::Pooling3d::set_input_shape ( const Shape & new_input_shape )

inlineoverridevirtual

Updates the input shape (sequence_length, features).

Parameters

new_input_shape New per-sample input shape.

Reimplemented from opennn::Layer.

◆ set_pooling_method() [1/2]

void opennn::Pooling3d::set_pooling_method ( const PoolingMethod & new_pooling_method )

inline

Sets the pooling method directly.

Parameters

new_pooling_method New reduction method enum.

◆ set_pooling_method() [2/2]

void opennn::Pooling3d::set_pooling_method ( const string & )

Sets the pooling method by name.

Receives "MaxPooling" or "AveragePooling".

◆ write_JSON_body()

void opennn::Pooling3d::write_JSON_body ( JsonWriter & ) const

overridevirtual

Writes the layer-specific JSON body (input shape and method).

Reimplemented from opennn::Layer.

◆ write_pooling_method()

string opennn::Pooling3d::write_pooling_method ( ) const

Returns the canonical string name of the pooling method.

Returns: "MaxPooling" or "AveragePooling".

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Pooling3d()

Member Function Documentation

◆ back_propagate()

◆ get_forward_specs()

◆ get_input_features()

◆ get_input_shape()

◆ get_operators()

◆ get_output_shape()

◆ get_pooling_method()

◆ get_sequence_length()

◆ read_JSON_body()

◆ set()

◆ set_input_shape()

◆ set_pooling_method() [1/2]

◆ set_pooling_method() [2/2]

◆ write_JSON_body()

◆ write_pooling_method()