#include <pooling_layer.h>

Inheritance diagram for PoolingLayer:

Public Types
enum class	PoolingMethod { NoPooling , MaxPooling , AveragePooling }
	Enumeration of available methods for pooling data. More...

Public Types inherited from Layer
enum class	Type { Scaling , Convolutional , Perceptron , Pooling , Probabilistic , LongShortTermMemory , Recurrent , Unscaling , Bounding }
	This enumeration represents the possible types of layers. More...

Public Member Functions
	PoolingLayer ()

	PoolingLayer (const Tensor< Index, 1 > &)

	PoolingLayer (const Tensor< Index, 1 > &, const Tensor< Index, 1 > &)

virtual	~PoolingLayer ()
	Destructor. More...

Tensor< Index, 1 >	get_outputs_dimensions () const
	Returns the layer's outputs dimensions. More...

Index	get_inputs_number () const
	Returns the number of inputs of the layer. More...

Index	get_inputs_channels_number () const
	Returns the number of channels of the layers' input. More...

Index	get_inputs_rows_number () const
	Returns the number of rows of the layer's input. More...

Index	get_inputs_columns_number () const
	Returns the number of columns of the layer's input. More...

Index	get_neurons_number () const
	Returns the number of neurons the layer applies to an image. More...

Index	get_outputs_rows_number () const
	Returns the number of rows of the layer's output. More...

Index	get_outputs_columns_number () const
	Returns the number of columns of the layer's output. More...

Index	get_padding_width () const
	Returns the padding width. More...

Index	get_row_stride () const
	Returns the pooling filter's row stride. More...

Index	get_column_stride () const
	Returns the pooling filter's column stride. More...

Index	get_pool_rows_number () const
	Returns the number of rows of the pooling filter. More...

Index	get_pool_columns_number () const
	Returns the number of columns of the pooling filter. More...

Index	get_parameters_number () const
	Returns the number of parameters of the layer. More...

Tensor< type, 1 >	get_parameters () const
	Returns the layer's parameters. More...

PoolingMethod	get_pooling_method () const
	Returns the pooling method. More...

void	set_inputs_number (const Index &)

void	set_neurons_number (const Index &)

void	set_input_variables_dimensions (const Tensor< Index, 1 > &)

void	set_padding_width (const Index &)

void	set_row_stride (const Index &)

void	set_column_stride (const Index &)

void	set_pool_size (const Index &, const Index &)

void	set_pooling_method (const PoolingMethod &)

void	set_default ()
	Sets the layer type to Layer::Pooling. More...

Tensor< type, 4 >	calculate_outputs (const Tensor< type, 4 > &)

void	calculate_activations (const Tensor< type, 4 > &, Tensor< type, 4 > &)

Tensor< type, 4 >	calculate_no_pooling_outputs (const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_max_pooling_outputs (const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_average_pooling_outputs (const Tensor< type, 4 > &) const

Tensor< type, 2 >	calculate_activations_derivatives (const Tensor< type, 2 > &) const

void	calculate_activations_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	forward_propagate (const Tensor< type, 4 > &, LayerForwardPropagation *)

Tensor< type, 4 >	calculate_hidden_delta (Layer *, const Tensor< type, 4 > &, const Tensor< type, 4 > &, const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_hidden_delta_convolutional (ConvolutionalLayer *, const Tensor< type, 4 > &, const Tensor< type, 4 > &, const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_hidden_delta_pooling (PoolingLayer *, const Tensor< type, 4 > &, const Tensor< type, 4 > &, const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_hidden_delta_perceptron (PerceptronLayer *, const Tensor< type, 4 > &, const Tensor< type, 4 > &, const Tensor< type, 4 > &) const

Tensor< type, 4 >	calculate_hidden_delta_probabilistic (ProbabilisticLayer *, const Tensor< type, 4 > &, const Tensor< type, 4 > &, const Tensor< type, 4 > &) const

Tensor< type, 1 >	calculate_error_gradient (const Tensor< type, 2 > &, const LayerForwardPropagation &, const Tensor< type, 2 > &)

Public Member Functions inherited from Layer
string	get_name () const

virtual void	set_parameters_constant (const type &)

virtual void	set_parameters_random ()

virtual void	set_parameters (const Tensor< type, 1 > &, const Index &)

void	set_threads_number (const int &)

virtual void	insert_gradient (LayerBackPropagation *, const Index &, Tensor< type, 1 > &) const

virtual Tensor< type, 2 >	calculate_outputs (const Tensor< type, 2 > &)

virtual Tensor< type, 2 >	calculate_outputs_from4D (const Tensor< type, 4 > &)

virtual Tensor< type, 4 >	calculate_outputs_4D (const Tensor< type, 4 > &)

virtual void	forward_propagate (const Tensor< type, 2 > &, LayerForwardPropagation *)

virtual void	forward_propagate (const Tensor< type, 4 > &, Tensor< type, 1 >, LayerForwardPropagation *)

virtual void	forward_propagate (const Tensor< type, 2 > &, Tensor< type, 1 >, LayerForwardPropagation *)

virtual void	calculate_hidden_delta (LayerForwardPropagation , LayerBackPropagation , LayerBackPropagation *) const

virtual void	calculate_hidden_delta_lm (LayerForwardPropagation , LayerBackPropagationLM , LayerBackPropagationLM *) const

virtual void	calculate_error_gradient (const Tensor< type, 2 > &, LayerForwardPropagation , LayerBackPropagation ) const

virtual void	calculate_error_gradient (const Tensor< type, 4 > &, LayerForwardPropagation , LayerBackPropagation ) const

virtual void	calculate_squared_errors_Jacobian_lm (const Tensor< type, 2 > &, LayerForwardPropagation , LayerBackPropagationLM )

virtual void	insert_squared_errors_Jacobian_lm (LayerBackPropagationLM *, const Index &, Tensor< type, 2 > &) const

virtual Index	get_synaptic_weights_number () const
	Returns the number of layer's synaptic weights. More...

Type	get_type () const

string	get_type_string () const
	Takes the type of layer used by the model. More...

virtual void	from_XML (const tinyxml2::XMLDocument &)

virtual void	write_XML (tinyxml2::XMLPrinter &) const

virtual string	write_expression (const Tensor< string, 1 > &, const Tensor< string, 1 > &) const

virtual string	write_expression_c () const

virtual string	write_expression_python () const

Protected Attributes
Tensor< Index, 1 >	input_variables_dimensions

Index	pool_rows_number = 2

Index	pool_columns_number = 2

Index	padding_width = 0

Index	row_stride = 1

Index	column_stride = 1

PoolingMethod	pooling_method = PoolingMethod::AveragePooling

Protected Attributes inherited from Layer
NonBlockingThreadPool *	non_blocking_thread_pool = nullptr

ThreadPoolDevice *	thread_pool_device = nullptr

string	layer_name = "layer"
	Layer name. More...

Type	layer_type = Type::Perceptron
	Layer type. More...

const Eigen::array< IndexPair< Index >, 1 >	A_BT = {IndexPair<Index>(1, 1)}

const Eigen::array< IndexPair< Index >, 1 >	AT_B = {IndexPair<Index>(0, 0)}

const Eigen::array< IndexPair< Index >, 1 >	A_B = {IndexPair<Index>(1, 0)}

Additional Inherited Members
Protected Member Functions inherited from Layer
void	hard_sigmoid (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	hyperbolic_tangent (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	logistic (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	linear (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	threshold (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	symmetric_threshold (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	rectified_linear (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	scaled_exponential_linear (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	soft_plus (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	soft_sign (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	exponential_linear (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	softmax (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	binary (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	competitive (const Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	hard_sigmoid_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	hyperbolic_tangent_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	linear_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	logistic_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	threshold_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	symmetric_threshold_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	rectified_linear_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	scaled_exponential_linear_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	soft_plus_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	soft_sign_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	exponential_linear_derivatives (const Tensor< type, 1 > &, Tensor< type, 1 > &, Tensor< type, 1 > &) const

void	hard_sigmoid (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	hyperbolic_tangent (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	logistic (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	linear (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	threshold (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	symmetric_threshold (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	rectified_linear (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	scaled_exponential_linear (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	soft_plus (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	soft_sign (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	exponential_linear (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	softmax (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	binary (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	competitive (const Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	hard_sigmoid_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	hyperbolic_tangent_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	linear_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	logistic_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	threshold_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	symmetric_threshold_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	rectified_linear_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	scaled_exponential_linear_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	soft_plus_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	soft_sign_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	exponential_linear_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 2 > &) const

void	logistic_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 3 > &) const

void	softmax_derivatives (const Tensor< type, 2 > &, Tensor< type, 2 > &, Tensor< type, 3 > &) const

void	linear (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	logistic (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	hyperbolic_tangent (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	threshold (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	symmetric_threshold (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	rectified_linear (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	scaled_exponential_linear (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	soft_plus (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	soft_sign (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	hard_sigmoid (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	exponential_linear (const Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	linear_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	logistic_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	hyperbolic_tangent_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	threshold_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	symmetric_threshold_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	rectified_linear_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	scaled_exponential_linear_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	soft_plus_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	soft_sign_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	hard_sigmoid_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

void	exponential_linear_derivatives (const Tensor< type, 4 > &, Tensor< type, 4 > &, Tensor< type, 4 > &) const

Detailed Description

This class is used to store information about the Pooling Layer in Convolutional Neural Network(CNN). Pooling: is the procross_entropy_errors of merging, ie, reducing the size of the data and remove some noise by different processes.

Definition at line 38 of file pooling_layer.h.

Member Enumeration Documentation

◆ PoolingMethod

enum class PoolingMethod

strong

Enumeration of available methods for pooling data.

Definition at line 45 of file pooling_layer.h.

Constructor & Destructor Documentation

◆ PoolingLayer() [1/3]

PoolingLayer ( )

explicit

Default constructor. It creates an empty PoolingLayer object.

Definition at line 17 of file pooling_layer.cpp.

◆ PoolingLayer() [2/3]

PoolingLayer ( const Tensor< Index, 1 > & new_input_variables_dimensions )

explicit

Input size setter constructor. After setting new dimensions for the input, it creates an empty PoolingLayer object.

Parameters

new_input_variables_dimensions A vector containing the new number of channels, rows and columns for the input.

Definition at line 26 of file pooling_layer.cpp.

◆ PoolingLayer() [3/3]

PoolingLayer	(	const Tensor< Index, 1 > &	new_input_variables_dimensions,
		const Tensor< Index, 1 > &	pool_dimensions
	)

explicit

Input size setter constructor. After setting new dimensions for the input, it creates an empty PoolingLayer object.

Parameters

new_input_variables_dimensions	A vector containing the desired number of rows and columns for the input.
pool_dimensions	A vector containing the desired number of rows and columns for the pool.

Definition at line 37 of file pooling_layer.cpp.

◆ ~PoolingLayer()

~PoolingLayer ( )

virtual

Destructor.

Definition at line 49 of file pooling_layer.cpp.

Member Function Documentation

◆ calculate_activations()

void calculate_activations	(	const Tensor< type, 4 > &	,
		Tensor< type, 4 > &
	)

inline

Definition at line 117 of file pooling_layer.h.

◆ calculate_activations_derivatives()

void calculate_activations_derivatives	(	const Tensor< type, 2 > &	,
		Tensor< type, 2 > &
	)		const

inline

Definition at line 129 of file pooling_layer.h.

◆ calculate_average_pooling_outputs()

Tensor< type, 4 > calculate_average_pooling_outputs ( const Tensor< type, 4 > & inputs ) const

Returns the result of applying average pooling to a batch of images.

Parameters

inputs The batch of images.

Definition at line 95 of file pooling_layer.cpp.

◆ calculate_error_gradient()

Tensor< type, 1 > calculate_error_gradient	(	const Tensor< type, 2 > &	,
		const LayerForwardPropagation &	,
		const Tensor< type, 2 > &
	)

Definition at line 577 of file pooling_layer.cpp.

◆ calculate_hidden_delta()

Tensor< type, 4 > calculate_hidden_delta	(	Layer *	next_layer_pointer,
		const Tensor< type, 4 > &	activations,
		const Tensor< type, 4 > &	activations_derivatives,
		const Tensor< type, 4 > &	next_layer_delta
	)		const

Definition at line 206 of file pooling_layer.cpp.

◆ calculate_hidden_delta_convolutional()

Tensor< type, 4 > calculate_hidden_delta_convolutional	(	ConvolutionalLayer *	next_layer_pointer,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	next_layer_delta
	)		const

Definition at line 247 of file pooling_layer.cpp.

◆ calculate_hidden_delta_perceptron()

Tensor< type, 4 > calculate_hidden_delta_perceptron	(	PerceptronLayer *	next_layer_pointer,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	next_layer_delta
	)		const

Definition at line 475 of file pooling_layer.cpp.

◆ calculate_hidden_delta_pooling()

Tensor< type, 4 > calculate_hidden_delta_pooling	(	PoolingLayer *	next_layer_pointer,
		const Tensor< type, 4 > &	activations,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	next_layer_delta
	)		const

Definition at line 315 of file pooling_layer.cpp.

◆ calculate_hidden_delta_probabilistic()

Tensor< type, 4 > calculate_hidden_delta_probabilistic	(	ProbabilisticLayer *	next_layer_pointer,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	,
		const Tensor< type, 4 > &	next_layer_delta
	)		const

Definition at line 526 of file pooling_layer.cpp.

◆ calculate_max_pooling_outputs()

Tensor< type, 4 > calculate_max_pooling_outputs ( const Tensor< type, 4 > & inputs ) const

Returns the result of applying max pooling to a batch of images.

Parameters

inputs The batch of images.

Definition at line 155 of file pooling_layer.cpp.

◆ calculate_no_pooling_outputs()

Tensor< type, 4 > calculate_no_pooling_outputs ( const Tensor< type, 4 > & inputs ) const

Returns the result of applying no pooling to a batch of images.

Parameters

inputs The batch of images.

Definition at line 146 of file pooling_layer.cpp.

◆ calculate_outputs()

Tensor< type, 4 > calculate_outputs ( const Tensor< type, 4 > & inputs )

Returns the output of the pooling layer applied to a batch of images.

Parameters

inputs The batch of images.

Definition at line 57 of file pooling_layer.cpp.

◆ forward_propagate()

void forward_propagate	(	const Tensor< type, 4 > &	,
		LayerForwardPropagation *
	)

inlinevirtual

Reimplemented from Layer.

Definition at line 136 of file pooling_layer.h.

◆ get_column_stride()

Index get_column_stride ( ) const

Returns the pooling filter's column stride.

Definition at line 683 of file pooling_layer.cpp.

◆ get_inputs_channels_number()

Index get_inputs_channels_number ( ) const

Returns the number of channels of the layers' input.

Definition at line 617 of file pooling_layer.cpp.

◆ get_inputs_columns_number()

Index get_inputs_columns_number ( ) const

Returns the number of columns of the layer's input.

Definition at line 637 of file pooling_layer.cpp.

◆ get_inputs_number()

Index get_inputs_number ( ) const

virtual

Returns the number of inputs of the layer.

Reimplemented from Layer.

Definition at line 609 of file pooling_layer.cpp.

◆ get_inputs_rows_number()

Index get_inputs_rows_number ( ) const

Returns the number of rows of the layer's input.

Definition at line 627 of file pooling_layer.cpp.

◆ get_neurons_number()

Index get_neurons_number ( ) const

virtual

Returns the number of neurons the layer applies to an image.

Reimplemented from Layer.

Definition at line 587 of file pooling_layer.cpp.

◆ get_outputs_columns_number()

Index get_outputs_columns_number ( ) const

Returns the number of columns of the layer's output.

Definition at line 657 of file pooling_layer.cpp.

◆ get_outputs_dimensions()

Tensor< Index, 1 > get_outputs_dimensions ( ) const

Returns the layer's outputs dimensions.

Definition at line 595 of file pooling_layer.cpp.

◆ get_outputs_rows_number()

Index get_outputs_rows_number ( ) const

Returns the number of rows of the layer's output.

Definition at line 647 of file pooling_layer.cpp.

◆ get_padding_width()

Index get_padding_width ( ) const

Returns the padding width.

Definition at line 667 of file pooling_layer.cpp.

◆ get_parameters()

Tensor< type, 1 > get_parameters ( ) const

virtual

Returns the layer's parameters.

Reimplemented from Layer.

Definition at line 715 of file pooling_layer.cpp.

◆ get_parameters_number()

Index get_parameters_number ( ) const

virtual

Returns the number of parameters of the layer.

Reimplemented from Layer.

Definition at line 707 of file pooling_layer.cpp.

◆ get_pool_columns_number()

Index get_pool_columns_number ( ) const

Returns the number of columns of the pooling filter.

Definition at line 699 of file pooling_layer.cpp.

◆ get_pool_rows_number()

Index get_pool_rows_number ( ) const

Returns the number of rows of the pooling filter.

Definition at line 691 of file pooling_layer.cpp.

◆ get_pooling_method()

PoolingLayer::PoolingMethod get_pooling_method ( ) const

Returns the pooling method.

Definition at line 723 of file pooling_layer.cpp.

◆ get_row_stride()

Index get_row_stride ( ) const

Returns the pooling filter's row stride.

Definition at line 675 of file pooling_layer.cpp.

◆ set_column_stride()

void set_column_stride ( const Index & new_column_stride )

Sets the pooling filter's column stride.

Parameters

new_column_stride The desired column stride.

Definition at line 759 of file pooling_layer.cpp.

◆ set_default()

void set_default ( )

Sets the layer type to Layer::Pooling.

Definition at line 789 of file pooling_layer.cpp.

◆ set_input_variables_dimensions()

void set_input_variables_dimensions ( const Tensor< Index, 1 > & new_input_variables_dimensions )

Sets the number of rows of the layer's input.

Parameters

new_input_rows_number The desired rows number.

Definition at line 732 of file pooling_layer.cpp.

◆ set_inputs_number()

void set_inputs_number ( const Index & )

inlinevirtual

Reimplemented from Layer.

Definition at line 96 of file pooling_layer.h.

◆ set_neurons_number()

void set_neurons_number ( const Index & )

inlinevirtual

Reimplemented from Layer.

Definition at line 97 of file pooling_layer.h.

◆ set_padding_width()

void set_padding_width ( const Index & new_padding_width )

Sets the padding width.

Parameters

new_padding_width The desired width.

Definition at line 741 of file pooling_layer.cpp.

◆ set_pool_size()

void set_pool_size	(	const Index &	new_pool_rows_number,
		const Index &	new_pool_columns_number
	)

Sets the pooling filter's dimensions.

Parameters

new_pool_rows_number	The desired number of rows.
new_pool_columns_number	The desired number of columns.

Definition at line 769 of file pooling_layer.cpp.

◆ set_pooling_method()

void set_pooling_method ( const PoolingMethod & new_pooling_method )

Sets the layer's pooling method.

Parameters

new_pooling_method The desired method.

Definition at line 781 of file pooling_layer.cpp.

◆ set_row_stride()

void set_row_stride ( const Index & new_row_stride )

Sets the pooling filter's row stride.

Parameters

new_row_stride The desired row stride.

Definition at line 750 of file pooling_layer.cpp.

Member Data Documentation

◆ column_stride

Index column_stride = 1

protected

Definition at line 165 of file pooling_layer.h.

◆ input_variables_dimensions

Tensor<Index, 1> input_variables_dimensions

protected

Definition at line 155 of file pooling_layer.h.

◆ padding_width

Index padding_width = 0

protected

Definition at line 161 of file pooling_layer.h.

◆ pool_columns_number

Index pool_columns_number = 2

protected

Definition at line 159 of file pooling_layer.h.

◆ pool_rows_number

Index pool_rows_number = 2

protected

Definition at line 157 of file pooling_layer.h.

◆ pooling_method

PoolingMethod pooling_method = PoolingMethod::AveragePooling

protected

Definition at line 167 of file pooling_layer.h.

◆ row_stride

Index row_stride = 1

protected

Definition at line 163 of file pooling_layer.h.

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ PoolingMethod

Constructor & Destructor Documentation

◆ PoolingLayer() [1/3]

◆ PoolingLayer() [2/3]

◆ PoolingLayer() [3/3]

◆ ~PoolingLayer()

Member Function Documentation

◆ calculate_activations()

◆ calculate_activations_derivatives()

◆ calculate_average_pooling_outputs()

◆ calculate_error_gradient()

◆ calculate_hidden_delta()

◆ calculate_hidden_delta_convolutional()

◆ calculate_hidden_delta_perceptron()

◆ calculate_hidden_delta_pooling()

◆ calculate_hidden_delta_probabilistic()

◆ calculate_max_pooling_outputs()

◆ calculate_no_pooling_outputs()

◆ calculate_outputs()

◆ forward_propagate()

◆ get_column_stride()

◆ get_inputs_channels_number()

◆ get_inputs_columns_number()

◆ get_inputs_number()

◆ get_inputs_rows_number()

◆ get_neurons_number()

◆ get_outputs_columns_number()

◆ get_outputs_dimensions()

◆ get_outputs_rows_number()

◆ get_padding_width()

◆ get_parameters()

◆ get_parameters_number()

◆ get_pool_columns_number()

◆ get_pool_rows_number()

◆ get_pooling_method()

◆ get_row_stride()

◆ set_column_stride()

◆ set_default()

◆ set_input_variables_dimensions()

◆ set_inputs_number()

◆ set_neurons_number()

◆ set_padding_width()

◆ set_pool_size()

◆ set_pooling_method()

◆ set_row_stride()

Member Data Documentation

◆ column_stride

◆ input_variables_dimensions

◆ padding_width

◆ pool_columns_number

◆ pool_rows_number

◆ pooling_method

◆ row_stride