opennn::Convolutional Class Reference

2D convolutional layer with kernel, stride, padding, activation, and optional batch normalization. More...

#include <convolutional_layer.h>

Inheritance diagram for opennn::Convolutional:

Public Member Functions
	Convolutional (const Shape &={3, 3, 1}, const Shape &={3, 3, 1, 1}, const string &="Identity", const Shape &={1, 1}, const string &="Valid", bool=false, const string &="convolutional_layer")
	Constructs a convolutional layer with the given shapes and activation.
Shape	get_input_shape () const override
	Returns the input tensor shape (height, width, channels).
Shape	get_output_shape () const override
	Returns the output tensor shape after convolution.
Index	get_output_height () const
	Returns the output feature map height.
Index	get_output_width () const
	Returns the output feature map width.
Index	get_input_height () const
Index	get_input_width () const
Index	get_input_channels () const
Index	get_kernel_height () const
Index	get_kernel_width () const
Index	get_kernel_channels () const
Index	get_kernels_number () const
Index	get_row_stride () const
Index	get_column_stride () const
pair< Index, Index >	get_padding () const
	Returns padding along height and width (in that order).
Index	get_padding_height () const
	Returns the padding applied along the height axis.
Index	get_padding_width () const
	Returns the padding applied along the width axis.
bool	get_use_padding () 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
vector< TensorSpec >	get_forward_specs (Index batch_size) const override
	Returns the tensor specifications used during forward propagation.
void	set (const Shape &={0, 0, 0}, const Shape &={3, 3, 1, 1}, const string &="Identity", const Shape &={1, 1}, const string &="Valid", bool=false, const string &="convolutional_layer")
	Reconfigures the layer with new shapes and parameters.
void	set_input_shape (const Shape &) override
	Updates the layer for a new input shape and reinitializes derived sizes.
void	on_compute_dtype_changed () override
	Rebuilds the convolution operator when the compute dtype changes.
void	set_row_stride (const Index)
void	set_column_stride (const Index)
void	set_convolution_type (const string &)
	Sets convolution type ("Valid" or "Same") and updates padding.
void	set_activation_function (const string &)
	Sets the activation function by name.
void	set_batch_normalization (bool)
	Enables or disables batch normalization after the convolution.
void	read_JSON_body (const Json *) override
	Reads the layer configuration from a JSON node.
void	write_JSON_body (JsonWriter &) const override
	Writes the layer configuration to a JSON writer.
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_backward_specs (Index batch_size) const
	Returns the tensor specs of the backward workspace; empty for non-trainable layers.
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 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 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

2D convolutional layer with kernel, stride, padding, activation, and optional batch normalization.

Constructor & Destructor Documentation

Convolutional()

opennn::Convolutional::Convolutional	(	const Shape &	= {3, 3, 1},
		const Shape &	= {3, 3, 1, 1},
		const string &	= "Identity",
		const Shape &	= {1, 1},
		const string &	= "Valid",
		bool	= false,
		const string &	= "convolutional_layer" )

Constructs a convolutional layer with the given shapes and activation.

Parameters

input_shape	Shape of the input tensor (height, width, channels).
kernel_shape	Shape of the convolution kernel (height, width, channels, kernels).
activation	Activation function name (e.g. "ReLU", "Identity").
stride_shape	Stride along height and width.
convolution_type	"Valid" or "Same" padding.
batch_normalization	If true, applies batch normalization after the convolution.
name	Layer name used for serialization.

Member Function Documentation

get_activation_function()

ActivationOp::Function opennn::Convolutional::get_activation_function ( ) const

inline

get_batch_normalization()

bool opennn::Convolutional::get_batch_normalization ( ) const

inline

get_column_stride()

Index opennn::Convolutional::get_column_stride ( ) const

inline

get_forward_specs()

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

overridevirtual

Returns the tensor specifications used during forward propagation.

Reimplemented from opennn::Layer.

get_input_channels()

Index opennn::Convolutional::get_input_channels

(

)

const

get_input_height()

Index opennn::Convolutional::get_input_height

(

)

const

get_input_shape()

Shape opennn::Convolutional::get_input_shape ( ) const

inlineoverridevirtual

Returns the input tensor shape (height, width, channels).

Reimplemented from opennn::Layer.

get_input_width()

Index opennn::Convolutional::get_input_width

(

)

const

get_kernel_channels()

Index opennn::Convolutional::get_kernel_channels ( ) const

inline

get_kernel_height()

Index opennn::Convolutional::get_kernel_height ( ) const

inline

get_kernel_width()

Index opennn::Convolutional::get_kernel_width ( ) const

inline

get_kernels_number()

Index opennn::Convolutional::get_kernels_number ( ) const

inline

get_output_activation()

ActivationOp::Function opennn::Convolutional::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_height()

Index opennn::Convolutional::get_output_height

(

)

const

Returns the output feature map height.

get_output_shape()

Shape opennn::Convolutional::get_output_shape ( ) const

overridevirtual

Returns the output tensor shape after convolution.

Implements opennn::Layer.

get_output_width()

Index opennn::Convolutional::get_output_width

(

)

const

Returns the output feature map width.

get_padding()

pair< Index, Index > opennn::Convolutional::get_padding

(

)

const

Returns padding along height and width (in that order).

get_padding_height()

Index opennn::Convolutional::get_padding_height

(

)

const

Returns the padding applied along the height axis.

get_padding_width()

Index opennn::Convolutional::get_padding_width

(

)

const

Returns the padding applied along the width axis.

get_row_stride()

Index opennn::Convolutional::get_row_stride ( ) const

inline

get_use_padding()

bool opennn::Convolutional::get_use_padding ( ) const

inline

on_compute_dtype_changed()

void opennn::Convolutional::on_compute_dtype_changed ( )

inlineoverridevirtual

Rebuilds the convolution operator when the compute dtype changes.

Reimplemented from opennn::Layer.

read_JSON_body()

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

overridevirtual

Reads the layer configuration from a JSON node.

Reimplemented from opennn::Layer.

set()

void opennn::Convolutional::set	(	const Shape &	= {0, 0, 0},
		const Shape &	= {3, 3, 1, 1},
		const string &	= "Identity",
		const Shape &	= {1, 1},
		const string &	= "Valid",
		bool	= false,
		const string &	= "convolutional_layer" )

Reconfigures the layer with new shapes and parameters.

set_activation_function()

void opennn::Convolutional::set_activation_function

(

const string &

)

Sets the activation function by name.

set_batch_normalization()

void opennn::Convolutional::set_batch_normalization

(

bool

)

Enables or disables batch normalization after the convolution.

set_column_stride()

void opennn::Convolutional::set_column_stride

(

const Index

)

set_convolution_type()

void opennn::Convolutional::set_convolution_type

(

const string &

)

Sets convolution type ("Valid" or "Same") and updates padding.

set_input_shape()

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

overridevirtual

Updates the layer for a new input shape and reinitializes derived sizes.

Reimplemented from opennn::Layer.

set_row_stride()

void opennn::Convolutional::set_row_stride

(

const Index

)

write_JSON_body()

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

overridevirtual

Writes the layer configuration to a JSON writer.

Reimplemented from opennn::Layer.