Base class for compute building blocks composed by layers (matmul, activation, dropout, etc.). More...

#include <operators.h>

Inheritance diagram for opennn::Operator:

Public Member Functions
virtual	~Operator ()=default

virtual vector< TensorSpec >	parameter_specs () const
	Returns the tensor specs of trainable parameters owned by this operator.

virtual vector< TensorSpec >	state_specs () const
	Returns the tensor specs of persistent state owned by this operator.

virtual void	link_parameters (span< const TensorView >)
	Binds parameter views provided by the hosting layer.

virtual void	link_gradients (span< const TensorView >)
	Binds gradient views provided by the hosting layer.

virtual void	link_states (span< const TensorView >)
	Binds state views provided by the hosting layer.

virtual void	set_parameters_random ()
	Initializes parameters with random values.

virtual void	set_parameters_glorot ()
	Initializes parameters using Glorot (Xavier) initialization.

virtual void	forward_propagate (ForwardPropagation &, size_t, bool) noexcept
	Runs the operator's forward computation.

virtual void	back_propagate (ForwardPropagation &, BackPropagation &, size_t) const noexcept
	Runs the operator's backward computation, accumulating into gradient/delta buffers.

virtual void	to_JSON (JsonWriter &) const
	Serializes the operator configuration to a JSON writer.

virtual void	from_JSON (const Json *)
	Restores the operator configuration from a JSON node.

virtual void	load_state_from_JSON (const Json *)
	Restores persistent state (e.g. running statistics) from a JSON node.

virtual void	destroy_cuda ()
	Releases CUDA resources owned by the operator; called from destructors.

TensorView &	get_input (ForwardPropagation &fp, size_t layer, size_t i=0) const noexcept

vector< TensorView > &	get_inputs (ForwardPropagation &fp, size_t layer, size_t i=0) const noexcept

TensorView &	get_output (ForwardPropagation &fp, size_t layer, size_t i=0) const noexcept

TensorView &	get_output_delta (BackPropagation &bp, size_t layer, size_t i=0) const noexcept

TensorView &	get_input_delta (BackPropagation &bp, size_t layer, size_t i=0) const noexcept

Public Attributes
vector< size_t >	input_slots = {0}

vector< size_t >	output_slots = {1}

vector< size_t >	input_delta_slots = {1}

vector< size_t >	output_delta_slots = {0}

Detailed Description

Base class for compute building blocks composed by layers (matmul, activation, dropout, etc.).

Constructor & Destructor Documentation

◆ ~Operator()

virtual opennn::Operator::~Operator ( )

virtualdefault

Member Function Documentation

◆ back_propagate()

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

inlinevirtualnoexcept

Runs the operator's backward computation, accumulating into gradient/delta buffers.

Parameters

fp	Forward propagation workspace (read-only).
bp	Back propagation workspace receiving gradients and deltas.
layer	Index of the hosting layer in the workspace.

Reimplemented in opennn::ActivationOp, opennn::AddOp, opennn::AttentionOp, opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::DropoutOp, opennn::EmbeddingLookupOp, opennn::FlatOp, opennn::LayerNormOp, opennn::MergeOp, opennn::MultiHeadProjectionOp, opennn::Pool3dOp, and opennn::PoolOp.

◆ destroy_cuda()

virtual void opennn::Operator::destroy_cuda ( )

inlinevirtual

Releases CUDA resources owned by the operator; called from destructors.

Reimplemented in opennn::ActivationOp, opennn::AttentionOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::DropoutOp, and opennn::PoolOp.

◆ forward_propagate()

virtual void opennn::Operator::forward_propagate	(	ForwardPropagation &	,
		size_t	,
		bool	)

inlinevirtualnoexcept

Runs the operator's forward computation.

Parameters

fp	Forward propagation workspace.
layer	Index of the hosting layer in the workspace.
is_training	If true, enables training-only behavior (e.g. dropout sampling).

Reimplemented in opennn::ActivationOp, opennn::AddOp, opennn::AttentionOp, opennn::BatchNormOp, opennn::BoundOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::DropoutOp, opennn::EmbeddingLookupOp, opennn::FlatOp, opennn::LayerNormOp, opennn::MergeOp, opennn::MultiHeadProjectionOp, opennn::Pool3dOp, opennn::PoolOp, opennn::ScaleOp, and opennn::UnscaleOp.

◆ from_JSON()

virtual void opennn::Operator::from_JSON ( const Json * )

inlinevirtual

Restores the operator configuration from a JSON node.

Reimplemented in opennn::ActivationOp, opennn::AttentionOp, opennn::BatchNormOp, and opennn::DropoutOp.

◆ get_input()

TensorView & opennn::Operator::get_input	(	ForwardPropagation &	fp,
		size_t	layer,
		size_t	i = 0 ) const

inlinenoexcept

◆ get_input_delta()

TensorView & opennn::Operator::get_input_delta	(	BackPropagation &	bp,
		size_t	layer,
		size_t	i = 0 ) const

inlinenoexcept

◆ get_inputs()

vector< TensorView > & opennn::Operator::get_inputs	(	ForwardPropagation &	fp,
		size_t	layer,
		size_t	i = 0 ) const

inlinenoexcept

◆ get_output()

TensorView & opennn::Operator::get_output	(	ForwardPropagation &	fp,
		size_t	layer,
		size_t	i = 0 ) const

inlinenoexcept

◆ get_output_delta()

TensorView & opennn::Operator::get_output_delta	(	BackPropagation &	bp,
		size_t	layer,
		size_t	i = 0 ) const

inlinenoexcept

◆ link_gradients()

virtual void opennn::Operator::link_gradients ( span< const TensorView > )

inlinevirtual

Binds gradient views provided by the hosting layer.

Reimplemented in opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::EmbeddingLookupOp, opennn::LayerNormOp, and opennn::MultiHeadProjectionOp.

◆ link_parameters()

virtual void opennn::Operator::link_parameters ( span< const TensorView > )

inlinevirtual

Binds parameter views provided by the hosting layer.

Reimplemented in opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::EmbeddingLookupOp, opennn::LayerNormOp, and opennn::MultiHeadProjectionOp.

◆ link_states()

virtual void opennn::Operator::link_states ( span< const TensorView > )

inlinevirtual

Binds state views provided by the hosting layer.

Reimplemented in opennn::BatchNormOp, and opennn::EmbeddingLookupOp.

◆ load_state_from_JSON()

virtual void opennn::Operator::load_state_from_JSON ( const Json * )

inlinevirtual

Restores persistent state (e.g. running statistics) from a JSON node.

Reimplemented in opennn::BatchNormOp.

◆ parameter_specs()

virtual vector< TensorSpec > opennn::Operator::parameter_specs ( ) const

inlinevirtual

Returns the tensor specs of trainable parameters owned by this operator.

Reimplemented in opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::EmbeddingLookupOp, opennn::LayerNormOp, and opennn::MultiHeadProjectionOp.

◆ set_parameters_glorot()

virtual void opennn::Operator::set_parameters_glorot ( )

inlinevirtual

Initializes parameters using Glorot (Xavier) initialization.

Reimplemented in opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::EmbeddingLookupOp, opennn::LayerNormOp, and opennn::MultiHeadProjectionOp.

◆ set_parameters_random()

virtual void opennn::Operator::set_parameters_random ( )

inlinevirtual

Initializes parameters with random values.

Reimplemented in opennn::BatchNormOp, opennn::CombinationOp, opennn::CombinationReluOp, opennn::ConvolutionOp, opennn::ConvolutionReluOp, opennn::EmbeddingLookupOp, opennn::LayerNormOp, and opennn::MultiHeadProjectionOp.

◆ state_specs()

virtual vector< TensorSpec > opennn::Operator::state_specs ( ) const

inlinevirtual

Returns the tensor specs of persistent state owned by this operator.

Reimplemented in opennn::BatchNormOp, and opennn::EmbeddingLookupOp.

◆ to_JSON()

virtual void opennn::Operator::to_JSON ( JsonWriter & ) const

inlinevirtual

Serializes the operator configuration to a JSON writer.

Reimplemented in opennn::ActivationOp, opennn::AttentionOp, opennn::BatchNormOp, and opennn::DropoutOp.

Member Data Documentation

◆ input_delta_slots

vector<size_t> opennn::Operator::input_delta_slots = {1}

◆ input_slots

vector<size_t> opennn::Operator::input_slots = {0}

◆ output_delta_slots

vector<size_t> opennn::Operator::output_delta_slots = {0}

◆ output_slots

vector<size_t> opennn::Operator::output_slots = {1}

Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ~Operator()

Member Function Documentation

◆ back_propagate()

◆ destroy_cuda()

◆ forward_propagate()

◆ from_JSON()

◆ get_input()

◆ get_input_delta()

◆ get_inputs()

◆ get_output()

◆ get_output_delta()

◆ link_gradients()

◆ link_parameters()

◆ link_states()

◆ load_state_from_JSON()

◆ parameter_specs()

◆ set_parameters_glorot()

◆ set_parameters_random()

◆ state_specs()

◆ to_JSON()

Member Data Documentation

◆ input_delta_slots

◆ input_slots

◆ output_delta_slots

◆ output_slots