athena__kipf_msgpass

Module implementing Kipf & Welling Graph Convolutional Network (GCN)

This module implements the graph convolutional layer from Kipf & Welling (2017) with symmetric degree normalisation for semi-supervised learning.

Mathematical operation: $H^{(l+1)} = \sigma\left( \tilde{D}^{-1/2} \tilde{A} \tilde{D}^{-1/2} H^{(l)} W^{(l)} \right)$

where: * $\tilde{A} = A + I$ (adjacency matrix with added self-loops) * $\tilde{D}$ is the degree matrix of $\tilde{A}$ * $H^{(l)}$ is the node feature matrix at layer l * $W^{(l)}$ is a learnable weight matrix * $\sigma$ is the activation function

The normalisation $\tilde{D}^{-1/2} \tilde{A} \tilde{D}^{-1/2}$ ensures proper scaling by degree. Preserves graph structure, producing node-level (not graph-level) outputs.

Reference: Kipf & Welling (2017), ICLR

Uses

- diffstruc
- athena__msgpass_layer
- athena__base_layer
- coreutils
- graphstruc
- athena__diffstruc_extd
- athena__misc_types

Interfaces

public interface kipf_msgpass_layer_type

Interface for setting up the MPNN layer

private module function layer_setup(num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose) result(layer)

Set up the message passing layer

Arguments

Type	Intent	Optional	Attributes		Name
integer,	intent(in),		dimension(:)	::	num_vertex_features	Number of features
integer,	intent(in)			::	num_time_steps	Number of time steps
class(*),	intent(in),	optional		::	activation	Activation function and kernel initialiser
class(*),	intent(in),	optional		::	kernel_initialiser	Activation function and kernel initialiser
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value type(kipf_msgpass_layer_type)

Instance of the message passing layer

Derived Types

type, public, extends(msgpass_layer_type) :: kipf_msgpass_layer_type

Components

Type	Visibility	Attributes		Name		Initial
class(base_actv_type),	public,	allocatable	::	activation			Activation function
class(base_init_type),	public,	allocatable	::	bias_init			Initialisers for kernel and bias
character(len=14),	public		::	bias_initialiser	=	''	Initialisers for kernel and bias
integer,	public,	allocatable, dimension(:)	::	bias_shape			Shape of biases
type(graph_type),	public,	allocatable, dimension(:)	::	graph			Graph structure of input data
integer,	public		::	id			Unique identifier
logical,	public		::	inference	=	.false.	Inference mode
integer,	public		::	input_rank	=	0	Rank of input data
integer,	public,	allocatable, dimension(:)	::	input_shape			Input shape
class(base_init_type),	public,	allocatable	::	kernel_init			Initialisers for kernel and bias
character(len=14),	public		::	kernel_initialiser	=	''	Initialisers for kernel and bias
character(len=:),	public,	allocatable	::	name			Layer name
integer,	public,	dimension(:), allocatable	::	num_edge_features			Number of edge features for each time step
integer,	public		::	num_output_edge_features			Number of output edge features
integer,	public		::	num_output_vertex_features			Number of output vertex features
integer,	public		::	num_outputs			Number of outputs (if output is not graph structure)
integer,	public		::	num_params	=	0	Number of learnable parameters
integer,	public,	dimension(:), allocatable	::	num_params_msg			Number of learnable parameters for each message
integer,	public		::	num_params_readout			Number of learnable parameters for the readout
integer,	public		::	num_time_steps			Number of time steps
integer,	public,	dimension(:), allocatable	::	num_vertex_features			Number of vertex features for each time step
class(array_type),	public,	allocatable, dimension(:,:)	::	output			Output
integer,	public		::	output_rank	=	0	Rank of output data
integer,	public,	allocatable, dimension(:)	::	output_shape			Output shape
type(array_type),	public,	allocatable, dimension(:)	::	params			Learnable parameters
character(len=20),	public		::	subtype	=	repeat(" ", 20)
character(len=4),	public		::	type	=	'base'	Layer type
logical,	public		::	use_bias	=	.false.	Layer has bias
logical,	public		::	use_graph_input	=	.false.	Use graph input
logical,	public		::	use_graph_output	=	.false.	Use graph output
integer,	public,	allocatable, dimension(:,:)	::	weight_shape			Shape of weights

Constructor

Interface for setting up the MPNN layer

private module function layer_setup (num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose)	Set up the message passing layer

Type-Bound Procedures

procedure, public :: add_t_t => add_learnable	Add two layers
procedure, public, pass(this) :: build_from_onnx => build_from_onnx_base	Build layer from ONNX node and initialiser
procedure, public, pass(this) :: emit_onnx_graph_inputs => emit_onnx_graph_inputs_base	Emit graph input tensor declarations for this layer
procedure, public, pass(this) :: emit_onnx_nodes => emit_onnx_nodes_kipf	Emit ONNX JSON nodes for Kipf GCN layer
procedure, public, pass(this) :: extract_output => extract_output_base	Extract the output of the layer as a standard real array
procedure, public, pass(this) :: forward => forward_msgpass	Forward pass for message passing layer
procedure, public, pass(this) :: forward_eval => forward_eval_base	Forward pass of layer and return output for evaluation
procedure, public, pass(this) :: get_attributes => get_attributes_kipf	Get the attributes of the layer (for ONNX export)
procedure, public, pass(this) :: get_gradients	Get parameter gradients of layer
procedure, public, pass(this) :: get_num_params => get_num_params_kipf	Get the number of parameters for the message passing layer
procedure, public, pass(this) :: get_params	Get learnable parameters of layer
procedure, public, pass(this) :: init => init_kipf	Initialise the message passing layer
procedure, public, pass(this) :: nullify_graph => nullify_graph_base	Nullify the forward pass data of the layer to free memory Read more…
generic, public :: operator(+) => add_t_t	Operator overloading for addition
procedure, public, pass(this) :: print => print_base	Print the layer to a file with additional information
procedure, public, pass(this) :: print_to_unit => print_to_unit_kipf	Print the message passing layer
procedure, public, pass(this) :: read => read_kipf	Read the message passing layer
procedure, public, pass(this) :: reduce => reduce_learnable	Merge another learnable layer into this one
procedure, public, pass(this) :: set_gradients	Set learnable parameters of layer
procedure, public, pass(this) :: set_graph => set_graph_msgpass
procedure, public, pass(this) :: set_hyperparams => set_hyperparams_kipf	Set the hyperparameters for the message passing layer
procedure, public, pass(this) :: set_params	Set learnable parameters of layer
procedure, public, pass(this) :: set_rank => set_rank_base	Set the input and output ranks of the layer
procedure, public, pass(this) :: set_shape => set_shape_base	Set the input shape of the layer
procedure, public, pass(this) :: update_message => update_message_kipf	Update the message
procedure, public, pass(this) :: update_readout => update_readout_kipf	Update the readout

Functions

public function read_kipf_msgpass_layer(unit, verbose) result(layer)

Read kipf message passing layer from file and return layer

Arguments

Type	Intent	Optional	Attributes		Name
integer,	intent(in)			::	unit	Unit number
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value class(base_layer_type), allocatable

Instance of the message passing layer

private function get_attributes_kipf(this) result(attributes)

Get the attributes of the Kipf GCN layer (for ONNX export)

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(in)			::	this	Instance of the message passing layer

Return Value type(onnx_attribute_type), allocatable, dimension(:)

Attributes for ONNX export

private pure function get_num_params_kipf(this) result(num_params)

Get the number of parameters for the message passing layer

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(in)			::	this	Instance of the message passing layer

Return Value integer

Number of parameters

private module function layer_setup(num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose) result(layer)

Set up the message passing layer

Arguments

Type	Intent	Optional	Attributes		Name
integer,	intent(in),		dimension(:)	::	num_vertex_features	Number of features
integer,	intent(in)			::	num_time_steps	Number of time steps
class(*),	intent(in),	optional		::	activation	Activation function and kernel initialiser
class(*),	intent(in),	optional		::	kernel_initialiser	Activation function and kernel initialiser
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value type(kipf_msgpass_layer_type)

Instance of the message passing layer

Subroutines

private subroutine emit_kipf_timestep(prefix, t, nv_in, nv_out, weight_data, activation_name, nodes, num_nodes, max_nodes, inits, num_inits, max_inits, vertex_out)

Emit ONNX nodes for one Kipf GCN time step.

Arguments

Type	Intent	Attributes		Name
character(len=*),	intent(in)		::	prefix
integer,	intent(in)		::	t
integer,	intent(in)		::	nv_in
integer,	intent(in)		::	nv_out
real(kind=real32),	intent(in)		::	weight_data(:)
character(len=*),	intent(in)		::	activation_name
type(onnx_node_type),	intent(inout),	dimension(:)	::	nodes
integer,	intent(inout)		::	num_nodes
integer,	intent(in)		::	max_nodes
type(onnx_initialiser_type),	intent(inout),	dimension(:)	::	inits
integer,	intent(inout)		::	num_inits
integer,	intent(in)		::	max_inits
character(len=128),	intent(out)		::	vertex_out

private subroutine emit_onnx_nodes_kipf(this, prefix, nodes, num_nodes, max_nodes, inits, num_inits, max_inits, input_name, is_last_layer, format)

Emit ONNX JSON nodes for Kipf GCN layer

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(in)			::	this	Instance of the layer
character(len=*),	intent(in)			::	prefix	Node name prefix (e.g. "node_2")
type(onnx_node_type),	intent(inout),		dimension(:)	::	nodes	Accumulator for ONNX nodes
integer,	intent(inout)			::	num_nodes	Current number of nodes
integer,	intent(in)			::	max_nodes	Maximum capacity
type(onnx_initialiser_type),	intent(inout),		dimension(:)	::	inits	Accumulator for ONNX initialisers
integer,	intent(inout)			::	num_inits	Current number of initialisers
integer,	intent(in)			::	max_inits	Maximum capacity
character(len=*),	intent(in),	optional		::	input_name	Unused sequential input name
logical,	intent(in),	optional		::	is_last_layer	Unused last-layer flag
integer,	intent(in),	optional		::	format	Unused export format selector

private subroutine init_kipf(this, input_shape, verbose)

Initialise the message passing layer

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(inout)			::	this	Instance of the fully connected layer
integer,	intent(in),		dimension(:)	::	input_shape	Input shape
integer,	intent(in),	optional		::	verbose	Verbosity level

private subroutine print_to_unit_kipf(this, unit)

Print kipf message passing layer to unit

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(in)			::	this	Instance of the message passing layer
integer,	intent(in)			::	unit	File unit

private subroutine read_kipf(this, unit, verbose)

Read the message passing layer

Arguments

Type	Intent	Optional		Name
class(kipf_msgpass_layer_type),	intent(inout)		::	this	Instance of the message passing layer
integer,	intent(in)		::	unit	Unit to read from
integer,	intent(in),	optional	::	verbose	Verbosity level

private subroutine set_hyperparams_kipf(this, num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose)

Set the hyperparameters for the message passing layer

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(inout)			::	this	Instance of the message passing layer
integer,	intent(in),		dimension(:)	::	num_vertex_features	Number of vertex features
integer,	intent(in)			::	num_time_steps	Number of time steps
class(base_actv_type),	intent(in),		allocatable	::	activation	Activation function
class(base_init_type),	intent(in),		allocatable	::	kernel_initialiser	Kernel initialiser
integer,	intent(in),	optional		::	verbose	Verbosity level

private subroutine update_message_kipf(this, input)

Update the message

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(inout),		target	::	this	Instance of the message passing layer
class(array_type),	intent(in),		dimension(:,:), target	::	input	Input to the message passing layer

private subroutine update_readout_kipf(this)

Update the readout (empty for node-level output)

Arguments

Type	Intent	Optional	Attributes		Name
class(kipf_msgpass_layer_type),	intent(inout),		target	::	this	Instance of the message passing layer

athena__kipf_msgpass_layer Module

Contents

Interfaces

Derived Types

Functions

Subroutines

Uses

Interfaces

public interface kipf_msgpass_layer_type

private module function layer_setup(num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose) result(layer) Implementation →

Arguments

Return Value type(kipf_msgpass_layer_type)

Derived Types

type, public, extends(msgpass_layer_type) :: kipf_msgpass_layer_type

Components

Constructor

Type-Bound Procedures

Functions

public function read_kipf_msgpass_layer(unit, verbose) result(layer)

Arguments

Return Value class(base_layer_type), allocatable

private function get_attributes_kipf(this) result(attributes)

Arguments

Return Value type(onnx_attribute_type), allocatable, dimension(:)

private pure function get_num_params_kipf(this) result(num_params)

Arguments

Return Value integer

private module function layer_setup(num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose) result(layer)

Arguments

Return Value type(kipf_msgpass_layer_type)

Subroutines

private subroutine emit_kipf_timestep(prefix, t, nv_in, nv_out, weight_data, activation_name, nodes, num_nodes, max_nodes, inits, num_inits, max_inits, vertex_out)

Arguments

private subroutine emit_onnx_nodes_kipf(this, prefix, nodes, num_nodes, max_nodes, inits, num_inits, max_inits, input_name, is_last_layer, format)

Arguments

private subroutine init_kipf(this, input_shape, verbose)

Arguments

private subroutine print_to_unit_kipf(this, unit)

Arguments

private subroutine read_kipf(this, unit, verbose)

Arguments

private subroutine set_hyperparams_kipf(this, num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose)

Arguments

private subroutine update_message_kipf(this, input)

Arguments

private subroutine update_readout_kipf(this)

Arguments

private module function layer_setup(num_vertex_features, num_time_steps, activation, kernel_initialiser, verbose) result(layer)