athena__network

public interface network_type

Interface for setting up the network (network initialisation)

private module function network_setup(layers, optimiser, loss_method, accuracy_method, metrics, batch_size) result(network)

Set up the network

Arguments

Type	Intent	Optional	Attributes		Name
type(container_layer_type),	intent(in),		dimension(:)	::	layers	Layers
class(base_optimiser_type),	intent(in),	optional		::	optimiser	Optimiser
class(*),	intent(in),	optional		::	loss_method	Loss method
character(len=*),	intent(in),	optional		::	accuracy_method	Accuracy method
class(*),	intent(in),	optional,	dimension(..)	::	metrics	Metrics
integer,	intent(in),	optional		::	batch_size	Batch size

Return Value type(network_type)

Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function accuracy_eval(this, output, start_index, end_index) result(accuracy)

Get the accuracy for the output

Arguments

Type	Intent	Attributes		Name
class(network_type),	intent(in)		::	this	Instance of network
class(*),	intent(in),	dimension(:,:)	::	output	Output
integer,	intent(in)		::	start_index	Start and end batch indices
integer,	intent(in)		::	end_index	Start and end batch indices

Return Value real(kind=real32)

Accuracy value

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine add(this, layer, input_list, output_list, operator)

Add a layer to the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(base_layer_type),	intent(in)			::	layer	Layer to add
integer,	intent(in),	optional,	dimension(:)	::	input_list	Input and output list
integer,	intent(in),	optional,	dimension(:)	::	output_list	Input and output list
class(*),	intent(in),	optional		::	operator	Operator

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine build_from_onnx(this, nodes, initialisers, inputs, value_info, verbose)

Build network from ONNX nodes and initialisers

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
type(onnx_node_type),	intent(in),		dimension(:)	::	nodes	Array of ONNX nodes
type(onnx_initialiser_type),	intent(in),		dimension(:)	::	initialisers	Array of ONNX initialisers
type(onnx_tensor_type),	intent(in),		dimension(:)	::	inputs	Array of ONNX input tensors
type(onnx_tensor_type),	intent(in),		dimension(:)	::	value_info	Array of ONNX value info tensors
integer,	intent(in),	optional		::	verbose	Verbosity level

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine build_leaf_vertices(this)

Calculate output vertices

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine build_root_vertices(this)

Calculate root vertices

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine build_vertex_order(this)

Generate vertex order

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine compile(this, optimiser, loss_method, accuracy_method, metrics, batch_size, verbose)

Compile the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(base_optimiser_type),	intent(in),	optional		::	optimiser	Optimiser
class(*),	intent(in),	optional		::	loss_method	Loss method
character(len=*),	intent(in),	optional		::	accuracy_method	Accuracy method
class(*),	intent(in),	optional,	dimension(..)	::	metrics	Metrics
integer,	intent(in),	optional		::	batch_size	Batch size
integer,	intent(in),	optional		::	verbose	Verbosity level

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private recursive module subroutine dfs(this, vertex_index, visited, order, order_index)

Depth first search

Arguments

Type	Intent	Attributes		Name
class(network_type),	intent(in)		::	this	Instance of the network
integer,	intent(in)		::	vertex_index	Vertex index
logical,	intent(inout),	dimension(this%auto_graph%num_vertices)	::	visited	Visited vertices
integer,	intent(inout),	dimension(this%auto_graph%num_vertices)	::	order	Order of vertices
integer,	intent(inout)		::	order_index	Index of order

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine extract_output_real(this, output)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of network
real(kind=real32),	intent(out),		dimension(..), allocatable	::	output	Output

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function forward_eval(this, input) result(output)

Forward pass evaluation

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
class(*),	intent(in),		dimension(:,:)	::	input	Input data

Return Value type(array_type), pointer, (:,:)

Output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function forward_eval_multi(this, input) result(output)

Forward pass evaluation for multiple outputs

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
class(*),	intent(in),		dimension(:,:)	::	input	Input data

Return Value type(array_ptr_type), pointer, (:)

Output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine forward_generic2d(this, input)

Forward pass for generic 2D input

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
class(*),	intent(in),		dimension(:,:)	::	input	Input data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private pure module function get_gradients(this) result(gradients)

Get gradients of learnable parameters

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

Return Value real(kind=real32), dimension(this%num_params)

Gradients

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private pure module function get_num_params(this) result(num_params)

Get number of learnable parameters in the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

Return Value integer

Number of parameters

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function get_output(this) result(output)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

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

Output

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function get_output_shape(this) result(output_shape)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

Return Value integer, dimension(2)

Output shape

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private pure module function get_params(this) result(params)

Get learnable parameters

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

Return Value real(kind=real32), dimension(this%num_params)

Learnable parameters

private interface get_sample

private module function get_sample_array(input, start_index, end_index, batch_size, as_graph) result(sample)

Get sample for mixed input

Arguments

Type	Intent	Attributes		Name
class(array_type),	intent(in),	dimension(:,:)	::	input	Input array
integer,	intent(in)		::	start_index	Start and end indices
integer,	intent(in)		::	end_index	Start and end indices
integer,	intent(in)		::	batch_size	Batch size
logical,	intent(in)		::	as_graph	Boolean whether to treat the input as a graph

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

Sample array

private module function get_sample_flang(input, start_index, end_index, batch_size) result(sample)

Get a sample from a rank

Arguments

Type	Intent	Attributes		Name
real(kind=real32),	intent(in),	dimension(..)	::	input	Input array
integer,	intent(in)		::	start_index	Start and end indices
integer,	intent(in)		::	end_index	Start and end indices
integer,	intent(in)		::	batch_size	Batch size

Return Value real(kind=real32), allocatable, (:,:)

Sample array

private module function get_sample_graph1d(input, start_index, end_index, batch_size) result(sample)

Get sample for graph input

Arguments

Type	Intent	Attributes		Name
class(graph_type),	intent(in),	dimension(:)	::	input	Input array
integer,	intent(in)		::	start_index	Start and end indices
integer,	intent(in)		::	end_index	Start and end indices
integer,	intent(in)		::	batch_size	Batch size

Return Value type(graph_type), dimension(1, batch_size)

Sample array

private module function get_sample_graph2d(input, start_index, end_index, batch_size) result(sample)

Get sample for graph input

Arguments

Type	Intent	Attributes		Name
class(graph_type),	intent(in),	dimension(:,:)	::	input	Input array
integer,	intent(in)		::	start_index	Start and end indices
integer,	intent(in)		::	end_index	Start and end indices
integer,	intent(in)		::	batch_size	Batch size

Return Value type(graph_type), dimension(size(input,1), batch_size)

Sample array

private module function get_sample_ptr(input, start_index, end_index, batch_size) result(sample_ptr)

Get a sample from a rank

Arguments

Type	Intent	Attributes		Name
real(kind=real32),	intent(in),	dimension(..), target	::	input	Input array
integer,	intent(in)		::	start_index	Start and end indices
integer,	intent(in)		::	end_index	Start and end indices
integer,	intent(in)		::	batch_size	Batch size

Return Value real(kind=real32), pointer, (:,:)

Pointer to sample

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function inverse_design_array_0d(this, target, x_init, optimiser, steps) result(x_opt)

Optimise input to match a target output (array_type inputs)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
type(array_type),	intent(in)			::	target	Target output values
type(array_type),	intent(in)			::	x_init	Initial input values
class(base_optimiser_type),	intent(in),	optional		::	optimiser	Optimiser for input updates (defaults to network optimiser)
integer,	intent(in)			::	steps	Number of optimisation iterations

Return Value type(array_type)

Optimised input

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function inverse_design_array_2d(this, target, x_init, optimiser, steps) result(x_opt)

Optimise input to match a target output (array_type inputs)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
type(array_type),	intent(in),		dimension(:,:)	::	target	Target output values
type(array_type),	intent(in),		dimension(:,:)	::	x_init	Initial input values
class(base_optimiser_type),	intent(in),	optional		::	optimiser	Optimiser for input updates (defaults to network optimiser)
integer,	intent(in)			::	steps	Number of optimisation iterations

Return Value type(array_type), dimension(size(x_init,1), size(x_init,2))

Optimised input

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function inverse_design_real(this, target, x_init, optimiser, steps) result(x_opt)

Optimise input to match a target output (real inputs)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout),		target	::	this	Instance of the network
real(kind=real32),	intent(in),		dimension(:,:)	::	target	Target output values
real(kind=real32),	intent(in),		dimension(:,:)	::	x_init	Initial input values
class(base_optimiser_type),	intent(in),	optional		::	optimiser	Optimiser for input updates (defaults to network optimiser)
integer,	intent(in)			::	steps	Number of optimisation iterations

Return Value real(kind=real32), dimension(size(x_init,1), size(x_init,2))

Optimised input

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function layer_from_id(this, id) result(layer)

Get the layer of the network from its ID

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in),		target	::	this	Instance of the network
integer,	intent(in)			::	id	Layer ID

Return Value class(base_layer_type), pointer

Layer pointer

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function loss_eval(this, start_index, end_index) result(loss)

Get the loss for the output

Arguments

Type	Intent	Attributes		Name
class(network_type),	intent(inout),	target	::	this	Instance of network
integer,	intent(in)		::	start_index	Start and end batch indices
integer,	intent(in)		::	end_index	Start and end batch indices

Return Value type(array_type), pointer

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine network_copy(this, source)

Copy a network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
type(network_type),	intent(in),		target	::	source	Source network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine network_reduction(this, source)

Reduce two networks down to one (i.e. add two networks - parallel)

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
type(network_type),	intent(in)			::	source	Source network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine nullify_graph(this)

Nullify graph data in the network to free memory

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine post_epoch_hook(this, epoch, loss, accuracy)

Hook called after each training epoch. The default implementation is a no-op; override in a derived type to add custom per-epoch behaviour (e.g. W&B metric logging).

Arguments

Type	Intent		Name
class(network_type),	intent(inout)	::	this	Instance of the network
integer,	intent(in)	::	epoch	Current epoch number (1-based)
real(kind=real32),	intent(in)	::	loss	Current loss value
real(kind=real32),	intent(in)	::	accuracy	Current accuracy value

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_array(this, input, verbose) result(output)

Predict the output for a generic input

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of network
class(array_type),	intent(in),		dimension(..)	::	input	Input graph
integer,	intent(in),	optional		::	verbose	Verbosity level

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

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_array_from_real(this, input, output_as_array, verbose) result(output)

Get predicted results as array from supplied inputs using the trained network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(*),	intent(in),		dimension(..)	::	input	Input data
logical,	intent(in)			::	output_as_array	Whether to output as array
integer,	intent(in),	optional		::	verbose	Verbosity level

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

Predicted output data as array

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_generic(this, input, verbose, output_as_graph) result(output)

Predict the output for a generic input

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of network
class(*),	intent(in),		dimension(:,:)	::	input	Input graph
integer,	intent(in),	optional		::	verbose	Verbosity level
logical,	intent(in),	optional		::	output_as_graph	Boolean whether to output as graph

Return Value class(*), dimension(:,:), allocatable

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_graph1d(this, input, verbose) result(output)

Get predicted results from supplied inputs using the trained network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
type(graph_type),	intent(in),		dimension(:)	::	input	Input data
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value type(graph_type), dimension(size(this%leaf_vertices),size(input))

Predicted output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_graph2d(this, input, verbose) result(output)

Get predicted results from supplied inputs using the trained network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
type(graph_type),	intent(in),		dimension(:,:)	::	input	Input data
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value type(graph_type), dimension(size(this%leaf_vertices),size(input, 2))

Predicted output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function predict_real(this, input, verbose) result(output)

Get predicted results from supplied inputs using the trained network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
real(kind=real32),	intent(in),		dimension(..)	::	input	Input data
integer,	intent(in),	optional		::	verbose	Verbosity level

Return Value real(kind=real32), dimension(:,:), allocatable

Predicted output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine print(this, file)

Print the network to file

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network
character(len=*),	intent(in)			::	file	File name

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine print_summary(this)

Print a summary of the network architecture

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(in)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine read(this, file)

Read the network from a file

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
character(len=*),	intent(in)			::	file	File name

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine read_network_settings(this, unit)

Read network settings from a file

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
integer,	intent(in)			::	unit	Unit number for input

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine read_optimiser_settings(this, unit)

Read optimiser settings from a file

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
integer,	intent(in)			::	unit	Unit number for input

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine reset(this)

Reset the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine reset_gradients(this)

Reset learnable parameter gradients

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine reset_state(this)

Reset hidden state of recurrent layers

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine restore_mode(this, mode_store)

Restore the training/inference mode of layers to the values stored in mode_store. This is used after temporarily switching modes for prediction or evaluation on a training batch.

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
logical,	intent(in),		dimension(:)	::	mode_store

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module function save_input_to_network(this, input) result(num_samples)

Convert and save polymorphic input to array or graph

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of network
class(*),	intent(in),		dimension(..)	::	input	Input

Return Value integer

Number of samples

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine save_output_to_network(this, output)

Convert and save polymorphic output to array or graph

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of network
class(*),	intent(in),		dimension(:,:)	::	output	Output

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_accuracy(this, accuracy_method, verbose)

Set network accuracy method

Arguments

Type	Intent	Optional		Name
class(network_type),	intent(inout)		::	this	Instance of the network
character(len=*),	intent(in)		::	accuracy_method	Accuracy method
integer,	intent(in),	optional	::	verbose	Verbosity level

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_batch_size(this, batch_size)

Set batch size

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
integer,	intent(in)			::	batch_size	Batch size

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_gradients(this, gradients)

Set learnable parameter gradients

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
real(kind=real32),	intent(in),		dimension(..)	::	gradients	Gradients

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_inference_mode(this, mode_store, layer_indices)

Put the network in inference mode. Layers such as dropout and batch normalisation use their inference behaviour after this call.

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
logical,	intent(out),	optional,	dimension(:), allocatable	::	mode_store	Optional array to store the training mode of each layer
integer,	intent(in),	optional,	dimension(:)	::	layer_indices	Optional array of layer indices to set to inference mode.

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_loss(this, loss_method, verbose)

Set network loss method

Arguments

Type	Intent	Optional		Name
class(network_type),	intent(inout)		::	this	Instance of the network
class(*),	intent(in)		::	loss_method	Loss method
integer,	intent(in),	optional	::	verbose	Verbosity level

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_metrics(this, metrics)

Set network metrics

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(*),	intent(in),		dimension(..)	::	metrics	Metrics

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_params(this, params)

Set learnable parameters

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
real(kind=real32),	intent(in),		dimension(this%num_params)	::	params	Learnable parameters

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine set_training_mode(this, mode_store, layer_indices)

Put the network in training mode. Layers such as dropout and batch normalisation use their training behaviour after this call.

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
logical,	intent(out),	optional,	dimension(:), allocatable	::	mode_store	Optional array to store the training mode of each layer
integer,	intent(in),	optional,	dimension(:)	::	layer_indices	Optional array of layer indices to set to training mode.

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine test(this, input, output, verbose)

Test the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(*),	intent(in),		dimension(..)	::	input	Input data
class(*),	intent(in),		dimension(:,:)	::	output	Expected output data (data labels)
integer,	intent(in),	optional		::	verbose	Verbosity level

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine train(this, input, output, num_epochs, batch_size, plateau_threshold, shuffle_batches, batch_print_step, verbose, print_precision, scientific_print, early_stopping, val_input, val_output)

Train the network

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network
class(*),	intent(in),		dimension(..)	::	input	Input data
class(*),	intent(in),		dimension(:,:)	::	output	Expected output data (data labels)
integer,	intent(in)			::	num_epochs	Number of epochs to train for
integer,	intent(in),	optional		::	batch_size	Batch size (DEPRECATED)
real(kind=real32),	intent(in),	optional		::	plateau_threshold	Threshold for checking learning plateau
logical,	intent(in),	optional		::	shuffle_batches	Shuffle batch order
integer,	intent(in),	optional		::	batch_print_step	Print step for batch
integer,	intent(in),	optional		::	verbose	Verbosity level
integer,	intent(in),	optional		::	print_precision	Number of decimal places to print for training metrics
logical,	intent(in),	optional		::	scientific_print	Whether to print training metrics in scientific notation
logical,	intent(in),	optional		::	early_stopping	Whether to stop training early if learning plateau is detected
class(*),	intent(in),	optional,	dimension(..)	::	val_input	Validation input data
class(*),	intent(in),	optional,	dimension(:,:)	::	val_output	Validation expected output data

interface

Interface for printing the network to file Interface for printing a summary of the network Interface for reading the network from a file Interface for reading network settings from a file Interface for reading optimiser settings from a file Interface for building network from ONNX nodes and initialisers Interface for adding a layer to the network Interface for resetting the network Interface for compiling the network Interface for setting batch size Interface for setting network metrics Interface for setting network loss method Interface for setting network accuracy method Interface for resetting state of recurrent layers Interface for saving input to network Interface for saving output to network Interface for training the network Interface for testing the network Interface for returning predicted results from supplied inputs using the trained network Interface for returning predicted results from supplied inputs using the trained network (graph input) Interface for updating the learnable parameters of the network based on gradients Interface for generating vertex order Interface for depth first search Interface for calculating root vertices Interface for calculating output vertices Interface for reducing two networks down to one (i.e. add two networks - parallel) Interface for copying a network Interface for getting number of learnable parameters in the network Interface for getting learnable parameters Interface for setting learnable parameters Interface for getting gradients of learnable parameters Interface for setting learnable parameter gradients Interface for resetting learnable parameter gradients Interface for forward pass

private module subroutine update(this)

Update the learnable parameters of the network based on gradients

Arguments

Type	Intent	Optional	Attributes		Name
class(network_type),	intent(inout)			::	this	Instance of the network

procedure, public, pass(this) :: accuracy_eval	Get the accuracy for the output
procedure, public, pass(this) :: add	Add a layer to the network
procedure, public, pass(this) :: build_from_onnx	Build network from ONNX nodes and initialisers
procedure, public, pass(this) :: compile	Compile the network
procedure, public, pass(this) :: copy => network_copy	Copy a network
procedure, public, pass(this) :: extract_output => extract_output_real	Extract network output as real array (only works for single output layer models)
procedure, public, pass(this) :: forward => forward_generic2d	Forward pass for generic 2D input
procedure, public, pass(this) :: forward_eval	Forward pass and return pointer to output (only works for single output layer models)
procedure, public, pass(this) :: get_gradients	Get gradients of learnable parameters
procedure, public, pass(this) :: get_num_params	Get number of learnable parameters in the network
procedure, public, pass(this) :: get_output	Get the output of the network
procedure, public, pass(this) :: get_output_shape	Get the output shape of the network
procedure, public, pass(this) :: get_params	Get learnable parameters
generic, public :: inverse_design => inverse_design_real, inverse_design_array_0d, inverse_design_array_2d	Optimise input to match a target output
procedure, public, pass(this) :: layer_from_id	Get the layer of the network from its ID
procedure, public, pass(this) :: loss_eval	Get the loss for the output
procedure, public, pass(this) :: nullify_graph	Nullify graph data in the network to free memory
procedure, public, pass(this) :: post_epoch_hook	Called after each training epoch; override in derived types for custom per-epoch callbacks (e.g. logging to Weights & Biases).
generic, public :: predict => predict_real, predict_graph1d, predict_graph2d, predict_array, predict_array_from_real	Predict function for different input types
procedure, public, pass(this) :: predict_array	Predict array type output for a generic input
procedure, public, pass(this) :: predict_array_from_real	Return predicted results as array from supplied inputs using the trained network
procedure, public, pass(this) :: predict_generic	Predict generic type output for a generic input
procedure, public, pass(this) :: predict_graph1d
procedure, public, pass(this) :: predict_graph2d	Return predicted results from supplied inputs using the trained network (graph input)
procedure, public, pass(this) :: predict_real	Return predicted results from supplied inputs using the trained network
procedure, public, pass(this) :: print	Print the network to file
procedure, public, pass(this) :: print_summary	Print a summary of the network architecture
procedure, public, pass(this) :: read	Read the network from a file
procedure, public, pass(this) :: reduce => network_reduction	Reduce two networks down to one (i.e. add two networks - parallel)
procedure, public, pass(this) :: reset	Reset the network
procedure, public, pass(this) :: reset_gradients	Reset learnable parameter gradients
procedure, public, pass(this) :: reset_state	Reset hidden state of recurrent layers
procedure, public, pass(this) :: save_input => save_input_to_network	Convert and save polymorphic input to array or graph
procedure, public, pass(this) :: save_output => save_output_to_network	Convert and save polymorphic output to array or graph
procedure, public, pass(this) :: set_accuracy	Set network accuracy method
procedure, public, pass(this) :: set_batch_size	Set batch size
procedure, public, pass(this) :: set_gradients	Set learnable parameter gradients
procedure, public, pass(this) :: set_inference_mode	Set inference mode for layers with training/inference-specific behaviour
procedure, public, pass(this) :: set_loss	Set network loss method
procedure, public, pass(this) :: set_metrics	Set network metrics
procedure, public, pass(this) :: set_params	Set learnable parameters
procedure, public, pass(this) :: set_training_mode	Set training mode for layers with training/inference-specific behaviour
procedure, public, pass(this) :: test	Test the network
procedure, public, pass(this) :: train	Train the network
procedure, public, pass(this) :: update	Update the learnable parameters of the network based on gradients
procedure, private, pass(this) :: build_leaf_vertices	Calculate output vertices
procedure, private, pass(this) :: build_root_vertices	Calculate root vertices
procedure, private, pass(this) :: build_vertex_order	Generate vertex order
procedure, private, pass(this) :: dfs	Depth first search
procedure, private, pass(this) :: inverse_design_array_0d	Inverse design with 0d array_type inputs
procedure, private, pass(this) :: inverse_design_array_2d	Inverse design with 2d array_type inputs
procedure, private, pass(this) :: inverse_design_real	Inverse design with real inputs
procedure, private, pass(this) :: read_network_settings	Read network settings from a file
procedure, private, pass(this) :: read_optimiser_settings	Read optimiser settings from a file
procedure, private, pass(this) :: restore_mode	Reset the training/inference mode of layers to the values stored in mode_store.

Type	Visibility	Attributes		Name		Initial
character(len=:),	public,	allocatable	::	accuracy_method			Loss and accuracy method names
real(kind=real32),	public		::	accuracy_val			Accuracy and loss of the network
type(graph_type),	public		::	auto_graph			Graph structure for the network
integer,	public		::	batch_size	=	0	Batch size
integer,	public		::	epoch	=	0	Epoch number
type(array_type),	public,	dimension(:,:), allocatable	::	expected_array			Expected output array for the network
integer,	public,	dimension(:), allocatable	::	fwd_layer_id			Layer ID for each vertex in forward order
integer,	public,	dimension(:), allocatable	::	fwd_layer_type			Layer type: 0=input, 1=merge, 2=default
integer,	public,	dimension(:), allocatable	::	fwd_num_inputs			Number of input layers for each vertex in forward order
integer,	public,	dimension(:), allocatable	::	fwd_parent_id			Parent layer ID for single-input vertices
procedure(compute_accuracy_function),	public,	nopass, pointer	::	get_accuracy	=>	null()	Pointer to accuracy function
type(array_type),	public,	dimension(:,:), allocatable	::	input_array			Input array for the network
type(graph_type),	public,	dimension(:,:), allocatable	::	input_graph			Input graph for the network
integer,	public,	dimension(:), allocatable	::	leaf_vertices			Root and output vertices
class(base_loss_type),	public,	allocatable	::	loss			Loss method for the network
character(len=:),	public,	allocatable	::	loss_method			Loss and accuracy method names
real(kind=real32),	public		::	loss_val			Accuracy and loss of the network
type(metric_dict_type),	public,	dimension(2)	::	metrics			Metrics for the network
type(container_layer_type),	public,	allocatable, dimension(:)	::	model			Model layers
character(len=:),	public,	allocatable	::	name			Name of the network
integer,	public		::	num_layers	=	0	Number of layers
integer,	public		::	num_outputs	=	0	Number of outputs
integer,	public		::	num_params	=	0	Number of parameters
class(base_optimiser_type),	public,	allocatable	::	optimiser			Optimiser for the network
integer,	public		::	param_num_segments	=	0	Number of parameter segments
integer,	public,	dimension(:), allocatable	::	param_seg_end			End offset in flat parameter array
integer,	public,	dimension(:), allocatable	::	param_seg_layer			Layer index for each parameter segment
integer,	public,	dimension(:), allocatable	::	param_seg_pidx			Param index within that layer for each segment
integer,	public,	dimension(:), allocatable	::	param_seg_start			Start offset in flat parameter array
integer,	public,	dimension(:), allocatable	::	root_vertices			Root and output vertices
logical,	public		::	use_graph_input	=	.false.	Boolean flag for graph input
logical,	public		::	use_graph_output	=	.false.	Boolean flag for graph output
integer,	public,	dimension(:), allocatable	::	vertex_order			Order of vertices

athena__network Module

Contents

Interfaces

Derived Types

Uses

Used by

Descendants:

Interfaces

public interface network_type

private module function network_setup(layers, optimiser, loss_method, accuracy_method, metrics, batch_size) result(network) Implementation →

Arguments

Return Value type(network_type)

interface

private module function accuracy_eval(this, output, start_index, end_index) result(accuracy) Implementation →

Arguments

Return Value real(kind=real32)

interface

private module subroutine add(this, layer, input_list, output_list, operator) Implementation →

Arguments

interface

private module subroutine build_from_onnx(this, nodes, initialisers, inputs, value_info, verbose) Implementation →

Arguments

interface

private module subroutine build_leaf_vertices(this) Implementation →

Arguments

interface

private module subroutine build_root_vertices(this) Implementation →

Arguments

interface

private module subroutine build_vertex_order(this) Implementation →

Arguments

interface

private module subroutine compile(this, optimiser, loss_method, accuracy_method, metrics, batch_size, verbose) Implementation →

Arguments

interface

private recursive module subroutine dfs(this, vertex_index, visited, order, order_index) Implementation →

Arguments

interface

private module subroutine extract_output_real(this, output) Implementation →

Arguments

interface

private module function forward_eval(this, input) result(output) Implementation →

Arguments

Return Value type(array_type), pointer, (:,:)

interface

private module function forward_eval_multi(this, input) result(output) Implementation →

Arguments

Return Value type(array_ptr_type), pointer, (:)

interface

private module subroutine forward_generic2d(this, input) Implementation →

Arguments

interface

private pure module function get_gradients(this) result(gradients) Implementation →

Arguments

Return Value real(kind=real32), dimension(this%num_params)

interface

private pure module function get_num_params(this) result(num_params) Implementation →

Arguments

Return Value integer

interface

private module function get_output(this) result(output) Implementation →

Arguments

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

interface

private module function get_output_shape(this) result(output_shape) Implementation →

Arguments

Return Value integer, dimension(2)

interface

private pure module function get_params(this) result(params) Implementation →

Arguments

Return Value real(kind=real32), dimension(this%num_params)

private interface get_sample

private module function get_sample_array(input, start_index, end_index, batch_size, as_graph) result(sample) Implementation →

Arguments

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

private module function get_sample_flang(input, start_index, end_index, batch_size) result(sample) Implementation →

Arguments

Return Value real(kind=real32), allocatable, (:,:)

private module function get_sample_graph1d(input, start_index, end_index, batch_size) result(sample) Implementation →

Arguments

private module function network_setup(layers, optimiser, loss_method, accuracy_method, metrics, batch_size) result(network)

private module function accuracy_eval(this, output, start_index, end_index) result(accuracy)

private module subroutine add(this, layer, input_list, output_list, operator)

private module subroutine build_from_onnx(this, nodes, initialisers, inputs, value_info, verbose)

private module subroutine build_leaf_vertices(this)

private module subroutine build_root_vertices(this)

private module subroutine build_vertex_order(this)

private module subroutine compile(this, optimiser, loss_method, accuracy_method, metrics, batch_size, verbose)

private recursive module subroutine dfs(this, vertex_index, visited, order, order_index)

private module subroutine extract_output_real(this, output)

private module function forward_eval(this, input) result(output)

private module function forward_eval_multi(this, input) result(output)

private module subroutine forward_generic2d(this, input)

private pure module function get_gradients(this) result(gradients)

private pure module function get_num_params(this) result(num_params)

private module function get_output(this) result(output)

private module function get_output_shape(this) result(output_shape)

private pure module function get_params(this) result(params)

private module function get_sample_array(input, start_index, end_index, batch_size, as_graph) result(sample)

private module function get_sample_flang(input, start_index, end_index, batch_size) result(sample)

private module function get_sample_graph1d(input, start_index, end_index, batch_size) result(sample)

private module function get_sample_graph2d(input, start_index, end_index, batch_size) result(sample)

private module function get_sample_ptr(input, start_index, end_index, batch_size) result(sample_ptr)

private module function inverse_design_array_0d(this, target, x_init, optimiser, steps) result(x_opt)

private module function inverse_design_array_2d(this, target, x_init, optimiser, steps) result(x_opt)

private module function inverse_design_real(this, target, x_init, optimiser, steps) result(x_opt)

private module function layer_from_id(this, id) result(layer)

private module function loss_eval(this, start_index, end_index) result(loss)

private module subroutine network_copy(this, source)

private module subroutine network_reduction(this, source)

private module subroutine nullify_graph(this)

private module subroutine post_epoch_hook(this, epoch, loss, accuracy)

private module function predict_array(this, input, verbose) result(output)

private module function predict_array_from_real(this, input, output_as_array, verbose) result(output)

private module function predict_generic(this, input, verbose, output_as_graph) result(output)

private module function predict_graph1d(this, input, verbose) result(output)

private module function predict_graph2d(this, input, verbose) result(output)

private module function predict_real(this, input, verbose) result(output)

private module subroutine print(this, file)

private module subroutine print_summary(this)