trainable_network_t Derived Type

type, public, extends(neural_network_t) :: trainable_network_t

Inherits

Help

Components

Type	Visibility	Attributes		Name		Initial
integer,	public,	kind	::	k	=	default_real
integer,	public,	kind	::	m	=	default_real
type(workspace_t),	private		::	workspace_

Constructor

public interface trainable_network_t

private module function default_real_construct_from_components(metadata, weights, biases, nodes, input_map, output_map) result(trainable_network)

Arguments

Type	Intent	Optional	Attributes		Name
type(string_t),	intent(in)			::	metadata(:)
real,	intent(in)			::	weights(:,:,:)
real,	intent(in)			::	biases(:,:)
integer,	intent(in)			::	nodes(0:)
type(tensor_map_t),	intent(in),	optional		::	input_map
type(tensor_map_t),	intent(in),	optional		::	output_map

Return Value type(trainable_network_t)

private impure elemental module function default_real_from_json(file) result(trainable_network)

Arguments

Type	Intent	Optional	Attributes		Name
type(file_t),	intent(in)			::	file

Return Value type(trainable_network_t)

private pure module function default_real_network(neural_network) result(trainable_network)

Arguments

Type	Intent	Optional	Attributes		Name
type(neural_network_t),	intent(in)			::	neural_network

Return Value type(trainable_network_t)

private module function perturbed_identity_network(training_configuration, perturbation_magnitude, metadata, input_map, output_map) result(trainable_network)

Arguments

Type	Intent	Optional	Attributes		Name
type(training_configuration_t),	intent(in)			::	training_configuration
real,	intent(in)			::	perturbation_magnitude
type(string_t),	intent(in)			::	metadata(:)
type(tensor_map_t)				::	input_map
type(tensor_map_t)				::	output_map

Return Value type(trainable_network_t)

Type-Bound Procedures

generic, public :: activation_function_name => default_real_activation_name, double_precision_activation_name

private interface default_real_activation_name()

Arguments
None
private interface double_precision_activation_name()

Arguments
None

generic, public :: infer => default_real_infer, double_precision_infer

private interface default_real_infer()

Arguments
None
private interface double_precision_infer()

Arguments
None

generic, public :: learn => default_real_learn

private interface default_real_learn()

Arguments
None

generic, public :: map_from_output_range => default_real_map_from_output_range, double_precision_map_from_output_range

private interface default_real_map_from_output_range()

Arguments
None
private interface double_precision_map_from_output_range()

Arguments
None

generic, public :: map_to_input_range => default_real_map_to_input_range, double_precision_map_to_input_range

private interface default_real_map_to_input_range()

Arguments
None
private interface double_precision_map_to_input_range()

Arguments
None

generic, public :: map_to_training_ranges => default_real_map_to_training_ranges

private interface default_real_map_to_training_ranges()

Arguments
None

generic, public :: nodes_per_layer => default_real_nodes_per_layer, double_precision_nodes_per_layer

private interface default_real_nodes_per_layer()

Arguments
None
private interface double_precision_nodes_per_layer()

Arguments
None

generic, public :: num_hidden_layers => default_real_num_hidden_layers, double_precision_num_hidden_layers

private interface default_real_num_hidden_layers()

Arguments
None
private interface double_precision_num_hidden_layers()

Arguments
None

generic, public :: num_inputs => default_real_num_inputs, double_precision_num_inputs

private interface default_real_num_inputs()

Arguments
None
private interface double_precision_num_inputs()

Arguments
None

generic, public :: num_outputs => default_real_num_outputs, double_precision_num_outputs

private interface default_real_num_outputs()

Arguments
None
private interface double_precision_num_outputs()

Arguments
None

generic, public :: operator(==) => default_real_approximately_equal, double_precision_approximately_equal

private interface default_real_approximately_equal()

Arguments
None
private interface double_precision_approximately_equal()

Arguments
None

generic, public :: skip => default_real_skip, double_precision_skip

private interface default_real_skip()

Arguments
None
private interface double_precision_skip()

Arguments
None

generic, public :: to_json => default_real_to_json, double_precision_to_json

private interface default_real_to_json()

Arguments
None
private interface double_precision_to_json()

Arguments
None

generic, public :: train => default_real_train

private interface default_real_train()

Arguments
None

procedure, private, non_overridable :: default_real_map_to_training_ranges

interface

private elemental module function default_real_map_to_training_ranges(self, input_output_pair) result(normalized_input_output_pair)

Arguments

Type	Intent	Optional	Attributes		Name
class(trainable_network_t),	intent(in)			::	self
type(input_output_pair_t),	intent(in)			::	input_output_pair

Return Value type(input_output_pair_t)

procedure, private, non_overridable :: default_real_train

interface

private pure module subroutine default_real_train(self, mini_batches_arr, cost, adam, learning_rate)

Arguments

Type	Intent	Optional	Attributes		Name
class(trainable_network_t),	intent(inout)			::	self
type(mini_batch_t),	intent(in)			::	mini_batches_arr(:)
real,	intent(out),	optional,	allocatable	::	cost(:)
logical,	intent(in)			::	adam
real,	intent(in)			::	learning_rate