inference_engine_m_ – Inference-Engine

Define an abstraction that supports inference operationsn on a neural network

Uses

- sourcery_string_m
- kind_parameters_m
- differentiable_activation_strategy_m
- tensor_range_m
- activation_strategy_m
- tensor_m
- sourcery_file_m
Help

Graph Key

Nodes of different colours represent the following:

Solid arrows point from a submodule to the (sub)module which it is descended from. Dashed arrows point from a module or program unit to modules which it uses.
Where possible, edges connecting nodes are given different colours to make them easier to distinguish in large graphs.

Variables

Type	Visibility	Attributes		Name		Initial
character(len=*),	private,	parameter	::	key(*)	=	[character(len=len("usingSkipConnections"))::"modelName", "modelAuthor", "compilationDate", "activationFunction", "usingSkipConnections"]

Interfaces

interface

public elemental module function infer(self, inputs) result(outputs)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self
type(tensor_t),	intent(in)			::	inputs

Return Value type(tensor_t)

public interface inference_engine_t

private impure elemental module function construct_from_json(file_) result(inference_engine)

Arguments

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

Return Value type(inference_engine_t)

private pure module function construct_from_padded_arrays(metadata, weights, biases, nodes, input_range, output_range) result(inference_engine)

Arguments

Type	Intent	Optional		Name
type(string_t),	intent(in)		::	metadata(:)
real(kind=rkind),	intent(in)		::	weights(:,:,:)
real(kind=rkind),	intent(in)		::	biases(:,:)
integer,	intent(in)		::	nodes(0:)
type(tensor_range_t),	intent(in),	optional	::	input_range
type(tensor_range_t),	intent(in),	optional	::	output_range

Return Value type(inference_engine_t)

interface

private elemental module function activation_function_name(self) result(activation_name)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value type(string_t)

interface

private elemental module subroutine assert_conformable_with(self, inference_engine)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self
type(inference_engine_t),	intent(in)			::	inference_engine

interface

private elemental module function map_from_output_range(self, normalized_tensor) result(tensor)

The result contains the output tensor values unnormalized via the inverse of the mapping used in training

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self
type(tensor_t),	intent(in)			::	normalized_tensor

Return Value type(tensor_t)

interface

private elemental module function map_to_input_range(self, tensor) result(normalized_tensor)

The result contains the input tensor values normalized to fall on the range used during training

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self
type(tensor_t),	intent(in)			::	tensor

Return Value type(tensor_t)

interface

private pure module function nodes_per_layer(self) result(node_count)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value integer, allocatable, (:)

interface

private elemental module function norm(self) result(norm_of_self)

Arguments

Type	Intent	Optional	Attributes		Name
class(difference_t),	intent(in)			::	self

Return Value real(kind=rkind)

interface

private elemental module function num_inputs(self) result(input_count)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value integer

interface

private elemental module function num_outputs(self) result(output_count)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value integer

interface

private pure module function skip(self) result(use_skip_connections)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value logical

interface

private elemental module function subtract(self, rhs) result(difference)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self
type(inference_engine_t),	intent(in)			::	rhs

Return Value type(difference_t)

interface

private pure module function to_exchange(self) result(exchange)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value type(exchange_t)

interface

private impure elemental module function to_json(self) result(json_file)

Arguments

Type	Intent	Optional	Attributes		Name
class(inference_engine_t),	intent(in)			::	self

Return Value type(file_t)

Derived Types

type, public :: difference_t

Components

Type	Visibility	Attributes		Name
real(kind=rkind),	private,	allocatable	::	biases_difference_(:,:)
integer,	private,	allocatable	::	nodes_difference_(:)
real(kind=rkind),	private,	allocatable	::	weights_difference_(:,:,:)

Type-Bound Procedures

procedure, public :: norm

type, public :: exchange_t

Components

Type	Visibility	Attributes		Name
class(activation_strategy_t),	public,	allocatable	::	activation_strategy_
real(kind=rkind),	public,	allocatable	::	biases_(:,:)
type(tensor_range_t),	public		::	input_range_
type(string_t),	public		::	metadata_(size(key))
integer,	public,	allocatable	::	nodes_(:)
type(tensor_range_t),	public		::	output_range_
real(kind=rkind),	public,	allocatable	::	weights_(:,:,:)

type, public :: inference_engine_t

Encapsulate the minimal information needed to perform inference

Components

Type	Visibility	Attributes		Name
class(activation_strategy_t),	private,	allocatable	::	activation_strategy_
real(kind=rkind),	private,	allocatable	::	biases_(:,:)
type(tensor_range_t),	private		::	input_range_
type(string_t),	private		::	metadata_(size(key))
integer,	private,	allocatable	::	nodes_(:)
type(tensor_range_t),	private		::	output_range_
real(kind=rkind),	private,	allocatable	::	weights_(:,:,:)

Constructor

private impure, elemental, module function construct_from_json (file_)
private pure, module function construct_from_padded_arrays (metadata, weights, biases, nodes, input_range, output_range)

Type-Bound Procedures

procedure, public :: activation_function_name
procedure, public :: assert_conformable_with
procedure, public :: infer
procedure, public :: map_from_output_range
procedure, public :: map_to_input_range
procedure, public :: nodes_per_layer
procedure, public :: num_inputs
procedure, public :: num_outputs
generic, public :: operator(-) => subtract
procedure, public :: skip
procedure, public :: to_exchange
procedure, public :: to_json
procedure, private :: subtract

inference_engine_m_ Module

Contents

Variables

Interfaces

Derived Types

Uses

Used by

Descendants:

Variables

Interfaces

interface

public elemental module function infer(self, inputs) result(outputs) Implementation →

Arguments

Return Value type(tensor_t)

public interface inference_engine_t

private impure elemental module function construct_from_json(file_) result(inference_engine) Implementation →

Arguments

Return Value type(inference_engine_t)

private pure module function construct_from_padded_arrays(metadata, weights, biases, nodes, input_range, output_range) result(inference_engine) Implementation →

Arguments

Return Value type(inference_engine_t)

interface

private elemental module function activation_function_name(self) result(activation_name) Implementation →

Arguments

Return Value type(string_t)

interface

private elemental module subroutine assert_conformable_with(self, inference_engine) Implementation →

Arguments

interface

private elemental module function map_from_output_range(self, normalized_tensor) result(tensor) Implementation →

Arguments

Return Value type(tensor_t)

interface

private elemental module function map_to_input_range(self, tensor) result(normalized_tensor) Implementation →

Arguments

Return Value type(tensor_t)

interface

private pure module function nodes_per_layer(self) result(node_count) Implementation →

Arguments

Return Value integer, allocatable, (:)

interface

private elemental module function norm(self) result(norm_of_self) Implementation →

Arguments

Return Value real(kind=rkind)

interface

private elemental module function num_inputs(self) result(input_count) Implementation →

Arguments

Return Value integer

interface

private elemental module function num_outputs(self) result(output_count) Implementation →

Arguments

Return Value integer

interface

private pure module function skip(self) result(use_skip_connections) Implementation →

Arguments

Return Value logical

interface

private elemental module function subtract(self, rhs) result(difference) Implementation →

Arguments

Return Value type(difference_t)

interface

private pure module function to_exchange(self) result(exchange) Implementation →

Arguments

Return Value type(exchange_t)

interface

private impure elemental module function to_json(self) result(json_file) Implementation →

Arguments

Return Value type(file_t)

Derived Types

type, public :: difference_t

Components

Type-Bound Procedures

type, public :: exchange_t

Components

type, public :: inference_engine_t

Components

Constructor

Type-Bound Procedures

public elemental module function infer(self, inputs) result(outputs)

private impure elemental module function construct_from_json(file_) result(inference_engine)

private pure module function construct_from_padded_arrays(metadata, weights, biases, nodes, input_range, output_range) result(inference_engine)

private elemental module function activation_function_name(self) result(activation_name)

private elemental module subroutine assert_conformable_with(self, inference_engine)

private elemental module function map_from_output_range(self, normalized_tensor) result(tensor)

private elemental module function map_to_input_range(self, tensor) result(normalized_tensor)

private pure module function nodes_per_layer(self) result(node_count)

private elemental module function norm(self) result(norm_of_self)

private elemental module function num_inputs(self) result(input_count)

private elemental module function num_outputs(self) result(output_count)

private pure module function skip(self) result(use_skip_connections)

private elemental module function subtract(self, rhs) result(difference)

private pure module function to_exchange(self) result(exchange)

private impure elemental module function to_json(self) result(json_file)