mark4

package

v0.0.0-...-5f2bfed Latest Latest Go to latest Published: Jan 30, 2024 License: BSD-3-Clause Imports: 12 Imported by: 0

Details

Valid go.mod file

The Go module system was introduced in Go 1.11 and is the official dependency management solution for Go.
Redistributable license

Redistributable licenses place minimal restrictions on how software can be used, modified, and redistributed.
Tagged version

Modules with tagged versions give importers more predictable builds.
Stable version

When a project reaches major version v1 it is considered stable.
Learn more about best practices

Repository

github.com/pointlander/lucid

Links

Open Source Insights

Documentation ¶

Index ¶

Constants
func Mark4()
func Mark4a()
type Net
- func NewNet(seed int64, inputs, outputs int) Net
- func (n Net) CalculateStatistics(systems []Sample) Set
- func (n *Net) Fire(input Matrix) (float32, Matrix)
type Random
type Sample
type Set
- func NewStatistics(inputs, outputs int) Set
- func (s Set) Sample(rng *rand.Rand, inputs, outputs int) []Matrix

Constants ¶

View Source

const (
	// Window is the window size
	Window = 8
	// Samples is the number of samples
	Samples = 256
	// Size is the size of the filter
	Size = 64
	// Inputs is the number of inputs
	Inputs = Size
	// Outputs is the number of outputs
	Outputs = 8
)

Variables ¶

This section is empty.

Functions ¶

func Mark4 ¶

func Mark4()

Mark4 is the mark4 model

func Mark4a ¶

func Mark4a()

Mark4a is the mark4a model

Types ¶

type Net ¶

type Net struct {
	Inputs  int
	Outputs int
	Rng     *rand.Rand
	Q       Set
	K       Set
	V       Set
}

Net is a net

func NewNet ¶

func NewNet(seed int64, inputs, outputs int) Net

NewNet makes a new network

func (Net) CalculateStatistics ¶

func (n Net) CalculateStatistics(systems []Sample) Set

CalculateStatistics calculates the statistics of systems

func (*Net) Fire ¶

func (n *Net) Fire(input Matrix) (float32, Matrix)

Fire runs the network

type Random ¶

type Random struct {
	Mean   float32
	StdDev float32
}

Random is a random variable

type Sample ¶

type Sample struct {
	Entropy float32
	Neurons []Matrix
	Outputs Matrix
	Out     Matrix
}

Sample is a sample of a random neural network

type Set ¶

type Set [][]Random

Set is a set of statistics

func NewStatistics ¶

func NewStatistics(inputs, outputs int) Set

NewStatistics generates a new statistics model

func (Set) Sample ¶

func (s Set) Sample(rng *rand.Rand, inputs, outputs int) []Matrix

Sample samples from the statistics

Source Files ¶

View all Source files

model.go

?	: This menu
/	: Search site
f or F	: Jump to
y or Y	: Canonical URL