Versions in this module Expand all Collapse all v1 v1.55.0 Jan 12, 2024 Changes in this version + const Beta1 + const Beta2 + var BatchSize = 16384 + var LearningRate = 0.01 + func Run(ctx context.Context, datasetProvider IDatasetProvider, ...) error + func ValidationCost(output, target float64) float64 + type ActivationFn interface + Sigma func(x float64) float64 + SigmaPrime func(x float64) float64 + type Gradient struct + M1 float64 + M2 float64 + Value float64 + func (g *Gradient) Apply(elem *float64) + func (g *Gradient) Calculate() float64 + func (g *Gradient) Reset() + func (g *Gradient) Update(delta float64) + type Gradients struct + Cols int + Data []Gradient + Rows int + func NewGradients(rows, cols int) Gradients + func (g *Gradients) AddMatrix(m *Matrix) + func (g *Gradients) Apply(m *Matrix) + type IDatasetProvider interface + Load func(ctx context.Context, dataset chan<- domain.DatasetItem) error + type Matrix struct + Cols int + Data []float64 + Rows int + func NewMatrix(rows, cols int) Matrix + func (m *Matrix) Add(row, col int, delta float64) + func (m *Matrix) Get(row, col int) float64 + func (m *Matrix) Reset() + type Network struct + Biases []Matrix + Id uint32 + Topology Topology + Weights []Matrix + func (n *Network) Save(file string) error + type Neuron struct + A float64 + E float64 + Prime float64 + type ReLu struct + func (s *ReLu) Sigma(x float64) float64 + func (s *ReLu) SigmaPrime(x float64) float64 + type Sample struct + Input []int16 + Target float32 + type Sigmoid struct + SigmoidScale float64 + func (s *Sigmoid) Sigma(x float64) float64 + func (s *Sigmoid) SigmaPrime(x float64) float64 + type ThreadData struct + type Topology struct + HiddenNeurons []uint32 + Inputs uint32 + Outputs uint32 + func (t *Topology) LayerSize() int + type Trainer struct + func NewTrainer(training, validation []Sample, topology []int, threads int, seed int64, ...) *Trainer + func (t *Trainer) Train(epochs int, binFolderPath string) error