Added NeuralNetworkInterface and updated learning rate config logic i…

…n gomind.go

gomind.go

@@ -8,13 +8,25 @@ import (
 	"time"
 
 	"github.com/surenderthakran/gomind/activation"
+	"github.com/surenderthakran/gomind/layer"
 	"github.com/surenderthakran/gomind/network"
 )
 
 const (
 	defaultActivationFunction = "LINEAR"
 )
 
+type NeuralNetworkInterface interface {
+	CalculateOutput(input []float64) []float64
+	LastOutput() []float64
+	HiddenLayer() *layer.Layer
+	OutputLayer() *layer.Layer
+	CalculateNewOutputLayerWeights(outputs, targetOutputs []float64) error
+	CalculateNewHiddenLayerWeights() error
+	UpdateWeights()
+	CalculateError(targetOutput []float64) (float64, error)
+}
+
 // Model type defines the neural network's architecture and metadata.
 type Model struct {
 	numberOfInputs                    int
@@ -23,7 +35,7 @@ type Model struct {
 	numberOfOutputs                   int
 	outputLayerActivationFunctionName string
 	learningRate                      float64
-	network                           *network.NeuralNetwork
+	network                           NeuralNetworkInterface
 }
 
 // ModelConfiguration type defines the network configuration template filled by external code while creating a new model.
@@ -108,11 +120,14 @@ func New(configuration *ModelConfiguration) (*Model, error) {
 	}
 	model.numberOfOutputs = configuration.NumberOfOutputs
 
-	model.learningRate = 0.5
-	if configuration.LearningRate <= 0 || configuration.LearningRate > 1 {
-		return nil, errors.New("LearningRate cannot be less than or equals to 0 or greater than 1.")
+	if configuration.LearningRate < 0 || configuration.LearningRate > 1 {
+		return nil, errors.New("LearningRate cannot be less than 0 or greater than 1.")
+	} else if configuration.LearningRate == 0 {
+		model.learningRate = 0.5
+		fmt.Println("Using default learning rate 0.5")
+	} else {
+		model.learningRate = configuration.LearningRate
 	}
-	model.learningRate = configuration.LearningRate
 
 	model.numberOfHiddenNeurons = configuration.NumberOfHiddenLayerNeurons
 	if model.numberOfHiddenNeurons == 0 {
@@ -127,7 +142,7 @@ func New(configuration *ModelConfiguration) (*Model, error) {
 	}
 
 	model.outputLayerActivationFunctionName = activation.ValidFunction(configuration.OutputLayerActivationFunctionName)
-	if model.hiddenLayerActivationFunctionName == "" {
+	if model.outputLayerActivationFunctionName == "" {
 		model.outputLayerActivationFunctionName = defaultActivationFunction
 		fmt.Println("Estimated Ideal Activation Function for Output Layer Neurons: ", model.outputLayerActivationFunctionName)
 	}

network/network.go

@@ -212,7 +212,7 @@ func (network *NeuralNetwork) CalculateError(targetOutput []float64) (float64, e
 func New(numberOfInputs, numberOfHiddenNeurons, numberOfOutputs int, learningRate float64, hiddenLayerActivationFunctionName, outputLayerActivationFunctionName string) (*NeuralNetwork, error) {
 	hiddenLayerActivationService, err := activation.New(hiddenLayerActivationFunctionName)
 	if err != nil {
-		return nil, fmt.Errorf("invalid activation function: %v", err)
+		return nil, fmt.Errorf("unable to create hidden layer activation service for %s: %v", hiddenLayerActivationFunctionName, err)
 	}
 	hiddenLayer, err := layer.New(numberOfHiddenNeurons, numberOfInputs, hiddenLayerActivationService)
 	if err != nil {
@@ -221,7 +221,7 @@ func New(numberOfInputs, numberOfHiddenNeurons, numberOfOutputs int, learningRat
 
 	outputLayerActivationService, err := activation.New(outputLayerActivationFunctionName)
 	if err != nil {
-		return nil, fmt.Errorf("invalid activation function: %v", err)
+		return nil, fmt.Errorf("unable to create output layer activation service for %s: %v", outputLayerActivationFunctionName, err)
 	}
 	outputLayer, err := layer.New(numberOfOutputs, numberOfHiddenNeurons, outputLayerActivationService)
 	if err != nil {