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- package neuralnetwork
- import (
- training "git.semlanik.org/semlanik/NeuralNetwork/training"
- mat "gonum.org/v1/gonum/mat"
- )
- const (
- StateIdle = 1
- StateLearning = 2
- StateValidation = 3
- StatePredict = 4
- )
- type SubscriptionFeatures uint8
- const (
- ActivationsSubscription SubscriptionFeatures = 1 << iota
- BiasesSubscription
- WeightsSubscription
- TrainingSubscription
- ValidationSubscription
- StateSubscription
- AllSubscription = 0xFF
- )
- type StateWatcher interface {
- Init(nn *NeuralNetwork)
- UpdateState(state int)
- UpdateActivations(l int, a *mat.Dense)
- UpdateBiases(l int, biases *mat.Dense)
- UpdateWeights(l int, weights *mat.Dense)
- UpdateTraining(t int, epocs int, samplesProcced int, totalSamplesCount int)
- UpdateValidation(validatorCount int, failCount int)
- GetSubscriptionFeatures() SubscriptionFeatures
- }
- func (f SubscriptionFeatures) Has(flag SubscriptionFeatures) bool {
- return f&flag != 0
- }
- func (f *SubscriptionFeatures) Set(flag SubscriptionFeatures) {
- *f |= flag
- }
- func (f *SubscriptionFeatures) Unset(flag SubscriptionFeatures) {
- *f &= (^flag)
- }
- func (f *SubscriptionFeatures) Clear() {
- *f = 0
- }
- type BatchWorker interface {
- Run(trainer training.Trainer, startIndex, endIndex int)
- Result(layer int) (dB, dW *mat.Dense)
- }
- type BatchWorkerFactory interface {
- GetBatchWorker() BatchWorker
- GetAvailableThreads() int
- }
- type EarlyStop interface {
- Test() bool
- Reset()
- }
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