Golang Cortex.Copy方法代码示例

func (shc *StochasticHillClimber) Train(cortex *ng.Cortex, scape Scape) (resultNeuralNet *ng.Cortex, fitness float64, succeeded bool) {

	shc.validate()

	numAttempts := 0

	fittestNeuralNet := cortex.Copy()
	resultNeuralNet = cortex

	// Apply NN to problem and save fitness
	fitness = scape.Fitness(fittestNeuralNet)
	logg.LogTo("MAIN", "Initial fitness: %v", fitness)

	if fitness > shc.FitnessThreshold {
		succeeded = true
		return
	}

	for i := 0; ; i++ {

		// Save the genotype
		candidateNeuralNet := fittestNeuralNet.Copy()

		// Perturb synaptic weights and biases
		PerturbParameters(candidateNeuralNet, shc.WeightSaturationRange)

		// Re-Apply NN to problem
		candidateFitness := scape.Fitness(candidateNeuralNet)
		logg.LogTo("DEBUG", "candidate fitness: %v", fitness)

		// If fitness of perturbed NN is higher, discard original NN and keep new
		// If fitness of original is higher, discard perturbed and keep old.

		if candidateFitness > fitness {
			logg.LogTo("MAIN", "i: %v candidateFitness: %v > fitness: %v", i, candidateFitness, fitness)
			i = 0
			fittestNeuralNet = candidateNeuralNet
			resultNeuralNet = candidateNeuralNet.Copy()
			fitness = candidateFitness
		}

		if candidateFitness > shc.FitnessThreshold {
			logg.LogTo("MAIN", "candidateFitness: %v > Threshold.  Success at i=%v", candidateFitness, i)
			succeeded = true
			break
		}

		if ng.IntModuloProper(i, shc.MaxIterationsBeforeRestart) {
			logg.LogTo("MAIN", "** restart hill climber.  fitness: %f i/max: %d/%d", fitness, numAttempts, shc.MaxAttempts)
			numAttempts += 1
			i = 0
			shc.resetParametersToRandom(fittestNeuralNet)
			ng.SeedRandom()
		}

		if numAttempts >= shc.MaxAttempts {
			succeeded = false
			break
		}

	}

	return

}

func (tmt *TopologyMutatingTrainer) Train(cortex *ng.Cortex, scape Scape) (fittestCortex *ng.Cortex, succeeded bool) {

	ng.SeedRandom()

	shc := tmt.StochasticHillClimber

	includeNonTopological := false
	mutators := CortexMutatorsNonRecurrent(includeNonTopological)

	originalCortex := cortex.Copy()

	currentCortex := cortex

	// Apply NN to problem and save fitness
	logg.LogTo("MAIN", "Get initial fitness")
	fitness := scape.Fitness(currentCortex)
	logg.LogTo("MAIN", "Initial fitness: %v", fitness)

	if fitness > shc.FitnessThreshold {
		succeeded = true
		return
	}

	for i := 0; ; i++ {

		logg.LogTo("MAIN", "Before mutate.  i/max: %d/%d", i, tmt.MaxAttempts)

		// before we mutate the cortex, we need to init it,
		// otherwise things like Outsplice will fail because
		// there are no DataChan's.
		currentCortex.Init()

		// mutate the network
		randInt := RandomIntInRange(0, len(mutators))
		mutator := mutators[randInt]
		ok, _ := mutator(currentCortex)
		if !ok {
			logg.LogTo("MAIN", "Mutate didn't work, retrying...")
			continue
		}

		isValid := currentCortex.Validate()
		if !isValid {
			logg.LogPanic("Cortex did not validate")
		}

		filenameJson := fmt.Sprintf("cortex-%v.json", i)
		currentCortex.MarshalJSONToFile(filenameJson)
		filenameSvg := fmt.Sprintf("cortex-%v.svg", i)
		currentCortex.RenderSVGFile(filenameSvg)
		logg.LogTo("MAIN", "Post mutate cortex svg: %v json: %v", filenameSvg, filenameJson)

		logg.LogTo("MAIN", "Run stochastic hill climber..")

		// memetic step: call stochastic hill climber and see if it can solve it
		fittestCortex, _, succeeded = shc.Train(currentCortex, scape)
		logg.LogTo("MAIN", "stochastic hill climber finished.  succeeded: %v", succeeded)

		if succeeded {
			succeeded = true
			break
		}

		if i >= tmt.MaxAttempts {
			succeeded = false
			break
		}

		if ng.IntModuloProper(i, tmt.MaxIterationsBeforeRestart) {
			logg.LogTo("MAIN", "** Restart .  i/max: %d/%d", i, tmt.MaxAttempts)

			currentCortex = originalCortex.Copy()
			isValid := currentCortex.Validate()
			if !isValid {
				currentCortex.Repair() // TODO: remove workaround
				isValid = currentCortex.Validate()
				if !isValid {
					logg.LogPanic("Cortex could not be repaired")
				}
			}

		}

	}

	return

}