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Merge pull request #65 from yaricom/parallel-experiment-simulation
Parallel experiments evaluation
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,144 @@ | ||
| package pole | ||
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| import ( | ||
| "context" | ||
| "fmt" | ||
| "github.com/yaricom/goNEAT/v4/experiment" | ||
| "github.com/yaricom/goNEAT/v4/experiment/utils" | ||
| "github.com/yaricom/goNEAT/v4/neat" | ||
| "github.com/yaricom/goNEAT/v4/neat/genetics" | ||
| "sync" | ||
| ) | ||
|
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| type cartPoleParallelGenerationEvaluator struct { | ||
| cartPoleGenerationEvaluator | ||
| } | ||
|
|
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| type parallelEvaluationResult struct { | ||
| genomeId int | ||
| fitness float64 | ||
| error float64 | ||
| winner bool | ||
| err error | ||
| } | ||
|
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| // NewCartPoleParallelGenerationEvaluator is to create generations evaluator for single-pole balancing experiment. | ||
| // This experiment performs evolution on single pole balancing task in order to produce appropriate genome. | ||
| func NewCartPoleParallelGenerationEvaluator(outDir string, randomStart bool, winBalanceSteps int) experiment.GenerationEvaluator { | ||
| return &cartPoleParallelGenerationEvaluator{ | ||
| cartPoleGenerationEvaluator{ | ||
| OutputPath: outDir, | ||
| RandomStart: randomStart, | ||
| WinBalancingSteps: winBalanceSteps, | ||
| }, | ||
| } | ||
| } | ||
|
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| // GenerationEvaluate evaluates one epoch for given population and prints results into output directory if any. | ||
| func (e *cartPoleParallelGenerationEvaluator) GenerationEvaluate(ctx context.Context, pop *genetics.Population, epoch *experiment.Generation) error { | ||
| options, ok := neat.FromContext(ctx) | ||
| if !ok { | ||
| return neat.ErrNEATOptionsNotFound | ||
| } | ||
|
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| organismMapping := make(map[int]*genetics.Organism) | ||
|
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| popSize := len(pop.Organisms) | ||
| resChan := make(chan parallelEvaluationResult, popSize) | ||
| // The wait group to wait for all GO routines | ||
| var wg sync.WaitGroup | ||
|
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| // Evaluate each organism in generation | ||
| for _, org := range pop.Organisms { | ||
| if _, ok = organismMapping[org.Genotype.Id]; ok { | ||
| return fmt.Errorf("organism with %d already exists in mapping", org.Genotype.Id) | ||
| } | ||
| organismMapping[org.Genotype.Id] = org | ||
| wg.Add(1) | ||
|
|
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| // run in separate GO thread | ||
| go func(organism *genetics.Organism, resChan chan<- parallelEvaluationResult, wg *sync.WaitGroup) { | ||
| defer wg.Done() | ||
|
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| // create simulator and evaluate | ||
| winner, err := OrganismEvaluate(organism, e.WinBalancingSteps, e.RandomStart) | ||
| if err != nil { | ||
| resChan <- parallelEvaluationResult{err: err} | ||
| return | ||
| } | ||
|
|
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| // create result | ||
| result := parallelEvaluationResult{ | ||
| genomeId: organism.Genotype.Id, | ||
| fitness: organism.Fitness, | ||
| error: organism.Error, | ||
| winner: winner, | ||
| } | ||
| resChan <- result | ||
|
|
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| }(org, resChan, &wg) | ||
| } | ||
|
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| // wait for evaluation results | ||
| wg.Wait() | ||
| close(resChan) | ||
|
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| for result := range resChan { | ||
| if result.err != nil { | ||
| return result.err | ||
| } | ||
| // find and update original organism | ||
| org, ok := organismMapping[result.genomeId] | ||
| if ok { | ||
| org.Fitness = result.fitness | ||
| org.Error = result.error | ||
| } else { | ||
| return fmt.Errorf("organism not found in mapping for id: %d", result.genomeId) | ||
| } | ||
|
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| if result.winner && (epoch.Champion == nil || org.Fitness > epoch.Champion.Fitness) { | ||
| // This will be winner in Markov case | ||
| epoch.Solved = true | ||
| epoch.WinnerNodes = len(org.Genotype.Nodes) | ||
| epoch.WinnerGenes = org.Genotype.Extrons() | ||
| epoch.WinnerEvals = options.PopSize*epoch.Id + org.Genotype.Id | ||
| epoch.Champion = org | ||
| org.IsWinner = true | ||
| } | ||
| } | ||
|
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| // Fill statistics about current epoch | ||
| epoch.FillPopulationStatistics(pop) | ||
|
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| // Only print to file every print_every generation | ||
| if epoch.Solved || epoch.Id%options.PrintEvery == 0 { | ||
| if _, err := utils.WritePopulationPlain(e.OutputPath, pop, epoch); err != nil { | ||
| neat.ErrorLog(fmt.Sprintf("Failed to dump population, reason: %s\n", err)) | ||
| return err | ||
| } | ||
| } | ||
|
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| if epoch.Solved { | ||
| // print winner organism's statistics | ||
| org := epoch.Champion | ||
| utils.PrintActivationDepth(org, true) | ||
|
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| genomeFile := "pole1_winner_genome" | ||
| // Prints the winner organism to file! | ||
| if orgPath, err := utils.WriteGenomePlain(genomeFile, e.OutputPath, org, epoch); err != nil { | ||
| neat.ErrorLog(fmt.Sprintf("Failed to dump winner organism's genome, reason: %s\n", err)) | ||
| } else { | ||
| neat.InfoLog(fmt.Sprintf("Generation #%d winner's genome dumped to: %s\n", epoch.Id, orgPath)) | ||
| } | ||
|
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| // Prints the winner organism's phenotype to the Cytoscape JSON file! | ||
| if orgPath, err := utils.WriteGenomeCytoscapeJSON(genomeFile, e.OutputPath, org, epoch); err != nil { | ||
| neat.ErrorLog(fmt.Sprintf("Failed to dump winner organism's phenome Cytoscape JSON graph, reason: %s\n", err)) | ||
| } else { | ||
| neat.InfoLog(fmt.Sprintf("Generation #%d winner's phenome Cytoscape JSON graph dumped to: %s\n", | ||
| epoch.Id, orgPath)) | ||
| } | ||
| } | ||
|
|
||
| return nil | ||
| } |
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