Source code for parallel

Runs evaluation functions in parallel subprocesses
in order to evaluate multiple genomes at once.
from multiprocessing import Pool

[docs]class ParallelEvaluator(object): def __init__(self, num_workers, eval_function, timeout=None): """ eval_function should take one argument, a tuple of (genome object, config object), and return a single float (the genome's fitness). """ self.num_workers = num_workers self.eval_function = eval_function self.timeout = timeout self.pool = Pool(num_workers)
[docs] def __del__(self): self.pool.close() # should this be terminate? self.pool.join()
[docs] def evaluate(self, genomes, config): jobs = [] for ignored_genome_id, genome in genomes: jobs.append(self.pool.apply_async(self.eval_function, (genome, config))) # assign the fitness back to each genome for job, (ignored_genome_id, genome) in zip(jobs, genomes): = job.get(timeout=self.timeout)