randomsearch.py 文件源码

def search(config):
    get_params = get_agent_class(config).get_random_config
    params_keys = list(get_params().keys())
    nb_hp_params = len(params_keys)

    if config['debug']:
        print('*** Number of hyper-parameters: %d' % nb_hp_params)

    config['max_iter'] = 5 if config['debug'] else 500
    futures = []
    with concurrent.futures.ProcessPoolExecutor(min(multiprocessing.cpu_count(), config['nb_process'])) as executor:
        nb_config = 5 if config['debug'] else 200 * nb_hp_params
        for i in range(nb_config): 
            params = get_params(config["fixed_params"])
            config.update(params)
            config['random_seed'] = 1

            futures.append(executor.submit(test_params, i, copy.deepcopy(config), copy.deepcopy(params)))
        concurrent.futures.wait(futures)

    results = [future.result() for future in futures]
    results = sorted(results, key=lambda result: result['mean_score'], reverse=True)
    best_params = results[0]['params']

    return { 
        'best_params': best_params
        , 'results': results
    }