optimize.py 文件源码

def run_a_trial():
    """Run one TPE meta optimisation step and save its results."""
    max_evals = nb_evals = 1

    print("Attempt to resume a past training if it exists:")

    try:
        # https://github.com/hyperopt/hyperopt/issues/267
        trials = pickle.load(open("results.pkl", "rb"))
        print("Found saved Trials! Loading...")
        max_evals = len(trials.trials) + nb_evals
        print("Rerunning from {} trials to add another one.".format(
            len(trials.trials)))
    except:
        trials = Trials()
        print("Starting from scratch: new trials.")

    best = fmin(
        build_and_optimize_cnn,
        space,
        algo=tpe.suggest,
        trials=trials,
        max_evals=max_evals
    )
    pickle.dump(trials, open("results.pkl", "wb"))

    print("\nOPTIMIZATION STEP COMPLETE.\n")
    print("Best results yet (note that this is NOT calculated on the 'loss' "
          "metric despite the key is 'loss' - we rather take the negative "
          "best accuracy throughout learning as a metric to minimize):")
    print(best)