

def minimize(self, model, data, max_evals):
    trials_list = self.compute_trials(model, data, max_evals)
    best_val = 10000000.0
    for trials in trials_list:
        for trial in trials:
            val = trial.get('result').get('loss')
            if (val < best_val):
                best_val = val
                best_model_yaml = best_model.get('result').get('model')
                best_model_weights = trial.get('result').get('weights')
    best_model = model_from_yaml(best_model_yaml)
    best_model.set_weights(pickle.loads(best_model_weights))
    return best_model

dataset/ETHPy150Open maxpumperla/elephas/elephas/hyperparam.py HyperParamModel.minimize/VarMisuse@76/108 `trial`->`best_model`