models.py 文件源码

def _joblib_meanfield_update_states(self,states_list,num_procs):
        if len(states_list) > 0:
            from joblib import Parallel, delayed
            import parallel

            joblib_args = list_split(
                    [self._get_joblib_pair(s) for s in states_list],
                    num_procs)

            parallel.model = self
            parallel.args = joblib_args

            allstats = Parallel(n_jobs=num_procs,backend='multiprocessing')\
                    (delayed(parallel._get_stats)(idx) for idx in range(len(joblib_args)))

            for s, stats in zip(
                    [s for grp in list_split(states_list) for s in grp],
                    [s for grp in allstats for s in grp]):
                s.all_expected_stats = stats