How to use the pathos.abstract_launcher.AbstractWorkerPool._AbstractWorkerPool__map function in pathos

def amap(self, f, *args, **kwds):
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        def submit(*argz):
            """send a job to the server"""
            _pool = self._serve()
           #print("using %s local workers" % _pool.get_ncpus())
            try:
                return _pool.submit(f, argz, globals=globals())
            except pp.DestroyedServerError:
                self._is_alive(None)
        override = True if 'size' in kwds else False
        elem_size = kwds.pop('size', 2)
        length = min(len(task) for task in args)
        args = zip(*args)  #XXX: zip iterator ok? or should be list?
        # submit all jobs, to be collected later with 'get()'
        tasks = [submit(*task) for task in args]
        tasks = [ApplyResult(task) for task in tasks]
        # build a correctly sized results object

def amap(self, f, *args, **kwds): # register a callback ?
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        _pool = self._serve()
        return _pool.map_async(star(f), zip(*args)) # chunksize
    amap.__doc__ = AbstractWorkerPool.amap.__doc__

def map(self, f, *args, **kwds):
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        return list(self.imap(f, *args))
    map.__doc__ = AbstractWorkerPool.map.__doc__

def map(self, f, *args, **kwds):
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        _pool = self._serve()
        return _pool.map(star(f), zip(*args)) # chunksize
    map.__doc__ = AbstractWorkerPool.map.__doc__

def amap(self, f, *args, **kwds): # register a callback ?
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        _pool = self._serve()
        return _pool.map_async(star(f), zip(*args)) # chunksize
    amap.__doc__ = AbstractWorkerPool.amap.__doc__

def map(self, f, *args, **kwds):
        AbstractWorkerPool._AbstractWorkerPool__map(self, f, *args, **kwds)
        _pool = self._serve()
        return _pool.map(star(f), zip(*args)) # chunksize
    map.__doc__ = AbstractWorkerPool.map.__doc__