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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _remote(self, args=None, kwargs=None, num_return_vals=None, num_cpus=None, num_gpus=None, resources=None):
 """An experimental alternate way to submit remote functions."""

        worker = ray.worker.get_global_worker()
        worker.check_connected()

        if self._last_export_session < worker._session_index:
            # If this function was exported in a previous session, we need to
            # export this function again, because current GCS doesn't have it.
            self._last_export_session = worker._session_index
            worker.function_actor_manager.export(self)

        kwargs = {} if kwargs is None else kwargs
        args = [] if args is None else args
        args = ray.signature.extend_args(self._function_signature, args,
                                         kwargs)

        if num_return_vals is None:
            num_return_vals = self._num_return_vals

        resources = ray.utils.resources_from_resource_arguments(
            self._num_cpus, self._num_gpus, self._resources, num_cpus,
            num_gpus, resources)
        if worker.mode == ray.worker.LOCAL_MODE:
            # In LOCAL_MODE, remote calls simply execute the function.
            # We copy the arguments to prevent the function call from
            # mutating them and to match the usual behavior of
            # immutable remote objects.
            result = self._function(*copy.deepcopy(args))
            return result
        object_ids = worker.submit_task(
            self._function_descriptor,
            args,
            num_return_vals=num_return_vals,
            resources=resources)
        if len(object_ids) == 1:
            return object_ids[0]
        elif len(object_ids) > 1:
            return object_ids