def _grow_ensemble_ready_fn():
    sizes = array_ops.unstack(split_sizes)
    partition_ids_list = list(array_ops.split(partition_ids, sizes, axis=0))
    if (self._learner_config.weak_learner_type == learner_pb2.LearnerConfig.OBLIVIOUS_DECISION_TREE):
        sizes = len(training_state.handlers)
    gains_list = list(array_ops.split(gains, sizes, axis=0))
    split_info_list = list(array_ops.split(split_infos, sizes, axis=0))
    return training_ops.grow_tree_ensemble(tree_ensemble_handle=self._ensemble_handle, stamp_token=ensemble_stamp, next_stamp_token=next_ensemble_stamp, learning_rate=learning_rate, partition_ids=partition_ids_list, gains=gains_list, splits=split_info_list, learner_config=self._learner_config_serialized, dropout_seed=dropout_seed, center_bias=self._center_bias, max_tree_depth=self._max_tree_depth, weak_learner_type=self._learner_config.weak_learner_type)
def _grow_ensemble_ready_fn():
    sizes = array_ops.unstack(split_sizes)
    partition_ids_list = list(array_ops.split(partition_ids, sizes, axis=0))
    if (self._learner_config.weak_learner_type == learner_pb2.LearnerConfig.OBLIVIOUS_DECISION_TREE):
        sizes = len(training_state.handlers)
    gains_list = list(array_ops.split(gains, sizes, axis=0))
    split_info_list = list(array_ops.split(split_infos, sizes, axis=0))
    return training_ops.grow_tree_ensemble(tree_ensemble_handle=self._ensemble_handle, stamp_token=ensemble_stamp, next_stamp_token=next_ensemble_stamp, learning_rate=learning_rate, partition_ids=partition_ids_list, gains=gains_list, splits=split_info_list, learner_config=self._learner_config_serialized, dropout_seed=dropout_seed, center_bias=self._center_bias, max_tree_depth=self._max_tree_depth, weak_learner_type=self._learner_config.weak_learner_type)