code: def vectorization(self, data_items):
      for idx in range(len(data_items)):
          data_items[idx] = self._vectorize_one_dataitem(
              data_items[idx]
          )
  
imports: from copy import deepcopy
  import stanfordcorenlp
  import torch
  from graph4nlp.pytorch.data.data import GraphData
  from graph4nlp.pytorch.data.dataset import SequenceLabelingDataset
  from dependency_graph_construction_without_tokenize import DependencyBasedGraphConstruction_without_tokenizer
  from line_graph_construction import LineBasedGraphConstruction
label_desc: Use image node_id 7 for calling the ConllDataset_inference obj's underlying member method code with example usage: obj.vectorization(data_items) without return types