code: def __init__(
      self,
      graph_name,
      static_or_dynamic="static",
      topology_builder=None,
      topology_subdir=None,
      pretrained_word_emb_cache_dir=None,
      edge_strategy=None,
      merge_strategy=None,
      tag_types=None,
      dynamic_init_graph_name=None,
      dynamic_init_topology_builder=None,
      for_inference=None,
      reused_vocab_model=None,
      **kwargs,
  ):
      super(ConllDataset_inference, self).__init__(
          topology_builder=topology_builder,
          topology_subdir=topology_subdir,
          graph_name=graph_name,
          static_or_dynamic=static_or_dynamic,
          edge_strategy=edge_strategy,
          merge_strategy=merge_strategy,
          tag_types=tag_types,
          dynamic_init_graph_name=dynamic_init_graph_name,
          dynamic_init_topology_builder=dynamic_init_topology_builder,
          pretrained_word_emb_cache_dir=pretrained_word_emb_cache_dir,
          for_inference=for_inference,
          reused_vocab_model=reused_vocab_model,
          **kwargs,
      )
  
      self.dynamic_init_topology_builder = dynamic_init_topology_builder
  
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 3 to create a new ConllDataset_inference object from inherited base classes: SequenceLabelingDataset with example: obj = ConllDataset_inference(graph_name, static_or_dynamic, topology_builder, topology_subdir, pretrained_word_emb_cache_dir, edge_strategy, merge_strategy, tag_types, dynamic_init_graph_name, dynamic_init_topology_builder, for_inference, reused_vocab_model)