code: def __init__(
      self,
      root_dir,
      topology_subdir,
      graph_name,
      static_or_dynamic="static",
      tokenizer=word_tokenize,
      lower_case=True,
      pretrained_word_emb_name="840B",
      pretrained_word_emb_url=None,
      target_pretrained_word_emb_name=None,
      target_pretrained_word_emb_url=None,
      pretrained_word_emb_cache_dir=".vector_cache/",
      use_val_for_vocab=False,
      seed=1234,
      thread_number=4,
      port=9000,
      timeout=15000,
      edge_strategy=None,
      share_vocab=True,
      word_emb_size=300,
      dynamic_init_graph_name=None,
      dynamic_init_topology_builder=None,
      dynamic_init_topology_aux_args=None,
      for_inference=False,
      reused_vocab_model=None,
      **kwargs,
  ):
      super(CNNDataset, self).__init__(
          root_dir=root_dir,
          topology_subdir=topology_subdir,
          graph_name=graph_name,
          static_or_dynamic=static_or_dynamic,
          tokenizer=tokenizer,
          lower_case=lower_case,
          pretrained_word_emb_name=pretrained_word_emb_name,
          pretrained_word_emb_url=pretrained_word_emb_url,
          target_pretrained_word_emb_name=target_pretrained_word_emb_name,
          target_pretrained_word_emb_url=target_pretrained_word_emb_url,
          pretrained_word_emb_cache_dir=pretrained_word_emb_cache_dir,
          use_val_for_vocab=use_val_for_vocab,
          seed=seed,
          thread_number=thread_number,
          port=port,
          timeout=timeout,
          edge_strategy=edge_strategy,
          share_vocab=share_vocab,
          word_emb_size=word_emb_size,
          dynamic_init_graph_name=dynamic_init_graph_name,
          dynamic_init_topology_builder=dynamic_init_topology_builder,
          dynamic_init_topology_aux_args=dynamic_init_topology_aux_args,
          for_inference=for_inference,
          reused_vocab_model=reused_vocab_model,
          **kwargs,
      )
  
file_path: graph4nlp/graph4nlp/pytorch/datasets/cnn.py
imports: import json
  import torch
  from nltk.tokenize import word_tokenize
  from graph4nlp.pytorch.data.dataset import Text2TextDataItem, Text2TextDataset
  from graph4nlp.pytorch.modules.utils.padding_utils import pad_2d_vals, pad_2d_vals_no_size
label_desc: Use image node_id 1 to create a new CNNDataset object from inherited base classes: Text2TextDataset with example: obj = CNNDataset(root_dir, topology_subdir, graph_name, static_or_dynamic, tokenizer, lower_case, pretrained_word_emb_name, pretrained_word_emb_url, target_pretrained_word_emb_name, target_pretrained_word_emb_url, pretrained_word_emb_cache_dir, use_val_for_vocab, seed, thread_number, port, timeout, edge_strategy, share_vocab, word_emb_size, dynamic_init_graph_name, dynamic_init_topology_builder, dynamic_init_topology_aux_args, for_inference, reused_vocab_model)