code: def collate_fn(data_list):
      graph_data = [item.graph for item in data_list]
      from graph4nlp.pytorch.data.data import to_batch
  
      big_graph = to_batch(graph_data)
      if isinstance(data_list[0].output_text, str):  # has ground truth
          output_numpy = [item.output_np for item in data_list]
          output_str = [
              item.output_text.lower().strip() for item in data_list
          ]
          output_pad = pad_2d_vals_no_size(output_numpy)
  
          tgt_seq = torch.from_numpy(output_pad).long()
      else:
          output_str = []
          tgt_seq = None
      return {
          "graph_data": big_graph,
          "tgt_seq": tgt_seq,
          "output_str": output_str,
      }
  
file_path: graph4nlp/examples/pytorch/nmt/dataset.py
imports: import pickle
  import nltk
  import torch
  from graph4nlp.pytorch.data.dataset import Text2TextDataItem, Text2TextDataset
  from graph4nlp.pytorch.modules.utils.padding_utils import pad_2d_vals_no_size
label_desc: Use image node_id 5 for calling the IWSLT14Dataset obj's underlying member method code with example usage: obj.collate_fn(data_list) and returns: dict