docstr: Read and parse the file specified by `file_path`.
  The file format is specified by each individual task-specific
  base class. Returns all the indices of data items in this file w.r.t. the whole dataset.
  
  For Text2TextDataset, the format of the input file should contain lines of input,
  each line representing one record of data. The input and output is separated by a tab(  ).
  
  Examples
  --------
  input: list job use languageid0 job ( ANS ) , language ( ANS , languageid0 )
  
  DataItem: input_text="list job use languageid0", output_text="job ( ANS ) ,
  language ( ANS , languageid0 )"
  
  Parameters
  ----------
  file_path: str
      The path of the input file.
  
  Returns
  -------
  list
      The indices of data items in the file w.r.t. the whole dataset.
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code: def parse_file(self, file_path) -> list:
      """
      Read and parse the file specified by `file_path`.
      The file format is specified by each individual task-specific
      base class. Returns all the indices of data items in this file w.r.t. the whole dataset.
  
      For Text2TextDataset, the format of the input file should contain lines of input,
      each line representing one record of data. The input and output is separated by a tab(\t).
  
      Examples
      --------
      input: list job use languageid0 job ( ANS ) , language ( ANS , languageid0 )
  
      DataItem: input_text="list job use languageid0", output_text="job ( ANS ) ,
      language ( ANS , languageid0 )"
  
      Parameters
      ----------
      file_path: str
          The path of the input file.
  
      Returns
      -------
      list
          The indices of data items in the file w.r.t. the whole dataset.
      """
      data = []
      with open(file_path, "rb") as f:
          lines = pickle.load(f)
      for line in lines:
          input, output = line
          if input.strip() == "" or output.strip() == "":
              continue
          input_len = len(input.split())
          output_len = len(output.split())
          if input_len > 50 or output_len > 50:
              continue
          data_item = Text2TextDataItem(
              input_text=input,
              output_text=output,
              tokenizer=self.tokenizer,
              share_vocab=self.share_vocab,
          )
          data.append(data_item)
      return data
  
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 3 for calling the IWSLT14Dataset obj's underlying member method code with example usage: obj.parse_file(file_path) and returns: data