class_docstr: The dataset class which is fit for all datatset of text classification.
class_docstr_tok: ["The","dataset","class","which","is","fit","for","all","datatset","of","text","classification","."]
docstr: Reads a tab separated value file.
  Args:
      input_file (:obj:str) : The file to be read.
      is_file_with_header(:obj:bool, `optional`, default to :obj: False) :
          Whether or not the file is with the header introduction.
  Returns:
      examples (:obj:`List[InputExample]`): All the input data.
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code: def _read_file(
      self, input_file, is_file_with_header: bool = False
  ) -> List[InputExample]:
      """
      Reads a tab separated value file.
      Args:
          input_file (:obj:str) : The file to be read.
          is_file_with_header(:obj:bool, `optional`, default to :obj: False) :
              Whether or not the file is with the header introduction.
      Returns:
          examples (:obj:`List[InputExample]`): All the input data.
      """
      if not os.path.exists(input_file):
          raise RuntimeError(
              "The file {} is not found.".format(input_file)
          )
      else:
          with io.open(input_file, "r", encoding="UTF-8") as f:
              reader = csv.reader(f, delimiter="\t", quotechar=None)
              examples = []
              seq_id = 0
              header = next(reader) if is_file_with_header else None
              for line in reader:
                  example = InputExample(
                      guid=seq_id, label=line[0], text_a=line[1]
                  )
                  seq_id += 1
                  examples.append(example)
              return examples
  
imports: import csv
  import io
  import os
  from typing import Dict, List, Optional, Union, Tuple
  import numpy
  import paddle
  import paddlenlp
  from packaging.version import Version
  from paddlehub.env import DATA_HOME
  from paddlenlp.transformers import PretrainedTokenizer
  from paddlenlp.data import JiebaTokenizer
  from paddlehub.utils.log import logger
  from paddlehub.utils.utils import download, reseg_token_label, pad_sequence, trunc_sequence
  from paddlehub.utils.xarfile import is_xarfile, unarchive
label_desc: Use image node_id 2 for calling the TextClassificationDataset obj's underlying member method code with example usage: obj._read_file(input_file, is_file_with_header) and returns: examples