code: def check_input_data(self, args):
      input_data = []
      if args.input_file:
          if not os.path.exists(args.input_file):
              raise FileNotFoundError(
                  "File %s does not exist." % args.input_file
              )
          else:
              input_data = txt_parser.parse(
                  args.input_file, use_strip=True
              )
      elif args.input_text:
          input_data = [args.input_text]
  
      return input_data
  
imports: import argparse
  import ast
  import os
  import re
  from typing import Any
  from typing import List
  from typing import Text
  from typing import Tuple
  import numpy
  import paddle
  import six
  from paddle.framework import core
  from paddlehub.compat import paddle_utils
  from paddlehub.compat.task.config import RunConfig
  from paddlehub.compat.task.reader import ClassifyReader
  from paddlehub.compat.task.transformer_emb_task import TransformerEmbeddingTask
  from paddlehub.module.module import RunModule
  from paddlehub.module.module import runnable
  from paddlehub.utils.parser import txt_parser
  from paddlehub.utils.utils import sys_stdin_encoding
label_desc: Use image node_id 7 for calling the NLPPredictionModule obj's underlying member method code with example usage: obj.check_input_data(args) and returns: input_data