class_docstr: Base task for NLP.
class_docstr_tok: ["Base","task","for","NLP","."]
docstr: Data pipeline function for common process.
  This function is used both by online training and offline inference.
docstr_tok: ["Data","pipeline","function","for","common","process",".","This","function","is","used","both","by","online","training","and","offline","inference","."]
code: def common_process_pipeline(self, batch):
      """
      Data pipeline function for common process.
      This function is used both by online training and offline inference.
      """
      text_vocab_file_path = self.task_config["text_vocab"]
      max_seq_len = self.task_config["max_seq_len"]
      vocab_path = os.path.abspath(text_vocab_file_path)
      token_ids = tokenize_sentence(batch, max_seq_len, vocab_path)
      return token_ids
  
file_path: delta/delta/data/task/base_text_task.py
imports: import os
  from absl import logging
  from delta.data.task.base_task import Task
  from delta import utils
  from delta.utils.register import registers
  from delta.data.preprocess.text_ops import clean_english_str_tf
  from delta.data.preprocess.text_ops import char_cut_tf
  from delta.data.preprocess.text_ops import tokenize_sentence
  from delta.data.preprocess.text_ops import chinese_word_cut_tf
label_desc: Use image node_id 5 for calling the TextTask obj's underlying member method code with example usage: obj.common_process_pipeline(batch) and returns: token_ids