class_docstr: FORMAT: col: col1 | col2 | col 3 row 1 : val1 | val2 | val3 row 2 : ...
docstr: Given a row, TableLinearize aims at converting it into a flatten sequence with special symbols.
docstr_tok: ["Given","a","row",",","TableLinearize","aims","at","converting","it","into","a","flatten","sequence","with","special","symbols","."]
code: def process_row(self, row: List, row_index: int):
      """
      Given a row, TableLinearize aims at converting it into a flatten sequence with special symbols.
      """
      row_str = ""
      row_cell_values = []
      for cell_value in row:
          if isinstance(cell_value, int):
              row_cell_values.append(str(cell_value))
          else:
              row_cell_values.append(cell_value)
      row_str += " | ".join(row_cell_values)
      return "row " + str(row_index) + " : " + row_str
  
imports: import json
  import os
  import random
  from functools import lru_cache
  from typing import Dict, List, Optional, Tuple, Union
  import regex
  from ...file_utils import ExplicitEnum, PaddingStrategy, TensorType, add_end_docstrings, is_pandas_available
  from ...tokenization_utils import AddedToken, PreTrainedTokenizer
  from ...tokenization_utils_base import ENCODE_KWARGS_DOCSTRING, BatchEncoding, TextInput, TruncationStrategy
  from ...utils import logging
label_desc: Use image node_id 3 for calling the IndexedRowTableLinearize obj's underlying member method code with example usage: obj.process_row(row, row_index) and returns: unknown