code: def char_cut_tf(input_str):
      """Cut sentence char by char with tensoflow operations."""
      input_str = tf.convert_to_tensor(input_str)
      rank = len(input_str.get_shape())
      if rank == 1:
          output_str = tf.strings.unicode_split(
              input_str, "UTF-8"
          ).to_tensor(default_value="")
          output_str = tf.strings.reduce_join(
              output_str, axis=1, separator=" "
          )
      elif rank == 0:
          output_str = tf.strings.unicode_split(input_str, "UTF-8")
          output_str = tf.strings.reduce_join(
              output_str, axis=0, separator=" "
          )
      else:
          logging.error("Please check the shape of input_str!")
          raise Exception("Error input shape for input_str.")
      output_str = tf.strings.strip(output_str)
      return output_str
  
file_path: delta/delta/data/preprocess/text_ops.py
imports: import delta.compat
  from absl import logging
  from delta import utils
  from core.ops import py_x_ops
  from delta.data.utils import read_lines_from_text_file
label_desc: Use image node_id 5 for calling a global function with example usage: char_cut_tf(input_str) and returns: output_str