docstr: Working with `numpy` arrays of strings requires setting the data type to avoid
  truncating examples. This function estimates the longest sentence expected
  during the sampling process, which is used to set the number of characters
  for the samples and examples arrays. This depends on the perturbation method
  used for sampling.
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code: def set_data_type(self) -> None:
      """
      Working with `numpy` arrays of strings requires setting the data type to avoid
      truncating examples. This function estimates the longest sentence expected
      during the sampling process, which is used to set the number of characters
      for the samples and examples arrays. This depends on the perturbation method
      used for sampling.
      """
      max_len = 0
      max_sent_len = 0
  
      for word in self.words:
          similar_words = self.synonyms[word]["words"]
          max_len = max(
              max_len,
              int(
                  similar_words.dtype.itemsize
                  / np.dtype(similar_words.dtype.char + "1").itemsize
              ),
          )
          max_sent_len += max_len
          self.dtype = "<U" + str(max_sent_len)
  
imports: import logging
  from abc import abstractmethod
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
  import numpy
  import spacy
label_desc: Use image node_id 6 for calling the SimilaritySampler obj's underlying member method code with example usage: obj.set_data_type() without return types