docstr: Deletes the subwords that follow a given token identified by the `(row, col)` pair in the `raw` matrix.
  A token is considered to be part of a word if is not a punctuation and if has the subword prefix
  specific to the used language model. The subwords are not actually deleted in, but they are replace
  by the empty string ``''``.
  
  Parameters
  ----------
  raw
      Array of tokens.
  row
      Row coordinate of the word to be removed.
  col
      Column coordinate of the word to be removed.
  punctuation
      String containing the punctuation to be considered.
  
  Returns
  -------
  raw
      Array of tokens where deleted subwords are replaced by the empty string.
docstr_tok: ["Deletes","the","subwords","that","follow","a","given","token","identified","by","the","`","(","row",",","col",")","`","pair","in","the","`","raw","`","matrix",".","A","token","is","considered","to","be","part","of","a","word","if","is","not","a","punctuation","and","if","has","the","subword","prefix","specific","to","the","used","language","model",".","The","subwords","are","not","actually","deleted","in",",","but","they","are","replace","by","the","empty","string","``","``","``",".","Parameters","--","--","--","--","--","raw","Array","of","tokens",".","row","Row","coordinate","of","the","word","to","be","removed",".","col","Column","coordinate","of","the","word","to","be","removed",".","punctuation","String","containing","the","punctuation","to","be","considered",".","Returns","--","--","--","-","raw","Array","of","tokens","where","deleted","subwords","are","replaced","by","the","empty","string","."]
code: def _remove_subwords(
      self,
      raw: np.ndarray,
      row: int,
      col: int,
      punctuation: str = "",
      **kwargs,
  ) -> np.ndarray:
      """
      Deletes the subwords that follow a given token identified by the `(row, col)` pair in the `raw` matrix.
      A token is considered to be part of a word if is not a punctuation and if has the subword prefix
      specific to the used language model. The subwords are not actually deleted in, but they are replace
      by the empty string ``''``.
  
      Parameters
      ----------
      raw
          Array of tokens.
      row
          Row coordinate of the word to be removed.
      col
          Column coordinate of the word to be removed.
      punctuation
          String containing the punctuation to be considered.
  
      Returns
      -------
      raw
          Array of tokens where deleted subwords are replaced by the empty string.
      """
      for next_col in range(col + 1, len(self.head_tokens)):
          # if encounter a punctuation, just stop
          if self.model.is_punctuation(raw[row, next_col], punctuation):
              break
  
          # if it is a subword prefix, then replace it by empty string
          if self.model.is_subword_prefix(raw[row, next_col]):
              raw[row, next_col] = ""
          else:
              break
  
      return raw
  
imports: import string
  from functools import partial
  from typing import Dict, List, Optional, Tuple
  import numpy
  import tensorflow
  from alibi.utils.lang_model import LanguageModel
  from alibi.explainers.anchors.text_samplers import AnchorTextSampler
label_desc: Use image node_id 10 for calling the LanguageModelSampler obj's underlying member method code with example usage: obj._remove_subwords(raw, row, col, punctuation) and returns: raw