code: def extract_fills(self, texts):
      # remove <pad> from beginning of each text
      texts = [
          x.replace("<pad>", "").replace("</s>", "").strip()
          for x in texts
      ]
  
      # return the text in between each matched mask token
      extracted_ids = [self.pattern.findall(x) for x in texts]
      extracted_fills = [self.pattern.split(x)[1:] for x in texts]
  
      # remove whitespace around each fill
      extracted_fills = [
          [y.strip() for y in x] for x in extracted_fills
      ]
      extracted_id_to_fill = [
          {
              idx: fill
              for idx, fill in zip(extracted_ids[i], extracted_fills[i])
          }
          for i, x in enumerate(texts)
      ]
      return extracted_id_to_fill
  
imports: import numpy
  from abc import ABC, abstractmethod
  from .text_utils import extract_non_overlapping_ngrams
label_desc: Use image node_id 6 for calling the PerturbationModel obj's underlying member method code with example usage: obj.extract_fills(texts) and returns: extracted_id_to_fill