class_docstr: An abstract class for transforming a sequence of text to produce a
  potential adversarial example.
docstr: Returns a list of all possible transformations for ``current_text``,
  only modifying ``indices_to_modify``. Must be overridden by specific
  transformations.
  
  Args:
      current_text: The ``AttackedText`` to transform.
      indicies_to_modify: Which word indices can be modified.
docstr_tok: ["Returns","a","list","of","all","possible","transformations","for","``","current_text","``",",","only","modifying","``","indices_to_modify","``",".","Must","be","overridden","by","specific","transformations",".","Args",":","current_text",":","The","``","AttackedText","``","to","transform",".","indicies_to_modify",":","Which","word","indices","can","be","modified","."]
code: def _get_transformations(self, current_text, indices_to_modify):
      """Returns a list of all possible transformations for ``current_text``,
      only modifying ``indices_to_modify``. Must be overridden by specific
      transformations.
  
      Args:
          current_text: The ``AttackedText`` to transform.
          indicies_to_modify: Which word indices can be modified.
      """
      raise NotImplementedError()
  
file_path: TextAttack/textattack/transformations/transformation.py
imports: from abc import ABC, abstractmethod
  from textattack.shared.utils import ReprMixin
label_desc: Use image node_id 2 for calling the Transformation obj's underlying member method code with example usage: obj._get_transformations(current_text, indices_to_modify) without return types