class_docstr: Abstract base class for population-based search methods.
  
  Examples include: genetic algorithm, particle swarm optimization
class_docstr_tok: ["Abstract","base","class","for","population-based","search","methods",".","Examples","include",":","genetic","algorithm",",","particle","swarm","optimization"]
docstr: Initialize a population of size `pop_size` with `initial_result`
  Args:
      initial_result (GoalFunctionResult): Original text
      pop_size (int): size of population
  Returns:
      population as `list[PopulationMember]`
docstr_tok: ["Initialize","a","population","of","size","`","pop_size","`","with","`","initial_result","`","Args",":","initial_result","(","GoalFunctionResult",")",":","Original","text","pop_size","(","int",")",":","size","of","population","Returns",":","population","as","`","list","[","PopulationMember","]","`"]
code: def _initialize_population(self, initial_result, pop_size):
      """
      Initialize a population of size `pop_size` with `initial_result`
      Args:
          initial_result (GoalFunctionResult): Original text
          pop_size (int): size of population
      Returns:
          population as `list[PopulationMember]`
      """
      raise NotImplementedError
  
file_path: TextAttack/textattack/search_methods/population_based_search.py
imports: from abc import ABC, abstractmethod
  from textattack.search_methods import SearchMethod
label_desc: Use image node_id 3 for calling the PopulationBasedSearch obj's underlying member method code with example usage: obj._initialize_population(initial_result, pop_size) without return types