text: import copy
  import numpy as np
  
  
  default_cond_params = {'utilities_skew': 0, 'prosociality_level': 0.3, 'hidden_embedding_size': 30, 'fairness_coeff': 0}
  
  def cond_params_iter():
      yield default_cond_params  # default parameters
      
      for utilities_skew in [round(i, 1) for i in np.arange(-1, 1.1, 0.4)]:
          cur_params = copy.deepcopy(default_cond_params)
          cur_params['utilities_skew'] = utilities_skew
          yield cur_params
          
      for fairness_coeff in [round(i, 1) for i in np.arange(0.0, 0.7, 0.1)]:
          cur_params = copy.deepcopy(default_cond_params)
          cur_params['fairness_coeff'] = fairness_coeff
          yield cur_params
          
      for prosociality_level in [round(i, 1) for i in np.arange(0, 1.1, 0.2)]:
          cur_params = copy.deepcopy(default_cond_params)
          cur_params['prosociality_level'] = prosociality_level
          yield cur_params
          
      for hidden_embedding_size in [5, 10, 20, 40, 80, 160]:
          cur_params = copy.deepcopy(default_cond_params)
          cur_params['hidden_embedding_size'] = hidden_embedding_size
          yield cur_params
          
  def cond_params_iter_pop_training():
      yield default_cond_params  # default parameters
          
      for fairness_coeff in [round(i, 1) for i in np.arange(0.0, 0.6, 0.1)]:
          cur_params = copy.deepcopy(default_cond_params)
          cur_params['fairness_coeff'] = fairness_coeff
          yield cur_params
          
  def round_cond_params(cond_params):
      res = cond_params.copy()
      res['utilities_skew'] = round(res['utilities_skew'], 1)
      res['fairness_coeff'] = round(res['fairness_coeff'], 1)
      res['prosociality_level'] = round(res['prosociality_level'], 1)
      return res
          
  #     for fairness_coeff in np.arange(0.0, 0.6, 0.1):
  #         cur_params = copy.deepcopy(default_cond_params)
  #         cur_params['fairness_coeff'] = fairness_coeff
  #         cur_params['prosociality_level'] = 1.0
  #         yield cur_params