docstr: SuccessiveHalving simply continues the best based on the current loss.
docstr_tok: ["SuccessiveHalving","simply","continues","the","best","based","on","the","current","loss","."]
code: def _advance_to_next_stage(self, config_ids, losses):
      """
      SuccessiveHalving simply continues the best based on the current loss.
      """
  
      ranks = np.argsort(np.argsort(losses))
      return ranks < max(
          self.min_samples_advance,
          self.num_configs[self.stage] * (1 - self.resampling_rate),
      )
  
imports: import sys
  from hpbandster.iterations.base import BaseIteration
  import numpy
label_desc: Use image node_id 2 for calling the SuccessiveResampling obj's underlying member method code with example usage: obj._advance_to_next_stage(config_ids, losses) and returns: unknown