class_docstr: Generates prior towers for Phoenix.
class_docstr_tok: ["Generates","prior","towers","for","Phoenix","."]
code: def build_priors_distillation(
      self, is_training, logits_dimension, trials, my_id, my_model_dir
  ):
      if not is_training:
          architecture_utils.set_number_of_towers(
              self.generator_name(), 0
          )
          return []
  
      # When distilling, we always want the best ensemble.
      num_trials_to_consider = 1
      best_trial = self._metadata.get_best_k(
          trials=trials, k=num_trials_to_consider
      )
  
      if not best_trial:
          architecture_utils.set_number_of_towers(
              self.generator_name(), 0
          )
          return []
  
      return trial_utils.import_towers_one_trial(
          phoenix_spec=self._phoenix_spec,
          is_training=is_training,
          logits_dimension=logits_dimension,
          prev_model_dir=architecture_utils.DirectoryHandler.trial_dir(
              best_trial
          ),
          force_freeze=self._force_freeze,
          allow_auxiliary_head=self._allow_auxiliary_head,
          caller_generator=self.generator_name(),
          my_model_dir=my_model_dir,
      )
  
file_path: model_search/model_search/generators/prior_generator.py
imports: import random
  from model_search.architecture import architecture_utils
  from model_search.generators import base_tower_generator
  from model_search.generators import trial_utils
  import tensorflow.compat.v2
label_desc: Use image node_id 8 for calling the PriorGenerator obj's underlying member method code with example usage: obj.build_priors_distillation(is_training, logits_dimension, trials, my_id, my_model_dir) and returns: trial_utils, list, list