class_docstr: Warm starts current trial with loss weighted average of previous trials.
class_docstr_tok: ["Warm","starts","current","trial","with","loss","weighted","average","of","previous","trials","."]
code: def _sort_previous_trial_variables(self, trial_to_var):
      return sorted(
          trial_to_var,
          key=lambda x: x[0].final_measurement.objective_value,
      )
  
file_path: model_search/model_search/meta/transfer_learning.py
imports: import abc
  from absl import logging
  from model_search.architecture import architecture_utils
  import tensorflow.compat.v2
label_desc: Use image node_id 1 for calling the LossWeightedAverageTransferLearningHook obj's underlying member method code with example usage: obj._sort_previous_trial_variables(trial_to_var) and returns: sorted