class_docstr: Abstract base class for transfer learning hooks.
  
  This hook initializes the model's variables with values from previously
  completed trials. Subclasses are responsible for determining how to combine
  matching variables from previous trials. If any variable of a particular
  previous trial does not match in name, shape, or dtype to corresponding
  variable of the current trial it will be ignored.
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docstr: Combines the variables from previous trials.
  
  Args:
    trial_to_var: A list of (Trial, tf.Variable) tuples corresponding to
      previous trial variables which match variables in the current trial.
  
  Returns:
    The tf.Variable with the combined value of all variables.
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code: def _combine_previous_trial_variables(self, trial_to_var):
      """Combines the variables from previous trials.
  
      Args:
        trial_to_var: A list of (Trial, tf.Variable) tuples corresponding to
          previous trial variables which match variables in the current trial.
  
      Returns:
        The tf.Variable with the combined value of all variables.
      """
  
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 3 for calling the BaseTransferLearningHook obj's underlying member method code with example usage: obj._combine_previous_trial_variables(trial_to_var) without return types