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.
class_docstr_tok: ["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","."]
code: def after_create_session(self, session, coord):
      del coord  # Unused.
      if self._assign_ops:
          session.run(self._assign_ops)
          self._assign_ops = []
  
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 6 for calling the BaseTransferLearningHook obj's underlying member method code with example usage: obj.after_create_session(session, coord) without return types