class_docstr: A class for Tensorflow specific optimizer logic.
  
  The major behavior change for this class is for tf.distribute.
  
  It will override methods from base Keras core Optimizer,
  which provide distribute specific functionality, e.g. variable
  creation, loss reduction, etc.
class_docstr_tok: ["A","class","for","Tensorflow","specific","optimizer","logic",".","The","major","behavior","change","for","this","class","is","for","tf.distribute",".","It","will","override","methods","from","base","Keras","core","Optimizer",",","which","provide","distribute","specific","functionality",",","e.g",".","variable","creation",",","loss","reduction",",","etc","."]
docstr: Overwrite model variables with their moving average values.
  
  This function overwrites variables on each device.
  Args:
    var_list: list of model variables.
docstr_tok: ["Overwrite","model","variables","with","their","moving","average","values",".","This","function","overwrites","variables","on","each","device",".","Args",":","var_list",":","list","of","model","variables","."]
code: def _overwrite_model_variables_with_average_value(
      self, trainable_variables
  ):
      """Overwrite model variables with their moving average values.
  
      This function overwrites variables on each device.
      Args:
        var_list: list of model variables.
      """
      trainable_variables = [
          v.value if isinstance(v, backend.Variable) else v
          for v in trainable_variables
      ]
      # Override model variable by the stored average value on all devices.
      for var, average_var in zip(
          trainable_variables, self._model_variables_moving_average
      ):
          self._distribution_strategy.extended.update(
              var, lambda a, b: a.assign(b), args=(average_var,)
          )
  
file_path: keras/keras/backend/tensorflow/optimizer.py
imports: import tensorflow
  from keras import backend
  from keras.backend.common import KerasVariable
  from keras.optimizers import base_optimizer
label_desc: Use image node_id 10 for calling the TFOptimizer obj's underlying member method code with example usage: obj._overwrite_model_variables_with_average_value(trainable_variables) without return types