code: def apply_gradients(self, grads_and_vars, name=None, **kwargs):
      self._optimizer._iterations = self.iterations
      return super().apply_gradients(grads_and_vars, name, **kwargs)
  
imports: import abc
  import warnings
  import tensorflow
  from tensorflow_addons.optimizers import KerasLegacyOptimizer
  from tensorflow_addons.utils import types
  from typeguard import typechecked
label_desc: Use image node_id 5 for calling the AveragedOptimizerWrapper obj's underlying member method code with example usage: obj.apply_gradients(grads_and_vars, name) and returns: super