code: def apply_gradients(self, grads_and_vars):
      grads, trainable_variables = zip(*grads_and_vars)
      self.apply(grads, trainable_variables)
      # Return iterations for compat with tf.keras.
      return self.iterations
  
imports: import re
  import warnings
  import numpy
  from keras import backend
  from keras import initializers
  from keras import ops
  from keras.optimizers.schedules import learning_rate_schedule
  from keras.saving import serialization_lib
  from keras.utils import tracking
  from keras.utils.naming import auto_name
label_desc: Use image node_id 14 for calling the BaseOptimizer obj's underlying member method code with example usage: obj.apply_gradients(grads_and_vars) and returns: self