          Parameters
          ----------
          loss: list
              The loss to update
          parans: list
              The variables
          """
          grads = self.get_gradients(loss, params)
          self.updates = [K.update_add(self.iterations, 1)]
  
 
</s> remove             List of tf variables to create slots for
 </s> add             List of tensorflow variables to create slots for </s> remove         the iterations count of the optimizer, followed by the optimizer's state variables in the
 </s> add         the iterations count of the optimizer, followed by the optimizers state variables in the </s> remove     Example of warmup:
 </s> add     Example of warm up: </s> remove         The weights of an optimizer are its state (ie, variables). This function takes the weight
 </s> add         The weights of an optimizer are its state (IE, variables). This function takes the weight
        params: list
          Parameters
          ----------
          loss: list
              The loss to update
        params: list
              The variables
          """
          grads = self.get_gradients(loss, params)
          self.updates = [K.update_add(self.iterations, 1)]
  
keep keep keep keep replace keep keep keep keep keep
 Update Travis Tests for optimizers 
lib/model/optimizers_plaid.py