How do I get the "sum-squared error" function for loss?

I just started learning Tensorflow/Keras and in this paper it says “We use SGD with momentum of 0.9 to optimize for sum-squared error in the output of our model and use a learning rate of 0.0001 and a weight decay of 0.0001 to train for 5 epochs.” I’m trying to implement that and I have this now

sgd = SGD(learning_rate=0.0001, decay=0.0001, momentum=0.9, nesterov=False) model.compile(optimizer=sgd, loss="mean_squared_error") 

I put “sum_squared_error” for loss but it doesn’t have have that function.