We will now subclass the RMSProp optimizer class modifying the tf.keras.optimizers.Optimizer.get_gradients() method where we now implement Gradient Centralization. On a high level the idea is that let us say we obtain our gradients through back propogation for a Dense or Convolution layer we then compute the mean of the column vectors of the weight matrix, and then remove the mean from each column vector.