Question about loss clipping on DeepMind's DQN • /r/MachineLearning

I am trying my own implementation of the DQN paper by Deepmind in tensor flow and am running into difficulty with clipping of the loss function. We also found it helpful to clip the error term from the update to be between 1 and 1. Because the absolute value loss function x has a derivative of 1 for all negative values of x and a derivative of 1 for all positive values of x, clipping the squared error to be between 1 and 1 corresponds to using an absolute value loss function for errors outside of the ( 1,1) interval. This form of error clipping further improved the stability of the algorithm. What I have tried so far is using tf.clip_by_value to clip the loss I calculate between -1 and 1.