In this Torch7 post, we outline how to train a recurrent attention model using a reinforcement learning method called REINFORCE. Reproducing the original paper in Torch7, we were able to obtain 0.85% error on the MNIST dataset. Compared to the paper's reported 1.07% that is a significant margin. The post includes some nice visualizations of the learned attention model and detailed explanation of how to use the training and evaluation scripts.