  We present RNNbow, an interactive tool for visualizing the gradient flow
during backpropagation training in recurrent neural networks. RNNbow is a web
application that displays the relative gradient contributions from Recurrent
Neural Network (RNN) cells in a neighborhood of an element of a sequence. We
describe the calculation of backpropagation through time (BPTT) that keeps
track of itemized gradients, or gradient contributions from one element of a
sequence to previous elements of a sequence. By visualizing the gradient, as
opposed to activations, RNNbow offers insight into how the network is learning.
We use it to explore the learning of an RNN that is trained to generate code in
the C programming language. We show how it uncovers insights into the vanishing
gradient as well as the evolution of training as the RNN works its way through
a corpus.
