While my transition from ArchLinux to Ubuntu went smoothly, I can’t say the same for the self-driving car model. I discovered that it was always predicting the same values no matter the inputs! In this video, I suspected that the problem was unscaled inputs, but fixing that didn’t resolve the problem.

Now I’m thinking that it may be the activations. I was using Rectified Linear for the convolutional layers. It could be that negative values are driving all my gradients to zero. In the DeepDrive model, Craig uses ReLU as well, but the CommaAI model uses “ELU” or exponential linear unit. Basically ELU is like ReLU but “leaks” a little when the input is below zero, and it does so in a nonlinear fashion. This might solve my gradient problem.