Debugging a Machine Learning model written in TensorFlow and Keras

In this article, you get to look over my shoulder as I go about debugging a TensorFlow model. I did a lot of dumb things, so please don't judge. You can see the final (working) model on GitHub. I'm building a model to predict lightning 30 minutes into the future and plan to present it at the American Meteorological Society. The basic idea is to create 64x64 image patches around each pixel of infrared and Global Lightning Mapper (GLM) GOES-16 data and label the pixel as "has_ltg 1" if the lighting image actually occurs 30 minutes later within a 16x16 image patch around the pixel. A model trained in this way can be used to predict lightning 30 minutes ahead in real-time given the current infrared and GLM data.