Keras uses way too much GPU memory when calling train_on_batch, fit, etc

Question

I\'ve been messing with Keras, and like it so far. There\'s one big issue I have been having, when working with fairly deep networks: When calling model.train_on_batch, or model

Answer 1

200M params for 2 Gb GPU is toooo much. Also your architecture not efficient, using local bottlenecks will be more efficient. Also you should go from small model to big, and not backwards, right now you have input 16x16, with this architecture that means that at the end most of your network will be "zero padded" and not based on input features. Your model layers depends on your input, so you cant just set arbitrary number of layers and sizes, you need count how much data will be passed to each of them, with understanding why are doing so. I would recommend you to watch this free course http://cs231n.github.io