Scaling TF Training to Large Amounts of Data Part 1: Dealing with Large Datasets
Introduction
At Reverie Labs, we focus on building state-of-the-art deep learning models to predict important molecular properties. One method we use in building such models is self-supervised pre-training, which we run over tens of millions of molecules.
This requires overcoming two major hurdles: Working around peculiarities in how Tensorflow handles
