symbol-lab is an environment for testing the models’ ability to encode input into a symbolic (discrete) compositional representation. With a structure that allows for fine-grained control over the difficulty of the task, and an arbitrary amount of training data, symbol-lab aids us in uncovering the strengths and weaknesses of existing methods and facilitates the development of new ones. - View it on GitHub