  Parametric computer-aided design (CAD) is a standard paradigm used to design
manufactured objects, where a 3D shape is represented as a program supported by
the CAD software. Despite the pervasiveness of parametric CAD and a growing
interest from the research community, currently there does not exist a dataset
of realistic CAD models in a concise programmatic form. In this paper we
present the Fusion 360 Gallery, consisting of a simple language with just the
sketch and extrude modeling operations, and a dataset of 8,625 human design
sequences expressed in this language. We also present an interactive
environment called the Fusion 360 Gym, which exposes the sequential
construction of a CAD program as a Markov decision process, making it amendable
to machine learning approaches. As a use case for our dataset and environment,
we define the CAD reconstruction task of recovering a CAD program from a target
geometry. We report results of applying state-of-the-art methods of program
synthesis with neurally guided search on this task.
