Experiments with Tree-Diffusion: Testing a New Code Generation Method on Graphics Languages

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Background & Related Work Method 3.1 Sampling Small Mutations 3.2 Policy 3.3 Value Network & Search 3.4 Architecture Experiments 4.1 Environments 4.2 Baselines 4.3 Ablations Conclusion, Acknowledgments and Disclosure of Funding, and References Background & Related Work Background & Related Work Background & Related Work Method 3.1 Sampling Small Mutations 3.2 Policy 3.3 Value Network & Search 3.4 Architecture Method Method 3.1 Sampling Small Mutations 3.1 Sampling Small Mutations 3.2 Policy 3.2 Policy 3.3 Value Network & Search 3.3 Value Network & Search 3.4 Architecture 3.4 Architecture Experiments 4.1 Environments 4.2 Baselines 4.3 Ablations Experiments 4.1 Environments 4.1 Environments 4.2 Baselines 4.2 Baselines 4.3 Ablations 4.3 Ablations Conclusion, Acknowledgments and Disclosure of Funding, and References Conclusion, Acknowledgments and Disclosure of Funding, and References Conclusion, Acknowledgments and Disclosure of Funding, and References Appendix Appendix A. Mutation Algorithm A. Mutation Algorithm B. Context-Free Grammars B. Context-Free Grammars C. Sketch Simulation C. Sketch Simulation D. Complexity Filtering D. Complexity Filtering E. Tree Path Algorithm E. Tree Path Algorithm F. Implementation Details F. Implementation Details 4 Experiments 4.1 Environments We conduct experiments on four domain-specific graphics languages, with complete grammar specifications provided in Appendix B. CSG2D A 2D constructive solid geometry language where primitive shapes are added and subtracted to create more complex forms, as explored in our baseline methods [11, 28]. We also create CSG2D-Sketch, which has an added observation model that simulates hand-drawn sketches using the algorithm from Wood et al. [39]. TinySVG A language featuring primitive shapes with color, along with Arrange commands for horizontal and vertical alignment, and Move commands for shape offsetting. Figure 1 portrays an example program. Unlike the compositional nature of CSG2D, TinySVG is hierarchical: subexpressions can be combined into compound objects for high-level manipulation. We also create, Rainbow, a simplified version of TinySVG without Move commands for ablation studies due to its reduced computational demands. We implemented these languages using the Lark [19] and Iceberg [16] Python libraries, with our tree-diffusion implementation designed to be generic and adaptable to any context-free grammar and observation model. Authors: (1) Shreyas Kapur, University of California, Berkeley (srkp@cs.berkeley.edu); (2) Erik Jenner, University of California, Berkeley (jenner@cs.berkeley.edu); (3) Stuart Russell, University of California, Berkeley (russell@cs.berkeley.edu). Authors: Authors (1) Shreyas Kapur, University of California, Berkeley (srkp@cs.berkeley.edu); (2) Erik Jenner, University of California, Berkeley (jenner@cs.berkeley.edu); (3) Stuart Russell, University of California, Berkeley (russell@cs.berkeley.edu). This paper is available on arxiv under CC BY-SA 4.0 DEED license. This paper is available on arxiv under CC BY-SA 4.0 DEED license. available on arxiv available on arxiv