GenCoG: A DSL-Based Approach to Generating Computation Graphs for TVM Testing

TVM is a popular deep learning (DL) compiler. It is designed for compiling DL models, which are naturally computation graphs, and as well promoting the efficiency of DL computation. State-of-the-art methods, such as Muffin and NNSmith, allow developers to generate computation graphs for testing DL compilers. However, these techniques are inefficient — their generated computation graphs are either type-invalid or inexpressive, and hence not able to test the core functionalities of a DL compiler.