DNNV is a framework for verifying deep neural networks (DNN). DNN verification takes in a neural network, and a property over that network, and checks whether the property is true, or false. One common DNN property is local robustness, which specifies that inputs near a given input, will be classified similarly to that given input.
DNNV standardizes the network and property input formats to enable multiple verification tools to run on a single network and property. This facilitates both verifier comparison, and artifact re-use.