A standard benchmark of assessing the robustness of vision models is to record their performance on corrupted datasets like ImageNet-C and CIFAR-10-C both of which were proposed in Benchmarking Neural Network Robustness to Common Corruptions and Perturbations. For this example, we will be using the CIFAR-10-C dataset which has 19 different corruptions on 5 different severity levels. To assess the robustness of the models on this dataset, we will do the following: