You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: We tried several versions of the residual version of Inception. Only twoof them are detailed here. The first one “Inception-ResNet-v1”roughly the computational cost of Inception-v3, while “Inception-ResNet-v2”matches the raw cost of the newly introduced Inception-v4 network. SeeFigure 15 for the large scale structure of bothvarianets. (However, the step time of Inception-v4 proved to be significantlyslower in practice, probably due to the larger number of layers.) •Inception-ResNet-v1: a hybrid Inception version that has asimilar computational cost to Inception-v3from [15].•Inception-ResNet-v2: a costlier hybrid Inception version withsignificantly improved recognition performance.•Inception-v4: a pure Inception variant without residual connectionswith roughly the same recognition performance as Inception-ResNet-v2. The last experiment reported here is an evaluation of an ensemble ofall the best performing models presented here. As it wasapparent that both Inception-v4 and Inception-ResNet-v2 performedsimilarly well, exceeding state-of-the art single frame performanceon the ImageNet validation dataset, we wanted to see how a combinationof those pushes the state of the art on this well studied dataset.Surprisingly, we found that gains on the single-frame performance do nottranslate into similarly large gains on ensembled performance. Nonetheless,it still allows us to report 3.1% top-5 error on the validation set withfour models ensembled setting a new state of the art, to our bestknowledge.

Question: What are the metrics used for comparing Inception-v4, Inception- ResNet-v1/2 and their ensembles?
Metrics used for the comparison of ensembles are: a) Computational Cost b) Recognition Performance c) Step Time d) top-5 error.