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: Additionally, by simply varying the number of the convolutional cells and number of filters in the convolutional cells, we can create different versions of NASNets with different computational demands. Thanks to this property of the cells, we can generate a family of models that achieve accuracies superior to all human-invented models at equivalent or smaller computational budgets [60, 29]. Notably, the smallest version of NASNet achieves 74.0% top-1 accuracy on ImageNet, which is 3.1% better than previously engineered architectures targeted towards mobile and embedded vision tasks [24, 70].

Question: What metric is used for measuring Computational demand of a network?
To measure the computational demand of the network, top-1 accuracy metric was used.