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: When the basic unit is ResNeXt, the AttentionNeXt-56 network performance is the same as ResNeXt-101 while the parameters and FLOPs are significantly fewer than ResNeXt-101. For Inception, The AttentionIncepiton-56 outperforms Inception-ResNet-v1 [32] by a margin with a 0.94% reduction on top-1 error and a 0.21% reduction on top-5 error. The results show that our method can be applied on different network structures.

Question: Why did the authors chose to do experiments on different basic units to prove the generalization of the residual attention network?
Proving generalization shows that the proposed method can be applied to multiple structures without a significant loss in performance.