We propose a new building block, IdleBlock, which naturally prunes connections within the block. To fully utilize the IdleBlock we break the tradition of monotonic design in state-of-the-art networks, and introducing hybrid composition with IdleBlock. We study hybrid composition on MobileNet v3 and EfficientNet-B0, two of the most efficient networks. Without any neural architecture search, the deeper "MobileNet v3" with hybrid composition design surpasses possibly all state-of-the-art image recognition network designed by human experts or neural architecture search algorithms. Similarly, the hybridized EfficientNet-B0 networks are more efficient than previous state-of-the-art networks with similar computation budgets. These results suggest a new simpler and more efficient direction for network design and neural architecture search.

翻译：我们建议一个新的建筑块, 即IdleBlock, 它自然会在这个建筑块内连接。 为了充分利用IdleBlock, 我们打破了最先进的网络中的单声波设计传统, 并引入了与 IdleBlock 的混合构成。 我们在 MobilNet v3 和高效Net-B0 上研究混合构成, 两个效率最高的网络。 没有进行神经结构搜索, 更深层的“ MobileNet v3 ” 和混合构成设计可能超越了人类专家或神经结构搜索算法设计的所有最先进的图像识别网络。 同样, 混合式高效网络- B0 网络比以往具有类似计算预算的最新网络效率更高。 这些结果显示网络设计和神经结构搜索有更简单、更高效的新方向 。