Deep learning models have shown their strengths in various application domains, however, they often struggle to meet safety requirements for their outputs. In this paper, we introduce PiShield, the first package ever allowing for the integration of the requirements into the neural networks' topology. PiShield guarantees compliance with these requirements, regardless of input. Additionally, it allows for integrating requirements both at inference and/or training time, depending on the practitioners' needs. Given the widespread application of deep learning, there is a growing need for frameworks allowing for the integration of the requirements across various domains. Here, we explore three application scenarios: functional genomics, autonomous driving, and tabular data generation.

翻译：深度学习模型在各类应用领域中展现出了显著优势，但它们常常难以满足输出的安全性要求。本文介绍PiShield——首个允许将需求集成到神经网络拓扑结构中的软件包。PiShield能够确保无论输入如何变化，模型输出始终符合这些需求。此外，它允许根据实践者的需求，在推理阶段和/或训练阶段集成需求。鉴于深度学习的广泛应用，跨领域集成需求的框架需求日益增长。本文探讨了三个应用场景：功能基因组学、自动驾驶与表格数据生成。