TorchCP is a Python toolbox for conformal prediction research on deep learning models. It contains various implementations for posthoc and training methods for classification and regression tasks (including multi-dimension output). TorchCP is built on PyTorch (Paszke et al., 2019) and leverages the advantages of matrix computation to provide concise and efficient inference implementations. The code is licensed under the LGPL license and is open-sourced at $\href{https://github.com/ml-stat-Sustech/TorchCP}{\text{this https URL}}$.

翻译：TorchCP是一个面向深度学习模型共形预测研究的Python工具箱。它包含分类与回归任务（包括多维度输出）的后验方法与训练方法的多种实现。TorchCP基于PyTorch（Paszke等人，2019）构建，利用矩阵运算的优势提供简洁高效的推理实现。该代码采用LGPL许可证，并在$\href{https://github.com/ml-stat-Sustech/TorchCP}{\text{此链接}}$开源发布。