TorchCP: A Library for Conformal Prediction based on PyTorch
Hongxin Wei Jianguo Huang
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 $\href{https://github.com/ml-stat-Sustech/TorchCP}{\text{this
https URL}}$.