  We present DeepAL, a Python library that implements several common strategies
for active learning, with a particular emphasis on deep active learning. DeepAL
provides a simple and unified framework based on PyTorch that allows users to
easily load custom datasets, build custom data handlers, and design custom
strategies without much modification of codes. DeepAL is open-source on Github
and welcome any contribution.
