nuts-ml is a data pre-processing library for GPU based deep learning that provides common pre-processing functions as independent, reusable units. These so called 'nuts' can be freely arranged to build data flows that are efficient, easy to read and modify.
The following example gives a taste of a nuts-ml data-flow that trains a network on image data and prints training loss and accuracy
(train_samples >> Stratify(1) >> read_image >> transform >> augment >>
Shuffle(100) >> build_batch >> network.train() >>
Print('train loss:{} acc:{}') >> Consume())nuts-ml is based on nuts-flow, which is described here.
