In this presentation we will detail the evolution of the DeepJet python environment. Initially envisaged to support the development of the namesake jet flavour tagger in CMS, DeepJet has grown to encompass multiple purposes within the collaboration. The presentation will describe the major features the environment sports: simple out-of-memory training with a multi-treaded approach to maximally exploit the hardware acceleration, simple and streamlined I/O to help bookkeeping of the developments, and finally docker image distribution, to simplify the deployment of the whole ecosystem on multiple datacenters. The talk will also cover future development, mainly aimed at improving user experience.
|Intended contribution length||20 minutes|