RNN track classification for HLT taus

Hello,

This MR implements the RNN track classification in the HLT tau reconstruction. For now, we use the json file of the offline RNN training. A quick rates estimate has been done (https://indico.cern.ch/event/862749/), and seems to give good performance. A new configuration called 'tracktwoRNN' schedules the RNN track classification, and also uses the BDT track classifier for FTF core tracks, recently added as 'tracktwoMVABDT'. A new Aux variable has been added in the tau EDM (new entry in an enum), because we need to store the number of charged tracks before RNN track classification, as explained in the talk linked above. In the hypo, we reject candidates that have tracks associated before RNN classification, and which end up as 0p after RNN classification. That way, we keep the possibility to use "real 0p" (candidates for which we loose the track) to recover some efficiency for true taus at low pt and high mu. Some tracktwoRNN chains have been added to the MC_pp_v8 menu for performance studies.

Cheers, Bertrand