Parameter server support.

[justheuristic]

Currently __train__er simply saves all params to the database assuming he is alone.
This makes running several parallel training processes useless [kind of bootstrap dqn for higher price].

There are, however, techniques that allow parallel updates with periodic synchronizations.
https://www.cs.cmu.edu/~muli/file/parameter_server_osdi14.pdf
May or may not be used here

The goal is to allow such parallelism with minimum lines of code.

• in this method handle the coefficient by which to change params on the server (default 1).
• in this method add flags:
  • whether to also LOAD params every save_period to synchronize with other trainers
  • a coefficient by which to change params on the server (default 1) - send it to save_all_params
• a flag here that allows to partially update params on server. Default 1. Warn if >1. If != 1, also make trainer load weights from server (prev point)

Also it may be wise to avoid locks in case someone wants this to work in 100500 processes. Or at least measure lock time loss and make sure it is small.

Would be super-nice if you first created implementation with max readability / min lines of code.