Prediction: remove direct dependency of container manager from evaluators, pass obstacles_container from top-level in evaluator_manager

* * log module test

* * add build options for MACRO MUDULE_NAME

* * update hdmap BUILD

* * apply build MODULE_NAME copts,modules:map,planning,prediction,routing

* * revert test codes

* * update log

* * remove on cuda file

* * apply build copts update in module dreamview

Prediction: put some helper functions shared by various evaluators into the evaluator.h as protected functions.

 
Prediction: Include what you need. (#6292)

This reverts commit 4c3b1043.

Conflicts:
	modules/perception/onboard/component/BUILD
	modules/planning/lattice/trajectory_generation/BUILD

* prediction: add rnn network proto

* Prediction: added build support for rnn network proto (#902)

* Prediction: added build support for rnn network proto

* Prediction: fixed an assertion bug

* prediction: add rnn model

* Prediction: Lint fixes

* Prediction: added RNN evaluator framework

* prediction: add rnn model file

* Prediction: build up functional framework for RNN evaluator

* Prediction: implement RNN model extract obstacle features

* Prediction: fixed a few lint errors

* Prediction: implement set lane feature

* Prediction: fixed cut in trajectory when obstacle is close to ego vehicle

* Prediction: init rnn state

* Prediction: a little more

* Prediction: almost implement Evaluate in RNN

* Prediction: implement load model

* Prediction: add conf for RNN model

* prediction: refine rnn model

* prediction: fixbug of rnn state

* prediction: increase minimun prediction length

* Prediction: move a hard-coded parameter to gflags

* Prediction: restructured network and fixed unit test

* prediction: add unit test for rnn_model (#1132)

* prediction: add acceleration in rnn model

* Prediction: add cyclist model

* Prediction: updated predictor manager to read configuration for cyclists (#1197)

* drivers: using cvar to trigger publishment (#931) (#1200)

* Prediction: use kf gflag to trigger motion part in move sequence predictor (#1282)

* prediction: add documents for network

* Prediction: a light weights rnn model

* Prediction: add gflag to use lane sequence acc