This PR seeks to bring habitat-API inline with this. StaticPointGoalSensor is now just a PointGoalSensor and the old PointGoalSensor is now a PointGoalWithGPSCompassSensor. There are also now explicit GPS and Compass sensors, such that you can fairly easily compute PointGoalWithGPSCompassSensor given [PointGoalSensor, GPSSensor, CompassSensor].
The PointGoal* sensors now also include {2d, 3d} x {Cartesian, Polar} support.

* refactor and  add generic trainer class

* fix to pass tests

* change BaseModel to BaseTrainer

* fix tensorboard import causing CI failure

* modify circle-ci test script accordingly

* doc, typing and other changes

* rename BASELINE to TRAINER

* merge from upstream master

* Update Habitat-API to allow for no rendering sensors (#139)

Update Habitat-API to allow for no rendering sensors

* Added installation requirements step for sim installation in CI setup. (#159)

Added installation requirements step for sim installation in CI setup

* move RolloutStorage to utils

* add environments.py

* make ckpt dir if not exist

* small fixes according to comments

* changes according to comments

* update readme

* fix old config compatibility

* fix missed isort lint

Added description how to use config system, fixed missing copyright headers, improved example and isort CI (#125)

* Added description how to use config system related to #20.
* Added missing copyright headers
* Improve registry example to be cleaner
* Adde habitat_sim as first party lib to isort CI setup

* Generalize PPO with both PointNav goal sensors
* generalize simple agents and fix lint
* Removed dataset specific nodes

- add config option NUM_SAMPLE_EPISODE, with default value -1 that
indicates use all episodes. When set value to non-negative integer,
pointna_dataset will sample the specified number of episodes.
- fix the functionality of merging multiple config files. Now can specify
more than one config file like this
	--task-config "a.yaml" "b.yaml"

* ORBSLAM2 agent refactored for new api

* Added monodepth agent

Benchmark and challenge implementations; PPO agents, Random, ForwardOnly, GoalFollower agents; High resolution top down map and bird-eye visualizations; Collisions measure introduced; SPL success criteria fix; Added deleter that closes subprocesses