Stable-baselines

- Hotfix for ppo2, the wrong placeholder was used for the value function

Note: this bug was present since v1.0, so we recommend to update to the latest version of stable-baselines

- added `async_eigen_decomp` parameter for ACKTR and set it to `False` by default (remove deprecation warnings)
- added methods for calling env methods/setting attributes inside a VecEnv (thanks to bjmuld)
- updated gym minimum version

- fixed MpiAdam synchronization issue in PPO1 (thanks to brendenpetersen) issue 50
- fixed dependency issues (new mujoco-py requires a mujoco licence + gym broke MultiDiscrete space shape)

**WARNING: This version contains breaking changes, please read the full details**

- added patch fix for equal function using gym.spaces.MultiDiscrete and gym.spaces.MultiBinary
- fixes for DQN action_probability
- re-added double DQN + refactored DQN policies **breaking changes**
- replaced async with async_eigen_decomp in ACKTR/KFAC for python 3.7 compatibility
- removed action clipping for prediction of continuous actions (see issue 36)
- fixed NaN issue due to clipping the continuous action in the wrong place (issue 36)

**WARNING: This version contains breaking changes, please read the full details**

- Renamed DeepQ to DQN **breaking changes**
- Renamed DeepQPolicy to DQNPolicy **breaking changes**
- fixed DDPG behavior **breaking changes**
- changed default policies for DDPG, so that DDPG now works correctly **breaking changes**
- added more documentation (some modules from common).
- added doc about using custom env
- added Tensorboard support for A2C, ACER, ACKTR, DDPG, DeepQ, PPO1, PPO2 and TRPO
- added episode reward to Tensorboard
- added documentation for Tensorboard usage
- added Identity for Box action space
- fixed render function ignoring parameters when using wrapped environments
- fixed PPO1 and TRPO done values for recurrent policies
- fixed image normalization not occurring when using images
- updated VecEnv objects for the new Gym version
- added test for DDPG
- refactored DQN policies
- added registry for policies, can be passed as string to the agent
- added documentation for custom policies + policy registration
- fixed numpy warning when using DDPG Memory
- fixed DummyVecEnv not copying the observation array when stepping and resetting
- added pre-built docker images + installation instructions
- added ``deterministic`` argument in the predict function
- added assert in PPO2 for recurrent policies
- fixed predict function to handle both vectorized and unwrapped environment
- added input check to the predict function
- refactored ActorCritic models to reduce code duplication
- refactored Off Policy models (to begin HER and replay_buffer refactoring)
- added tests for auto vectorization detection
- fixed render function, to handle positional arguments

- added html documentation using sphinx + integration with read the docs
- cleaned up README + typos
- fixed normalization for DQN with images
- fixed DQN identity test