* GraphManager.set_session also sets self.sess
* make sure that GraphManager.fetch_from_worker uses training phase
* remove unnecessary phase setting in training worker
* reorganize rollout worker
* provide default name to GlobalVariableSaver.__init__ since it isn't really used anyway
* allow dividing TrainingSteps and EnvironmentSteps
* add timestamps to the log
* added redis data store
* conflict merge fix
allowing for the last training batch drawn to be smaller than batch_size + adding support for more agents in BatchRL by adding softmax with temperature to the corresponding heads + adding a CartPole_QR_DQN preset with a golden test + cleanups
1. Having the standard checkpoint prefix in order for the data store to grab it, and sync it to S3.
2. Removing the reference to Redis so that it won't try to pickle that in.
3. Enable restoring a checkpoint into a single-worker run, which was saved by a single-node-multiple-worker run.
* Adding checkpointing framework as well as mxnet checkpointing implementation.
- MXNet checkpoint for each network is saved in a separate file.
* Adding checkpoint restore for mxnet to graph-manager
* Add unit-test for get_checkpoint_state()
* Added match.group() to fix unit-test failing on CI
* Added ONNX export support for MXNet
* Enable setting the data store factory in Graph manager
This change enables us to use custom data store for storing and retrieving models.
We currently need this to have use a data store that loads temporary AWS credentials
from disk before calling store or load operations.
* Removed data store factory and introduced data store as a attribute
* updating the documentation website
* adding the built docs
* update of api docstrings across coach and tutorials 0-2
* added some missing api documentation
* New Sphinx based documentation
Adding mxnet components to rl_coach architectures.
- Supports PPO and DQN
- Tested with CartPole_PPO and CarPole_DQN
- Normalizing filters don't work right now (see #49) and are disabled in CartPole_PPO preset
- Checkpointing is disabled for MXNet
* refactoring the merging of the task parameters and the command line parameters
* removing some unused command line arguments
* fix for saving checkpoints when not passing through coach.py
* Integrate coach.py params with distributed Coach.
* Minor improvements
- Use enums instead of constants.
- Reduce code duplication.
- Ask experiment name with timeout.
Zach Dwiel