* Initial commit, need more work on the test
* Fixing the tests
* [skip ci] Update com.unity.ml-agents/Runtime/Agent.cs
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Bug fixing : Do nothing if here are no VectorObs
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
* [skip ci] WIP : Modify the base_env.py file
* [skip ci] typo
* [skip ci] renamed some methods
* [skip ci] Incorporated changes from our meeting
* [skip ci] everything is broken
* [skip ci] everything is broken
* [skip ci] formatting
* Fixing the gym tests
* Fixing bug, C# has an error that needs fixing
* Fixing the test
* relaxing the threshold of 0.99 to 0.9
* fixing the C# side
* formating
* Fixed the llapi integratio test
* [Increasing steps for testing]
* Fixing the python tests
* Need __contains__ after all
* changing the max_steps in the tests
* addressing comments
* Making env_manager logic clearer as proposed in the comments
* Remove duplicated logic and added back in episode length (#3728)
* removing mentions of multi-agent in gym and changed the docstring in base_env.py
* Edited the Documentation for the changes to the LLAPI (#3733)
* Edite...
* Trying to build a specific environment
* forgot to replace one testPlayer
* reverting 3DBall to default
* removed the multi-agent test and replaced it with a single agent test
* forgot to add this file...
* Deprecating Academy.Instance.FloatProperties
* Made the registered side channels a static property and created the sideChannelUtils class to handle side channel stuff
* Clearing the sending message queue in the Academy when the communicaor is not on
* addressing comments
This commit surfaces exceptions from environment worker subprocesses,
and changes the SubprocessEnvManager to raise those exceptions when
caught. Additionally TrainerController was changed to treat environment
exceptions differently than KeyboardInterrupts. We now raise the
environment exceptions after exporting the model, so that ML-Agents will
correctly exit with a non-zero return code.
The "docker target" feature and associated command-line flag
--docker-target-name were created for use with the now-deprecated
Docker setup. This feature redirects the paths used by learn.py
for the environment and config files to be based from a directory
other than the current working directory. Additionally it wrapped
the environment execution with xvfb-run.
This commit removes the "docker target" feature because:
* Renaming the paths doesn't fix any problem. Absolute paths can
already be passed for configs and environment executables.
* Use of xserver, Xvfb, or xvfb-run are independent of mlagents-learn
and can be used outside of the mlagents-learn call. Further, xvfb-run
is not the only solution for software rendering.
The timeout duration for closing an environment was set to the
same duration as the timeout when waiting for a response from the
still-running environment. This led to long waits for the error
response when communication version wasn't matching.
This change forces a timeout duration of 0 when handling errors.
* Hotfix memory leak on Python
* Fixing
* Fixing a bug in the heuristic policy. A decision should not be requested when the agent is done
* [bug-fix] Make Python able to deal with 0-step episodes (#3671)
* adding some comments
Co-authored-by: Ervin T <ervin@unity3d.com>
GitHub
Andrew Cohen
Yuan Gao