Previously in v0.8 we added parallel environments via the
SubprocessUnityEnvironment, which exposed the same abstraction as
UnityEnvironment while actually wrapping many parallel environments
via subprocesses.
Wrapping many environments with the same interface as a single
environment had some downsides, however:
* Ordering needed to be preserved for agents across different envs,
complicating the SubprocessEnvironment logic
* Asynchronous environments with steps taken out of sync with the
trainer aren't viable with the Environment abstraction
This PR introduces a new EnvManager abstraction which exposes a
reduced subset of the UnityEnvironment abstraction and a
SubprocessEnvManager implementation which replaces the
SubprocessUnityEnvironment.
SubprocessEnvManager takes steps synchronously to reproduce old
behavior, meaning all parallel environments will need to wait for
the slowest environment to take a step. If some steps take much
longer than others, this can lead to a substantial overall slowdown
in practice. We've seen extreme cases where we see almost a 2x
speedup from using asynchronous stepping, with no downside for our
faster environments. (Bouncer 16% improvement, Walker 14% improvement
in tests).
This PR changes the SubprocessEnvManager to use async stepping.
This means on the "step" call the environment manager will enqueue
step requests to workers, and then only wait until at least one
step has been completed before returning.
* Timer proof-of-concept
* micro optimizations
* add some timers
* cleanup, add asserts
* Cleanup (no start/end methods) and handle exceptions
* unit test and decorator
* move output code, add a decorator
* cleanup
* module docstring
* actually write the timings when done with training
* use __qualname__ instead
* add a few more timers
* fix mock import
* fix unit test
* get timers from worker process (WIP)
* clean up timer merging
* typo
* WIP
* cleanup merging code
* bad merge
* undo accidental change
* remove reset command
* fix style
* fix unit tests
* fix unit tests (they got overwrote in merge)
* get timer root though a function
* timer around communicate
* Initial Commit
* Remove the Academy Done flag from the protobuf definitions
* remove global_done in the environment
* Removed irrelevant unitTests
* Remove the max_step from the Academy inspector
* Removed global_done from the python scripts
* Modified and removed some tests
* This actually does not break either curriculum nor generalization training
* Replace global_done with reserved.
Addressing Chris Elion's comment regarding the deprecation of the global_done field. We will use a reserved field to make sure the global done does not get replaced in the future causing errors.
* Removed unused fake brain
* Tested that the first call to step was the same as a reset call
* black formating
* Added documentation changes
* Editing the migrating doc
* Addressing comments on the Migrating doc
* Addressing comments :
- Removing dead code
- Resolving forgotten merged conflicts
- Editing documentations...
We have been ignoring unused imports and star imports via flake8. These are
both bad practice and grow over time without automated checking. This
commit attempts to fix all existing import errors and add back the corresponding
flake8 checks.
* [WIP] Side Channel initial layout
* Working prototype for raw bytes
* fixing format mistake
* Added some errors and some unit tests in C#
* Added the side channel for the Engine Configuration. (#2958)
* Added the side channel for the Engine Configuration.
Note that this change does not require modifying a lot of files :
- Adding a sender in Python
- Adding a receiver in C#
- subscribe the receiver to the communicator (here is a one liner in the Academy)
- Add the side channel to the Python UnityEnvironment (not represented here)
Adding the side channel to the environment would look like such :
```python
from mlagents.envs.environment import UnityEnvironment
from mlagents.envs.side_channel.raw_bytes_channel import RawBytesChannel
from mlagents.envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
channel0 = RawBytesChannel()
channel1 = EngineConfigurationChanne...
* initial commit for LL-API
* fixing ml-agents-envs tests
* Implementing action masks
* training is fixed for 3DBall
* Tests all fixed, gym is broken and missing documentation changes
* adding case where no vector obs
* Fixed Gym
* fixing tests of float64
* fixing float64
* reverting some of brain.py
* removing old proto apis
* comment type fixes
* added properties to AgentGroupSpec and edited the notebooks.
* clearing the notebook outputs
* Update gym-unity/gym_unity/tests/test_gym.py
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Update gym-unity/gym_unity/tests/test_gym.py
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Update ml-agents-envs/mlagents/envs/base_env.py
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Update ml-agents-envs/mlagents/envs/base_env.py
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* addressing first comments
* NaN checks for r...
This PR makes it so that the env_manager only sends one current BrainInfo and the previous actions (if any) to the AgentManager. The list of agents was added to the ActionInfo and used appropriately.
This PR moves the AgentManagers from the TrainerController into the env_manager. This way, the TrainerController only needs to create the components (Trainers, AgentManagers) and call advance() on the EnvManager and the Trainers.
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.
* [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...
* Update Dockerfile
* Separate send environment data from reset (#4128)
* Fixed a typo on ML-Agents-Overview.md (#4130)
Fixed redundant "to" word from the sentence since it is probably a typo in document.
* Updated the badge’s link to point to the newest doc version
* Replaced all of the doc to release_3_doc
* Fix 3DBall and 3DBallHard SAC regressions (#4132)
* Move memory validation to settings
* Update docs
* Add settings test
* Update to release_3 in installation.md (#4144)
* rename to SideChannelManager +backcompat (#4137)
* Remove comment about logo with --help (#4148)
* [bugfix] Make FoodCollector heuristic playable (#4147)
* Make FoodCollector heuristic playable
* Update changelog
* script to check for old release links and references (#4153)
* Remove package validation suite from Project (#4146)
* RayPerceptionSensor: handle empty and invalid tags (#4155...
GitHub
Chris Elion
Ervin Teng
Andrew Cohen
brccabral
vincentpierre