This commit adds support for running Unity environments in parallel.
An abstract base class was created for UnityEnvironment which a new
SubprocessUnityEnvironment inherits from.
SubprocessUnityEnvironment communicates through a pipe in order to
send commands which will be run in parallel to its workers.
A few significant changes needed to be made as a side-effect:
* UnityEnvironments are created via a factory method (a closure)
rather than being directly created by the main process.
* In mlagents-learn "worker-id" has been replaced by "base-port"
and "num-envs", and worker_ids are automatically assigned across runs.
* BrainInfo objects now convert all fields to numpy arrays or lists to
avoid serialization issues.
A change was made to the way the "train_mode" flag was used by
environments when SubprocessUnityEnvironment was added which was
intended to be part of a separate change set. This broke the CLI
'--slow' flag. This change undoes those changes, so that the slow
/ fast simulation option works correctly.
As a minor additional change, the remaining tests from top level
'tests' folders have been moved into the new test folders.
When using parallel SubprocessUnityEnvironment instances along
with Academy Done(), a new step might be taken when reset should
have been called because some environments may have been done while
others were not (making "global done" less useful).
This change manages the reset on `global_done` at the level of the
environment worker, and removes the global reset from
TrainerController.
* WIP precommit on top level
* update CI
* circleci fixes
* intentionally fail black
* use --show-diff-on-failure in CI
* fix command order
* rebreak a file
* apply black
* WIP enable mypy
* run mypy on each package
* fix trainer_metrics mypy errors
* more mypy errors
* more mypy
* Fix some partially typed functions
* types for take_action_outputs
* fix formatting
* cleanup
* generate stubs for proto objects
* fix ml-agents-env mypy errors
* disallow-incomplete-defs for gym-unity
* Add CI notes to CONTRIBUTING.md
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.
* 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
* don't need fwd reference
* cleanup root
* always write timers, add comments
* undo accidental change
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
* Add Sampler and SamplerManager
* Enable resampling of reset parameters during training
* Documentation for Sampler and example YAML configuration file
* 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.
* Feature Deprecation : Online Behavioral Cloning
In this PR :
- Delete the online_bc_trainer
- Delete the tests for online bc
- delete the configuration file for online bc training
* Deleting the BCTeacherHelper.cs Script
TODO :
- Remove usages in the scene
- Documentation Edits
*DO NOT MERGE*
* IMPORTANT : REMOVED ALL IL SCENES
- Removed all the IL scenes from the Examples folder
* Removed all mentions of online BC training in the Documentation
* Made a note in the Migrating.md doc about the removal of the Online BC feature.
* Modified the Academy UI to remove the control checkbox and replaced it with a train in the editor checkbox
* Removed the Broadcast functionality from the non-Learning brains
* Bug fix
* Note that the scenes are broken since the BroadcastHub has changed
* Modified the LL-API for Python to remove the broadcasting functiuonality.
* All unit tests are running
* Modifie...
* [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 = EngineConfigurationChannel()
env = UnityEnvironme...
* [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...
* pass shape to WriteAdapter
* handle floats on python side
* cleanup
* whitespace
* rename GetFloatObservationShape, support uncompressed in RenderTexture sensor
* numpy float32
* remove unused using
* Float sensor and unit test
* replace asserts with exceptions, docstrings
* Make ChannelId a property and renamed ReservedChannelId
* Changes on the Python side for consistency
* Modified the tutorial appropriately
* fixing bugs
* Update ml-agents-envs/mlagents_envs/environment.py
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Update com.unity.ml-agents/Runtime/Grpc/RpcCommunicator.cs
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Addressing comments
* Update docs/Python-API.md
Co-Authored-By: Chris Elion <chris.elion@unity3d.com>
* Added a Utils class on the side channel (#3447)
- No change in user facing API
- Simplifies the code in the side channel implementations as it makes it easier to check if a side channel id is within ranges
- No changes to tests
- No changes to Documentation
* Simplifying
* Fixing a bug
* Replace the int ChannelId with a GUID/UUID ChannelId (#3454)
* renaming channel_type to channel_id
* Making the constant GUID const...
* [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...
* [communication] Use semantic versioning to test communication compatibility between C# and Python.
- Add tests for the change.
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
* Fix typo
* Made a side channel utils to reduce the complexity of UnityEnvironment
* Added a get_side_channel_dict utils method
* Better executable launcher (unarguably)
* Fixing the broken test
* Addressing comments
* [skip ci] Update ml-agents-envs/mlagents_envs/side_channel/side_channel_manager.py
Co-authored-by: Jonathan Harper <jharper+moar@unity3d.com>
* No catch all
Co-authored-by: Jonathan Harper <jharper+moar@unity3d.com>
* Replaced get_behavior_names and get_behavior_spec with behavior_specs property
* Fixing the test
* [ci]
* addressing some comments
* use typing.Mapping (#3948)
* Update ml-agents-envs/mlagents_envs/base_env.py
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
* Adding the documentation
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
* Making some things private in UnityEnvironment
* Readding the default ports as public
* removing _SCALAR_ACTION_TYPES and _SINGLE_BRAIN_ACTION_TYPES
* Removing unused method
* [WIP] Unity Environment Registry
[JIRA ticket](https://jira.unity3d.com/browse/MLA-997)
[Design Document](https://docs.google.com/document/d/1bFQ3_oXsA80FMou8kwqYxC53kqG5L3i0mbTQUH4shY4/edit#)
In This PR : Prototype of the Unity Environment Registry
Uploaded the 3DBall and Basic Environments for mac only
How to use on Python :
```python
from mlagents_envs.registry import UnityEnvRegistry
registry = UnityEnvRegistry()
print(registry["3DBall"].description)
env = registry["3DBall"].make()
env.reset()
for i in range(10):
print(i)
env.step()
env.close()
```
* Other approach:
- UnityEnvRegistry is no longer static and needs to be instantiated
- Providing a default_registry that will contains our environments
- Added a functionality to register RemoteRegistryEntry with a yaml file
* Some extra verification of the url : The binary will have a hash of the url in its name to make sure the right environ...
* Added a random action creator on the BehaviorSpecs
* Bumping numpy version
* Bumping numpy version
* Not using np.random.Generator as it seems to still be under developement
* 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...
Added stacking to multi-dimensional and compressed observations and added compressed channel mapping in communicator to support decompression.
Co-authored-by: Vincent-Pierre BERGES <vincentpierre@unity3d.com>
Co-authored-by: Chris Elion <chris.elion@unity3d.com>
* Add hybrid action capability flag (#4576)
* Change BrainParametersProto to support ActionSpec (#4579)
* Assign new BrainParametersProto fields based on capabilities (#4581)
* ActionBuffer with hybrid actions for RemotePolicy (#4592)
* Barracuda inference for hybrid actions (#4611)
* Refactor BarracudaModel loader checks (#4629)
* Export separate nodes for continuous/discrete actions (#4655)
* Separate continuous/discrete actions in AgentActionProto (#4698)
* Force different nodes for new and deprecated action output (#4705)
* [Bug Fix] set_action_for_agent expects a ActionTuple with batch size 1.
* moving a line around
(cherry picked from commit aac2ee6cb650e6969a6d8b9f7c966f69b9e2df04)
Ervin T
GitHub
Jonathan Harper
eshvk
Chris Elion
Ervin Teng
Anupam Bhatnagar
Andrew Cohen
vincentpierre
Arthur Juliani
Christopher Goy
HH
Ruo-Ping Dong
brccabral