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Changelog
All notable changes to this package will be documented in this file.
The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
[Unreleased]
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
Minor Changes
com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- The
encoding_size
setting for RewardSignals has been deprecated. Please usenetwork_settings
instead. (#4982)
Bug Fixes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- An issue that caused
GAIL
to fail for environments where agents can terminate episodes by self-sacrifice has been fixed. (#4971)
[1.8.0-preview] - 2021-02-17
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- TensorFlow trainers have been removed, please use the Torch trainers instead. (#4707)
- A plugin system for
mlagents-learn
has been added. You can now define customStatsWriter
implementations and register them to be called during training. More types of plugins will be added in the future. (#4788)
Minor Changes
com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
- The
ActionSpec
constructor is now public. Previously, it was not possible to create an ActionSpec with both continuous and discrete actions from code. (#4896) StatAggregationMethod.Sum
can now be passed toStatsRecorder.Add()
. This will result in the values being summed (instead of averaged) when written to TensorBoard. Thanks to @brccabral for the contribution! (#4816)- The upper limit for the time scale (by setting the
--time-scale
paramater in mlagents-learn) was removed when training with a player. The Editor still requires it to be clamped to 100. (#4867) - Added the IHeuristicProvider interface to allow IActuators as well as Agent implement the Heuristic function to generate actions. Updated the Basic example and the Match3 Example to use Actuators. Changed the namespace and file names of classes in com.unity.ml-agents.extensions. (#4849)
- Added
VectorSensor.AddObservation(IList<float>)
.VectorSensor.AddObservation(IEnumerable<float>)
is deprecated. TheIList
version is recommended, as it does not generate any additional memory allocations. (#4887) - Added
ObservationWriter.AddList()
and deprecatedObservationWriter.AddRange()
.AddList()
is recommended, as it does not generate any additional memory allocations. (#4887) - The Barracuda dependency was upgraded to 1.3.0. (#4898)
- Added
ActuatorComponent.CreateActuators
, and deprecateActuatorComponent.CreateActuator
. The default implementation will wrapActuatorComponent.CreateActuator
in an array and return that. (#4899) InferenceDevice.Burst
was added, indicating that Agent's model will be run using Barracuda's Burst backend. This is the default for new Agents, but existing ones that useInferenceDevice.CPU
should update toInferenceDevice.Burst
. (#4925)- Add an InputActuatorComponent to allow the generation of Agent action spaces from an InputActionAsset. Projects wanting to use this feature will need to add the Input System Package at version 1.1.0-preview.3 or later. (#4881)
ml-agents / ml-agents-envs / gym-unity (Python)
- Tensorboard now logs the Environment Reward as both a scalar and a histogram. (#4878)
- Added a
--torch-device
commandline option tomlagents-learn
, which sets the defaulttorch.device
used for training. (#4888) - The
--cpu
commandline option had no effect and was removed. Use--torch-device=cpu
to force CPU training. (#4888) - The
mlagents_env
API has changed,BehaviorSpec
now has aobservation_specs
property containing a list ofObservationSpec
. For more information onObservationSpec
see here. (#4763, #4825)
Bug Fixes
com.unity.ml-agents (C#)
- Fix a compile warning about using an obsolete enum in
GrpcExtensions.cs
. (#4812) - CameraSensor now logs an error if the GraphicsDevice is null. (#4880)
- Removed unnecessary memory allocations in
ActuatorManager.UpdateActionArray()
(#4877) - Removed unnecessary memory allocations in
SensorShapeValidator.ValidateSensors()
(#4879) - Removed unnecessary memory allocations in
SideChannelManager.GetSideChannelMessage()
(#4886) - Removed several memory allocations that happened during inference. On a test scene, this reduced the amount of memory allocated by approximately 25%. (#4887)
- Removed several memory allocations that happened during inference with discrete actions. (#4922)
- Properly catch permission errors when writing timer files. (#4921)
- Unexpected exceptions during training initialization and shutdown are now logged. If you see "noisy" logs, please let us know! (#4930, #4935)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed a bug that would cause an exception when
RunOptions
was deserialized viapickle
. (#4842) - Fixed a bug that can cause a crash if a behavior can appear during training in multi-environment training. (#4872)
- Fixed the computation of entropy for continuous actions. (#4869)
- Fixed a bug that would cause
UnityEnvironment
to wait the full timeout period and report a misleading error message if the executable crashed without closing the connection. It now periodically checks the process status while waiting for a connection, and raises a better error message if it crashes. (#4880) - Passing a
-logfile
option in the--env-args
option tomlagents-learn
is no longer overwritten. (#4880) - The
load_weights
function was being called unnecessarily often in the Ghost Trainer leading to training slowdowns. (#4934)
[1.7.2-preview] - 2020-12-22
Bug Fixes
com.unity.ml-agents (C#)
- Add analytics package dependency to the package manifest. (#4794)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed the docker build process. (#4791)
[1.7.0-preview] - 2020-12-21
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- PyTorch trainers now support training agents with both continuous and discrete action spaces. (#4702)
The
.onnx
models generated by the trainers of this release are incompatible with versions of Barracuda before1.2.1-preview
. If you upgrade the trainers, you must upgrade the version of the Barracuda package as well (which can be done by upgrading thecom.unity.ml-agents
package).
Minor Changes
com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
- Agents with both continuous and discrete actions are now supported. You can specify both continuous and discrete action sizes in Behavior Parameters. (#4702, #4718)
- In order to improve the developer experience for Unity ML-Agents Toolkit, we have added in-editor analytics. Please refer to "Information that is passively collected by Unity" in the Unity Privacy Policy. (#4677)
- The FoodCollector example environment now uses continuous actions for moving and discrete actions for shooting. (#4746)
ml-agents / ml-agents-envs / gym-unity (Python)
ActionSpec.validate_action()
now enforces thatUnityEnvironment.set_action_for_agent()
receives a 1Dnp.array
. (#4691)
Bug Fixes
com.unity.ml-agents (C#)
- Removed noisy warnings about API minor version mismatches in both the C# and python code. (#4688)
ml-agents / ml-agents-envs / gym-unity (Python)
[1.6.0-preview] - 2020-11-18
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- PyTorch trainers are now the default. See the
installation docs for
more information on installing PyTorch. For the time being, TensorFlow is still available;
you can use the TensorFlow backend by adding
--tensorflow
to the CLI, or addingframework: tensorflow
in the configuration YAML. (#4517)
Minor Changes
com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
- The Barracuda dependency was upgraded to 1.1.2 (#4571)
- Utilities were added to
com.unity.ml-agents.extensions
to make it easier to integrate with match-3 games. See the readme for more details. (#4515)
ml-agents / ml-agents-envs / gym-unity (Python)
- The
action_probs
node is no longer listed as an output in TensorFlow models (#4613).
Bug Fixes
com.unity.ml-agents (C#)
Agent.CollectObservations()
andAgent.EndEpisode()
will now throw an exception if they are called recursively (for example, if they callAgent.EndEpisode()
). Previously, this would result in an infinite loop and cause the editor to hang. (#4573)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed an issue where runs could not be resumed when using TensorFlow and Ghost Training. (#4593)
- Change the tensor type of step count from int32 to int64 to address the overflow issue when step goes larger than 2^31. Previous Tensorflow checkpoints will become incompatible and cannot be loaded. (#4607)
- Remove extra period after "Training" in console log. (#4674)
[1.5.0-preview] - 2020-10-14
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- Added the Random Network Distillation (RND) intrinsic reward signal to the Pytorch
trainers. To use RND, add a
rnd
section to thereward_signals
section of your yaml configuration file. More information here (#4473)
Minor Changes
com.unity.ml-agents (C#)
- Stacking for compressed observations is now supported. An additional setting
option
Observation Stacks
is added in editor to sensor components that support compressed observations. A new classISparseChannelSensor
with an additional methodGetCompressedChannelMapping()
is added to generate a mapping of the channels in compressed data to the actual channel after decompression, for the python side to decompress correctly. (#4476) - Added a new visual 3DBall environment. (#4513)
ml-agents / ml-agents-envs / gym-unity (Python)
- The Communication API was changed to 1.2.0 to indicate support for stacked
compressed observation. A new entry
compressed_channel_mapping
is added to the proto to handle decompression correctly. Newer versions of the package that wish to make use of this will also need a compatible version of the Python trainers. (#4476) - In the
VisualFoodCollector
scene, a vector flag representing the frozen state of the agent is added to the input observations in addition to the original first-person camera frame. The scene is able to train with the provided default config file. (#4511) - Added conversion to string for sampler classes to increase the verbosity of the curriculum lesson changes. The lesson updates would now output the sampler stats in addition to the lesson and parameter name to the console. (#4484)
- Localized documentation in Russian is added. Thanks to @SergeyMatrosov for the contribution. (#4529)
Bug Fixes
com.unity.ml-agents (C#)
- Fixed a bug where accessing the Academy outside of play mode would cause the Academy to get stepped multiple times when in play mode. (#4532)
ml-agents / ml-agents-envs / gym-unity (Python)
[1.4.0-preview] - 2020-09-16
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
Minor Changes
com.unity.ml-agents (C#)
- The
IActuator
interface andActuatorComponent
abstract class were added. These are analogous toISensor
andSensorComponent
, but for applying actions for an Agent. They allow you to control the action space more programmatically than defining the actions in the Agent's Behavior Parameters. See BasicActuatorComponent.cs for an example of how to use them. (#4297, #4315) - Update Barracuda to 1.1.1-preview (#4482)
- Enabled C# formatting using
dotnet-format
. (#4362) - GridSensor was added to the
com.unity.ml-agents.extensions
package. Thank you to Jaden Travnik from Eidos Montreal for the contribution! (#4399) - Added
Agent.EpisodeInterrupted()
, which can be used to reset the agent when it has reached a user-determined maximum number of steps. This behaves similarly toAgent.EndEpsiode()
but has a slightly different effect on training (#4453).
ml-agents / ml-agents-envs / gym-unity (Python)
- Experimental PyTorch support has been added. Use
--torch
when runningmlagents-learn
, or addframework: pytorch
to your trainer configuration (under the behavior name) to enable it. Note that PyTorch 1.6.0 or greater should be installed to use this feature; see the PyTorch website for installation instructions and the relevant ML-Agents docs for usage. (#4335) - The minimum supported version of TensorFlow was increased to 1.14.0. (#4411)
- Compressed visual observations with >3 channels are now supported. In
ISensor.GetCompressedObservation()
, this can be done by writing 3 channels at a time to a PNG and concatenating the resulting bytes. (#4399) - The Communication API was changed to 1.1.0 to indicate support for concatenated PNGs (see above). Newer versions of the package that wish to make use of this will also need a compatible version of the trainer. (#4462)
- A CNN (
vis_encode_type: match3
) for smaller grids, e.g. board games, has been added. (#4434) - You can now again specify a default configuration for your behaviors. Specify
default_settings
in your trainer configuration to do so. (#4448) - Improved the executable detection logic for environments on Windows. (#4485)
Bug Fixes
com.unity.ml-agents (C#)
- Previously,
com.unity.ml-agents
was not declaring built-in packages as dependencies in its package.json. The relevant dependencies are now listed. (#4384) - Agents no longer try to send observations when they become disabled if the Academy has been shut down. (#4489)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed the sample code in the custom SideChannel example. (#4466)
- A bug in the observation normalizer that would cause rewards to decrease
when using
--resume
was fixed. (#4463) - Fixed a bug in exporting Pytorch models when using multiple discrete actions. (#4491)
[1.3.0-preview] - 2020-08-12
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- The minimum supported Python version for ml-agents-envs was changed to 3.6.1. (#4244)
- The interaction between EnvManager and TrainerController was changed; EnvManager.advance() was split into to stages, and TrainerController now uses the results from the first stage to handle new behavior names. This change speeds up Python training by approximately 5-10%. (#4259)
Minor Changes
com.unity.ml-agents (C#)
- StatsSideChannel now stores multiple values per key. This means that multiple
calls to
StatsRecorder.Add()
with the same key in the same step will no longer overwrite each other. (#4236)
ml-agents / ml-agents-envs / gym-unity (Python)
- The versions of
numpy
supported by ml-agents-envs were changed to disallow 1.19.0 or later. This was done to reflect a similar change in TensorFlow's requirements. (#4274) - Model checkpoints are now also saved as .nn files during training. (#4127)
- Model checkpoint info is saved in TrainingStatus.json after training is concluded (#4127)
- CSV statistics writer was removed (#4300).
Bug Fixes
com.unity.ml-agents (C#)
- Academy.EnvironmentStep() will now throw an exception if it is called recursively (for example, by an Agent's CollectObservations method). Previously, this would result in an infinite loop and cause the editor to hang. (#4226)
ml-agents / ml-agents-envs / gym-unity (Python)
- The algorithm used to normalize observations was introducing NaNs if the initial observations were too large due to incorrect initialization. The initialization was fixed and is now the observation means from the first trajectory processed. (#4299)
[1.2.0-preview] - 2020-07-15
Major Changes
ml-agents / ml-agents-envs / gym-unity (Python)
- The Parameter Randomization feature has been refactored to enable sampling of new parameters per episode to improve robustness. The
resampling-interval
parameter has been removed and the config structure updated. More information here. (#4065) - The Parameter Randomization feature has been merged with the Curriculum feature. It is now possible to specify a sampler in the lesson of a Curriculum. Curriculum has been refactored and is now specified at the level of the parameter, not the behavior. More information here.(#4160)
Minor Changes
com.unity.ml-agents (C#)
SideChannelsManager
was renamed toSideChannelManager
. The old name is still supported, but deprecated. (#4137)RayPerceptionSensor.Perceive()
now additionally store the GameObject that was hit by the ray. (#4111)- The Barracuda dependency was upgraded to 1.0.1 (#4188)
ml-agents / ml-agents-envs / gym-unity (Python)
- Added new Google Colab notebooks to show how to use `UnityEnvironment'. (#4117)
Bug Fixes
com.unity.ml-agents (C#)
- Fixed an issue where RayPerceptionSensor would raise an exception when the list of tags was empty, or a tag in the list was invalid (unknown, null, or empty string). (#4155)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed an error when setting
initialize_from
in the trainer confiiguration YAML tonull
. (#4175) - Fixed issue with FoodCollector, Soccer, and WallJump when playing with keyboard. (#4147, #4174)
- Fixed a crash in StatsReporter when using threaded trainers with very frequent summary writes (#4201)
mlagents-learn
will now raise an error immediately if--num-envs
is greater than 1 without setting the--env
argument. (#4203)
[1.1.0-preview] - 2020-06-10
Major Changes
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
- Added new Walker environments. Improved ragdoll stability/performance. (#4037)
max_step
in theTerminalStep
andTerminalSteps
objects was renamedinterrupted
.beta
andepsilon
inPPO
are no longer decayed by default but follow the same schedule as learning rate. (#3940)get_behavior_names()
andget_behavior_spec()
on UnityEnvironment were replaced by thebehavior_specs
property. (#3946)- The first version of the Unity Environment Registry (Experimental) has been released. More information here(#3967)
use_visual
andallow_multiple_visual_obs
in theUnityToGymWrapper
constructor were replaced byallow_multiple_obs
which allows one or more visual observations and vector observations to be used simultaneously. (#3981) Thank you @shakenes !- Curriculum and Parameter Randomization configurations have been merged into the main training configuration file. Note that this means training configuration files are now environment-specific. (#3791)
- The format for trainer configuration has changed, and the "default" behavior has been deprecated. See the Migration Guide for more details. (#3936)
- Training artifacts (trained models, summaries) are now found in the
results/
directory. (#3829) - When using Curriculum, the current lesson will resume if training is quit and resumed. As such,
the
--lesson
CLI option has been removed. (#4025)
Minor Changes
com.unity.ml-agents (C#)
ObservableAttribute
was added. Adding the attribute to fields or properties on an Agent will allow it to generate observations via reflection. (#3925, #4006)
ml-agents / ml-agents-envs / gym-unity (Python)
- Unity Player logs are now written out to the results directory. (#3877)
- Run configuration YAML files are written out to the results directory at the end of the run. (#3815)
- The
--save-freq
CLI option has been removed, and replaced by acheckpoint_interval
option in the trainer configuration YAML. (#4034) - When trying to load/resume from a checkpoint created with an earlier verison of ML-Agents, a warning will be thrown. (#4035)
Bug Fixes
- Fixed an issue where SAC would perform too many model updates when resuming from a
checkpoint, and too few when using
buffer_init_steps
. (#4038) - Fixed a bug in the onnx export that would cause constants needed for inference to not be visible to some versions of the Barracuda importer. (#4073)
com.unity.ml-agents (C#)
ml-agents / ml-agents-envs / gym-unity (Python)
[1.0.2-preview] - 2020-05-20
Bug Fixes
com.unity.ml-agents (C#)
- Fix missing .meta file
[1.0.1-preview] - 2020-05-19
Bug Fixes
com.unity.ml-agents (C#)
- A bug that would cause the editor to go into a loop when a prefab was selected was fixed. (#3949)
- BrainParameters.ToProto() no longer throws an exception if none of the fields have been set. (#3930)
- The Barracuda dependency was upgraded to 0.7.1-preview. (#3977)
ml-agents / ml-agents-envs / gym-unity (Python)
- An issue was fixed where using
--initialize-from
would resume from the past step count. (#3962) - The gym wrapper error for the wrong number of agents now fires more consistently, and more details were added to the error message when the input dimension is wrong. (#3963)
[1.0.0-preview] - 2020-04-30
Major Changes
com.unity.ml-agents (C#)
- The
MLAgents
C# namespace was renamed toUnity.MLAgents
, and other nested namespaces were similarly renamed. (#3843) - The offset logic was removed from DecisionRequester. (#3716)
- The signature of
Agent.Heuristic()
was changed to take a float array as a parameter, instead of returning the array. This was done to prevent a common source of error where users would return arrays of the wrong size. (#3765) - The communication API version has been bumped up to 1.0.0 and will use Semantic Versioning to do compatibility checks for communication between Unity and the Python process. (#3760)
- The obsolete
Agent
methodsGiveModel
,Done
,InitializeAgent
,AgentAction
andAgentReset
have been removed. (#3770) - The SideChannel API has changed:
- Introduced the
SideChannelManager
to register, unregister and access side channels. (#3807) Academy.FloatProperties
was replaced byAcademy.EnvironmentParameters
. See the Migration Guide for more details on upgrading. (#3807)SideChannel.OnMessageReceived
is now a protected method (was public)- SideChannel IncomingMessages methods now take an optional default argument, which is used when trying to read more data than the message contains. (#3751)
- Added a feature to allow sending stats from C# environments to TensorBoard
(and other python StatsWriters). To do this from your code, use
Academy.Instance.StatsRecorder.Add(key, value)
. (#3660)
- Introduced the
CameraSensorComponent.m_Grayscale
andRenderTextureSensorComponent.m_Grayscale
were changed frompublic
toprivate
. These can still be accessed via their corresponding properties. (#3808)- Public fields and properties on several classes were renamed to follow Unity's
C# style conventions. All public fields and properties now use "PascalCase"
instead of "camelCase"; for example,
Agent.maxStep
was renamed toAgent.MaxStep
. For a full list of changes, see the pull request. (#3828) WriteAdapter
was renamed toObservationWriter
. If you have a customISensor
implementation, you will need to change the signature of itsWrite()
method. (#3834)- The Barracuda dependency was upgraded to 0.7.0-preview (which has breaking namespace and assembly name changes). (#3875)
ml-agents / ml-agents-envs / gym-unity (Python)
- The
--load
and--train
command-line flags have been deprecated. Training now happens by default, and use--resume
to resume training instead of--load
. (#3705) - The Jupyter notebooks have been removed from the repository. (#3704)
- The multi-agent gym option was removed from the gym wrapper. For multi-agent scenarios, use the Low Level Python API. (#3681)
- The low level Python API has changed. You can look at the document
Low Level Python API
documentation for more information. If you use
mlagents-learn
for training, this should be a transparent change. (#3681) - Added ability to start training (initialize model weights) from a previous run ID. (#3710)
- The GhostTrainer has been extended to support asymmetric games and the asymmetric example environment Strikers Vs. Goalie has been added. (#3653)
- The
UnityEnv
class from thegym-unity
package was renamedUnityToGymWrapper
and no longer creates theUnityEnvironment
. Instead, theUnityEnvironment
must be passed as input to the constructor ofUnityToGymWrapper
(#3812)
Minor Changes
com.unity.ml-agents (C#)
- Added new 3-joint Worm ragdoll environment. (#3798)
StackingSensor
was changed frominternal
visibility topublic
. (#3701)- The internal event
Academy.AgentSetStatus
was renamed toAcademy.AgentPreStep
and made public. (#3716) - Academy.InferenceSeed property was added. This is used to initialize the random number generator in ModelRunner, and is incremented for each ModelRunner. (#3823)
Agent.GetObservations()
was added, which returns a read-only view of the observations added inCollectObservations()
. (#3825)UnityRLCapabilities
was added to help inform users when RL features are mismatched between C# and Python packages. (#3831)
ml-agents / ml-agents-envs / gym-unity (Python)
- Format of console output has changed slightly and now matches the name of the model/summary directory. (#3630, #3616)
- Renamed 'Generalization' feature to 'Environment Parameter Randomization'. (#3646)
- Timer files now contain a dictionary of metadata, including things like the package version numbers. (#3758)
- The way that UnityEnvironment decides the port was changed. If no port is
specified, the behavior will depend on the
file_name
parameter. If it isNone
, 5004 (the editor port) will be used; otherwise 5005 (the base environment port) will be used. (#3673) - Running
mlagents-learn
with the same--run-id
twice will no longer overwrite the existing files. (#3705) - Model updates can now happen asynchronously with environment steps for better performance. (#3690)
num_updates
andtrain_interval
for SAC were replaced withsteps_per_update
. (#3690)- The maximum compatible version of tensorflow was changed to allow tensorflow 2.1 and 2.2. This will allow use with python 3.8 using tensorflow 2.2.0rc3. (#3830)
mlagents-learn
will no longer set the width and height of the executable window to 84x84 when no width nor height arguments are given. (#3867)
Bug Fixes
com.unity.ml-agents (C#)
- Fixed a display bug when viewing Demonstration files in the inspector. The shapes of the observations in the file now display correctly. (#3771)
ml-agents / ml-agents-envs / gym-unity (Python)
- Fixed an issue where exceptions from environments provided a return code of 0. (#3680)
- Self-Play team changes will now trigger a full environment reset. This prevents trajectories in progress during a team change from getting into the buffer. (#3870)
[0.15.1-preview] - 2020-03-30
Bug Fixes
- Raise the wall in CrawlerStatic scene to prevent Agent from falling off. (#3650)
- Fixed an issue where specifying
vis_encode_type
was required only for SAC. (#3677) - Fixed the reported entropy values for continuous actions (#3684)
- Fixed an issue where switching models using
SetModel()
during training would use an excessive amount of memory. (#3664) - Environment subprocesses now close immediately on timeout or wrong API version. (#3679)
- Fixed an issue in the gym wrapper that would raise an exception if an Agent called EndEpisode multiple times in the same step. (#3700)
- Fixed an issue where logging output was not visible; logging levels are now set consistently. (#3703)
[0.15.0-preview] - 2020-03-18
Major Changes
Agent.CollectObservations
now takes a VectorSensor argument. (#3352, #3389)- Added
Agent.CollectDiscreteActionMasks
virtual method with aDiscreteActionMasker
argument to specify which discrete actions are unavailable to the Agent. (#3525) - Beta support for ONNX export was added. If the
tf2onnx
python package is installed, models will be saved to.onnx
as well as.nn
format. Note that Barracuda 0.6.0 or later is required to import the.onnx
files properly - Multi-GPU training and the
--multi-gpu
option has been removed temporarily. (#3345) - All Sensor related code has been moved to the namespace
MLAgents.Sensors
. - All SideChannel related code has been moved to the namespace
MLAgents.SideChannels
. BrainParameters
andSpaceType
have been removed from the public APIBehaviorParameters
have been removed from the public API.- The following methods in the
Agent
class have been deprecated and will be removed in a later release:InitializeAgent()
was renamed toInitialize()
AgentAction()
was renamed toOnActionReceived()
AgentReset()
was renamed toOnEpisodeBegin()
Done()
was renamed toEndEpisode()
GiveModel()
was renamed toSetModel()
Minor Changes
- Monitor.cs was moved to Examples. (#3372)
- Automatic stepping for Academy is now controlled from the AutomaticSteppingEnabled property. (#3376)
- The GetEpisodeCount, GetStepCount, GetTotalStepCount and methods of Academy were changed to EpisodeCount, StepCount, TotalStepCount properties respectively. (#3376)
- Several classes were changed from public to internal visibility. (#3390)
- Academy.RegisterSideChannel and UnregisterSideChannel methods were added. (#3391)
- A tutorial on adding custom SideChannels was added (#3391)
- The stepping logic for the Agent and the Academy has been simplified (#3448)
- Update Barracuda to 0.6.1-preview
- The interface for
RayPerceptionSensor.PerceiveStatic()
was changed to take an input class and write to an output class, and the method was renamed toPerceive()
.
- The checkpoint file suffix was changed from
.cptk
to.ckpt
(#3470) - The command-line argument used to determine the port that an environment will
listen on was changed from
--port
to--mlagents-port
. DemonstrationRecorder
can now record observations outside of the editor.DemonstrationRecorder
now has an optional path for the demonstrations. This will default toApplication.dataPath
if not set.DemonstrationStore
was changed to accept aStream
for its constructor, and was renamed toDemonstrationWriter
- The method
GetStepCount()
on the Agent class has been replaced with the property getterStepCount
RayPerceptionSensorComponent
and related classes now display the debug gizmos whenever the Agent is selected (not just Play mode).- Most fields on
RayPerceptionSensorComponent
can now be changed while the editor is in Play mode. The exceptions to this are fields that affect the number of observations. - Most fields on
CameraSensorComponent
andRenderTextureSensorComponent
were changed to private and replaced by properties with the same name. - Unused static methods from the
Utilities
class (ShiftLeft, ReplaceRange, AddRangeNoAlloc, and GetSensorFloatObservationSize) were removed. - The
Agent
class is no longer abstract. - SensorBase was moved out of the package and into the Examples directory.
AgentInfo.actionMasks
has been renamed toAgentInfo.discreteActionMasks
.DecisionRequester
has been made internal (you can still use the DecisionRequesterComponent from the inspector).RepeatAction
was renamedTakeActionsBetweenDecisions
for clarity. (#3555)- The
IFloatProperties
interface has been removed. - Fix #3579.
- Improved inference performance for models with multiple action branches. (#3598)
- Fixed an issue when using GAIL with less than
batch_size
number of demonstrations. (#3591) - The interfaces to the
SideChannel
classes (on C# and python) have changed to use newIncomingMessage
andOutgoingMessage
classes. These should make reading and writing data to the channel easier. (#3596) - Updated the ExpertPyramid.demo example demonstration file (#3613)
- Updated project version for example environments to 2018.4.18f1. (#3618)
- Changed the Product Name in the example environments to remove spaces, so that the default build executable file doesn't contain spaces. (#3612)
[0.14.1-preview] - 2020-02-25
Bug Fixes
- Fixed an issue which caused self-play training sessions to consume a lot of memory. (#3451)
- Fixed an IndexError when using GAIL or behavioral cloning with demonstrations recorded with 0.14.0 or later (#3464)
- Updated the
gail_config.yaml
to work with per-Agent steps (#3475) - Fixed demonstration recording of experiences when the Agent is done. (#3463)
- Fixed a bug with the rewards of multiple Agents in the gym interface (#3471, #3496)
[0.14.0-preview] - 2020-02-13
Major Changes
- A new self-play mechanism for training agents in adversarial scenarios was added (#3194)
- Tennis and Soccer environments were refactored to enable training with self-play (#3194, #3331)
- UnitySDK folder was split into a Unity Package (com.unity.ml-agents) and our examples were moved to the Project folder (#3267)
- Academy is now a singleton and is no longer abstract (#3210, #3184)
- In order to reduce the size of the API, several classes and methods were marked as internal or private. Some public fields on the Agent were trimmed (#3342, #3353, #3269)
- Decision Period and on-demand decision checkboxes were removed from the Agent. on-demand decision is now the default (#3243)
- Calling Done() on the Agent will reset it immediately and call the AgentReset virtual method (#3291, #3242)
- The "Reset on Done" setting in AgentParameters was removed; this is now always true. AgentOnDone virtual method on the Agent was removed (#3311, #3222)
- Trainer steps are now counted per-Agent, not per-environment as in previous versions. For instance, if you have 10 Agents in the scene, 20 environment steps now correspond to 200 steps as printed in the terminal and in Tensorboard (#3113)
Minor Changes
- Barracuda was updated to 0.5.0-preview (#3329)
- --num-runs option was removed from mlagents-learn (#3155)
- Curriculum config files are now YAML formatted and all curricula for a training run are combined into a single file (#3186)
- ML-Agents components, such as BehaviorParameters and various Sensor implementations, now appear in the Components menu (#3231)
- Exceptions are now raised in Unity (in debug mode only) if NaN observations or rewards are passed (#3221)
- RayPerception MonoBehavior, which was previously deprecated, was removed (#3304)
- Uncompressed visual (i.e. 3d float arrays) observations are now supported. CameraSensorComponent and RenderTextureSensor now have an option to write uncompressed observations (#3148)
- Agent’s handling of observations during training was improved so that an extra copy of the observations is no longer maintained (#3229)
- Error message for missing trainer config files was improved to include the absolute path (#3230)
- Support for 2017.4 LTS was dropped (#3121, #3168)
- Some documentation improvements were made (#3296, #3292, #3295, #3281)
Bug Fixes
- Numpy warning when stats don’t exist (#3251)
- A bug that caused RayPerceptionSensor to behave inconsistently with transforms that have non-1 scale was fixed (#3321)
- Some small bugfixes to tensorflow_to_barracuda.py were backported from the barracuda release (#3341)
- Base port in the jupyter notebook example was updated to use the same port that the editor uses (#3283)
[0.13.0-preview] - 2020-01-24
This is the first release of Unity Package ML-Agents.
Short description of this release