Merge remote-tracking branch 'origin/master' into MLA-1734-demo-provider

.github/workflows/pytest.yml

 jobs:
   pytest:
     runs-on: ubuntu-latest
+    env:
+        TEST_ENFORCE_BUFFER_KEY_TYPES: 1
     strategy:
       matrix:
         python-version: [3.6.x, 3.7.x, 3.8.x]
       run: python -c "import sys; print(sys.version)"
     - name: Install dependencies
       run: |
-        # pin pip to workaround https://github.com/pypa/pip/issues/9180
-        python -m pip install pip==20.2
+        python -m pip install --upgrade pip
+        python -m pip install --progress-bar=off -e ./ml-agents-plugin-examples
     - name: Save python dependencies
       run: |
         pip freeze > pip_versions-${{ matrix.python-version }}.txt

.yamato/com.unity.ml-agents-performance.yml

 test_editors:
   - version: 2019.4
-  - version: 2020.1
   - version: 2020.2
 ---
 {% for editor in test_editors %}

.yamato/com.unity.ml-agents-test.yml

     enableCodeCoverage: !!bool true
     testProject: DevProject
     enableNoDefaultPackages: !!bool true
-  - version: 2020.1
-    enableCodeCoverage: !!bool true
-    testProject: DevProject
-    enableNoDefaultPackages: !!bool true
   - version: 2020.2
     enableCodeCoverage: !!bool true
     testProject: DevProject

.yamato/compressed-sensor-test.yml

     - .yamato/standalone-build-test.yml#test_linux_standalone_{{ editor.version }}
   triggers:
     cancel_old_ci: true
+    {% if editor.extra_test == "sensor" %}
     expression: |
       (pull_request.target eq "master" OR
       pull_request.target match "release.+") AND
       pull_request.changes.any match "Project/**" OR
-      pull_request.changes.any match "ml-agents/**" OR
+      pull_request.changes.any match "ml-agents/tests/yamato/**" OR
+    {% endif %}
 {% endfor %}

.yamato/gym-interface-test.yml

     - .yamato/standalone-build-test.yml#test_linux_standalone_{{ editor.version }}
   triggers:
     cancel_old_ci: true
+    {% if editor.extra_test == "gym" %}
     expression: |
       (pull_request.target eq "master" OR
       pull_request.target match "release.+") AND
-      pull_request.changes.any match "ml-agents/**" OR
+      pull_request.changes.any match "ml-agents/tests/yamato/**" OR
+    {% endif %}
 {% endfor %}

.yamato/python-ll-api-test.yml

     - .yamato/standalone-build-test.yml#test_linux_standalone_{{ editor.version }}
   triggers:
     cancel_old_ci: true
+    {% if editor.extra_test == "llapi" %}
     expression: |
       (pull_request.target eq "master" OR
       pull_request.target match "release.+") AND
-      pull_request.changes.any match "ml-agents/**" OR
+      pull_request.changes.any match "ml-agents/tests/yamato/**" OR
+    {% endif %}
 {% endfor %}

.yamato/test_versions.metafile

 # List of editor versions for standalone-build-test and its dependencies.
-# csharp_backcompat_version is used in training-int-tests to determine the
-# older package version to run the backwards compat tests against.
+# We always run training-int-tests for all versions of the editor
+# For each "other" test, we only run it against a single version of the
+# editor to reduce the number of yamato jobs
-    csharp_backcompat_version: 1.0.0
+    extra_test: llapi
-    csharp_backcompat_version: 1.0.0
-  - version: 2020.1
-    csharp_backcompat_version: 1.0.0
+    extra_test: gym
-    # 2020.2 moved the AssetImporters namespace
-    # but we didn't handle this until 1.2.0
-    csharp_backcompat_version: 1.2.0
+    extra_test: sensor

DevProject/Packages/manifest.json

     "com.unity.purchasing": "2.1.0",
     "com.unity.test-framework": "1.1.16",
     "com.unity.test-framework.performance": "2.2.0-preview",
-    "com.unity.testtools.codecoverage": "0.2.2-preview",
+    "com.unity.testtools.codecoverage": "1.0.0-pre.3",
     "com.unity.textmeshpro": "2.0.1",
     "com.unity.timeline": "1.2.12",
     "com.unity.ugui": "1.0.0",

Project/Assets/ML-Agents/Editor/Tests/StandaloneBuildTest.cs

                 scenes,
                 outputPath,
                 buildTarget,
-                BuildOptions.None
+                BuildOptions.Development
             );
             var isOk = buildResult.summary.result == BuildResult.Succeeded;
             var error = "";

Project/Assets/ML-Agents/Examples/3DBall/Prefabs/3DBall.prefab

   m_BrainParameters:
     VectorObservationSize: 8
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 2
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: 3DBall
   TeamId: 0

Project/Assets/ML-Agents/Examples/3DBall/Prefabs/3DBallHardNew.prefab

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    vectorObservationSize: 5
-    numStackedVectorObservations: 9
-    vectorActionSize: 02000000
-    vectorActionDescriptions: []
-    vectorActionSpaceType: 1
-  m_Model: {fileID: 11400000, guid: 27d49984757ed46b181090a532ef48e5, type: 3}
-  m_InferenceDevice: 0
+    VectorObservationSize: 0
+    NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 2
+      BranchSizes: 
+    VectorActionSize: 02000000
+    VectorActionDescriptions: []
+    VectorActionSpaceType: 1
+    hasUpgradedBrainParametersWithActionSpec: 1
+  m_Model: {fileID: 11400000, guid: d179c44c147aa4ffbbb725f009eca3b8, type: 3}
+  m_InferenceDevice: 2
+  m_UseChildActuators: 1
+  m_ObservableAttributeHandling: 1
 --- !u!114 &114466000339026140
 MonoBehaviour:
   m_ObjectHideFlags: 0
   agentParameters:
     maxStep: 0
   hasUpgradedFromAgentParameters: 1
-  maxStep: 5000
+  MaxStep: 5000
   ball: {fileID: 1142513601053358}
 --- !u!114 &8193279139064749781
 MonoBehaviour:
   m_EditorClassIdentifier: 
   DecisionPeriod: 5
   TakeActionsBetweenDecisions: 1
-  offsetStep: 0
 --- !u!114 &7923264721978289873
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   m_ObjectHideFlags: 0
   m_Script: {fileID: 11500000, guid: 3a6da8f78a394c6ab027688eab81e04d, type: 3}
   m_Name: 
   m_EditorClassIdentifier: 
+  debugCommandLineOverride: 
 --- !u!1 &1978072206102878
 GameObject:
   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/3DBall/Prefabs/Visual3DBall.prefab

   m_BrainParameters:
     VectorObservationSize: 0
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 2
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Visual3DBall
   TeamId: 0

Project/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DHardAgent.cs

 using Unity.MLAgents;
 using Unity.MLAgents.Actuators;
 using Unity.MLAgents.Sensors;
+using Unity.MLAgents.Sensors.Reflection;
 
 public class Ball3DHardAgent : Agent
 {
         SetResetParameters();
     }
 
-    public override void CollectObservations(VectorSensor sensor)
+    [Observable(numStackedObservations: 9)]
+    Vector2 Rotation
-        sensor.AddObservation(gameObject.transform.rotation.z);
-        sensor.AddObservation(gameObject.transform.rotation.x);
-        sensor.AddObservation((ball.transform.position - gameObject.transform.position));
+        get
+        {
+            return new Vector2(gameObject.transform.rotation.z, gameObject.transform.rotation.x);
+        }
+    }
+
+    [Observable(numStackedObservations: 9)]
+    Vector3 PositionDelta
+    {
+        get
+        {
+            return ball.transform.position - gameObject.transform.position;
+        }
     }
 
     public override void OnActionReceived(ActionBuffers actionBuffers)

Project/Assets/ML-Agents/Examples/Basic/Prefabs/Basic.prefab

   m_BrainParameters:
     VectorObservationSize: 0
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Basic
   TeamId: 0

Project/Assets/ML-Agents/Examples/Basic/Scripts/BasicActuatorComponent.cs

         /// Creates a BasicActuator.
         /// </summary>
         /// <returns></returns>
+#pragma warning disable 672
+#pragma warning restore 672
         {
             return new BasicActuator(basicController);
         }

Project/Assets/ML-Agents/Examples/Bouncer/Prefabs/Environment.prefab

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    vectorObservationSize: 6
-    numStackedVectorObservations: 3
-    vectorActionSize: 03000000
-    vectorActionDescriptions: []
-    vectorActionSpaceType: 1
+    VectorObservationSize: 6
+    NumStackedVectorObservations: 3
+    m_ActionSpec:
+      m_NumContinuousActions: 3
+      BranchSizes: 
+    VectorActionSize: 03000000
+    VectorActionDescriptions: []
+    VectorActionSpaceType: 1
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
+  m_UseChildActuators: 1
+  m_ObservableAttributeHandling: 0
 --- !u!114 &114878620968301562
 MonoBehaviour:
   m_ObjectHideFlags: 0
   agentParameters:
     maxStep: 0
   hasUpgradedFromAgentParameters: 1
-  maxStep: 0
+  MaxStep: 0
   target: {fileID: 1160631129428284}
   bodyObject: {fileID: 1680588139522898}
   strength: 500
   m_Script: {fileID: 11500000, guid: 3a6da8f78a394c6ab027688eab81e04d, type: 3}
   m_Name: 
   m_EditorClassIdentifier: 
+  debugCommandLineOverride: 
 --- !u!1 &1680588139522898
 GameObject:
   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/Crawler/Prefabs/CrawlerBase.prefab

   m_BrainParameters:
     VectorObservationSize: 32
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 20
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: 
   TeamId: 0

Project/Assets/ML-Agents/Examples/FoodCollector/Prefabs/FoodCollectorArea.prefab

     VectorActionSpaceType: 1
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 3210b528a2bc44a86bd6bd1d571070f8, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: FoodCollector
   TeamId: 0
     VectorActionSpaceType: 1
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 3210b528a2bc44a86bd6bd1d571070f8, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: FoodCollector
   TeamId: 0
     VectorActionSpaceType: 1
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 3210b528a2bc44a86bd6bd1d571070f8, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: FoodCollector
   TeamId: 0
     VectorActionSpaceType: 1
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 3210b528a2bc44a86bd6bd1d571070f8, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: FoodCollector
   TeamId: 0
     VectorActionSpaceType: 1
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 3210b528a2bc44a86bd6bd1d571070f8, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: FoodCollector
   TeamId: 0

Project/Assets/ML-Agents/Examples/FoodCollector/Prefabs/GridFoodCollectorArea.prefab

     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 75910f45f20be49b18e2b95879a217b2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 75910f45f20be49b18e2b95879a217b2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 75910f45f20be49b18e2b95879a217b2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 75910f45f20be49b18e2b95879a217b2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 75910f45f20be49b18e2b95879a217b2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridFoodCollector
   TeamId: 0

Project/Assets/ML-Agents/Examples/FoodCollector/Prefabs/VisualFoodCollectorArea.prefab

     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: ec4b31b5d66ca4e51ae3ac41945facb2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: VisualFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: ec4b31b5d66ca4e51ae3ac41945facb2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: VisualFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: ec4b31b5d66ca4e51ae3ac41945facb2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: VisualFoodCollector
   TeamId: 0
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: ec4b31b5d66ca4e51ae3ac41945facb2, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: VisualFoodCollector
   TeamId: 0

Project/Assets/ML-Agents/Examples/GridWorld/Prefabs/Area.prefab

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    vectorObservationSize: 0
-    numStackedVectorObservations: 1
-    vectorActionSize: 05000000
-    vectorActionDescriptions: []
-    vectorActionSpaceType: 0
+    VectorObservationSize: 0
+    NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 05000000
+    VectorActionSize: 05000000
+    VectorActionDescriptions: []
+    VectorActionSpaceType: 0
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
+  m_UseChildActuators: 1
+  m_ObservableAttributeHandling: 0
 --- !u!114 &114650561397225712
 MonoBehaviour:
   m_ObjectHideFlags: 0
   agentParameters:
     maxStep: 0
   hasUpgradedFromAgentParameters: 1
-  maxStep: 100
+  MaxStep: 100
   area: {fileID: 114704252266302846}
   timeBetweenDecisionsAtInference: 0.15
   renderCamera: {fileID: 0}
   m_Width: 84
   m_Height: 64
   m_Grayscale: 0
+  m_ObservationStacks: 1
   m_Compression: 1
 --- !u!114 &7980686505185502968
 MonoBehaviour:
   m_Script: {fileID: 11500000, guid: 3a6da8f78a394c6ab027688eab81e04d, type: 3}
   m_Name: 
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   m_ObjectHideFlags: 0
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   pitPref: {fileID: 1811317785436014, guid: d13ee2db77b3a4dcc8664d2fe2a0f219, type: 3}
+  numberOfObstacles: 1
 --- !u!1 &1656910849934022
 GameObject:
   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/GridWorld/Scenes/GridWorld.unity

   m_ReflectionIntensity: 1
   m_CustomReflection: {fileID: 0}
   m_Sun: {fileID: 0}
-  m_IndirectSpecularColor: {r: 0.44971228, g: 0.49977815, b: 0.57563734, a: 1}
+  m_IndirectSpecularColor: {r: 0.4497121, g: 0.49977785, b: 0.57563704, a: 1}
   m_UseRadianceAmbientProbe: 0
 --- !u!157 &3
 LightmapSettings:
   m_BrainParameters:
     VectorObservationSize: 0
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 05000000
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: GridWorld
   TeamId: 0

Project/Assets/ML-Agents/Examples/Hallway/Prefabs/SymbolFinderArea.prefab

   m_BrainParameters:
     VectorObservationSize: 1
     NumStackedVectorObservations: 3
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 05000000
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Hallway
   TeamId: 0

Project/Assets/ML-Agents/Examples/Hallway/Prefabs/VisualSymbolFinderArea.prefab

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    vectorObservationSize: 0
-    numStackedVectorObservations: 1
-    vectorActionSize: 05000000
-    vectorActionDescriptions: []
-    vectorActionSpaceType: 0
+    VectorObservationSize: 0
+    NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 05000000
+    VectorActionSize: 05000000
+    VectorActionDescriptions: []
+    VectorActionSpaceType: 0
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
-  m_TeamID: 0
-  m_useChildSensors: 1
+  TeamId: 0
+  m_UseChildSensors: 1
+  m_UseChildActuators: 1
+  m_ObservableAttributeHandling: 0
 --- !u!114 &114451776683649118
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   m_Script: {fileID: 11500000, guid: b446afae240924105b36d07e8d17a608, type: 3}
   m_Name: 
   m_EditorClassIdentifier: 
-  maxStep: 3000
+  agentParameters:
+    maxStep: 0
+  hasUpgradedFromAgentParameters: 1
+  MaxStep: 3000
   ground: {fileID: 1625056884785366}
   area: {fileID: 1689874756253538}
   symbolOGoal: {fileID: 1800868804754718}
   m_Script: {fileID: 11500000, guid: 282f342c2ab144bf38be65d4d0c4e07d, type: 3}
   m_Name: 
   m_EditorClassIdentifier: 
-  camera: {fileID: 20961984019151212}
-  sensorName: CameraSensor
-  width: 84
-  height: 84
-  grayscale: 0
-  compression: 1
+  m_Camera: {fileID: 20961984019151212}
+  m_SensorName: CameraSensor
+  m_Width: 84
+  m_Height: 84
+  m_Grayscale: 0
+  m_ObservationStacks: 1
+  m_Compression: 1
 --- !u!114 &640264344416331590
 MonoBehaviour:
   m_ObjectHideFlags: 0
   m_Name: 
   m_EditorClassIdentifier: 
   DecisionPeriod: 6
-  RepeatAction: 1
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+  TakeActionsBetweenDecisions: 1
 --- !u!1 &1377584197416466
 GameObject:
   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/Match3/Prefabs/Match3Heuristic.prefab

     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: c34da50737a3c4a50918002b20b2b927, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Match3SmartHeuristic
   TeamId: 0
   Columns: 8
   NumCellTypes: 6
   NumSpecialTypes: 2
-  RandomSeed: -1
+  RandomSeed: -1
 --- !u!114 &3508723250470608014
 MonoBehaviour:
   m_ObjectHideFlags: 0
   m_Name: 
   m_EditorClassIdentifier: 
   ActuatorName: Match3 Actuator
+  RandomSeed: -1
-  HeuristicQuality: 0
 --- !u!1 &3508723250774301855
 GameObject:
   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/Match3/Prefabs/Match3VectorObs.prefab

     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 9e89b8e81974148d3b7213530d00589d, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Match3VectorObs
   TeamId: 0
   Columns: 8
   NumCellTypes: 6
   NumSpecialTypes: 2
-  RandomSeed: -1
+  RandomSeed: -1
 --- !u!114 &2118285884327540680
 MonoBehaviour:
   m_ObjectHideFlags: 0
   m_Name: 
   m_EditorClassIdentifier: 
   ActuatorName: Match3 Actuator
+  RandomSeed: -1
-  HeuristicQuality: 0

Project/Assets/ML-Agents/Examples/Match3/Prefabs/Match3VisualObs.prefab

     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Model: {fileID: 11400000, guid: 48d14da88fea74d0693c691c6e3f2e34, type: 3}
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: Match3VisualObs
   TeamId: 0
   Columns: 8
   NumCellTypes: 6
   NumSpecialTypes: 2
-  RandomSeed: -1
+  RandomSeed: -1
 --- !u!114 &3019509692332007783
 MonoBehaviour:
   m_ObjectHideFlags: 0
   m_Name: 
   m_EditorClassIdentifier: 
   ActuatorName: Match3 Actuator
+  RandomSeed: -1
-  HeuristicQuality: 0

Project/Assets/ML-Agents/Examples/Match3/Scripts/Match3ExampleActuatorComponent.cs

     public class Match3ExampleActuatorComponent : Match3ActuatorComponent
     {
         /// <inheritdoc/>
+#pragma warning disable 672
+#pragma warning restore 672
         {
             var board = GetComponent<Match3Board>();
             var agent = GetComponentInParent<Agent>();

Project/Assets/ML-Agents/Examples/PushBlock/Prefabs/PushBlockArea.prefab

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    vectorObservationSize: 0
-    numStackedVectorObservations: 2
-    vectorActionSize: 07000000
-    vectorActionDescriptions: []
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+    VectorObservationSize: 0
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+    VectorActionSpaceType: 0
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 --- !u!114 &114505490781873732
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     maxStep: 0
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+  MaxStep: 5000
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   TakeActionsBetweenDecisions: 1
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Project/Assets/ML-Agents/Examples/PushBlock/Prefabs/PushBlockVisualArea.prefab

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Project/Assets/ML-Agents/Examples/Pyramids/Prefabs/AreaPB.prefab

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Project/Assets/ML-Agents/Examples/Pyramids/Prefabs/VisualAreaPyramids.prefab

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+  m_SensorName: CameraSensor
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+  m_Height: 84
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Project/Assets/ML-Agents/Examples/Reacher/Prefabs/Agent.prefab

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+    VectorActionDescriptions: []
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Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/ModelOverrider.cs

         const string k_CommandLineModelOverrideDirectoryFlag = "--mlagents-override-model-directory";
         const string k_CommandLineModelOverrideExtensionFlag = "--mlagents-override-model-extension";
         const string k_CommandLineQuitAfterEpisodesFlag = "--mlagents-quit-after-episodes";
+        const string k_CommandLineQuitAfterSeconds = "--mlagents-quit-after-seconds";
         const string k_CommandLineQuitOnLoadFailure = "--mlagents-quit-on-load-failure";
 
         // The attached Agent
         // Max episodes to run. Only used if > 0
         // Will default to 1 if override models are specified, otherwise 0.
         int m_MaxEpisodes;
+
+        // Deadline - exit if the time exceeds this
+        DateTime m_Deadline = DateTime.MaxValue;
 
         int m_NumSteps;
         int m_PreviousNumSteps;
         void GetAssetPathFromCommandLine()
         {
             var maxEpisodes = 0;
+            var timeoutSeconds = 0;
+
             string[] commandLineArgsOverride = null;
             if (!string.IsNullOrEmpty(debugCommandLineOverride) && Application.isEditor)
             {
                 {
                     Int32.TryParse(args[i + 1], out maxEpisodes);
                 }
+                else if (args[i] == k_CommandLineQuitAfterSeconds && i < args.Length - 1)
+                {
+                    Int32.TryParse(args[i + 1], out timeoutSeconds);
+                }
                 else if (args[i] == k_CommandLineQuitOnLoadFailure)
                 {
                     m_QuitOnLoadFailure = true;
                 m_MaxEpisodes = maxEpisodes > 0 ? maxEpisodes : 1;
                 Debug.Log($"setting m_MaxEpisodes to {maxEpisodes}");
             }
+
+            if (timeoutSeconds > 0)
+            {
+                m_Deadline = DateTime.Now + TimeSpan.FromSeconds(timeoutSeconds);
+                Debug.Log($"setting deadline to {timeoutSeconds} from now.");
+
+            }
         }
 
         void OnEnable()
                     EditorApplication.isPlaying = false;
 #endif
                 }
+                else if (DateTime.Now >= m_Deadline)
+                {
+                    Debug.Log(
+                        $"Deadline exceeded. " +
+                        $"{TotalCompletedEpisodes}/{m_MaxEpisodes} episodes and " +
+                        $"{TotalNumSteps}/{m_MaxEpisodes * m_Agent.MaxStep} steps completed. Exiting.");
+                    Application.Quit(0);
+#if UNITY_EDITOR
+                    EditorApplication.isPlaying = false;
+#endif
+                }
+
             m_NumSteps++;
         }
 

Project/Assets/ML-Agents/Examples/Soccer/Prefabs/SoccerFieldTwos.prefab

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     NumStackedVectorObservations: 1
+    m_ActionSpec:
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+      BranchSizes: 030000000300000003000000
+    hasUpgradedBrainParametersWithActionSpec: 1
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+  m_UseChildActuators: 1
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Project/Assets/ML-Agents/Examples/Soccer/Prefabs/StrikersVsGoalieField.prefab

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+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 030000000300000003000000
+    hasUpgradedBrainParametersWithActionSpec: 1
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+  m_UseChildActuators: 1
   m_ObservableAttributeHandling: 0
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+    m_ActionSpec:
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+      BranchSizes: 030000000300000003000000
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
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+    m_ActionSpec:
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+    hasUpgradedBrainParametersWithActionSpec: 1
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+  m_UseChildActuators: 1
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Project/Assets/ML-Agents/Examples/Tennis/Prefabs/TennisArea.prefab

   m_BrainParameters:
     VectorObservationSize: 9
     NumStackedVectorObservations: 3
+    m_ActionSpec:
+      m_NumContinuousActions: 3
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
+  m_UseChildActuators: 1
+  m_ObservableAttributeHandling: 0
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+  debugCommandLineOverride: 
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   m_ObjectHideFlags: 0
   m_BrainParameters:
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   m_ObjectHideFlags: 0

Project/Assets/ML-Agents/Examples/Walker/Prefabs/Ragdoll/WalkerRagdollBase.prefab

   m_BrainParameters:
     VectorObservationSize: 243
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 39
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
+  m_UseChildActuators: 1
   m_ObservableAttributeHandling: 0
 --- !u!114 &7408209125961349353
 MonoBehaviour:
     maxStep: 0
   hasUpgradedFromAgentParameters: 1
   MaxStep: 5000
-  targetWalkingSpeed: 10
+  m_TargetWalkingSpeed: 10
-  walkDirectionMethod: 0
-  worldDirToWalk: {x: 1, y: 0, z: 0}
-  worldPosToWalkTo: {x: 0, y: 0, z: 0}
   target: {fileID: 0}
   hips: {fileID: 895268871264836332}
   chest: {fileID: 7933235354845945071}

Project/Assets/ML-Agents/Examples/Walker/Prefabs/Ragdoll/WalkerRagdollDySingleSpeedVariant.prefab

       value: 
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+    - target: {fileID: 895268871377934297, guid: 765582efd9dda46ed98564603316353f,
+        type: 3}
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         type: 3}
       propertyPath: m_LocalPosition.x

Project/Assets/ML-Agents/Examples/WallJump/Prefabs/WallJumpArea.prefab

   m_BrainParameters:
     VectorObservationSize: 4
     NumStackedVectorObservations: 6
+    m_ActionSpec:
+      m_NumContinuousActions: 0
+      BranchSizes: 03000000030000000300000002000000
+    hasUpgradedBrainParametersWithActionSpec: 1
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+  m_UseChildActuators: 1
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 --- !u!114 &114925928594762506
 MonoBehaviour:

Project/Assets/ML-Agents/Examples/Worm/Prefabs/WormBasePrefab.prefab

   m_BrainParameters:
     VectorObservationSize: 64
     NumStackedVectorObservations: 1
+    m_ActionSpec:
+      m_NumContinuousActions: 9
+      BranchSizes: 
+    hasUpgradedBrainParametersWithActionSpec: 1
-  m_InferenceDevice: 0
+  m_InferenceDevice: 2
   m_BehaviorType: 0
   m_BehaviorName: WormDynamic
   TeamId: 0

Project/ProjectSettings/TagManager.asset

   - symbol_O_Goal
   - purpleAgent
   - purpleGoal
+  - tile
   layers:
   - Default
   - TransparentFX

com.unity.ml-agents.extensions/Runtime/Match3/Match3ActuatorComponent.cs

         public bool ForceHeuristic;
 
         /// <inheritdoc/>
+#pragma warning disable 672
+#pragma warning restore 672
         {
             var board = GetComponent<AbstractBoard>();
             var agent = GetComponentInParent<Agent>();

com.unity.ml-agents/CHANGELOG.md

 and this project adheres to
 [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+### Major Changes
+#### com.unity.ml-agents (C#)
+#### ml-agents / ml-agents-envs / gym-unity (Python)
-## [Unreleased]
+### Minor Changes
+#### com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
+#### ml-agents / ml-agents-envs / gym-unity (Python)
+
+### Bug Fixes
+#### com.unity.ml-agents (C#)
+#### ml-agents / ml-agents-envs / gym-unity (Python)
+
+
+## [1.8.0-preview] - 2021-02-17
+- A plugin system for `mlagents-learn` has been added. You can now define custom
+  `StatsWriter` 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#)
   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)
+  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 `ObservationWriter.AddList()` and deprecated `ObservationWriter.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 deprecate `ActuatorComponent.CreateActuator`.  The
+  default implementation will wrap `ActuatorComponent.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 use `InferenceDevice.CPU` should update to
+  `InferenceDevice.Burst`. (#4925)
+- Tensorboard now logs the Environment Reward as both a scalar and a histogram. (#4878)
+- The `mlagents_env` API has changed, `BehaviorSpec` now has a `observation_specs` property containing a list of `ObservationSpec`. For more information on `ObservationSpec` see [here](https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Python-API.md#behaviorspec). (#4763, #4825)
 
 ### Bug Fixes
 #### com.unity.ml-agents (C#)
 - 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 via `pickle`. (#4842)
   while waiting for a connection, and raises a better error message if it crashes. (#4880)
 - Passing a `-logfile` option in the `--env-args` option to `mlagents-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

com.unity.ml-agents/Editor/BehaviorParametersEditor.cs

 
             // Grab the sensor components, since we need them to determine the observation sizes.
             // TODO make these methods of BehaviorParameters
-            SensorComponent[] sensorComponents;
-            if (behaviorParameters.UseChildSensors)
-            {
-                sensorComponents = behaviorParameters.GetComponentsInChildren<SensorComponent>();
-            }
-            else
-            {
-                sensorComponents = behaviorParameters.GetComponents<SensorComponent>();
-            }
+            var agent = behaviorParameters.gameObject.GetComponent<Agent>();
+            agent.sensors = new List<ISensor>();
+            agent.InitializeSensors();
+            var sensors = agent.sensors.ToArray();
 
             ActuatorComponent[] actuatorComponents;
             if (behaviorParameters.UseChildActuators)
             // Get the total size of the sensors generated by ObservableAttributes.
             // If there are any errors (e.g. unsupported type, write-only properties), display them too.