Adding the goal conditioning sensors with the new observation specs (#…

…5159) * Fixing networks.py for the merge * fix compile error * Adding the goal conditioning sensors with the new observation specs * addressing feedback * I forgot to change the m_observationType * Renaming Goal to GoalSignal (#5190) * Renaming GOAL to GOAL_SIGNAL * VectorSensorComponent to use new API * Adding docstrings * verbose pytest on github action Co-authored-by: Chris Elion <chris.elion@unity3d.com>
Unity-Technologies · Mar 29, 2021 · ca0fca7 · ca0fca7
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commit ca0fca7
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Showing 19 changed files with 194 additions and 55 deletions.
diff --git a/.github/workflows/pytest.yml b/.github/workflows/pytest.yml
@@ -61,7 +61,7 @@ jobs:
  pip freeze > pip_versions-${{ matrix.python-version }}.txt
  cat pip_versions-${{ matrix.python-version }}.txt
  - name: Run pytest
- run: pytest --cov=ml-agents --cov=ml-agents-envs --cov=gym-unity --cov-report html --junitxml=junit/test-results-${{ matrix.python-version }}.xml -p no:warnings
+ run: pytest --cov=ml-agents --cov=ml-agents-envs --cov=gym-unity --cov-report html --junitxml=junit/test-results-${{ matrix.python-version }}.xml -p no:warnings -v
  - name: Upload pytest test results
  uses: actions/upload-artifact@v2
  with:

diff --git a/com.unity.ml-agents/Editor/CameraSensorComponentEditor.cs b/com.unity.ml-agents/Editor/CameraSensorComponentEditor.cs
@@ -25,6 +25,7 @@ public override void OnInspectorGUI()
  EditorGUILayout.PropertyField(so.FindProperty("m_Height"), true);
  EditorGUILayout.PropertyField(so.FindProperty("m_Grayscale"), true);
  EditorGUILayout.PropertyField(so.FindProperty("m_ObservationStacks"), true);
+ EditorGUILayout.PropertyField(so.FindProperty("m_ObservationType"), true);
  }
  EditorGUI.EndDisabledGroup();
  EditorGUILayout.PropertyField(so.FindProperty("m_Compression"), true);

diff --git a/com.unity.ml-agents/Editor/VectorSensorComponentEditor.cs b/com.unity.ml-agents/Editor/VectorSensorComponentEditor.cs
@@ -0,0 +1,30 @@
+using UnityEditor;
+using Unity.MLAgents.Sensors;
+
+namespace Unity.MLAgents.Editor
+{
+ [CustomEditor(typeof(VectorSensorComponent))]
+ [CanEditMultipleObjects]
+ internal class VectorSensorComponentEditor : UnityEditor.Editor
+ {
+ public override void OnInspectorGUI()
+ {
+ var so = serializedObject;
+ so.Update();
+
+ // Drawing the VectorSensorComponent
+
+ EditorGUI.BeginDisabledGroup(!EditorUtilities.CanUpdateModelProperties());
+ {
+ // These fields affect the sensor order or observation size,
+ // So can't be changed at runtime.
+ EditorGUILayout.PropertyField(so.FindProperty("m_SensorName"), true);
+ EditorGUILayout.PropertyField(so.FindProperty("m_ObservationSize"), true);
+ EditorGUILayout.PropertyField(so.FindProperty("m_ObservationType"), true);
+ }
+ EditorGUI.EndDisabledGroup();
+
+ so.ApplyModifiedProperties();
+ }
+ }
+}
diff --git a/com.unity.ml-agents/Editor/VectorSensorComponentEditor.cs.meta b/com.unity.ml-agents/Editor/VectorSensorComponentEditor.cs.meta
diff --git a/com.unity.ml-agents/Runtime/Grpc/CommunicatorObjects/Observation.cs b/com.unity.ml-agents/Runtime/Grpc/CommunicatorObjects/Observation.cs
@@ -35,10 +35,10 @@ static ObservationReflection() {
  "b25fdHlwZRgHIAEoDjIqLmNvbW11bmljYXRvcl9vYmplY3RzLk9ic2VydmF0",
  "aW9uVHlwZVByb3RvEgwKBG5hbWUYCCABKAkaGQoJRmxvYXREYXRhEgwKBGRh",
  "dGEYASADKAJCEgoQb2JzZXJ2YXRpb25fZGF0YSopChRDb21wcmVzc2lvblR5",
- "cGVQcm90bxIICgROT05FEAASBwoDUE5HEAEqRgoUT2JzZXJ2YXRpb25UeXBl",
- "UHJvdG8SCwoHREVGQVVMVBAAEggKBEdPQUwQARIKCgZSRVdBUkQQAhILCgdN",
- "RVNTQUdFEANCJaoCIlVuaXR5Lk1MQWdlbnRzLkNvbW11bmljYXRvck9iamVj",
- "dHNiBnByb3RvMw=="));
+ "cGVQcm90bxIICgROT05FEAASBwoDUE5HEAEqQAoUT2JzZXJ2YXRpb25UeXBl",
+ "UHJvdG8SCwoHREVGQVVMVBAAEg8KC0dPQUxfU0lHTkFMEAEiBAgCEAIiBAgD",
+ "EANCJaoCIlVuaXR5Lk1MQWdlbnRzLkNvbW11bmljYXRvck9iamVjdHNiBnBy",
+ "b3RvMw=="));
  descriptor = pbr::FileDescriptor.FromGeneratedCode(descriptorData,
  new pbr::FileDescriptor[] { },
  new pbr::GeneratedClrTypeInfo(new[] {typeof(global::Unity.MLAgents.CommunicatorObjects.CompressionTypeProto), typeof(global::Unity.MLAgents.CommunicatorObjects.ObservationTypeProto), }, new pbr::GeneratedClrTypeInfo[] {
@@ -56,9 +56,7 @@ internal enum CompressionTypeProto {
 
  internal enum ObservationTypeProto {
  [pbr::OriginalName("DEFAULT")] Default = 0,
- [pbr::OriginalName("GOAL")] Goal = 1,
- [pbr::OriginalName("REWARD")] Reward = 2,
- [pbr::OriginalName("MESSAGE")] Message = 3,
+ [pbr::OriginalName("GOAL_SIGNAL")] GoalSignal = 1,
  }
 
  #endregion

diff --git a/com.unity.ml-agents/Runtime/Sensors/CameraSensor.cs b/com.unity.ml-agents/Runtime/Sensors/CameraSensor.cs
@@ -44,16 +44,17 @@ public SensorCompressionType CompressionType
  /// <param name="grayscale">Whether to convert the generated image to grayscale or keep color.</param>
  /// <param name="name">The name of the camera sensor.</param>
  /// <param name="compression">The compression to apply to the generated image.</param>
+ /// <param name="observationType">The type of observation.</param>
  public CameraSensor(
- Camera camera, int width, int height, bool grayscale, string name, SensorCompressionType compression)
+ Camera camera, int width, int height, bool grayscale, string name, SensorCompressionType compression, ObservationType observationType = ObservationType.Default)
  {
  m_Camera = camera;
  m_Width = width;
  m_Height = height;
  m_Grayscale = grayscale;
  m_Name = name;
  var channels = grayscale ? 1 : 3;
- m_ObservationSpec = ObservationSpec.Visual(height, width, channels);
+ m_ObservationSpec = ObservationSpec.Visual(height, width, channels, observationType);
  m_CompressionType = compression;
  }
 

diff --git a/com.unity.ml-agents/Runtime/Sensors/CameraSensorComponent.cs b/com.unity.ml-agents/Runtime/Sensors/CameraSensorComponent.cs
@@ -75,6 +75,18 @@ public bool Grayscale
  set { m_Grayscale = value; }
  }
 
+ [HideInInspector, SerializeField]
+ ObservationType m_ObservationType;
+
+ /// <summary>
+ /// The type of the observation.
+ /// </summary>
+ public ObservationType ObservationType
+ {
+ get { return m_ObservationType; }
+ set { m_ObservationType = value; UpdateSensor(); }
+ }
+
  [HideInInspector, SerializeField]
  [Range(1, 50)]
  [Tooltip("Number of camera frames that will be stacked before being fed to the neural network.")]
@@ -108,7 +120,7 @@ public int ObservationStacks
  /// <returns>The created <see cref="CameraSensor"/> object for this component.</returns>
  public override ISensor[] CreateSensors()
  {
- m_Sensor = new CameraSensor(m_Camera, m_Width, m_Height, Grayscale, m_SensorName, m_Compression);
+ m_Sensor = new CameraSensor(m_Camera, m_Width, m_Height, Grayscale, m_SensorName, m_Compression, m_ObservationType);
 
  if (ObservationStacks != 1)
  {

diff --git a/com.unity.ml-agents/Runtime/Sensors/ISensor.cs b/com.unity.ml-agents/Runtime/Sensors/ISensor.cs
@@ -42,17 +42,7 @@ public enum ObservationType
  /// <summary>
  /// Collected observations contain goal information.
  /// </summary>
- Goal = 1,
-
- /// <summary>
- /// Collected observations contain reward information.
- /// </summary>
- Reward = 2,
-
- /// <summary>
- /// Collected observations are messages from other agents.
- /// </summary>
- Message = 3,
+ GoalSignal = 1,
  }
 
  /// <summary>

diff --git a/com.unity.ml-agents/Runtime/Sensors/VectorSensor.cs b/com.unity.ml-agents/Runtime/Sensors/VectorSensor.cs
@@ -21,16 +21,20 @@ public class VectorSensor : ISensor, IBuiltInSensor
  /// </summary>
  /// <param name="observationSize">Number of vector observations.</param>
  /// <param name="name">Name of the sensor.</param>
- public VectorSensor(int observationSize, string name = null)
+ public VectorSensor(int observationSize, string name = null, ObservationType observationType = ObservationType.Default)
  {
- if (name == null)
+ if (string.IsNullOrEmpty(name))
  {
  name = $"VectorSensor_size{observationSize}";
+ if (observationType != ObservationType.Default)
+ {
+ name += $"_{observationType.ToString()}";
+ }
  }
 
  m_Observations = new List<float>(observationSize);
  m_Name = name;
- m_ObservationSpec = ObservationSpec.Vector(observationSize);
+ m_ObservationSpec = ObservationSpec.Vector(observationSize, observationType);
  }
 
  /// <inheritdoc/>

diff --git a/com.unity.ml-agents/Runtime/Sensors/VectorSensorComponent.cs b/com.unity.ml-agents/Runtime/Sensors/VectorSensorComponent.cs
@@ -0,0 +1,68 @@
+using UnityEngine;
+using UnityEngine.Serialization;
+
+namespace Unity.MLAgents.Sensors
+{
+ /// <summary>
+ /// A SensorComponent that creates a <see cref="VectorSensor"/>.
+ /// </summary>
+ [AddComponentMenu("ML Agents/Vector Sensor", (int)MenuGroup.Sensors)]
+ public class VectorSensorComponent : SensorComponent
+ {
+ /// <summary>
+ /// Name of the generated <see cref="VectorSensor"/> object.
+ /// Note that changing this at runtime does not affect how the Agent sorts the sensors.
+ /// </summary>
+ public string SensorName
+ {
+ get { return m_SensorName; }
+ set { m_SensorName = value; }
+ }
+ [HideInInspector, SerializeField]
+ private string m_SensorName = "VectorSensor";
+
+ /// <summary>
+ /// The number of float observations in the VectorSensor
+ /// </summary>
+ public int ObservationSize
+ {
+ get { return m_ObservationSize; }
+ set { m_ObservationSize = value; }
+ }
+
+ [HideInInspector, SerializeField]
+ int m_ObservationSize;
+
+ [HideInInspector, SerializeField]
+ ObservationType m_ObservationType;
+
+ VectorSensor m_Sensor;
+
+ /// <summary>
+ /// The type of the observation.
+ /// </summary>
+ public ObservationType ObservationType
+ {
+ get { return m_ObservationType; }
+ set { m_ObservationType = value; }
+ }
+
+ /// <summary>
+ /// Creates a VectorSensor.
+ /// </summary>
+ /// <returns></returns>
+ public override ISensor[] CreateSensors()
+ {
+ m_Sensor = new VectorSensor(m_ObservationSize, m_SensorName, m_ObservationType);
+ return new ISensor[] { m_Sensor };
+ }
+
+ /// <summary>
+ /// Returns the underlying VectorSensor
+ /// </summary>
+ public VectorSensor GetSensor()
+ {
+ return m_Sensor;
+ }
+ }
+}
diff --git a/com.unity.ml-agents/Runtime/Sensors/VectorSensorComponent.cs.meta b/com.unity.ml-agents/Runtime/Sensors/VectorSensorComponent.cs.meta
diff --git a/com.unity.ml-agents/Tests/Runtime/Sensor/CameraSensorTest.cs b/com.unity.ml-agents/Tests/Runtime/Sensor/CameraSensorTest.cs
@@ -37,5 +37,22 @@ public void TestCameraSensor()
  }
  }
  }
+
+ [Test]
+ public void TestObservationType()
+ {
+ var width = 24;
+ var height = 16;
+ var camera = Camera.main;
+ var sensor = new CameraSensor(camera, width, height, true, "TestCameraSensor", SensorCompressionType.None);
+ var spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.Default);
+ sensor = new CameraSensor(camera, width, height, true, "TestCameraSensor", SensorCompressionType.None, ObservationType.Default);
+ spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.Default);
+ sensor = new CameraSensor(camera, width, height, true, "TestCameraSensor", SensorCompressionType.None, ObservationType.GoalSignal);
+ spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.GoalSignal);
+ }
  }
 }
diff --git a/com.unity.ml-agents/Tests/Runtime/Sensor/VectorSensorTests.cs b/com.unity.ml-agents/Tests/Runtime/Sensor/VectorSensorTests.cs
@@ -42,6 +42,20 @@ public void TestAddObservationFloat()
  SensorTestHelper.CompareObservation(sensor, new[] { 1.2f });
  }
 
+ [Test]
+ public void TestObservationType()
+ {
+ var sensor = new VectorSensor(1);
+ var spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.Default);
+ sensor = new VectorSensor(1, observationType: ObservationType.Default);
+ spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.Default);
+ sensor = new VectorSensor(1, observationType: ObservationType.GoalSignal);
+ spec = sensor.GetObservationSpec();
+ Assert.AreEqual((int)spec.ObservationType, (int)ObservationType.GoalSignal);
+ }
+
  [Test]
  public void TestAddObservationInt()
  {

diff --git a/ml-agents-envs/mlagents_envs/base_env.py b/ml-agents-envs/mlagents_envs/base_env.py
@@ -486,11 +486,7 @@ class ObservationType(Enum):
  # Observation information is generic.
  DEFAULT = 0
  # Observation contains goal information for current task.
- GOAL = 1
- # Observation contains reward information for current task.
- REWARD = 2
- # Observation contains a message from another agent.
- MESSAGE = 3
+ GOAL_SIGNAL = 1
 
 
 class ObservationSpec(NamedTuple):

diff --git a/ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py b/ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py
diff --git a/ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.pyi b/ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.pyi
@@ -64,13 +64,9 @@ class ObservationTypeProto(builtin___int):
  @classmethod
  def items(cls) -> typing___List[typing___Tuple[builtin___str, 'ObservationTypeProto']]: ...
  DEFAULT = typing___cast('ObservationTypeProto', 0)
- GOAL = typing___cast('ObservationTypeProto', 1)
- REWARD = typing___cast('ObservationTypeProto', 2)
- MESSAGE = typing___cast('ObservationTypeProto', 3)
+ GOAL_SIGNAL = typing___cast('ObservationTypeProto', 1)
 DEFAULT = typing___cast('ObservationTypeProto', 0)
-GOAL = typing___cast('ObservationTypeProto', 1)
-REWARD = typing___cast('ObservationTypeProto', 2)
-MESSAGE = typing___cast('ObservationTypeProto', 3)
+GOAL_SIGNAL = typing___cast('ObservationTypeProto', 1)
 
 class ObservationProto(google___protobuf___message___Message):
  DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...

diff --git a/ml-agents/mlagents/trainers/tests/simple_test_envs.py b/ml-agents/mlagents/trainers/tests/simple_test_envs.py
@@ -121,7 +121,7 @@ def _make_observation_specs(self) -> List[ObservationSpec]:
  obs_spec[i] = ObservationSpec(
  shape=obs_spec[i].shape,
  dimension_property=obs_spec[i].dimension_property,
- observation_type=ObservationType.GOAL,
+ observation_type=ObservationType.GOAL_SIGNAL,
  name=obs_spec[i].name,
  )
  return obs_spec

diff --git a/ml-agents/mlagents/trainers/torch/networks.py b/ml-agents/mlagents/trainers/torch/networks.py
@@ -60,7 +60,7 @@ def __init__(
  self._total_goal_enc_size = 0
  self._goal_processor_indices: List[int] = []
  for i in range(len(observation_specs)):
- if observation_specs[i].observation_type == ObservationType.GOAL:
+ if observation_specs[i].observation_type == ObservationType.GOAL_SIGNAL:
  self._total_goal_enc_size += self.embedding_sizes[i]
  self._goal_processor_indices.append(i)