using System.Linq; using NUnit.Framework; using UnityEngine; using UnityEditor; using Unity.Barracuda; using Unity.MLAgents.Actuators; using Unity.MLAgents.Inference; using Unity.MLAgents.Sensors; using Unity.MLAgents.Policies; namespace Unity.MLAgents.Tests { public class Test3DSensorComponent : SensorComponent { public ISensor Sensor; public override ISensor[] CreateSensors() { return new ISensor[] { Sensor }; } } public class Test3DSensor : ISensor, IBuiltInSensor { int m_Width; int m_Height; int m_Channels; string m_Name; // Dummy value for the IBuiltInSensor interface public const int k_BuiltInSensorType = -42; public Test3DSensor(string name, int width, int height, int channels) { m_Width = width; m_Height = height; m_Channels = channels; m_Name = name; } public ObservationSpec GetObservationSpec() { return ObservationSpec.Visual(m_Height, m_Width, m_Channels); } public int Write(ObservationWriter writer) { for (int i = 0; i < m_Width * m_Height * m_Channels; i++) { writer[i] = 0.0f; } return m_Width * m_Height * m_Channels; } public byte[] GetCompressedObservation() { return new byte[0]; } public void Update() { } public void Reset() { } public CompressionSpec GetCompressionSpec() { return CompressionSpec.Default(); } public string GetName() { return m_Name; } public BuiltInSensorType GetBuiltInSensorType() { return (BuiltInSensorType)k_BuiltInSensorType; } } [TestFixture] public class ParameterLoaderTest { const string k_discrete_ONNX_v2 = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/discrete_rank2_vector_v2_0.onnx"; // ONNX model with continuous/discrete action output (support hybrid action) const string k_continuousONNXPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/continuous2vis8vec2action_v1_0.onnx"; const string k_discreteONNXPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/discrete1vis0vec_2_3action_recurr_v1_0.onnx"; const string k_hybridONNXPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/hybrid0vis53vec_3c_2daction_v1_0.onnx"; // NN model with single action output (deprecated, does not support hybrid action). // Same BrainParameters settings as the corresponding ONNX model. const string k_continuousNNPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/continuous2vis8vec2action_deprecated_v1_0.nn"; const string k_discreteNNPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/discrete1vis0vec_2_3action_recurr_deprecated_v1_0.nn"; NNModel rank2ONNXModel; NNModel continuousONNXModel; NNModel discreteONNXModel; NNModel hybridONNXModel; NNModel continuousNNModel; NNModel discreteNNModel; Test3DSensorComponent sensor_21_20_3; Test3DSensorComponent sensor_20_22_3; BufferSensor sensor_23_20; VectorSensor sensor_8; VectorSensor sensor_10; BrainParameters GetContinuous2vis8vec2actionBrainParameters() { var validBrainParameters = new BrainParameters(); validBrainParameters.VectorObservationSize = 8; validBrainParameters.NumStackedVectorObservations = 1; validBrainParameters.ActionSpec = ActionSpec.MakeContinuous(2); return validBrainParameters; } BrainParameters GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters() { var validBrainParameters = new BrainParameters(); validBrainParameters.VectorObservationSize = 0; validBrainParameters.NumStackedVectorObservations = 1; validBrainParameters.ActionSpec = ActionSpec.MakeDiscrete(2, 3); return validBrainParameters; } BrainParameters GetHybridBrainParameters() { var validBrainParameters = new BrainParameters(); validBrainParameters.VectorObservationSize = 53; validBrainParameters.NumStackedVectorObservations = 1; validBrainParameters.ActionSpec = new ActionSpec(3, new[] { 2 }); return validBrainParameters; } BrainParameters GetRank2BrainParameters() { var validBrainParameters = new BrainParameters(); validBrainParameters.VectorObservationSize = 4; validBrainParameters.NumStackedVectorObservations = 2; validBrainParameters.ActionSpec = ActionSpec.MakeDiscrete(3, 3, 3); return validBrainParameters; } [SetUp] public void SetUp() { continuousONNXModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_continuousONNXPath, typeof(NNModel)); discreteONNXModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_discreteONNXPath, typeof(NNModel)); hybridONNXModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_hybridONNXPath, typeof(NNModel)); continuousNNModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_continuousNNPath, typeof(NNModel)); discreteNNModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_discreteNNPath, typeof(NNModel)); rank2ONNXModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_discrete_ONNX_v2, typeof(NNModel)); var go = new GameObject("SensorA"); sensor_21_20_3 = go.AddComponent(); sensor_21_20_3.Sensor = new Test3DSensor("SensorA", 21, 20, 3); sensor_20_22_3 = go.AddComponent(); sensor_20_22_3.Sensor = new Test3DSensor("SensorA", 20, 22, 3); sensor_23_20 = new BufferSensor(20, 23, "BufferSensor"); sensor_8 = new VectorSensor(8, "VectorSensor8"); sensor_10 = new VectorSensor(10, "VectorSensor10"); } [Test] public void TestModelExist() { Assert.IsNotNull(continuousONNXModel); Assert.IsNotNull(discreteONNXModel); Assert.IsNotNull(hybridONNXModel); Assert.IsNotNull(continuousNNModel); Assert.IsNotNull(discreteNNModel); Assert.IsNotNull(rank2ONNXModel); } [TestCase(true)] [TestCase(false)] public void TestGetInputTensorsContinuous(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(continuousNNModel) : ModelLoader.Load(continuousONNXModel); var inputNames = model.GetInputNames(); // Model should contain 3 inputs : vector, visual 1 and visual 2 Assert.AreEqual(3, inputNames.Count()); Assert.Contains(TensorNames.VectorObservationPlaceholder, inputNames); Assert.Contains(TensorNames.VisualObservationPlaceholderPrefix + "0", inputNames); Assert.Contains(TensorNames.VisualObservationPlaceholderPrefix + "1", inputNames); Assert.AreEqual(2, model.GetNumVisualInputs()); // Test if the model is null model = null; Assert.AreEqual(0, model.GetInputTensors().Count); Assert.AreEqual(0, model.GetNumVisualInputs()); } [TestCase(true)] [TestCase(false)] public void TestGetInputTensorsDiscrete(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(discreteNNModel) : ModelLoader.Load(discreteONNXModel); var inputNames = model.GetInputNames(); // Model should contain 2 inputs : recurrent and visual 1 Assert.Contains(TensorNames.VisualObservationPlaceholderPrefix + "0", inputNames); // TODO :There are some memory tensors as well } [Test] public void TestGetInputTensorsHybrid() { var model = ModelLoader.Load(hybridONNXModel); var inputNames = model.GetInputNames(); Assert.Contains(TensorNames.VectorObservationPlaceholder, inputNames); } [TestCase(true)] [TestCase(false)] public void TestGetOutputTensorsContinuous(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(continuousNNModel) : ModelLoader.Load(continuousONNXModel); var outputNames = model.GetOutputNames(); var actionOutputName = useDeprecatedNNModel ? TensorNames.ActionOutputDeprecated : TensorNames.ContinuousActionOutput; Assert.Contains(actionOutputName, outputNames); Assert.AreEqual(1, outputNames.Count()); model = null; Assert.AreEqual(0, model.GetOutputNames().Count()); } [TestCase(true)] [TestCase(false)] public void TestGetOutputTensorsDiscrete(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(discreteNNModel) : ModelLoader.Load(discreteONNXModel); var outputNames = model.GetOutputNames(); var actionOutputName = useDeprecatedNNModel ? TensorNames.ActionOutputDeprecated : TensorNames.DiscreteActionOutput; Assert.Contains(actionOutputName, outputNames); // TODO : There are some memory tensors as well } [Test] public void TestGetOutputTensorsHybrid() { var model = ModelLoader.Load(hybridONNXModel); var outputNames = model.GetOutputNames(); Assert.AreEqual(2, outputNames.Count()); Assert.Contains(TensorNames.ContinuousActionOutput, outputNames); Assert.Contains(TensorNames.DiscreteActionOutput, outputNames); model = null; Assert.AreEqual(0, model.GetOutputNames().Count()); } [Test] public void TestCheckModelRank2() { var model = ModelLoader.Load(rank2ONNXModel); var validBrainParameters = GetRank2BrainParameters(); var errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { sensor_23_20, sensor_10, sensor_8 }, new ActuatorComponent[0] ); Assert.AreEqual(0, errors.Count()); // There should not be any errors errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { sensor_23_20, sensor_10 }, new ActuatorComponent[0] ); Assert.AreNotEqual(0, errors.Count()); // Wrong number of sensors errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { new BufferSensor(20, 40, "BufferSensor"), sensor_10, sensor_8 }, new ActuatorComponent[0] ); Assert.AreNotEqual(0, errors.Count()); // Wrong buffer sensor size errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { sensor_23_20, sensor_10, sensor_10 }, new ActuatorComponent[0] ); Assert.AreNotEqual(0, errors.Count()); // Wrong vector sensor size } [TestCase(true)] [TestCase(false)] public void TestCheckModelValidContinuous(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(continuousNNModel) : ModelLoader.Load(continuousONNXModel); var validBrainParameters = GetContinuous2vis8vec2actionBrainParameters(); var errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { new VectorSensor(8), sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.AreEqual(0, errors.Count()); // There should not be any errors } [TestCase(true)] [TestCase(false)] public void TestCheckModelValidDiscrete(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(discreteNNModel) : ModelLoader.Load(discreteONNXModel); var validBrainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters(); var errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.AreEqual(0, errors.Count()); // There should not be any errors } [Test] public void TestCheckModelValidHybrid() { var model = ModelLoader.Load(hybridONNXModel); var validBrainParameters = GetHybridBrainParameters(); var errors = BarracudaModelParamLoader.CheckModel( model, validBrainParameters, new ISensor[] { new VectorSensor(validBrainParameters.VectorObservationSize) }, new ActuatorComponent[0] ); Assert.AreEqual(0, errors.Count()); // There should not be any errors } [TestCase(true)] [TestCase(false)] public void TestCheckModelThrowsVectorObservationContinuous(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(continuousNNModel) : ModelLoader.Load(continuousONNXModel); var brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.VectorObservationSize = 9; // Invalid observation var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.NumStackedVectorObservations = 2;// Invalid stacking errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [TestCase(true)] [TestCase(false)] public void TestCheckModelThrowsVectorObservationDiscrete(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(discreteNNModel) : ModelLoader.Load(discreteONNXModel); var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters(); brainParameters.VectorObservationSize = 1; // Invalid observation var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [Test] public void TestCheckModelThrowsVectorObservationHybrid() { var model = ModelLoader.Load(hybridONNXModel); var brainParameters = GetHybridBrainParameters(); brainParameters.VectorObservationSize = 9; // Invalid observation var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.NumStackedVectorObservations = 2;// Invalid stacking errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [TestCase(true)] [TestCase(false)] public void TestCheckModelThrowsActionContinuous(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(continuousNNModel) : ModelLoader.Load(continuousONNXModel); var brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.ActionSpec = ActionSpec.MakeContinuous(3); // Invalid action var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.ActionSpec = ActionSpec.MakeDiscrete(3); // Invalid SpaceType errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [TestCase(true)] [TestCase(false)] public void TestCheckModelThrowsActionDiscrete(bool useDeprecatedNNModel) { var model = useDeprecatedNNModel ? ModelLoader.Load(discreteNNModel) : ModelLoader.Load(discreteONNXModel); var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters(); brainParameters.ActionSpec = ActionSpec.MakeDiscrete(3, 3); // Invalid action var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.ActionSpec = ActionSpec.MakeContinuous(2); // Invalid SpaceType errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [Test] public void TestCheckModelThrowsActionHybrid() { var model = ModelLoader.Load(hybridONNXModel); var brainParameters = GetHybridBrainParameters(); brainParameters.ActionSpec = new ActionSpec(3, new[] { 3 }); // Invalid discrete action size var errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); brainParameters = GetContinuous2vis8vec2actionBrainParameters(); brainParameters.ActionSpec = ActionSpec.MakeDiscrete(2); // Missing continuous action errors = BarracudaModelParamLoader.CheckModel( model, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } [Test] public void TestCheckModelThrowsNoModel() { var brainParameters = GetContinuous2vis8vec2actionBrainParameters(); var errors = BarracudaModelParamLoader.CheckModel( null, brainParameters, new ISensor[] { sensor_21_20_3.CreateSensors()[0], sensor_20_22_3.CreateSensors()[0] }, new ActuatorComponent[0] ); Assert.Greater(errors.Count(), 0); } } }