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