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101 行
4.5 KiB
101 行
4.5 KiB
using NUnit.Framework;
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using UnityEngine;
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using UnityEditor;
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using Barracuda;
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using MLAgents.Inference;
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using MLAgents.Sensors;
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using System.Linq;
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using MLAgents.Policies;
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namespace MLAgents.Tests
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{
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[TestFixture]
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public class ModelRunnerTest
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{
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const string k_continuous2vis8vec2actionPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/continuous2vis8vec2action.nn";
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const string k_discrete1vis0vec_2_3action_recurrModelPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/discrete1vis0vec_2_3action_recurr.nn";
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NNModel continuous2vis8vec2actionModel;
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NNModel discrete1vis0vec_2_3action_recurrModel;
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Test3DSensorComponent sensor_21_20_3;
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Test3DSensorComponent sensor_20_22_3;
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private 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.VectorActionSize = new int[] { 2 };
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validBrainParameters.NumStackedVectorObservations = 1;
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validBrainParameters.VectorActionSpaceType = SpaceType.Continuous;
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return validBrainParameters;
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}
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private 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.VectorActionSize = new int[] { 2, 3 };
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validBrainParameters.NumStackedVectorObservations = 1;
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validBrainParameters.VectorActionSpaceType = SpaceType.Discrete;
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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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continuous2vis8vec2actionModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_continuous2vis8vec2actionPath, typeof(NNModel));
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discrete1vis0vec_2_3action_recurrModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_discrete1vis0vec_2_3action_recurrModelPath, 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("SensorB", 20, 22, 3);
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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(continuous2vis8vec2actionModel);
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Assert.IsNotNull(discrete1vis0vec_2_3action_recurrModel);
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}
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[Test]
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public void TestCreation()
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{
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var modelRunner = new ModelRunner(continuous2vis8vec2actionModel, GetContinuous2vis8vec2actionBrainParameters());
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modelRunner.Dispose();
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modelRunner = new ModelRunner(discrete1vis0vec_2_3action_recurrModel, GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters());
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modelRunner.Dispose();
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}
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[Test]
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public void TestHasModel()
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{
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var modelRunner = new ModelRunner(continuous2vis8vec2actionModel, GetContinuous2vis8vec2actionBrainParameters(), InferenceDevice.CPU);
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Assert.True(modelRunner.HasModel(continuous2vis8vec2actionModel, InferenceDevice.CPU));
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Assert.False(modelRunner.HasModel(continuous2vis8vec2actionModel, InferenceDevice.GPU));
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Assert.False(modelRunner.HasModel(discrete1vis0vec_2_3action_recurrModel, InferenceDevice.CPU));
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modelRunner.Dispose();
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}
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[Test]
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public void TestRunModel()
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{
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var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters();
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var modelRunner = new ModelRunner(discrete1vis0vec_2_3action_recurrModel, brainParameters);
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var info1 = new AgentInfo();
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info1.episodeId = 1;
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modelRunner.PutObservations(info1, new ISensor[] { sensor_21_20_3.CreateSensor() }.ToList());
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var info2 = new AgentInfo();
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info2.episodeId = 2;
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modelRunner.PutObservations(info2, new ISensor[] { sensor_21_20_3.CreateSensor() }.ToList());
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modelRunner.DecideBatch();
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Assert.IsNotNull(modelRunner.GetAction(1));
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Assert.IsNotNull(modelRunner.GetAction(2));
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Assert.IsNull(modelRunner.GetAction(3));
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Assert.AreEqual(brainParameters.VectorActionSize.Count(), modelRunner.GetAction(1).Count());
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modelRunner.Dispose();
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}
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}
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}
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