Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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using NUnit.Framework;
using UnityEngine;
using UnityEditor;
using Unity.Barracuda;
using MLAgents.Inference;
using MLAgents.Sensors;
using System.Linq;
using MLAgents.Policies;
namespace MLAgents.Tests
{
public class Test3DSensorComponent : SensorComponent
{
public ISensor Sensor;
public override ISensor CreateSensor()
{
return Sensor;
}
public override int[] GetObservationShape()
{
return Sensor.GetObservationShape();
}
}
public class Test3DSensor : ISensor
{
int m_Width;
int m_Height;
int m_Channels;
string m_Name;
public Test3DSensor(string name, int width, int height, int channels)
{
m_Width = width;
m_Height = height;
m_Channels = channels;
m_Name = name;
}
public int[] GetObservationShape()
{
return new int[] {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 SensorCompressionType GetCompressionType()
{
return SensorCompressionType.None;
}
public string GetName()
{
return m_Name;
}
}
[TestFixture]
public class ParameterLoaderTest
{
const string k_continuous2vis8vec2actionPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/continuous2vis8vec2action.nn";
const string k_discrete1vis0vec_2_3action_recurrModelPath = "Packages/com.unity.ml-agents/Tests/Editor/TestModels/discrete1vis0vec_2_3action_recurr.nn";
NNModel continuous2vis8vec2actionModel;
NNModel discrete1vis0vec_2_3action_recurrModel;
Test3DSensorComponent sensor_21_20_3;
Test3DSensorComponent sensor_20_22_3;
private BrainParameters GetContinuous2vis8vec2actionBrainParameters()
{
var validBrainParameters = new BrainParameters();
validBrainParameters.VectorObservationSize = 8;
validBrainParameters.VectorActionSize = new int[] { 2 };
validBrainParameters.NumStackedVectorObservations = 1;
validBrainParameters.VectorActionSpaceType = SpaceType.Continuous;
return validBrainParameters;
}
private BrainParameters GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters()
{
var validBrainParameters = new BrainParameters();
validBrainParameters.VectorObservationSize = 0;
validBrainParameters.VectorActionSize = new int[] { 2, 3 };
validBrainParameters.NumStackedVectorObservations = 1;
validBrainParameters.VectorActionSpaceType = SpaceType.Discrete;
return validBrainParameters;
}
[SetUp]
public void SetUp()
{
continuous2vis8vec2actionModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_continuous2vis8vec2actionPath, typeof(NNModel));
discrete1vis0vec_2_3action_recurrModel = (NNModel)AssetDatabase.LoadAssetAtPath(k_discrete1vis0vec_2_3action_recurrModelPath, typeof(NNModel));
var go = new GameObject("SensorA");
sensor_21_20_3 = go.AddComponent<Test3DSensorComponent>();
sensor_21_20_3.Sensor = new Test3DSensor("SensorA", 21, 20, 3);
sensor_20_22_3 = go.AddComponent<Test3DSensorComponent>();
sensor_20_22_3.Sensor = new Test3DSensor("SensorA", 20, 22, 3);
}
[Test]
public void TestModelExist()
{
Assert.IsNotNull(continuous2vis8vec2actionModel);
Assert.IsNotNull(discrete1vis0vec_2_3action_recurrModel);
}
[Test]
public void TestGetInputTensors1()
{
var model = ModelLoader.Load(continuous2vis8vec2actionModel);
var inputTensors = BarracudaModelParamLoader.GetInputTensors(model);
var inputNames = inputTensors.Select(x => x.name).ToList();
// 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, BarracudaModelParamLoader.GetNumVisualInputs(model));
// Test if the model is null
Assert.AreEqual(0, BarracudaModelParamLoader.GetInputTensors(null).Count);
Assert.AreEqual(0, BarracudaModelParamLoader.GetNumVisualInputs(null));
}
[Test]
public void TestGetInputTensors2()
{
var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
var inputTensors = BarracudaModelParamLoader.GetInputTensors(model);
var inputNames = inputTensors.Select(x => x.name).ToList();
// 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 TestGetOutputTensors1()
{
var model = ModelLoader.Load(continuous2vis8vec2actionModel);
var outputNames = BarracudaModelParamLoader.GetOutputNames(model);
Assert.Contains(TensorNames.ActionOutput, outputNames);
Assert.AreEqual(1, outputNames.Count());
Assert.AreEqual(0, BarracudaModelParamLoader.GetOutputNames(null).Count());
}
[Test]
public void TestGetOutputTensors2()
{
var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
var outputNames = BarracudaModelParamLoader.GetOutputNames(model);
Assert.Contains(TensorNames.ActionOutput, outputNames);
// TODO : There are some memory tensors as well
}
[Test]
public void TestCheckModelValid1()
{
var model = ModelLoader.Load(continuous2vis8vec2actionModel);
var validBrainParameters = GetContinuous2vis8vec2actionBrainParameters();
var errors = BarracudaModelParamLoader.CheckModel(model, validBrainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.AreEqual(0, errors.Count()); // There should not be any errors
}
[Test]
public void TestCheckModelValid2()
{
var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
var validBrainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters();
var errors = BarracudaModelParamLoader.CheckModel(model, validBrainParameters, new SensorComponent[] { sensor_21_20_3 });
Assert.AreEqual(0, errors.Count()); // There should not be any errors
}
[Test]
public void TestCheckModelThrowsVectorObservation1()
{
var model = ModelLoader.Load(continuous2vis8vec2actionModel);
var brainParameters = GetContinuous2vis8vec2actionBrainParameters();
brainParameters.VectorObservationSize = 9; // Invalid observation
var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.Greater(errors.Count(), 0);
brainParameters = GetContinuous2vis8vec2actionBrainParameters();
brainParameters.NumStackedVectorObservations = 2;// Invalid stacking
errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.Greater(errors.Count(), 0);
}
[Test]
public void TestCheckModelThrowsVectorObservation2()
{
var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters();
brainParameters.VectorObservationSize = 1; // Invalid observation
var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3 });
Assert.Greater(errors.Count(), 0);
}
[Test]
public void TestCheckModelThrowsAction1()
{
var model = ModelLoader.Load(continuous2vis8vec2actionModel);
var brainParameters = GetContinuous2vis8vec2actionBrainParameters();
brainParameters.VectorActionSize = new int[] { 3 }; // Invalid action
var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.Greater(errors.Count(), 0);
brainParameters = GetContinuous2vis8vec2actionBrainParameters();
brainParameters.VectorActionSpaceType = SpaceType.Discrete;// Invalid SpaceType
errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.Greater(errors.Count(), 0);
}
[Test]
public void TestCheckModelThrowsAction2()
{
var model = ModelLoader.Load(discrete1vis0vec_2_3action_recurrModel);
var brainParameters = GetDiscrete1vis0vec_2_3action_recurrModelBrainParameters();
brainParameters.VectorActionSize = new int[] { 3, 3 }; // Invalid action
var errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3 });
Assert.Greater(errors.Count(), 0);
brainParameters = GetContinuous2vis8vec2actionBrainParameters();
brainParameters.VectorActionSpaceType = SpaceType.Continuous;// Invalid SpaceType
errors = BarracudaModelParamLoader.CheckModel(model, brainParameters, new SensorComponent[] { sensor_21_20_3 });
Assert.Greater(errors.Count(), 0);
}
[Test]
public void TestCheckModelThrowsNoModel()
{
var brainParameters = GetContinuous2vis8vec2actionBrainParameters();
var errors = BarracudaModelParamLoader.CheckModel(null, brainParameters, new SensorComponent[] { sensor_21_20_3, sensor_20_22_3 });
Assert.Greater(errors.Count(), 0);
}
}
}