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 System.Collections.Generic;
using System.IO;
using System.Reflection;
using NUnit.Framework;
using UnityEngine;
using Unity.MLAgents.Integrations.Match3;
using Unity.MLAgents.Sensors;
namespace Unity.MLAgents.Tests.Integrations.Match3
{
public class Match3SensorTests
{
// Whether the expected PNG data should be written to a file.
// Only set this to true if the compressed observation format changes.
private bool WritePNGDataToFile = false;
private const string k_CellObservationPng = "match3obs_";
private const string k_SpecialObservationPng = "match3obs_special_";
private const string k_Suffix2x2 = "2x2_";
[TestCase(true, TestName = "Full Board")]
[TestCase(false, TestName = "Small Board")]
public void TestVectorObservations(bool fullBoard)
{
var boardString =
@"000
000
010";
var gameObj = new GameObject("board");
var board = gameObj.AddComponent<StringBoard>();
board.SetBoard(boardString);
if (!fullBoard)
{
board.CurrentRows = 2;
board.CurrentColumns = 2;
}
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
sensorComponent.ObservationType = Match3ObservationType.Vector;
var sensor = sensorComponent.CreateSensors()[0];
var expectedShape = new InplaceArray<int>(3 * 3 * 2);
Assert.AreEqual(expectedShape, sensor.GetObservationSpec().Shape);
float[] expectedObs;
if (fullBoard)
{
expectedObs = new float[]
{
1, 0, /* 0 */ 0, 1, /* 1 */ 1, 0, /* 0 */
1, 0, /* 0 */ 1, 0, /* 0 */ 1, 0, /* 0 */
1, 0, /* 0 */ 1, 0, /* 0 */ 1, 0, /* 0 */
};
}
else
{
expectedObs = new float[]
{
1, 0, /* 0 */ 0, 1, /* 1 */ 0, 0, /* empty */
1, 0, /* 0 */ 1, 0, /* 0 */ 0, 0, /* empty */
0, 0, /* empty */ 0, 0, /* empty */ 0, 0, /* empty */
};
}
SensorTestHelper.CompareObservation(sensor, expectedObs);
}
[Test]
public void TestVectorObservationsSpecial()
{
var boardString =
@"000
000
010";
var specialString =
@"010
200
000";
var gameObj = new GameObject("board");
var board = gameObj.AddComponent<StringBoard>();
board.SetBoard(boardString);
board.SetSpecial(specialString);
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
sensorComponent.ObservationType = Match3ObservationType.Vector;
var sensors = sensorComponent.CreateSensors();
var cellSensor = sensors[0];
var specialSensor = sensors[1];
{
var expectedShape = new InplaceArray<int>(3 * 3 * 2);
Assert.AreEqual(expectedShape, cellSensor.GetObservationSpec().Shape);
var expectedObs = new float[]
{
1, 0, /* (0) */ 0, 1, /* (1) */ 1, 0, /* (0) */
1, 0, /* (0) */ 1, 0, /* (0) */ 1, 0, /* (0) */
1, 0, /* (0) */ 1, 0, /* (0) */ 1, 0, /* (0) */
};
SensorTestHelper.CompareObservation(cellSensor, expectedObs);
}
{
var expectedShape = new InplaceArray<int>(3 * 3 * 3);
Assert.AreEqual(expectedShape, specialSensor.GetObservationSpec().Shape);
var expectedObs = new float[]
{
1, 0, 0, /* (0) */ 1, 0, 0, /* (1) */ 1, 0, 0, /* (0) */
0, 0, 1, /* (2) */ 1, 0, 0, /* (0) */ 1, 0, 0, /* (0) */
1, 0, 0, /* (0) */ 0, 1, 0, /* (1) */ 1, 0, 0, /* (0) */
};
SensorTestHelper.CompareObservation(specialSensor, expectedObs);
}
}
[TestCase(true, TestName = "Full Board")]
[TestCase(false, TestName = "Small Board")]
public void TestVisualObservations(bool fullBoard)
{
var boardString =
@"000
000
010";
var gameObj = new GameObject("board");
var board = gameObj.AddComponent<StringBoard>();
board.SetBoard(boardString);
if (!fullBoard)
{
board.CurrentRows = 2;
board.CurrentColumns = 2;
}
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
sensorComponent.ObservationType = Match3ObservationType.UncompressedVisual;
var sensor = sensorComponent.CreateSensors()[0];
var expectedShape = new InplaceArray<int>(3, 3, 2);
Assert.AreEqual(expectedShape, sensor.GetObservationSpec().Shape);
Assert.AreEqual(SensorCompressionType.None, sensor.GetCompressionSpec().SensorCompressionType);
float[] expectedObs;
float[,,] expectedObs3D;
if (fullBoard)
{
expectedObs = new float[]
{
1, 0, /**/ 0, 1, /**/ 1, 0,
1, 0, /**/ 1, 0, /**/ 1, 0,
1, 0, /**/ 1, 0, /**/ 1, 0,
};
expectedObs3D = new float[,,]
{
{{1, 0}, {0, 1}, {1, 0}},
{{1, 0}, {1, 0}, {1, 0}},
{{1, 0}, {1, 0}, {1, 0}},
};
}
else
{
expectedObs = new float[]
{
1, 0, /* 0 */ 0, 1, /* 1 */ 0, 0, /* empty */
1, 0, /* 0 */ 1, 0, /* 0 */ 0, 0, /* empty */
0, 0, /* empty */ 0, 0, /* empty */ 0, 0, /* empty */
};
expectedObs3D = new float[,,]
{
{{1, 0}, {0, 1}, {0, 0}},
{{1, 0}, {1, 0}, {0, 0}},
{{0, 0}, {0, 0}, {0, 0}},
};
}
SensorTestHelper.CompareObservation(sensor, expectedObs);
SensorTestHelper.CompareObservation(sensor, expectedObs3D);
}
[Test]
public void TestVisualObservationsSpecial()
{
var boardString =
@"000
000
010";
var specialString =
@"010
200
000";
var gameObj = new GameObject("board");
var board = gameObj.AddComponent<StringBoard>();
board.SetBoard(boardString);
board.SetSpecial(specialString);
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
sensorComponent.ObservationType = Match3ObservationType.UncompressedVisual;
var sensors = sensorComponent.CreateSensors();
var cellSensor = sensors[0];
var specialSensor = sensors[1];
{
var expectedShape = new InplaceArray<int>(3, 3, 2);
Assert.AreEqual(expectedShape, cellSensor.GetObservationSpec().Shape);
Assert.AreEqual(SensorCompressionType.None, cellSensor.GetCompressionSpec().SensorCompressionType);
var expectedObs = new float[]
{
1, 0, /* (0) */ 0, 1, /* (1) */ 1, 0, /* (0) */
1, 0, /* (0) */ 1, 0, /* (0) */ 1, 0, /* (0) */
1, 0, /* (0) */ 1, 0, /* (0) */ 1, 0, /* (0) */
};
SensorTestHelper.CompareObservation(cellSensor, expectedObs);
var expectedObs3D = new float[,,]
{
{{1, 0}, {0, 1}, {1, 0}},
{{1, 0}, {1, 0}, {1, 0}},
{{1, 0}, {1, 0}, {1, 0}},
};
SensorTestHelper.CompareObservation(cellSensor, expectedObs3D);
}
{
var expectedShape = new InplaceArray<int>(3, 3, 3);
Assert.AreEqual(expectedShape, specialSensor.GetObservationSpec().Shape);
Assert.AreEqual(SensorCompressionType.None, specialSensor.GetCompressionSpec().SensorCompressionType);
var expectedObs = new float[]
{
1, 0, 0, /* (0) */ 1, 0, 0, /* (1) */ 1, 0, 0, /* (0) */
0, 0, 1, /* (2) */ 1, 0, 0, /* (0) */ 1, 0, 0, /* (0) */
1, 0, 0, /* (0) */ 0, 1, 0, /* (1) */ 1, 0, 0, /* (0) */
};
SensorTestHelper.CompareObservation(specialSensor, expectedObs);
var expectedObs3D = new float[,,]
{
{{1, 0, 0}, {1, 0, 0}, {1, 0, 0}},
{{0, 0, 1}, {1, 0, 0}, {1, 0, 0}},
{{1, 0, 0}, {0, 1, 0}, {1, 0, 0}},
};
SensorTestHelper.CompareObservation(specialSensor, expectedObs3D);
}
// Test that Dispose() cleans up the component and its sensors
sensorComponent.Dispose();
var flags = BindingFlags.Instance | BindingFlags.NonPublic;
var componentSensors = (ISensor[])typeof(Match3SensorComponent).GetField("m_Sensors", flags).GetValue(sensorComponent);
Assert.IsNull(componentSensors);
var cellTexture = (Texture2D)typeof(Match3Sensor).GetField("m_ObservationTexture", flags).GetValue(cellSensor);
Assert.IsNull(cellTexture);
var specialTexture = (Texture2D)typeof(Match3Sensor).GetField("m_ObservationTexture", flags).GetValue(cellSensor);
Assert.IsNull(specialTexture);
}
[TestCase(true, false, TestName = "Full Board, No Special")]
[TestCase(false, false, TestName = "Small Board, No Special")]
[TestCase(true, true, TestName = "Full Board, Special")]
[TestCase(false, true, TestName = "Small Board, Special")]
public void TestCompressedVisualObservationsSpecial(bool fullBoard, bool useSpecial)
{
var boardString =
@"003
000
010";
var specialString =
@"014
200
000";
var gameObj = new GameObject("board");
var board = gameObj.AddComponent<StringBoard>();
board.SetBoard(boardString);
var paths = new List<string> { k_CellObservationPng };
if (useSpecial)
{
board.SetSpecial(specialString);
paths.Add(k_SpecialObservationPng);
}
if (!fullBoard)
{
// Shrink the board, and change the paths we're using for the ground truth PNGs
board.CurrentRows = 2;
board.CurrentColumns = 2;
for (var i = 0; i < paths.Count; i++)
{
paths[i] = paths[i] + k_Suffix2x2;
}
}
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
sensorComponent.ObservationType = Match3ObservationType.CompressedVisual;
var sensors = sensorComponent.CreateSensors();
var expectedNumChannels = new[] { 4, 5 };
for (var i = 0; i < paths.Count; i++)
{
var sensor = sensors[i];
var expectedShape = new InplaceArray<int>(3, 3, expectedNumChannels[i]);
Assert.AreEqual(expectedShape, sensor.GetObservationSpec().Shape);
Assert.AreEqual(SensorCompressionType.PNG, sensor.GetCompressionSpec().SensorCompressionType);
var pngData = sensor.GetCompressedObservation();
if (WritePNGDataToFile)
{
// Enable this if the format of the observation changes
SavePNGs(pngData, paths[i]);
}
var expectedPng = LoadPNGs(paths[i], 2);
Assert.AreEqual(expectedPng, pngData);
}
}
/// <summary>
/// Helper method for un-concatenating PNG observations.
/// </summary>
/// <param name="concatenated"></param>
/// <returns></returns>
List<byte[]> SplitPNGs(byte[] concatenated)
{
var pngsOut = new List<byte[]>();
var pngHeader = new byte[] { 137, 80, 78, 71, 13, 10, 26, 10 };
var current = new List<byte>();
for (var i = 0; i < concatenated.Length; i++)
{
current.Add(concatenated[i]);
// Check if the header starts at the next position
// If so, we'll start a new output array.
var headerIsNext = false;
if (i + 1 < concatenated.Length - pngHeader.Length)
{
for (var j = 0; j < pngHeader.Length; j++)
{
if (concatenated[i + 1 + j] != pngHeader[j])
{
break;
}
if (j == pngHeader.Length - 1)
{
headerIsNext = true;
}
}
}
if (headerIsNext)
{
pngsOut.Add(current.ToArray());
current = new List<byte>();
}
}
pngsOut.Add(current.ToArray());
return pngsOut;
}
void SavePNGs(byte[] concatenatedPngData, string pathPrefix)
{
var splitPngs = SplitPNGs(concatenatedPngData);
for (var i = 0; i < splitPngs.Count; i++)
{
var pngData = splitPngs[i];
var path = $"Packages/com.unity.ml-agents/Tests/Editor/Integrations/Match3/{pathPrefix}{i}.png";
using (var sw = File.Create(path))
{
foreach (var b in pngData)
{
sw.WriteByte(b);
}
}
}
}
byte[] LoadPNGs(string pathPrefix, int numExpected)
{
var bytesOut = new List<byte>();
for (var i = 0; i < numExpected; i++)
{
var path = $"Packages/com.unity.ml-agents/Tests/Editor/Integrations/Match3/{pathPrefix}{i}.png";
var res = File.ReadAllBytes(path);
bytesOut.AddRange(res);
}
return bytesOut.ToArray();
}
[Test]
public void TestNoBoardReturnsEmptySensors()
{
var gameObj = new GameObject("board");
var sensorComponent = gameObj.AddComponent<Match3SensorComponent>();
var sensors = sensorComponent.CreateSensors();
Assert.AreEqual(0, sensors.Length);
}
}
}