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105 行
2.7 KiB
105 行
2.7 KiB
using NUnit.Framework;
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using MLAgents.Sensors;
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namespace MLAgents.Tests
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{
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public class Float2DSensor : ISensor
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{
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public int Width { get; }
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public int Height { get; }
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string m_Name;
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int[] m_Shape;
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public float[,] floatData;
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public Float2DSensor(int width, int height, string name)
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{
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Width = width;
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Height = height;
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m_Name = name;
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m_Shape = new[] { height, width, 1 };
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floatData = new float[Height, Width];
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}
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public Float2DSensor(float[,] floatData, string name)
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{
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this.floatData = floatData;
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Height = floatData.GetLength(0);
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Width = floatData.GetLength(1);
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m_Name = name;
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m_Shape = new[] { Height, Width, 1 };
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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 int[] GetObservationShape()
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{
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return m_Shape;
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}
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public byte[] GetCompressedObservation()
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{
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return null;
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}
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public int Write(ObservationWriter writer)
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{
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using (TimerStack.Instance.Scoped("Float2DSensor.Write"))
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{
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for (var h = 0; h < Height; h++)
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{
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for (var w = 0; w < Width; w++)
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{
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writer[h, w, 0] = floatData[h, w];
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}
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}
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var numWritten = Height * Width;
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return numWritten;
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}
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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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}
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public class FloatVisualSensorTests
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{
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[Test]
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public void TestFloat2DSensorWrite()
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{
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var sensor = new Float2DSensor(3, 4, "floatsensor");
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for (var h = 0; h < 4; h++)
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{
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for (var w = 0; w < 3; w++)
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{
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sensor.floatData[h, w] = 3 * h + w;
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}
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}
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var output = new float[12];
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var writer = new ObservationWriter();
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writer.SetTarget(output, sensor.GetObservationShape(), 0);
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sensor.Write(writer);
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for (var i = 0; i < 9; i++)
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{
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Assert.AreEqual(i, output[i]);
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}
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}
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[Test]
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public void TestFloat2DSensorExternalData()
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{
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var data = new float[4, 3];
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var sensor = new Float2DSensor(data, "floatsensor");
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Assert.AreEqual(sensor.Height, 4);
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Assert.AreEqual(sensor.Width, 3);
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}
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}
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}
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