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83 行
2.2 KiB
83 行
2.2 KiB
using System;
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using Barracuda;
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using MLAgents.InferenceBrain;
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using MLAgents.InferenceBrain.Utils;
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using NUnit.Framework;
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namespace MLAgents.Tests
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{
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public class TensorUtilsTest
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{
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[Test]
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public void RandomNormalTestTensorInt()
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{
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var rn = new RandomNormal(1982);
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var t = new TensorProxy
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{
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valueType = TensorProxy.TensorType.Integer
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};
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Assert.Throws<NotImplementedException>(
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() => TensorUtils.FillTensorWithRandomNormal(t, rn));
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}
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[Test]
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public void RandomNormalTestDataNull()
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{
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var rn = new RandomNormal(1982);
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var t = new TensorProxy
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{
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valueType = TensorProxy.TensorType.FloatingPoint
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};
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Assert.Throws<ArgumentNullException>(
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() => TensorUtils.FillTensorWithRandomNormal(t, rn));
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}
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[Test]
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public void RandomNormalTestTensor()
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{
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var rn = new RandomNormal(1982);
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var t = new TensorProxy
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{
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valueType = TensorProxy.TensorType.FloatingPoint,
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data = new Tensor(1, 3, 4, 2)
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};
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TensorUtils.FillTensorWithRandomNormal(t, rn);
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var reference = new[]
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{
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-0.4315872f,
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-1.11074f,
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0.3414804f,
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-1.130287f,
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0.1413168f,
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-0.5105762f,
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-0.3027347f,
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-0.2645015f,
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1.225356f,
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-0.02921959f,
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0.3716498f,
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-1.092338f,
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0.9561074f,
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-0.5018106f,
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1.167787f,
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-0.7763879f,
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-0.07491868f,
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0.5396146f,
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-0.1377991f,
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0.3331701f,
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0.06144788f,
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0.9520947f,
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1.088157f,
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-1.177194f,
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};
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for (var i = 0; i < t.data.length; i++)
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{
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Assert.AreEqual(t.data[i], reference[i], 0.0001);
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}
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}
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}
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}
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