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276 行
10 KiB
276 行
10 KiB
using System;
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using System.Text.RegularExpressions;
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using Google.Protobuf;
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using NUnit.Framework;
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using Unity.MLAgents.Actuators;
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using Unity.MLAgents.Demonstrations;
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using Unity.MLAgents.Policies;
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using Unity.MLAgents.Sensors;
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using Unity.MLAgents.Analytics;
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using Unity.MLAgents.CommunicatorObjects;
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using UnityEngine;
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using UnityEngine.TestTools;
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namespace Unity.MLAgents.Tests
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{
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[TestFixture]
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public class GrpcExtensionsTests
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{
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[SetUp]
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public void SetUp()
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{
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
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}
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[Test]
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public void TestDefaultBrainParametersToProto()
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{
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// Should be able to convert a default instance to proto.
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var brain = new BrainParameters();
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brain.ToProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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brain.ToProto("foo", false);
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}
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[Test]
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public void TestDefaultActionSpecToProto()
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{
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// Should be able to convert a default instance to proto.
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var actionSpec = new ActionSpec();
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actionSpec.ToBrainParametersProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
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// Continuous
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actionSpec = ActionSpec.MakeContinuous(3);
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actionSpec.ToBrainParametersProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
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// Discrete
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actionSpec = ActionSpec.MakeDiscrete(1, 2, 3);
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actionSpec.ToBrainParametersProto("foo", false);
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false);
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}
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[Test]
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public void ToBrainParameters()
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{
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// Should be able to convert a default instance to proto.
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var actionSpec = new ActionSpec();
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
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// Continuous
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actionSpec = ActionSpec.MakeContinuous(3);
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities();
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// Discrete
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actionSpec = ActionSpec.MakeDiscrete(1, 2, 3);
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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HybridActions = false
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};
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actionSpec.ToBrainParametersProto("foo", false).ToBrainParameters();
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}
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[Test]
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public void TestDefaultAgentInfoToProto()
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{
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// Should be able to convert a default instance to proto.
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var agentInfo = new AgentInfo();
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var pairProto = agentInfo.ToInfoActionPairProto();
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pairProto.AgentInfo.Observations.Add(new ObservationProto
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{
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CompressedData = ByteString.Empty,
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CompressionType = CompressionTypeProto.None,
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FloatData = new ObservationProto.Types.FloatData(),
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ObservationType = ObservationTypeProto.Default,
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Name = "Sensor"
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});
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pairProto.AgentInfo.Observations[0].Shape.Add(0);
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pairProto.GetObservationSummaries();
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agentInfo.ToAgentInfoProto();
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agentInfo.groupId = 1;
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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MultiAgentGroups = false
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};
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agentInfo.ToAgentInfoProto();
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LogAssert.Expect(LogType.Warning, new Regex(".+"));
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Academy.Instance.TrainerCapabilities = new UnityRLCapabilities
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{
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BaseRLCapabilities = true,
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MultiAgentGroups = true
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};
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agentInfo.ToAgentInfoProto();
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}
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[Test]
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public void TestDefaultDemonstrationMetaDataToProto()
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{
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// Should be able to convert a default instance to proto.
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var demoMetaData = new DemonstrationMetaData();
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demoMetaData.ToProto();
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}
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class DummySensor : ISensor
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{
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public ObservationSpec ObservationSpec;
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public SensorCompressionType CompressionType;
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public ObservationSpec GetObservationSpec()
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{
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return ObservationSpec;
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}
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public int Write(ObservationWriter writer)
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{
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return 0;
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}
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public byte[] GetCompressedObservation()
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{
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return new byte[] { 13, 37 };
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}
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public void Update() { }
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public void Reset() { }
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public CompressionSpec GetCompressionSpec()
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{
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return new CompressionSpec(CompressionType);
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}
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public string GetName()
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{
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return "Dummy";
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}
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}
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[Test]
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public void TestGetObservationProtoCapabilities()
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{
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// Shape, compression type, concatenatedPngObservations, expect throw
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var variants = new[]
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{
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// Vector observations
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(new[] {3}, SensorCompressionType.None, false, false),
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// Uncompressed floats
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(new[] {4, 4, 3}, SensorCompressionType.None, false, false),
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// Compressed floats, 3 channels
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(new[] {4, 4, 3}, SensorCompressionType.PNG, false, true),
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// Compressed floats, >3 channels
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(new[] {4, 4, 4}, SensorCompressionType.PNG, false, false), // Unsupported - results in uncompressed
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(new[] {4, 4, 4}, SensorCompressionType.PNG, true, true), // Supported compressed
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};
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foreach (var (shape, compressionType, supportsMultiPngObs, expectCompressed) in variants)
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{
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var inplaceShape = InplaceArray<int>.FromList(shape);
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var dummySensor = new DummySensor();
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var obsWriter = new ObservationWriter();
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if (shape.Length == 1)
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{
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dummySensor.ObservationSpec = ObservationSpec.Vector(shape[0]);
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}
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else if (shape.Length == 3)
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{
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dummySensor.ObservationSpec = ObservationSpec.Visual(shape[0], shape[1], shape[2]);
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}
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else
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{
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throw new ArgumentOutOfRangeException();
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}
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dummySensor.CompressionType = compressionType;
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obsWriter.SetTarget(new float[128], inplaceShape, 0);
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var caps = new UnityRLCapabilities
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{
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ConcatenatedPngObservations = supportsMultiPngObs
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};
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Academy.Instance.TrainerCapabilities = caps;
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var obsProto = dummySensor.GetObservationProto(obsWriter);
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if (expectCompressed)
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{
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Assert.Greater(obsProto.CompressedData.Length, 0);
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Assert.AreEqual(obsProto.FloatData, null);
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}
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else
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{
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Assert.Greater(obsProto.FloatData.Data.Count, 0);
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Assert.AreEqual(obsProto.CompressedData.Length, 0);
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}
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}
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}
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[Test]
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public void TestDefaultTrainingEvents()
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{
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var trainingEnvInit = new TrainingEnvironmentInitialized
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{
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PythonVersion = "test",
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};
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var trainingEnvInitEvent = trainingEnvInit.ToTrainingEnvironmentInitializedEvent();
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Assert.AreEqual(trainingEnvInit.PythonVersion, trainingEnvInitEvent.TrainerPythonVersion);
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var trainingBehavInit = new TrainingBehaviorInitialized
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{
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BehaviorName = "testBehavior",
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ExtrinsicRewardEnabled = true,
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CuriosityRewardEnabled = true,
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RecurrentEnabled = true,
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SelfPlayEnabled = true,
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};
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var trainingBehavInitEvent = trainingBehavInit.ToTrainingBehaviorInitializedEvent();
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Assert.AreEqual(trainingBehavInit.BehaviorName, trainingBehavInitEvent.BehaviorName);
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Assert.AreEqual(RewardSignals.Extrinsic | RewardSignals.Curiosity, trainingBehavInitEvent.RewardSignalFlags);
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Assert.AreEqual(TrainingFeatures.Recurrent | TrainingFeatures.SelfPlay, trainingBehavInitEvent.TrainingFeatureFlags);
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}
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}
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}
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