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Moving domain randomization to C# (#4065)
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Original file line number | Diff line number | Diff line change |
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using System; | ||
using System.Collections.Generic; | ||
using Unity.MLAgents.Inference.Utils; | ||
using UnityEngine; | ||
using Random=System.Random; | ||
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namespace Unity.MLAgents | ||
{ | ||
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/// <summary> | ||
/// Takes a list of floats that encode a sampling distribution and returns the sampling function. | ||
/// </summary> | ||
internal static class SamplerFactory | ||
{ | ||
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public static Func<float> CreateUniformSampler(float min, float max, int seed) | ||
{ | ||
Random distr = new Random(seed); | ||
return () => min + (float)distr.NextDouble() * (max - min); | ||
} | ||
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public static Func<float> CreateGaussianSampler(float mean, float stddev, int seed) | ||
{ | ||
RandomNormal distr = new RandomNormal(seed, mean, stddev); | ||
return () => (float)distr.NextDouble(); | ||
} | ||
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public static Func<float> CreateMultiRangeUniformSampler(IList<float> intervals, int seed) | ||
{ | ||
//RNG | ||
Random distr = new Random(seed); | ||
// Will be used to normalize intervalFuncs | ||
float sumIntervalSizes = 0; | ||
//The number of intervals | ||
int numIntervals = (int)(intervals.Count/2); | ||
// List that will store interval lengths | ||
float[] intervalSizes = new float[numIntervals]; | ||
// List that will store uniform distributions | ||
IList<Func<float>> intervalFuncs = new Func<float>[numIntervals]; | ||
// Collect all intervals and store as uniform distrus | ||
// Collect all interval sizes | ||
for(int i = 0; i < numIntervals; i++) | ||
{ | ||
var min = intervals[2 * i]; | ||
var max = intervals[2 * i + 1]; | ||
var intervalSize = max - min; | ||
sumIntervalSizes += intervalSize; | ||
intervalSizes[i] = intervalSize; | ||
intervalFuncs[i] = () => min + (float)distr.NextDouble() * intervalSize; | ||
} | ||
// Normalize interval lengths | ||
for(int i = 0; i < numIntervals; i++) | ||
{ | ||
intervalSizes[i] = intervalSizes[i] / sumIntervalSizes; | ||
} | ||
// Build cmf for intervals | ||
for(int i = 1; i < numIntervals; i++) | ||
{ | ||
intervalSizes[i] += intervalSizes[i - 1]; | ||
} | ||
Multinomial intervalDistr = new Multinomial(seed + 1); | ||
float MultiRange() | ||
{ | ||
int sampledInterval = intervalDistr.Sample(intervalSizes); | ||
return intervalFuncs[sampledInterval].Invoke(); | ||
} | ||
return MultiRange; | ||
} | ||
} | ||
} |
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Original file line number | Diff line number | Diff line change |
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using System; | ||
using NUnit.Framework; | ||
using System.IO; | ||
using System.Collections.Generic; | ||
using UnityEngine; | ||
using Unity.MLAgents.SideChannels; | ||
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namespace Unity.MLAgents.Tests | ||
{ | ||
public class SamplerTests | ||
{ | ||
const int k_Seed = 1337; | ||
const double k_Epsilon = 0.0001; | ||
EnvironmentParametersChannel m_Channel; | ||
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public SamplerTests() | ||
{ | ||
m_Channel = SideChannelsManager.GetSideChannel<EnvironmentParametersChannel>(); | ||
// if running test on its own | ||
if (m_Channel == null) | ||
{ | ||
m_Channel = new EnvironmentParametersChannel(); | ||
SideChannelsManager.RegisterSideChannel(m_Channel); | ||
} | ||
} | ||
[Test] | ||
public void UniformSamplerTest() | ||
{ | ||
float min_value = 1.0f; | ||
float max_value = 2.0f; | ||
string parameter = "parameter1"; | ||
using (var outgoingMsg = new OutgoingMessage()) | ||
{ | ||
outgoingMsg.WriteString(parameter); | ||
// 1 indicates this meessage is a Sampler | ||
outgoingMsg.WriteInt32(1); | ||
outgoingMsg.WriteInt32(k_Seed); | ||
outgoingMsg.WriteInt32((int)SamplerType.Uniform); | ||
outgoingMsg.WriteFloat32(min_value); | ||
outgoingMsg.WriteFloat32(max_value); | ||
byte[] message = GetByteMessage(m_Channel, outgoingMsg); | ||
SideChannelsManager.ProcessSideChannelData(message); | ||
} | ||
Assert.AreEqual(1.208888f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
Assert.AreEqual(1.118017f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
} | ||
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[Test] | ||
public void GaussianSamplerTest() | ||
{ | ||
float mean = 3.0f; | ||
float stddev = 0.2f; | ||
string parameter = "parameter2"; | ||
using (var outgoingMsg = new OutgoingMessage()) | ||
{ | ||
outgoingMsg.WriteString(parameter); | ||
// 1 indicates this meessage is a Sampler | ||
outgoingMsg.WriteInt32(1); | ||
outgoingMsg.WriteInt32(k_Seed); | ||
outgoingMsg.WriteInt32((int)SamplerType.Gaussian); | ||
outgoingMsg.WriteFloat32(mean); | ||
outgoingMsg.WriteFloat32(stddev); | ||
byte[] message = GetByteMessage(m_Channel, outgoingMsg); | ||
SideChannelsManager.ProcessSideChannelData(message); | ||
} | ||
Assert.AreEqual(2.936162f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
Assert.AreEqual(2.951348f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
} | ||
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[Test] | ||
public void MultiRangeUniformSamplerTest() | ||
{ | ||
float[] intervals = new float[4]; | ||
intervals[0] = 1.2f; | ||
intervals[1] = 2f; | ||
intervals[2] = 3.2f; | ||
intervals[3] = 4.1f; | ||
string parameter = "parameter3"; | ||
using (var outgoingMsg = new OutgoingMessage()) | ||
{ | ||
outgoingMsg.WriteString(parameter); | ||
// 1 indicates this meessage is a Sampler | ||
outgoingMsg.WriteInt32(1); | ||
outgoingMsg.WriteInt32(k_Seed); | ||
outgoingMsg.WriteInt32((int)SamplerType.MultiRangeUniform); | ||
outgoingMsg.WriteFloatList(intervals); | ||
byte[] message = GetByteMessage(m_Channel, outgoingMsg); | ||
SideChannelsManager.ProcessSideChannelData(message); | ||
} | ||
Assert.AreEqual(3.387999f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
Assert.AreEqual(1.294413f, m_Channel.GetWithDefault(parameter, 1.0f), k_Epsilon); | ||
} | ||
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internal static byte[] GetByteMessage(SideChannel sideChannel, OutgoingMessage msg) | ||
{ | ||
byte[] message = msg.ToByteArray(); | ||
using (var memStream = new MemoryStream()) | ||
{ | ||
using (var binaryWriter = new BinaryWriter(memStream)) | ||
{ | ||
binaryWriter.Write(sideChannel.ChannelId.ToByteArray()); | ||
binaryWriter.Write(message.Length); | ||
binaryWriter.Write(message); | ||
} | ||
return memStream.ToArray(); | ||
} | ||
} | ||
} | ||
} |
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