NanoBrain/NanoBrain-unitypackage
NanoBrain/NanoBrain-unitypackage
2
0
Fork 0
Code Issues Pull Requests Actions Packages Releases Activity

Compare commits

base: NanoBrain:main
Branches Tags
NanoBrain:main
NanoBrain:Training
..
compare: NanoBrain:Training
Branches Tags
NanoBrain:main
NanoBrain:Training

No commits in common. "main" and "Training" have entirely different histories.
main ... Training

14 changed files with 146 additions and 806 deletions
Show Stats Expand all files Collapse all files

58
Editor/ClusterEditor.cs
View File

@ -27,12 +27,13 @@ namespace NanoBrain.Unity {
}
}
clusterPrefab.cluster.name = clusterPrefab.name;
clusterPrefab.cluster.Cleanup();
view.currentCluster = clusterPrefab.cluster;
view.currentCluster ??= clusterPrefab.cluster;
view.currentNucleus = clusterPrefab.cluster.defaultOutput;
view.selectedOutput = view.currentNucleus;
clusterPrefab.cluster.name = clusterPrefab.name;
clusterPrefab.cluster.Cleanup();
}
void OnDisable() {
@ -47,30 +48,28 @@ namespace NanoBrain.Unity {
EditorGUI.BeginChangeCheck();
// Begin horizontal split
// EditorGUILayout.BeginHorizontal();
EditorGUILayout.BeginHorizontal();
// // Left: fixed-width drawing area
// GUILayoutOption[] leftOptions = { GUILayout.Width(drawAreaWidth) };
// Rect drawRect = GUILayoutUtility.GetRect(drawAreaWidth, 450f, leftOptions); // height adjustable
// Left: fixed-width drawing area
GUILayoutOption[] leftOptions = { GUILayout.Width(drawAreaWidth) };
Rect drawRect = GUILayoutUtility.GetRect(drawAreaWidth, 450f, leftOptions); // height adjustable
// // add padding inside rect
// Rect innerRect = new(drawRect.x + padding, drawRect.y + padding,
// drawRect.width - padding * 2, drawRect.height - padding * 2);
// add padding inside rect
Rect innerRect = new(drawRect.x + padding, drawRect.y + padding,
drawRect.width - padding * 2, drawRect.height - padding * 2);
// view.Render(innerRect);
view.Render(innerRect);
// Right: info panel (takes remaining width)
EditorGUILayout.BeginVertical(GUILayout.ExpandWidth(true));
float prevLabelWidth = EditorGUIUtility.labelWidth;
EditorGUIUtility.labelWidth = 100f; // smaller labels -> larger fields
if (GUILayout.Button("Import"))
ImportJson();
InspectorHandler(serializedObject);
EditorGUIUtility.labelWidth = prevLabelWidth;
EditorGUILayout.EndVertical(); // end right column
// EditorGUILayout.EndHorizontal(); // end split
EditorGUILayout.EndHorizontal(); // end split
if (EditorGUI.EndChangeCheck()) {
serializedObject.Update();
@ -84,35 +83,6 @@ namespace NanoBrain.Unity {
}
protected void ImportJson() {
string path = EditorUtility.OpenFilePanel(
"Import JSON",
"",
"json"
);
if (!string.IsNullOrEmpty(path) && System.IO.File.Exists(path)) {
ClusterData newClusterData = Cluster.Import(path);
clusterPrefab.cluster = new(newClusterData) {
name = clusterPrefab.name
};
clusterPrefab.cluster.Cleanup();
view.currentCluster = clusterPrefab.cluster;
view.currentNucleus = clusterPrefab.cluster.defaultOutput;
view.selectedOutput = view.currentNucleus;
}
}
public override bool HasPreviewGUI() => true;
public override void OnPreviewGUI(Rect r, GUIStyle background) {
base.OnPreviewGUI(r, background);
GUI.Label(r, "welcome");
view.Render(r);
}
#region Inspector
private bool showSynapses = true;

9
Editor/ClusterJson_Drawer.cs.meta
View File

@ -1,11 +1,2 @@
fileFormatVersion: 2
guid: 879b585246de16598959c21b724cf105
MonoImporter:
externalObjects: {}
serializedVersion: 2
defaultReferences: []
executionOrder: 0
icon: {instanceID: 0}
userData:
assetBundleName:
assetBundleVariant:

40
Editor/ClusterView.cs
View File

@ -316,7 +316,6 @@ namespace NanoBrain.Unity {
foreach (Synapse synapse in receiverNeuron.synapses) {
Nucleus nucleus = synapse.neuron;
if (nucleus.parent != null && currentNucleus != null && nucleus.parent != currentNucleus.parent) {
// if (nucleus.parent != null && nucleus.parent != currentCluster) {
nucleus = nucleus.parent;
}
string nucleusName = nucleus.name;
@ -508,11 +507,11 @@ namespace NanoBrain.Unity {
}
Vector3 labelPos = position - Vector3.down * (discRadius + 5); // below neuron
string name = $"{nucleus.parent.instances[0].baseName}\n{nucleus.name}";
GUIStyle style = new(EditorStyles.label) {
alignment = TextAnchor.UpperCenter,
normal = { textColor = Color.white },
fontStyle = FontStyle.Bold,
};
GUIStyle style = new(EditorStyles.label) {
alignment = TextAnchor.UpperCenter,
normal = { textColor = Color.white },
fontStyle = FontStyle.Bold,
};
Handles.Label(labelPos, name, style);
expandArray = false;
}
@ -625,27 +624,14 @@ namespace NanoBrain.Unity {
if (nucleus.parent != null && this.currentNucleus != null && nucleus.parent != this.currentNucleus.parent && nucleus.parent is Cluster parentCluster1) {
// This neuron is part of another cluster
if (nucleus is Cluster cluster) {
string clusterName = cluster.prefab.name;
int colonPos = clusterName.IndexOf(":");
string baseName;
if (colonPos > 0 && colonPos < clusterName.Length - 2)
baseName = clusterName[..colonPos] + "\n";
else
baseName = clusterName + "\n";
Handles.Label(labelPos, baseName + nucleus.name, style);
}
else {
parentCluster1.name ??= "";
int colonPos = parentCluster1.name.IndexOf(":");
string baseName;
if (colonPos > 0 && colonPos < parentCluster1.name.Length - 2)
baseName = parentCluster1.name[..colonPos] + "\n";
else
baseName = parentCluster1.name + "\n";
Handles.Label(labelPos, baseName + nucleus.name, style);
}
parentCluster1.name ??= "";
int colonPos = parentCluster1.name.IndexOf(":");
string baseName;
if (colonPos > 0 && colonPos < parentCluster1.name.Length - 2)
baseName = parentCluster1.name[..colonPos] + "\n";
else
baseName = parentCluster1.name + "\n";
Handles.Label(labelPos, baseName + nucleus.name, style);
}
else {
nucleus.name ??= "";

16
Editor/Cluster_Drawer.cs
View File

@ -38,18 +38,13 @@ namespace NanoBrain.Unity {
}
private void InstantiateCluster(SerializedProperty property, ClusterView clusterView) {
if (property == null || clusterView.initialized)
return;
SerializedObject serializedObject = property.serializedObject;
if (serializedObject == null)
return;
UnityEngine.Object targetObject = serializedObject.targetObject;
if (targetObject == null)
if (property == null || property.serializedObject == null || clusterView.initialized)
return;
SerializedProperty prefabProp = property.FindPropertyRelative(nameof(Cluster.prefab));
UnityEngine.Object targetObject = property.serializedObject.targetObject;
if (targetObject == null)
return;
Debug.Log($"Instantiate new Cluster for {targetObject.name}");
@ -75,14 +70,11 @@ namespace NanoBrain.Unity {
int indent = EditorGUI.indentLevel;
EditorGUI.indentLevel = 0;
//SerializedProperty jsonProp = property.FindPropertyRelative(nameof(Cluster.jsonAsset));
SerializedProperty prefabProp = property.FindPropertyRelative(nameof(Cluster.prefab));
// Draw the object field on the top line
Rect fieldRect = new(position.x, position.y, position.width, EditorGUIUtility.singleLineHeight);
EditorGUI.BeginChangeCheck();
//EditorGUI.PropertyField(fieldRect, jsonProp, label);
EditorGUI.PropertyField(fieldRect, prefabProp, label);
// If a new prefab has been selected
if (EditorGUI.EndChangeCheck()) {

9
Editor/Neuron_Drawer.cs.meta
View File

@ -1,11 +1,2 @@
fileFormatVersion: 2
guid: ecce20d60829feced84788f7f9dcfe08
MonoImporter:
externalObjects: {}
serializedVersion: 2
defaultReferences: []
executionOrder: 0
icon: {instanceID: 0}
userData:
assetBundleName:
assetBundleVariant:

0
Runtime/Scripts/ScriptableObjects/ClusterJson.cs → Runtime/Scripts/ClusterJson.cs
View File

2
Runtime/Scripts/ClusterJson.cs.meta Normal file
View File

@ -0,0 +1,2 @@
fileFormatVersion: 2
guid: 8ea9c456ab9da37daaa610edaadc38bb

394
Runtime/Scripts/Core/Cluster.cs
View File

@ -26,7 +26,6 @@ namespace NanoBrain {
/// Cluster should always be created from prefabs
public ClusterPrefab prefab;
public ClusterJson json;
public TextAsset jsonAsset;
//[HideInInspector]
@ -70,86 +69,15 @@ namespace NanoBrain {
/// </summary>
/// In a multi-cluster each instance can be used for a thing.
/// Cluster instance may also not (yet) be mapped to a thing.
// [NonSerialized]
// public Dictionary<int, Cluster> thingClusters = new();
public int thingId;
[NonSerialized]
public Dictionary<int, Cluster> thingClusters = new();
/// <summary>
/// All nuclei in this cluster
/// </summary>
[SerializeReference]
[HideInInspector]
public List<Nucleus> nuclei = new();
#region Timed Actions
public class TimedAction {
public TimedAction(string neuronName, Action action, long timestamp) {
this.neuronName = neuronName;
this.timestamp = timestamp;
this.action = action;
}
public string neuronName;
public long timestamp;
public Action action;
public static void AddTo(List<TimedAction> actions, string neuronName, Action action, long timestamp) {
int ix = -1;
int insertIx = actions.Count; // default: add at end
// Find existing item and the first item with timestamp > this.timestamp
for (int i = 0; i < actions.Count; i++) {
TimedAction item = actions[i];
if (ix < 0 && item.neuronName == neuronName) {
ix = i;
break;
}
}
if (ix >= 0) {
// Debug.Log($"update {neuronName} {timestamp}");
actions[ix].action = action;
actions[ix].timestamp = timestamp;
return;
}
// Debug.Log($"new {neuronName} {timestamp}");
// No existing item; compute insertion point (sorted by timestamp ascending)
for (int i = 0; i < actions.Count; i++) {
if (actions[i].timestamp > timestamp) {
insertIx = i;
break;
}
}
TimedAction newAction = new(neuronName, action, timestamp);
actions.Insert(insertIx, newAction);
}
public static void Check(List<TimedAction> actions) {
long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
// if (actions.Count > 0) {
// Debug.Log($"{actions.Count} actions, {actions[0].neuronName} {actions[0].timestamp} {now} {actions[0].timestamp - now}");
// }
while (actions.Count > 0 && actions[0].timestamp <= now) {
Action action = actions[0].action;
actions.RemoveAt(0);
action();
}
}
}
public readonly List<TimedAction> actions = new();
public void CheckActions() {
TimedAction.Check(this.actions);
foreach (Nucleus nucleus in this.nuclei) {
if (nucleus is not Cluster cluster)
continue;
cluster.CheckActions();
}
}
#endregion Timed Actions
#region Init
public Cluster() {
@ -200,14 +128,8 @@ namespace NanoBrain {
this.prefab = prefab;
this.version = prefab.version;
this.name = prefab.name;
if (parent != null) {
TextAsset jsonFile = Resources.Load<TextAsset>(parent.name);
string json = jsonFile.text;
ClusterData clusterData = JsonUtility.FromJson<ClusterData>(json);
//ClusterData clusterData = Cluster.Import(jsonPath);
parent.cluster = new(clusterData);
if (parent != null)
this.parent = parent.cluster;
}
ClonePrefab();
}
@ -250,27 +172,21 @@ namespace NanoBrain {
foreach (NeuronData neuronData in clusterData.neurons) {
Neuron receiver = this.GetNeuron(neuronData.name);
foreach (SynapseData synapseData in neuronData.synapses) {
// If the synapse points to another cluster
if (synapseData.clusterName != this.name) {
// Add reference to external cluster
// Do we know the external cluster already?
ExternalClusterData externalClusterData = clusterData.GetCluster(synapseData.clusterName);
Cluster extCluster = this.GetCluster(synapseData.clusterName);
if (extCluster == null) {
// if not: create new external cluster
Debug.Log("New ext cluster");
ClusterPrefab extPrefab = Resources.Load(externalClusterData.prefabName) as ClusterPrefab;
extCluster = new(extPrefab, this, instanceCount) {
name = externalClusterData.name
};
}
extCluster.instanceCount = externalClusterData.instanceCount;
// Do we have the synapse already?
Neuron extNeuron = extCluster.GetNeuron(synapseData.neuronName);
Synapse synapse = receiver.GetSynapse(extNeuron); //extCluster, synapseData.neuronName);
if (synapse == null) {
Debug.Log("new receiver for external");
// If not: create new synapse
ClusterPrefab extPrefab = Resources.Load(synapseData.clusterName) as ClusterPrefab;
if (extPrefab == null)
Debug.LogError($"Could not find cluster Resource {synapseData.clusterName}");
else {
uint instanceCount = 1;
foreach (ExternalClusterData externalCluster in clusterData.clusters) {
if (externalCluster.name == synapseData.clusterName)
instanceCount = externalCluster.instanceCount;
}
if (this.nuclei.Find(nucleus => nucleus.name == synapseData.clusterName) is not Cluster extCluster)
extCluster = new(extPrefab, this, instanceCount);
Neuron extNeuron = extCluster.GetNeuron(synapseData.neuronName);
Debug.Log("Add receiver for external");
extNeuron.AddReceiver(receiver);
}
}
@ -282,6 +198,7 @@ namespace NanoBrain {
}
}
/// <summary>
/// Clone a prefab.
/// </summary>
@ -372,71 +289,6 @@ namespace NanoBrain {
}
}
public Cluster Copy() {
Cluster clone = new() {
name = this.name,
prefab = this.prefab,
version = this.version,
parent = this.parent
};
if (clone.parent != null) {
// Do we need to clone the parent here too????
}
// first clone the nuclei without their connections
foreach (Nucleus nucleus in this.nuclei)
nucleus.ShallowCloneTo(clone);
Nucleus[] clonedNuclei = clone.nuclei.ToArray();
// Now clone the connections
for (int nucleusIx = 0; nucleusIx < this.nuclei.Count; nucleusIx++) {
Nucleus sourceNucleus = this.nuclei[nucleusIx];
if (sourceNucleus is not Neuron sourceNeuron)
continue;
Nucleus clonedNucleus = clonedNuclei[nucleusIx];
if (clonedNucleus == null || clonedNucleus is not Neuron clonedNeuron)
continue;
foreach (Synapse sourceSynapse in sourceNeuron.synapses) {
Neuron synapseNeuron = sourceSynapse.neuron;
if (synapseNeuron.parent.prefab != null && synapseNeuron.parent.prefab != clone.prefab) {
// Neuron is in another cluster, find the cloned cluster first
Cluster sourceCluster = synapseNeuron.parent;
//Cluster clonedCluster = clone.nuclei.Find(n => n.name == sourceCluster.name) as Cluster;
Nucleus clonedClusterNucleus = clone.nuclei.Find(n => n.name == sourceCluster.name);
if (clonedClusterNucleus is not Cluster clonedCluster)
continue;
// Now find the neuron in that cloned cluster
int neuronIx = GetNucleusIndex(sourceCluster.nuclei, sourceSynapse.neuron.name);
if (neuronIx < 0)
// Could not find the neuron in the prefab cluster
continue;
if (clonedCluster.nuclei[neuronIx] is not Neuron clonedSender)
// Could not find the neuron in the cloned cluster
continue;
clonedSender.AddReceiver(clonedNeuron, sourceSynapse.weight, sourceSynapse.trainable);
//Debug.Log($"Add synapse {clonedCluster.name}.{clonedSender.name} -> {clonedNeuron.name} [{clonedSender.receivers.Count}]");
}
else {
int ix = GetNucleusIndex(clone.prefab.cluster.nuclei, sourceSynapse.neuron);
if (ix < 0)
continue;
if (clonedNuclei[ix] is not Neuron clonedSender)
continue;
// Copy the receivers which will also create the synapse
clonedSender.AddReceiver(clonedNeuron, sourceSynapse.weight, sourceSynapse.trainable);
// Debug.Log($"Add synapse {clonedSender.name} -> {clonedNeuron.name}");
}
}
}
return clone;
}
/// \copydoc NanoBrain::Nucleus::ShallowCloneTo
public override Nucleus ShallowCloneTo(Cluster parent) {
// Clusters should not be cloned, but instantiated from the prefab....
@ -493,8 +345,8 @@ namespace NanoBrain {
public static int GetNucleusIndex(List<Nucleus> nuclei, Nucleus nucleus) {
int i = 0;
foreach (Nucleus nucleiElement in nuclei) {
// if (nucleiElement == nucleus)
if (nucleiElement.name == nucleus.name)
//for (int i = 0; i < nuclei.Length; i++) {
if (nucleiElement == nucleus)
return i;
i++;
}
@ -518,37 +370,6 @@ namespace NanoBrain {
return -1;
}
/// <summary>
/// Initializes all trainable weights to random values
/// </summary>
public void InitializeRandom() {
System.Random randomGenerator = new();
foreach (Nucleus nucleus in this.nuclei) {
if (nucleus is Neuron neuron) {
foreach (Synapse synapse in neuron.synapses) {
if (synapse.trainable) {
synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
// Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
}
}
}
}
}
public void GaussianAdditiveMutation(float sigma) {
foreach (Nucleus nucleus in this.nuclei) {
if (nucleus is Neuron neuron) {
foreach (Synapse synapse in neuron.synapses) {
if (synapse.trainable) {
synapse.GaussianAdditiveMutation(sigma);
//synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
// Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
}
}
}
}
}
#endregion Init
#region Cluster Array
@ -622,20 +443,18 @@ namespace NanoBrain {
/// Remove a mapping from a thing to a cluster such that it becomes available for new things
/// </summary>
/// <param name="cluster">The multi-cluster instance which not no longer be mapped</param>
public void RemoveThingCluster(Cluster cluster) {
cluster.thingId = 0;
// int keyToRemove = -1;
// foreach (KeyValuePair<int, Cluster> kvp in this.thingClusters) {
// if (kvp.Value == cluster) {
// keyToRemove = kvp.Key;
// break;
// }
// }
private void RemoveThingCluster(Cluster cluster) {
List<int> keysToRemove = new();
foreach (KeyValuePair<int, Cluster> kvp in thingClusters) {
if (kvp.Value == cluster)
keysToRemove.Add(kvp.Key);
}
// if (keyToRemove >= 0)
// this.thingClusters.Remove(keyToRemove);
foreach (int thingId in keysToRemove)
thingClusters.Remove(thingId);
}
public List<Neuron> GetAllInstances(Neuron nucleus) {
List<Neuron> allInstances = new();
@ -656,6 +475,28 @@ namespace NanoBrain {
return allInstances;
}
// public void Backpropagation(Func<Cluster, float> Observer, float target, float learningRate) {
// foreach (Nucleus nucleus in this.instances[0].nuclei) {
// if (nucleus is not Neuron neuron)
// continue;
// foreach (Synapse synapse in neuron.synapses) {
// List<Neuron> allSynapseNeurons = GetAllInstances(synapse.neuron);
// Vector3 dSSRdW = Vector3.zero;
// for (int clusterIx = 0; clusterIx < this.instances.Length; clusterIx++) {
// Cluster clusterInstance = this.instances[clusterIx];
// Neuron neuronInstance = allSynapseNeurons[clusterIx];
// // Simple case, without receivers...
// dSSRdW += (Vector3)(-2 * (Observer(clusterInstance) - target) * neuronInstance.activation);
// }
// synapse.weight += learningRate * dSSRdW.magnitude;
// }
// }
// }
#endregion ClusterArray
/// <summary>
@ -671,7 +512,7 @@ namespace NanoBrain {
if (_computeOrders == null || _computeOrders.Count == 0) {
_computeOrders = new();
foreach (Nucleus nucleus in this.nuclei)
_computeOrders[nucleus] = TopologicalSort(nucleus);
_computeOrders[nucleus] = TopologicalSort2(nucleus);
}
return _computeOrders;
}
@ -683,7 +524,7 @@ namespace NanoBrain {
this._computeOrders = null;
}
private List<Nucleus> TopologicalSort(Nucleus startNode) {
private List<Nucleus> TopologicalSort2(Nucleus startNode) {
Dictionary<Nucleus, int> inDegree = new();
//HashSet<Nucleus> visited = new();
@ -868,18 +709,13 @@ namespace NanoBrain {
/// <returns>The found neuron or null when it is not found</returns>
/// The cluster instance mapped to the thing will be neuron.parent if a neuron is found.
public Neuron GetNeuron(int thingId, string neuronName, string thingName = null) {
// If this is not an ClusterArray, just take the neuron
if (this.instances == null || this.instances.Length <= 1)
return this.GetNeuron(neuronName);
// See if we are already using a cluster for thingId
// thingClusters ??= new();
// if (thingClusters.TryGetValue(thingId, out Cluster cluster))
// return cluster.GetNeuron(neuronName);
foreach (Cluster sibling in this.instances) {
if (sibling.thingId == thingId)
return sibling.GetNeuron(neuronName);
}
thingClusters ??= new();
if (thingClusters.TryGetValue(thingId, out Cluster cluster))
return cluster.GetNeuron(neuronName);
// Find the cluster with the lowest value neuron
Neuron lowestNeuron = null;
@ -891,8 +727,7 @@ namespace NanoBrain {
Cluster selectedCluster = lowestNeuron.parent;
RemoveThingCluster(selectedCluster);
selectedCluster.name = baseName + ": " + thingName;
//thingClusters[thingId] = selectedCluster;
selectedCluster.thingId = thingId;
thingClusters[thingId] = selectedCluster;
return lowestNeuron;
}
@ -917,65 +752,6 @@ namespace NanoBrain {
return true;
}
public static bool EqualStructure(Cluster cluster1, Cluster cluster2) {
int n1 = cluster1.nuclei.Count;
int n2 = cluster2.nuclei.Count;
if (n1 != n2)
return false;
for (int i = 0; i < cluster1.nuclei.Count; i++) {
if (EqualStructure(cluster1.nuclei[i], cluster2.nuclei[i]) == false)
return false;
}
return true;
}
public bool CopyWeightsFrom(Cluster source) {
int thisNucleiCount = this.nuclei.Count;
int sourceNucleiCount = source.nuclei.Count;
if (thisNucleiCount != sourceNucleiCount)
return false;
for (int i = 0; i < this.nuclei.Count; i++) {
if (this.nuclei[i] is Neuron thisNeuron &&
source.nuclei[i] is Neuron sourceNeuron) {
if (thisNeuron.CopyWeightsFrom(sourceNeuron) == false)
return false;
}
}
return true;
}
public void ProcessWeightsFrom(Cluster source, Func<float, float, float> processor) {
if (processor is null)
throw new ArgumentNullException(nameof(processor));
if (source is null)
throw new ArgumentNullException(nameof(source));
int thisNucleiCount = this.nuclei.Count;
int sourceNucleiCount = source.nuclei.Count;
if (thisNucleiCount != sourceNucleiCount)
throw new ArgumentException("Lists must have the same length.", nameof(source));
for (int i = 0; i < thisNucleiCount; i++) {
if (this.nuclei[i] is Neuron thisNeuron &&
source.nuclei[i] is Neuron sourceNeuron) {
thisNeuron.ProcessWeightsFrom(sourceNeuron, processor);
}
}
}
public void ProcessWeights(Func<float, float> processor) {
if (processor is null)
throw new ArgumentNullException(nameof(processor));
for (int i = 0; i < this.nuclei.Count; i++) {
if (this.nuclei[i] is Neuron thisNeuron)
thisNeuron.ProcessWeight(processor);
}
}
#region Receivers
/// <summary>
@ -1040,15 +816,14 @@ namespace NanoBrain {
List<Nucleus> computeOrder = this.computeOrders[startNucleus];
foreach (Nucleus nucleus in computeOrder) {
if (nucleus is Cluster)
continue;
nucleus.UpdateStateIsolated();
if (nucleus is Neuron neuron) {
foreach (Nucleus receiver in neuron.receivers) {
if (receiver.parent != this) {
//Debug.Log($" External: {receiver.parent.name}.{receiver.name}");
receiver.parent.UpdateFromNucleus(receiver);
if (nucleus is not Cluster) {
nucleus.UpdateStateIsolated();
if (nucleus is Neuron neuron) {
foreach (Nucleus receiver in neuron.receivers) {
if (receiver.parent != this) {
//Debug.Log($" External: {receiver.parent.name}.{receiver.name}");
receiver.parent.UpdateFromNucleus(receiver);
}
}
}
}
@ -1090,10 +865,10 @@ namespace NanoBrain {
#region Serialization
public void Export(string path) {
ClusterData data = new(this);
ClusterData data = new(this); //this.ToJSON();
string json = JsonUtility.ToJson(data, prettyPrint: true);
Debug.Log($"Exporting {this.name} to {path}");
// Debug.Log($"Exporting json to {path}");
File.WriteAllText(path, json);
}
@ -1115,41 +890,30 @@ namespace NanoBrain {
public ClusterData(Cluster cluster) {
this.name = cluster.name;
foreach (Nucleus nucleus in cluster.nuclei) {
if (nucleus is not Neuron neuron)
continue;
NeuronData neuronData = new(neuron);
this.neurons.Add(neuronData);
foreach (Synapse synapse in neuron.synapses) {
if (synapse.neuron.parent.baseName == cluster.name)
continue;
ExternalClusterData clusterData = new(synapse.neuron.parent);
if (GetCluster(clusterData.name) == null)
this.clusters.Add(clusterData);
if (nucleus is Neuron neuron) {
NeuronData neuronData = new(neuron);
this.neurons.Add(neuronData);
foreach (Synapse synapse in neuron.synapses) {
if (synapse.neuron.parent.name != cluster.name) {
ExternalClusterData clusterData = new(synapse.neuron.parent);
if (this.clusters.Find(data => data.name == clusterData.name) == null) {
this.clusters.Add(clusterData);
//Debug.Log("Add cluster");
}
}
}
}
}
}
public ExternalClusterData GetCluster(string clusterName) {
foreach (ExternalClusterData cluster in this.clusters) {
if (cluster.name == clusterName)
return cluster;
}
return null;
}
}
[Serializable]
public class ExternalClusterData {
public string name;
public string prefabName;
public uint instanceCount;
public ExternalClusterData(Cluster cluster) {
this.name = cluster.baseName;
this.prefabName = cluster.prefab.name;
this.name = cluster.name;
this.instanceCount = (uint)cluster.instanceCount;
}
}

152
Runtime/Scripts/Core/Neuron.cs
View File

@ -1,7 +1,5 @@
using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
using UnityEngine;
#if UNITY_MATHEMATICS
using Unity.Mathematics;
@ -37,7 +35,6 @@ namespace NanoBrain {
this.parent.nuclei ??= new();
this.parent.nuclei.Add(this);
}
this.resetStimulus = ResetStimulus;
}
#region Serialization
@ -98,12 +95,6 @@ namespace NanoBrain {
return this.GetSynapse(sender);
}
public Synapse GetSynapse(Cluster cluster, string senderNeuronName) {
Neuron sender = cluster.GetNeuron(senderNeuronName);
if (sender == null)
return null;
return this.GetSynapse(sender);
}
/// <summary>
/// Remove a synapse from a Nucleus
@ -121,7 +112,7 @@ namespace NanoBrain {
/// <param name="inputValue"></param>
public virtual void SetBias(Vector3 inputValue) {
this.bias = inputValue;
// this.lastUpdate = Time.time;
this.lastUpdate = Time.time;
this.parent?.UpdateFromNucleus(this);
}
@ -184,16 +175,11 @@ namespace NanoBrain {
/// The output value of the neuron
/// </summary>
public virtual float3 outputValue {
get {
this.parent.CheckActions();
return _outputValue;
}
get { return _outputValue; }
set {
_outputValue = value;
if (this.isFiring)
WhenFiring?.Invoke();
else
WhenNotFiring?.Invoke();
}
}
public float3 activation => outputValue;
@ -242,39 +228,37 @@ namespace NanoBrain {
/// </summary>
public Action WhenFiring;
public Action WhenNotFiring;
/// <summary>
/// When true, the value will not be reset after timeToSleep.
/// </summary>
//public bool persistOutput = false;
public bool persistOutput = false;
/// <summary>
/// True when the neuron is not persisting and has not be updated for timeToSleep seconds
/// </summary>
//public virtual bool isSleeping => false; //!persistOutput && (Time.time - this.lastUpdate > timeToSleep);
public virtual bool isSleeping => !persistOutput && (Time.time - this.lastUpdate > timeToSleep);
/// <summary>
/// Check if the neuron is sleeping.
/// </summary>
/// This will reset the output value if it is sleeping
// public void SleepCheck() {
// if (this.isSleeping && this.outputSqrMagnitude > 0) {
// #if UNITY_MATHEMATICS
// this._outputValue = new float3(0, 0, 0);
// #else
// this._outputValue = new Vector3(0,0,0);
// #endif
// }
// }
public void SleepCheck() {
if (this.isSleeping && this.outputSqrMagnitude > 0) {
#if UNITY_MATHEMATICS
this._outputValue = new float3(0, 0, 0);
#else
this._outputValue = new Vector3(0,0,0);
#endif
}
}
/// <summary>
/// The time at which the last update has been done
/// </summary>
// [HideInInspector]
// public float lastUpdate = 0;
[HideInInspector]
public float lastUpdate = 0;
/// <summary>
/// Time in seconds after the last update the neuron can go to sleep
/// </summary>
// public static readonly float timeToSleep = 0.5f;
public static readonly float timeToSleep = 0.5f;
/// <summary>
/// When true, Unity will pause exection when this neuron is updated
@ -298,63 +282,12 @@ namespace NanoBrain {
protected virtual void CloneFields(Neuron clone) {
clone.bias = this.bias;
clone.trainableBias = this.trainableBias;
//clone.persistOutput = this.persistOutput;
clone.persistOutput = this.persistOutput;
clone.combinator = this.combinator;
clone.activator = this.activator;
clone.breakOnUpdate = this.breakOnUpdate;
}
public static bool EqualStructure(Neuron neuron1, Neuron neuron2) {
int synapseCount1 = neuron1.synapses.Count;
int synapseCount2 = neuron2.synapses.Count;
if (synapseCount1 != synapseCount2)
return false;
for (int i = 0; i < synapseCount1; i++) {
if (Synapse.EqualStructure(neuron1.synapses[i], neuron2.synapses[i]) == false)
return false;
}
return true;
}
public bool CopyWeightsFrom(Neuron source) {
int thisSynapseCount = this.synapses.Count;
int sourceSynapseCount = source.synapses.Count;
if (thisSynapseCount != sourceSynapseCount)
return false;
for (int i = 0; i < thisSynapseCount; i++) {
Synapse thisSynapse = this.synapses[i];
if (thisSynapse.trainable) {
Synapse sourceSynapse = source.synapses[i];
thisSynapse.weight = sourceSynapse.weight;
}
}
return true;
}
public void ProcessWeightsFrom(Neuron source, Func<float, float, float> processor) {
int thisSynapseCount = this.synapses.Count;
int sourceSynapseCount = source.synapses.Count;
if (thisSynapseCount != sourceSynapseCount)
return;
for (int i = 0; i < thisSynapseCount; i++) {
Synapse thisSynapse = this.synapses[i];
if (thisSynapse.trainable) {
Synapse sourceSynapse = source.synapses[i];
thisSynapse.weight = processor(thisSynapse.weight, sourceSynapse.weight);
}
}
}
public void ProcessWeight(Func<float, float> processor) {
foreach (Synapse thisSynapse in this.synapses) {
if (thisSynapse.trainable)
thisSynapse.weight = processor(thisSynapse.weight);
}
}
/// <summary>
/// Delete the give neuron
/// </summary>
@ -408,7 +341,7 @@ namespace NanoBrain {
}
this.combination = Combinator(this.bias, this.synapses);
this.outputValue = Activator(this.combination);
// this.lastUpdate = Time.time;
this.lastUpdate = Time.time;
}
#region Combinator
@ -443,8 +376,8 @@ namespace NanoBrain {
public static float3 CombinatorSum(float3 bias, List<Synapse> synapses) {
float3 sum = bias;
foreach (Synapse synapse in synapses) {
// synapse.neuron.SleepCheck();
sum += synapse.weight * synapse.neuron._outputValue;
synapse.neuron.SleepCheck();
sum += synapse.weight * synapse.neuron.outputValue;
}
return sum;
}
@ -458,8 +391,8 @@ namespace NanoBrain {
public static float3 CombinatorProduct(float3 bias, List<Synapse> synapses) {
float3 product = bias;
foreach (Synapse synapse in synapses) {
// synapse.neuron.SleepCheck();
product *= synapse.weight * synapse.neuron._outputValue;
synapse.neuron.SleepCheck();
product *= synapse.weight * synapse.neuron.outputValue;
}
return product;
}
@ -770,14 +703,14 @@ namespace NanoBrain {
foreach (Synapse synapse in this.synapses)
synapse.BackPropagation3D(this, derivative, learningRate);
// As the weight cannot change the direction of the derivative
// we can use the simpler, 1D backpropagation here
// But we still need to determine the sign of the derivative
// As the weight cannot change the direction of the derivative
// we can use the simpler, 1D backpropagation here
// But we still need to determine the sign of the derivative
// if (Synapse.AreOpposed(derivative, synapse.neuron.activation))
// synapse.BackPropagation(this, -derivativeMagnitude, learningRate);
// else
// synapse.BackPropagation(this, derivativeMagnitude, learningRate);
// if (Synapse.AreOpposed(derivative, synapse.neuron.activation))
// synapse.BackPropagation(this, -derivativeMagnitude, learningRate);
// else
// synapse.BackPropagation(this, derivativeMagnitude, learningRate);
// Bias
if (this.trainableBias) {
@ -796,32 +729,14 @@ namespace NanoBrain {
#endregion Back propagation
private CancellationTokenSource _cts;
private Action resetStimulus;
/// <summary>
/// Process an external stimulus
/// </summary>
/// <param name="inputValue">The value of the stimulus</param>
public virtual void ProcessStimulus(Vector3 inputValue, float autoResetDelay = 0) {
// this.lastUpdate = Time.time;
public virtual void ProcessStimulus(Vector3 inputValue) {
this.lastUpdate = Time.time;
this.bias = inputValue;
this.parent?.UpdateFromNucleus(this);
this.resetStimulus ??= ResetStimulus;
if (autoResetDelay > 0) {
long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
long resetTime = now + (long)(autoResetDelay * 1000.0f);
Cluster.TimedAction.AddTo(this.parent.actions, this.parent.name + "." + this.name, this.resetStimulus, resetTime);
}
}
private void ResetStimulus() {
// Debug.Log($"reset stimulus {this.parent.name + "." +this.name}");
this.parent.name = this.parent.baseName;
this.bias = Vector3.zero;
this.parent.thingId = 0;
this.parent?.UpdateFromNucleus(this);
}
}
@ -845,11 +760,6 @@ namespace NanoBrain {
this.activationType = neuron.activator;
foreach (Synapse synapse in neuron.synapses) {
// Check whether synapse exists already first
if (this.synapses.Find(s => s.neuronName == synapse.neuron.name) != null)
// But then: what to do with the weights???? :-)
continue;
SynapseData synapseData = new(synapse);
this.synapses.Add(synapseData);
}

27
Runtime/Scripts/Core/Nucleus.cs
View File

@ -50,33 +50,6 @@ namespace NanoBrain {
#endregion Update
public static bool EqualStructure(Nucleus nucleus1, Nucleus nucleus2) {
if (nucleus1.parent != null && nucleus2.parent != null) {
if (nucleus1.parent.baseName != nucleus2.parent.baseName)
return false;
} else {
// mainly to check one is null, other is not.
if (nucleus1.parent != nucleus2.parent)
return false;
}
if (nucleus1 is Neuron neuron1) {
if (nucleus2 is not Neuron neuron2)
return false;
if (neuron1.name != neuron2.name)
return false;
return Neuron.EqualStructure(neuron1, neuron2);
}
else if (nucleus1 is Cluster cluster1) {
if (nucleus2 is not Cluster cluster2)
return false;
if (cluster1.baseName != cluster2.baseName)
return false;
return Cluster.EqualStructure(cluster1, cluster2);
}
return false;
}
}
}

185
Runtime/Scripts/Core/Population.cs
View File

@ -1,185 +0,0 @@
using System.Collections.Generic;
using UnityEngine;
namespace NanoBrain {
public class Population {
# region Members
public class Member {
public Member(Cluster cluster) {
this.brain = cluster;
this.performance = 0;
this.initialized = true;
}
public Cluster brain;
public float performance;
public bool initialized;
}
public List<Member> members = new();
public Member AddMember(Cluster brain) {
Member newMember = new(brain);
this.members.Add(newMember);
return newMember;
}
#endregion Members
#region Saving
public enum SaveMethod {
Average,
Mean,
First,
All
}
public void Save(string path, SaveMethod saveMethod = SaveMethod.Average) {
Cluster cluster = null;
switch (saveMethod) {
case SaveMethod.First:
Member member = this.members[0];
if (member == null)
return;
cluster = member.brain;
break;
case SaveMethod.Average:
cluster = CalculateAverageCluster();
break;
}
cluster?.Export(path);
}
protected Cluster CalculateAverageCluster() {
if (members.Count <= 0)
return null;
Cluster result = members[0].brain.Copy();
for (int memberIx = 1; memberIx < members.Count; memberIx++) {
Member member = members[memberIx];
result.ProcessWeightsFrom(member.brain, Sum);
}
result.ProcessWeights(w => w / members.Count);
return result;
}
#endregion Saving
#region New Generation
public void NewGeneration() {
foreach (Member member in this.members) {
member.initialized = false;
}
}
protected List<Member> SelectElite(float percentage) {
return SelectElite((int)(members.Count * percentage));
}
protected List<Member> SelectElite(int count) {
List<Member> selectedMembers = new();
SortMembers();
for (int i = 0; i < count; i++) {
Member member = this.members[i];
if (!member.initialized) {
Debug.Log($"Selected {i}: {member.performance}");
member.initialized = true;
selectedMembers.Add(member);
// LogTrainableWeights(member.brain);
}
}
return selectedMembers;
}
private void SortMembers() {
members.Sort((a, b) => a.performance.CompareTo(b.performance));
}
protected List<Member> GenerateMutants(List<Member> elite, float percentage) {
return GenerateMutants(elite, (int)(members.Count * percentage));
}
protected List<Member> GenerateMutants(List<Member> elite, int count) {
List<Member> selectedMembers = new();
int i = 0;
int n = 0;
while (n < count && i < this.members.Count) {
Member member = this.members[i];
if (member.initialized == false) {
GenerateMutant(member, elite);
member.initialized = true;
n++;
selectedMembers.Add(member);
}
i++;
}
return selectedMembers;
}
protected void GenerateMutant(Member member, List<Member> ants) {
System.Random randomGenerator = new();
int n = ants.Count;
int parent1 = randomGenerator.Next(0, n);
int parent2 = randomGenerator.Next(0, n);
Debug.Log($"Mutate from {members[parent1].performance} and {members[parent2].performance}");
member.brain.CopyWeightsFrom(ants[parent1].brain);
member.brain.ProcessWeightsFrom(ants[parent2].brain, Average);
// LogTrainableWeights(member.brain);
member.brain.GaussianAdditiveMutation(1e-2f);
// LogTrainableWeights(member.brain);
}
private static float Average(float a, float b) {
return (a + b) / 2;
}
private static float Sum(float a, float b) {
return a + b;
}
protected List<Member> GenerateRandom() {
return GenerateRandom(int.MaxValue);
}
protected List<Member> GenerateRandom(int count) {
List<Member> selectedMembers = new();
int i = 0;
int n = 0;
while (n < count && i < this.members.Count) {
Member member = this.members[i];
if (member.initialized == false) {
Debug.Log($"Randomized {i}: {member.performance}");
member.brain.InitializeRandom();
member.initialized = true;
selectedMembers.Add(member);
n++;
}
i++;
}
return selectedMembers;
}
#endregion New Generation
private void LogTrainableWeights(Cluster cluster) {
string s = "";
foreach (Nucleus nucleus in cluster.nuclei) {
if (nucleus is Neuron neuron) {
foreach (Synapse synapse in neuron.synapses) {
if (synapse.trainable) {
s += synapse.weight + " ";
}
}
}
}
Debug.Log(s);
}
public virtual void Update() { }
}
}

11
Runtime/Scripts/Core/Population.cs.meta
View File

@ -1,11 +0,0 @@
fileFormatVersion: 2
guid: a820ab88a63bed6e881dbb82eae0a824
MonoImporter:
externalObjects: {}
serializedVersion: 2
defaultReferences: []
executionOrder: 0
icon: {instanceID: 0}
userData:
assetBundleName:
assetBundleVariant:

34
Runtime/Scripts/Core/Synapse.cs
View File

@ -36,10 +36,6 @@ namespace NanoBrain {
this.weight = weight;
}
public static bool EqualStructure(Synapse synapse1, Synapse synapse2) {
return synapse1.neuron.name == synapse2.neuron.name;
}
public virtual void BackPropagation(Neuron receiver, float derivative, float learningRate) {
switch (receiver.activator) {
case Neuron.ActivationType.Linear:
@ -114,30 +110,6 @@ namespace NanoBrain {
// Check if the angle between the vectors is > 90 degrees
return Vector3.Dot(a, b) < 0f;
}
public void GaussianAdditiveMutation(float sigma) {
if (this.trainable == false)
return;
float deltaWeight = NormalDistribution.Sample(sigma);
this.weight += deltaWeight;
}
}
public static class NormalDistribution {
private static readonly System.Random rng = new();
// Returns a single sample from N(0, sigma^2)
public static float Sample(float sigma) {
// u1 must be > 0 to avoid log(0)
float u1 = 1.0f - (float)rng.NextDouble(); // in (0,1]
float u2 = (float) rng.NextDouble(); // in [0,1)
float stdNormal =
Mathf.Sqrt(-2.0f * Mathf.Log(u1)) * Mathf.Cos(2.0f * Mathf.PI * u2);
return sigma * stdNormal;
}
}
[Serializable]
@ -148,11 +120,7 @@ namespace NanoBrain {
public bool trainable;
public SynapseData(Synapse synapse) {
// if (synapse.neuron.parent.prefab != null)
// this.clusterName = synapse.neuron.parent.prefab.name;
// else
// this.clusterName = synapse.neuron.parent.name;
this.clusterName = synapse.neuron.parent.baseName;
this.clusterName = synapse.neuron.parent.name;
this.neuronName = synapse.neuron.name;
this.weight = synapse.weight;
this.trainable = synapse.trainable;

11
Runtime/Scripts/ScriptableObjects/ClusterJson.cs.meta
View File

@ -1,11 +0,0 @@
fileFormatVersion: 2
guid: 8ea9c456ab9da37daaa610edaadc38bb
MonoImporter:
externalObjects: {}
serializedVersion: 2
defaultReferences: []
executionOrder: 0
icon: {instanceID: 0}
userData:
assetBundleName:
assetBundleVariant: