auto stimulus reset
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@ -392,7 +392,7 @@ namespace NanoBrain {
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foreach (Synapse synapse in neuron.synapses) {
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if (synapse.trainable) {
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synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
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Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
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// Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
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}
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}
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}
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@ -859,14 +859,15 @@ namespace NanoBrain {
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List<Nucleus> computeOrder = this.computeOrders[startNucleus];
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foreach (Nucleus nucleus in computeOrder) {
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if (nucleus is not Cluster) {
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nucleus.UpdateStateIsolated();
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if (nucleus is Neuron neuron) {
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foreach (Nucleus receiver in neuron.receivers) {
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if (receiver.parent != this) {
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//Debug.Log($" External: {receiver.parent.name}.{receiver.name}");
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receiver.parent.UpdateFromNucleus(receiver);
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}
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if (nucleus is Cluster)
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continue;
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nucleus.UpdateStateIsolated();
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if (nucleus is Neuron neuron) {
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foreach (Nucleus receiver in neuron.receivers) {
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if (receiver.parent != this) {
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//Debug.Log($" External: {receiver.parent.name}.{receiver.name}");
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receiver.parent.UpdateFromNucleus(receiver);
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}
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}
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}
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@ -940,7 +941,7 @@ namespace NanoBrain {
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if (synapse.neuron.parent.name != cluster.name) {
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ExternalClusterData clusterData = new(synapse.neuron.parent);
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if (GetCluster(clusterData.name) == null) {
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//if (this.clusters.Find(data => data.name == clusterData.name) == null) {
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//if (this.clusters.Find(data => data.name == clusterData.name) == null) {
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this.clusters.Add(clusterData);
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//Debug.Log("Add cluster");
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}
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@ -1,5 +1,7 @@
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using System;
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using System.Collections.Generic;
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using System.Threading;
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using System.Threading.Tasks;
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using UnityEngine;
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#if UNITY_MATHEMATICS
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using Unity.Mathematics;
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@ -713,14 +715,14 @@ namespace NanoBrain {
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foreach (Synapse synapse in this.synapses)
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synapse.BackPropagation3D(this, derivative, learningRate);
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// As the weight cannot change the direction of the derivative
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// we can use the simpler, 1D backpropagation here
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// But we still need to determine the sign of the derivative
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// As the weight cannot change the direction of the derivative
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// we can use the simpler, 1D backpropagation here
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// But we still need to determine the sign of the derivative
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// if (Synapse.AreOpposed(derivative, synapse.neuron.activation))
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// synapse.BackPropagation(this, -derivativeMagnitude, learningRate);
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// else
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// synapse.BackPropagation(this, derivativeMagnitude, learningRate);
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// if (Synapse.AreOpposed(derivative, synapse.neuron.activation))
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// synapse.BackPropagation(this, -derivativeMagnitude, learningRate);
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// else
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// synapse.BackPropagation(this, derivativeMagnitude, learningRate);
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// Bias
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if (this.trainableBias) {
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@ -739,14 +741,40 @@ namespace NanoBrain {
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#endregion Back propagation
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private CancellationTokenSource _cts;
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/// <summary>
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/// Process an external stimulus
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/// </summary>
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/// <param name="inputValue">The value of the stimulus</param>
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public virtual void ProcessStimulus(Vector3 inputValue) {
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public virtual void ProcessStimulus(Vector3 inputValue, float autoResetDelay = 0) {
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this.lastUpdate = Time.time;
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this.bias = inputValue;
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this.parent?.UpdateFromNucleus(this);
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if (autoResetDelay > 0) {
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_cts?.Cancel();
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_cts?.Dispose();
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_cts = new CancellationTokenSource();
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_ = CallResetAfterDelayAsync(_cts.Token, autoResetDelay);
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}
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}
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private async Task CallResetAfterDelayAsync(CancellationToken token, float autoResetDelay) {
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try {
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await Task.Delay(TimeSpan.FromSeconds(autoResetDelay), token);
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if (!token.IsCancellationRequested)
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ResetStimulus();
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}
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catch (TaskCanceledException) {
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// Expected when Stimulus is called again; do nothing
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}
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}
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protected async void ResetStimulus() {
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//Debug.Log("reset stimulus");
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this.bias = Vector3.zero;
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this.parent?.UpdateFromNucleus(this);
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}
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}
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