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neuralnet.php
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Corrections [Genome+NeuralNetwork+NeuralNetworkCore] + optimization

This commit is contained in:
xdrm-brackets 2016-10-28 15:35:55 +02:00
parent 7aefda0bf0
commit 1c7f4e6566
9 changed files with 54 additions and 216 deletions
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5
build/neuralnetwork/core/Genome.php
View File

@ -4,8 +4,6 @@
use filemanager\core\FileManager;
// FIXME: Propagation of outputNeurons from NeuralNetwork to Genome
class Genome implements \Serializable{
/************************************************
@ -158,7 +156,7 @@
/* (4) Set neurons number */
$this->inputN = $father->inputN;
$this->neurons = $father->neurons;
$this->outputN = $father->inputN;
$this->outputN = $father->outputN;
/* (5) Do random crossover for synapses */
$this->synapses = [];
@ -309,7 +307,6 @@
/* [3] Callback the output layer's values
=========================================================*/
echo $this->outputN;
call_user_func($this->callback, $input, array_slice($neurons, -$this->outputN) );
}

34
build/neuralnetwork/core/NeuralNetworkCore.php
View File

@ -352,8 +352,9 @@
/* [2] Creates the First generation and serialize it
=========================================================*/
/* (1) Initializes data & storage */
$this->gnr = 0;
$this->gnm = 0;
$this->gnr = 0;
$this->gnm = 0;
$this->maxFit = null;
FileManager::write($this->storage['gn']['filename'], '');
FileManager::write($this->storage['ft']['filename'], '');
@ -483,10 +484,31 @@
$ftRead = FileManager::read($this->storage['ft']['filename']);
$fitnesses = explode("\n", trim($ftRead) );
/* (3) Checks if theres a fitness evolution */
/* (3) Checks if fitnessEnd is reached */
$fitnessEnd = max($fitnesses) == $this->fitEnd;
/* (3.1) Stop process and store learned data */
if( $fitnessEnd ){
/* (1) Get the 2 best genomes */
$best = FileManager::readline($this->storage['gn']['filename'], 0);
$best.= FileManager::readline($this->storage['gn']['filename'], 1);
/* (2) Stores data to learnt data */
FileManager::write($this->storage['ln']['filename'], $best);
/* (3) Destroy cursors */
$this->gnr = null;
$this->gnm = null;
return;
}
/* (4) Checks if theres a fitness evolution */
$fitnessEvolution = is_null($this->maxFit) || max($fitnesses) > $this->maxFit;
/* (3.1) If evolution -> choose best + cross-over ... */
/* (4.1) If evolution -> choose best + cross-over ... */
if( $fitnessEvolution ){
// {1} Extract @mother & @father indexes //
@ -496,7 +518,7 @@
$sFather = FileManager::readline($this->storage['gn']['filename'], $iBest[0]);
$sMother = FileManager::readline($this->storage['gn']['filename'], $iBest[1]);
// {3} Unserializes them //
// {4} Unserializes them //
$father = new Genome(2, 2, 2, 2);
$father->unserialize($sFather);
@ -505,7 +527,7 @@
$this->maxFit = max($fitnesses);
/* (3.2) If regression -> renew generation */
/* (4.2) If regression -> renew generation */
}else{
// {1} Extract 2 parents of the current generation //

16
build/neuralnetwork/storage/test/test1.ex
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@ -1,16 +0,0 @@
0,0,0;0
0,0,1;-1
0,1,0;1
0,1,1;0
1,0,0;1
1,0,1;0
1,1,0;2
1,1,1;1
0,0,0;0
0,0,2;-2
0,2,0;2
0,2,2;0
2,0,0;2
2,0,2;0
2,2,0;4
2,2,2;2

67
build/neuralnetwork/storage/test/test1.ft
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@ -1,67 +0,0 @@
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100
build/neuralnetwork/storage/test/test1.gn
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@ -1,100 +0,0 @@
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2
build/neuralnetwork/storage/test/test1.ln
View File

@ -1,2 +0,0 @@
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3,3,3,3;-0.673048732,-0.412463881,-0.736532526,0.829005319,-0.813510365,-0.502031047,0.950266852,0.818343199,0.03824395,0.219597033,-0.339935295,-0.181847521,-0.820436519,-0.762547916,0.165912707,0.799397635,-0.883427944,0.304251916,-0.414343129,0.25450569,-0.472308773,-0.804309556,0.137957493,0.576775783,-0.004366962,-0.494472245,-0.518802319,-0.819242309,0.447490839,0.506983895,0.452629618,-0.248047378,0.468150892,0.291926346,0.947744258,0.536874463,-0.73260191,0.834541621,0.177465943

2
build/neuralnetwork/storage/test/test1.ln.save
View File

@ -1,2 +0,0 @@
3,3,3,3;-0.673048732,-0.412463881,-0.736532526,0.829005319,-0.813510365,-0.502031047,0.950266852,0.818343199,0.03824395,0.219597033,-0.339935295,-0.181847521,-0.820436519,-0.762547916,0.165912707,0.799397635,-0.883427944,0.304251916,-0.414343129,0.25450569,-0.472308773,-0.804309556,0.137957493,0.576775783,-0.004366962,-0.494472245,-0.518802319,-0.819242309,0.447490839,0.506983895,0.452629618,-0.248047378,0.468150892,0.291926346,0.947744258,0.536874463,-0.73260191,0.834541621,0.177465943
3,3,3,3;-0.673048732,-0.412463881,-0.736532526,0.829005319,-0.813510365,-0.502031047,0.950266852,0.818343199,0.03824395,0.219597033,-0.339935295,-0.181847521,-0.820436519,-0.762547916,0.165912707,0.799397635,-0.883427944,0.304251916,-0.414343129,0.25450569,-0.472308773,-0.804309556,0.137957493,0.576775783,-0.004366962,-0.494472245,-0.518802319,-0.819242309,0.447490839,0.506983895,0.452629618,-0.248047378,0.468150892,0.291926346,0.947744258,0.536874463,-0.73260191,0.834541621,0.177465943

1
build/neuralnetwork/storage/test/test1.nn
View File

@ -1 +0,0 @@
{"maxGnr":50,"maxGnm":100,"mutThr":0.005,"fitEnd":1,"numHid":3,"numNeu":3,"inpNeu":3,"outNeu":1,"storage":{"nn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.nn","exists":false},"ex":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ex","exists":false},"gn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.gn","exists":false},"ft":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ft","exists":false},"ln":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ln","exists":false}}}

43
public/main.php
View File

@ -10,7 +10,13 @@
return [($abc[0] + $abc[1] - $abc[2])];
}
if( false && 'learning_process' ){
$train = false;
$guess = !$train;
if( $train && 'learning_process' ){
$part = 1;
@ -22,8 +28,8 @@
=========================================================*/
try{
$nn = NeuralNetwork::load('test/test1');
echo "$part. NeuralNetwork loaded from 'test/test1'\n"; $part++;
$nn = NeuralNetwork::load('test1/test1');
echo "$part. NeuralNetwork loaded from 'test1/test1'\n"; $part++;
/* [2] Else, creates it
=========================================================*/
@ -31,11 +37,12 @@
$nn = NeuralNetwork::create(50, 100);
$nn->setHiddenLayersCount(3);
$nn->setHiddenLayerNeuronsCount(3);
$nn->setInputLayerCount(3);
$nn->setOutputLayerCount(1);
$nn->setMutationThreshold(0.3);
$nn->setHiddenLayersCount(3); // 3 Hidden layers
$nn->setHiddenLayerNeuronsCount(3); // Composed with 3 neurons each
$nn->setInputLayerCount(3); // 3 inputs
$nn->setOutputLayerCount(1); // 1 output
$nn->setMutationThreshold(0.3); // mutation 30% each generation
$nn->setFitnessEnd(0); // Algorith is done when fitness reaches 0
echo "$part. NeuralNetwork configured\n"; $part++;
@ -57,8 +64,8 @@
$d = [2, 2, 2]; $nn->addSample($d, behaviour($d));
echo "$part. Samples added to NeuralNetwork\n"; $part++;
$nn->store('test/test1', true);
echo "$part. NeuralNetwork stored to 'test/test1'\n"; $part++;
$nn->store('test1/test1', true);
echo "$part. NeuralNetwork stored to 'test1/test1'\n"; $part++;
}
@ -69,7 +76,7 @@
$max_fit = 0;
$nn->loadLearningRoutine(function($input, $output){
global $fitness;
$fitness -= abs($output[0] - behaviour($input)[0]);
$fitness -= abs(round($output[0]) - behaviour($input)[0]);
});
echo "$part. Learning routine initialized.\n"; $part++;
@ -93,11 +100,11 @@
/* (2.1) Get current genome */
$g = $nn->getGenome();
echo "\r[x] gnm ".($nn->gnm+1)."/100 on gnr ".($nn->gnr+1)."/50 - max_fit: $max_fit ";
echo "\r[x] gnm ".($nn->gnm+1)."/100 on gnr ".($nn->gnr+1)."/50 - max_fit: $max_fit ";
/* (2.2) Train genome with random samples */
for( $r = 0 ; $r < 100 ; $r++ )
$g->train([rand(0,10), rand(0,10), rand(0,10)]);
$g->train([rand(0,100), rand(0,100), rand(0,100)]);
/* (2.3) Set fitness & go to next genome */
if( $fitness > $max_fit ) $max_fit = $fitness;
@ -116,7 +123,7 @@
if( $nn->gnr > $last_gnr)
echo "\n\t".((microtime(true)-$start))."s\n";
if( $nn->gnr == 50-1 )
if( is_null($nn->gnr) || $nn->gnr == 50-1 )
break;
}
@ -125,7 +132,7 @@
}
if( true && 'guessing_process' ){
if( $guess && 'guessing_process' ){
$part = 1;
@ -136,8 +143,8 @@
=========================================================*/
try{
$nn = NeuralNetwork::load('test/test1');
echo "$part. NeuralNetwork loaded from 'test/test1'\n"; $part++;
$nn = NeuralNetwork::load('test1/test1');
echo "$part. NeuralNetwork loaded from 'test1/test1'\n"; $part++;
/* [2] Else, creates it
=========================================================*/
@ -157,7 +164,7 @@
echo "callback result: ".implode(',', behaviour($in))."\n";
});
$genome->train([rand(0,10), rand(0,10), rand(0,10)]);
$genome->train([rand(0,100), rand(0,100), rand(0,100)]);