From da50b0320206621406d21fe8cb121aacc0bfbc5b Mon Sep 17 00:00:00 2001 From: xdrm-brackets Date: Thu, 27 Oct 2016 18:34:28 +0200 Subject: [PATCH] Gestion de quasi-tout -> FONCTIONNELLLLLLL --- build/filemanager/core/FileManager.php | 54 +- build/neuralnetwork/core/Genome.php | 55 +- build/neuralnetwork/core/NeuralNetwork.php | 8 +- .../neuralnetwork/core/NeuralNetworkCore.php | 262 ++++- build/neuralnetwork/storage/_buffer.ex | 8 - .../storage/{_buffer.ln => _buffer.ft} | 0 .../storage/{test/test1.ln => _buffer.gn} | 0 build/neuralnetwork/storage/test/test1.ex | 8 + build/neuralnetwork/storage/test/test1.ft | 520 +++++++++ build/neuralnetwork/storage/test/test1.gn | 1000 +++++++++++++++++ build/neuralnetwork/storage/test/test1.nn | 2 +- config/neural-network.json | 1 - public/main.php | 113 +- 13 files changed, 1919 insertions(+), 112 deletions(-) rename build/neuralnetwork/storage/{_buffer.ln => _buffer.ft} (100%) rename build/neuralnetwork/storage/{test/test1.ln => _buffer.gn} (100%) create mode 100644 build/neuralnetwork/storage/test/test1.ft create mode 100644 build/neuralnetwork/storage/test/test1.gn diff --git a/build/filemanager/core/FileManager.php b/build/filemanager/core/FileManager.php index 3ea4c7b..0a3e58d 100644 --- a/build/filemanager/core/FileManager.php +++ b/build/filemanager/core/FileManager.php @@ -23,7 +23,7 @@ try{ fclose( fopen($file, 'w') ); return true; - }catch(Exception $e){ return false; } + }catch(\Exception $e){ return false; } } @@ -35,7 +35,7 @@ public static function read($file){ /* (0) Checks arguments */ if( !is_string($file) ) - throw new \Error('Wrong argument for read().'); + throw new \Exception('Wrong argument for read().'); /* (1) Initializing driver on file (read-flag) */ $driver = new \SplFileObject($file, 'r'); @@ -53,6 +53,54 @@ return $read; } + /* READS A FILE'S SPECIFIC LINE + * + * @file File to read + * @line Line to read + * + */ + public static function readline($file, $line){ + /* (0) Checks arguments */ + if( !is_string($file) || intval($line) !== $line ) + throw new \Exception('Wrong argument for readline(, ).'); + + /* (1) Initializing driver on file (read-flag) */ + $driver = new \SplFileObject($file, 'r'); + + /* (2) Goto specific line */ + $driver->seek($line); + + /* (3) Return line's content */ + if( $driver->key() == $line ) + return $driver->current(); + else + return null; + } + + /* WRITES A FILE'S SPECIFIC LINE + * + * @file File to read + * @line Line to read + * + */ + public static function writeline($file, $line){ + /* (0) Checks arguments */ + if( !is_string($file) || intval($line) !== $line ) + throw new \Exception('Wrong argument for writeline(, ).'); + + /* (1) Initializing driver on file (read-flag) */ + $driver = new \SplFileObject($file, 'r'); + + /* (2) Goto specific line */ + $driver->seek($line); + + /* (3) Return line's content */ + if( $driver->key() == $line ) + return $driver->current(); + else + return null; + } + /* WRITES CONTENT TO A FILE * @@ -72,7 +120,7 @@ /* (1) Erase file */ try{ fclose( fopen($file, 'w') ); - }catch(Exception $e){ return false; } + }catch(\Exception $e){ return false; } /* (2) Get driver (write-flag) */ $driver = new \SplFileObject($file, 'r+'); diff --git a/build/neuralnetwork/core/Genome.php b/build/neuralnetwork/core/Genome.php index d7ae481..551d09d 100644 --- a/build/neuralnetwork/core/Genome.php +++ b/build/neuralnetwork/core/Genome.php @@ -54,23 +54,24 @@ $argv = func_get_args(); $argc = count($argv); - - /* (2) If CrossoverCreation */ - if( $argc > 1 && $argv[0] instanceof Genome && $argv[1] instanceof Genome ) - $this->construct_crossover($argv[0], $argv[1]); - - /* (3) If RandomCreation */ - else if( $argc > 3 && is_numeric($argv[0]) && is_numeric($argv[1]) && is_numeric($argv[2]) && is_numeric($argv[3]) ) + /* (2) If RandomCreation */ + if( $argc > 3 && is_numeric($argv[0]) && is_numeric($argv[1]) && is_numeric($argv[2]) && is_numeric($argv[3]) ) $this->construct_new($argv[0], $argv[1], $argv[2], $argv[3]); + /* (3) If CrossoverCreation */ + else if( $argc > 1 && $argv[0] instanceof Genome && $argv[1] instanceof Genome ) + $this->construct_crossover($argv[0], $argv[1]); + /* (4) If InheritanceCreation (clone) */ else if( $argc > 0 && $argv[0] instanceof Genome ) $this->construct_inheritance($argv[0]); /* (5) If no match */ else - throw new \Error('Invalid Genome constructor\'s arguments.'); + throw new \Exception('Invalid Genome constructor\'s arguments.'); + /* (6) Default values */ + $this->fitness = null; $this->callback = function(){}; } @@ -159,7 +160,7 @@ /* (5) Do random crossover for synapses */ $this->synapses = []; - for( $i = 0, $l = $this->neurons*($this->inputN+$this->outputN+$this->neurons*$this->layers) ; $i < $l ; $i++ ) + for( $i = 0, $l = count($mother->synapses) ; $i < $l ; $i++ ) if( !!rand(0,1) ) $this->synapses[$i] = $father->synapses[$i]; else $this->synapses[$i] = $mother->synapses[$i]; @@ -180,7 +181,7 @@ public function setCallback($callback=null){ /* (1) Checks @callback argument */ if( !is_callable($callback) ) - throw new \Error('Wrong argument for Genome\'s callback function.'); + throw new \Exception('Wrong argument for Genome\'s callback function.'); /* (2) Set callback function */ $this->callback = $callback; @@ -194,13 +195,27 @@ public function setFitness($fitness=null){ /* (1) Checks @fitness argument */ if( !is_numeric($fitness) ) - throw new \Error('Wrong argument for specifying Genome\'s fitness.'); + throw new \Exception('Wrong argument for specifying Genome\'s fitness.'); /* (2) Set fitness */ $this->fitness = floatval($fitness); } + /************************************************ + **** Getter **** + ************************************************/ + + /* RETURNS THE FITNESS OF THE GENOME + * + * @return fitness Current fitness (or NULL if not defined) + * + */ + public function getFitness(){ + return $this->fitness; + } + + /************************************************ **** Genome Actions **** ************************************************/ @@ -213,10 +228,10 @@ public function mutation($threshold=0.5){ /* (1) Checks @threshold argument */ if( floatval($threshold) !== $threshold || $threshold < 0 || $threshold > 1 ) - throw new \Error('Invalid threshold for Genome mutation.'); + throw new \Exception('Invalid threshold for Genome mutation.'); /* (2) Calculates how many neurons/synapses to mutate */ - $synapsesMutations = round( (count($this->synapses) - 1) * $threshold ); + $synapsesMutations = round( (count($this->synapses) - 1) * rand(0, $threshold*self::MAX)/self::MAX ); /* (3) Choose random synapses' indexes */ $iSynapses = []; @@ -243,7 +258,7 @@ public function train($input=null, $callback=null){ /* (1) Checks @input argument */ if( !is_array($input) || count($input) !== $this->inputN ) - throw new \Error('Invalid @input for Genome\'s training.'); + throw new \Exception('Invalid @input for Genome\'s training.'); /* (2) Checks optional @callback argument */ if( is_callable($callback) ) @@ -366,7 +381,7 @@ /* (3) If between hidden/output */ }else if( $layer == $this->layers+1 ){ - $offset = $this->neurons * ($this->inputN+$this->neurons*$this->layers); + $offset = $this->neurons * ($this->inputN+$this->neurons*($this->layers-1)); for( $s = $offset+$neuron, $sl = $offset+$this->neurons*$this->outputN ; $s < $sl ; $s += $this->outputN ) yield $this->inputN+$this->neurons*($this->layers-1) + ($s-$offset-$neuron)/$this->outputN => $s; @@ -408,21 +423,21 @@ */ public function unserialize($serialized){ /* (1) Segmenting data */ - $segments = explode(';', $serialized); + $segments = explode(';', trim($serialized) ); // Manage segmentation error - if( count($segments) < 3 ) - throw new \Error('Format error during Genome unserialization.'); + if( count($segments) < 2 ) + throw new \Exception('Format error during Genome unserialization.'); /* (2) Get global attributes */ $globals = explode(',', $segments[0]); if( count($globals) < 4 ) - throw new \Error('Format error during Genome unserialization.'); + throw new \Exception('Format error during Genome unserialization.'); $this->layers = intval($globals[0]); $this->inputN = intval($globals[1]); - $this->layers = intval($globals[2]); + $this->neurons = intval($globals[2]); $this->outputN = intval($globals[3]); /* (3) Get synapses values */ diff --git a/build/neuralnetwork/core/NeuralNetwork.php b/build/neuralnetwork/core/NeuralNetwork.php index 370f669..6d280a3 100644 --- a/build/neuralnetwork/core/NeuralNetwork.php +++ b/build/neuralnetwork/core/NeuralNetwork.php @@ -34,14 +34,14 @@ /* (1) Checks argument */ if( is_null($storage=NeuralNetworkCore::getStorage($storage)) ) - throw new Error('Wrong NeuralNetwork loader\'s argument.'); + throw new \Exception('Wrong NeuralNetwork loader\'s argument.'); /* (2) If files doesn't exist, raise error */ - if( !$storage[0]['exists'] || !$storage[1]['exists'] || !$storage[2]['exists'] ) - throw new Error('Loaded storage have file(s) missing.'); + if( !$storage['nn']['exists'] ) + throw new \Exception('Loaded storage have file(s) missing.'); /* (3) Unserialize last NeuralNetwork */ - $last_network = FileManager::read($storage[0]['filename']); + $last_network = FileManager::read($storage['nn']['filename']); /* (4) Creates and fill instance */ $instance = new NeuralNetworkCore(0, 0); diff --git a/build/neuralnetwork/core/NeuralNetworkCore.php b/build/neuralnetwork/core/NeuralNetworkCore.php index d8b6c99..3808e5f 100644 --- a/build/neuralnetwork/core/NeuralNetworkCore.php +++ b/build/neuralnetwork/core/NeuralNetworkCore.php @@ -11,21 +11,22 @@ ************************************************/ private $maxGnr; // Maximum generation iterations private $maxGnm; // Maximum genomes per generation - private $kptGnm; // Number of genomes kept for each generation private $mutThr; // Mutation threshold private $fitEnd; // Fitness range to end process private $numHid; // Number of hidden layer(s) private $numNeu; // Number of neurons for each hidden layer + private $inpNeu; // Number of input neurons + private $outNeu; // Number of output neurons - private $storage; // path to storage + private $storage; // path to storage + private $callback; // callback training function /************************************************ **** LOCAL ATTRIBUTES **** ************************************************/ - private $gnr; // Current generation index - private $gmns; // Current generation's genomes - private $gnm; // Current genome index - private $fit; // Current fitness + public $gnr; // Current generation index + public $gnm; // Current genome index + private $genome; // Current genome instance @@ -70,15 +71,18 @@ /* (2) Checks file's existence and returns it */ return [ - [ + 'nn' => [ 'filename' => $absolute_path.'.nn', // will contain neural network data 'exists' => is_file($absolute_path.'.nn') - ],[ + ], 'ex' => [ 'filename' => $absolute_path.'.ex', // will contain samples 'exists' => is_file($absolute_path.'.ex') - ],[ - 'filename' => $absolute_path.'.ln', // will contain values & weights - 'exists' => is_file($absolute_path.'.ln') + ], 'gn' => [ + 'filename' => $absolute_path.'.gn', // will contain genomes of the generation + 'exists' => is_file($absolute_path.'.gn') + ], 'ft' => [ + 'filename' => $absolute_path.'.ft', // will contain genomes' fitness + 'exists' => is_file($absolute_path.'.ft') ] ]; @@ -107,17 +111,16 @@ /* (2) Default attributes */ $default = self::conf()['default']; - $this->setKeptGenomes($default['genomes_kept']); // default value $this->setMutationThreshold($default['mutation_threshold']); // default value $this->setFitnessEnd($default['fitness_end']); // default value $this->setHiddenLayersCount($default['hidden_layers']); // default value $this->setHiddenLayerNeuronsCount($default['layer_neurons']); // default value $this->max = null; // default value $this->setStorage($default['storage']); // default value + $this->callback = function(){}; // default value } - /************************************************ **** Attributes Setters **** ************************************************/ @@ -146,12 +149,12 @@ /* [2] Initializes files =========================================================*/ /* (1) Creates directory/ies */ - if( !is_dir(dirname(($this->storage[0]['filename']))) ) - mkdir( dirname($this->storage[0]['filename']), 0775, true ); + if( !is_dir(dirname(($this->storage['nn']['filename']))) ) + mkdir( dirname($this->storage['nn']['filename']), 0775, true ); // Checks - if( !is_dir(dirname(($this->storage[0]['filename']))) ) - throw new \Error('Error creating directory: '.dirname(($this->storage[0]['filename']))); + if( !is_dir(dirname(($this->storage['nn']['filename']))) ) + throw new \Exception('Error creating directory: '.dirname(($this->storage['nn']['filename']))); /* (2) Creates files */ foreach($this->storage as $file) @@ -215,14 +218,49 @@ $this->numHid = $numHid; } + /* SET NUMBER OF NEURONS OF THE INPUT LAYER + * + * @inpNeu Number of neurons for the input layer + * + */ + public function setInputLayerCount($inpNeu){ + if( abs(intval($inpNeu)) !== $inpNeu ) return; + + $this->inpNeu = $inpNeu; + } + + /* SET NUMBER OF NEURONS OF THE OUTPUT LAYER + * + * @outNeu Number of neurons for the output layer + * + */ + public function setOutputLayerCount($outNeu){ + if( abs(intval($outNeu)) !== $outNeu ) return; + + $this->outNeu = $outNeu; + } + /************************************************ **** Sample Setters **** ************************************************/ /* ADD SAMPLE TO THE NEURAL NETWORK + * + * @input Set of input of the sample + * @output Set of output of the sample + * + */ public function addSample($input, $output){ - FileManager::append( $this->storage[1]['filename'], implode(',',$input) .';'. implode(',',$output) ); + /* (1) Checks number of input neurons */ + if( !is_array($input) || is_null($this->inpNeu) || count($input) != $this->inpNeu ) + throw new \Exception('Wrong @input argument for addSample() method.'); + + /* (2) Checks number of output neurons */ + if( !is_array($output) || is_null($this->outNeu) || count($output) != $this->outNeu ) + throw new \Exception('Wrong @output argument for addSample() method.'); + + FileManager::append( $this->storage['ex']['filename'], implode(',',$input) .';'. implode(',',$output) ); } @@ -245,9 +283,9 @@ $storage = self::getStorage($path); /* (2) Checks if files doesn't exist */ - if( $storage[0]['exists'] || $storage[1]['exists'] || $storage[2]['exists'] ) + if( $storage['nn']['exists'] ) if( !$override ) - throw new \Error('This storage already exists, you can only load() it.'); + throw new \Exception('This storage already exists, you can only load() it.'); /* [2] Creates storage & its files @@ -264,65 +302,185 @@ /* [3] Stores data =========================================================*/ /* (1) Stores NeuralNetwork state (attributes) */ - FileManager::write($storage[0]['filename'], $this->serialize()); + FileManager::write($storage['nn']['filename'], $this->serialize()); /* (2) Stores samples */ - FileManager::write($storage[1]['filename'], FileManager::read($last_storage[1]['filename'])); + FileManager::write($storage['ex']['filename'], FileManager::read($last_storage['ex']['filename'])); /* (3) Stores NeuralNetwork values & weights */ - FileManager::write($storage[2]['filename'], FileManager::read($last_storage[2]['filename'])); + FileManager::write($storage['gn']['filename'], FileManager::read($last_storage['gn']['filename'])); } - - /* STARTS THE LEARNING ROUTINE + /* INITIALIZES THE LEARNING ROUTINE * * @callback Callback function to display current state * */ - public function learn($callback=null){ + public function initLearningRoutine($callback=null){ /* [1] Manages @callback argument =========================================================*/ if( !is_callable($callback) ) - $callback = function(){}; + $this->callback = function(){}; + else + $this->callback = $callback; - /* [2] Creates the neural network + /* [2] Creates the First generation and serialize it =========================================================*/ - // best of last generation - $best = null; + /* (1) Initializes data & storage */ + $this->gnr = 0; + $this->gnm = 0; + FileManager::write($this->storage['gn']['filename'], ''); + FileManager::write($this->storage['ft']['filename'], ''); + + /* (2) Stores random genomes to storage */ + for( $g = 0 ; $g < $this->maxGnm ; $g++ ){ + $gnm = new Genome($this->numHid, $this->numNeu, $this->inpNeu, $this->outNeu); + FileManager::append($this->storage['gn']['filename'], $gnm->serialize()); + } + + } + + /* RETURNS THE CURRENT GENOME + * + * @return genome Returns the current genome + * + */ + public function getGenome(){ + /* (1) Checks if learning routine has beem started */ + if( !is_numeric($this->gnm) ) + throw new \Exception('Learning routine closed.'); + + /* (2) Reads the current genome from storage */ + $serialized = FileManager::readline($this->storage['gn']['filename'], $this->gnm); + + /* (3) Unserializes genome */ + $this->genome = new Genome(2, 2, 2, 2); + + try{ + + $this->genome->unserialize($serialized); + $this->genome->setCallback($this->callback); + + return $this->genome; + + /* (4) If error */ + }catch(Exception $e){ return null; } + + } + + /* ITERATES TO THE NEXT GENOME (IF SAME GENERATION) + * + */ + public function nextGenome(){ + /* (0) Checks if Genome's fitness has been set + ---------------------------------------------------------*/ + if( !($this->genome instanceof Genome) || is_null($this->genome->getFitness()) ) + throw new \Exception('The learning routine is closed.'); + + /* (1) Stores fitness */ + FileManager::append($this->storage['ft']['filename'], strval($this->genome->getFitness()) ); - /* (1) For each generation - ---------------------------------------------------------*/ - for( $this->gnr = 0 ; $this->gnr < $this->maxGnr ; $this->gnr++ ){ + /* (1) Iterates if possible + ---------------------------------------------------------*/ + if( $this->gnm < $this->maxGnm-1 ){ - /* (1) Initializes genome list for current generation */ - $this->gnms = []; + $this->gnm++; - /* (2) For each genome of the generation */ - for( $this->gnm = 0 ; $this->gnm < $this->maxGnm ; $this->gnm++ ){ + /* (2) If must change generation + ---------------------------------------------------------*/ + }else if( $this->gnr < $this->maxGnr-1 ){ - // {2.1} First Generation -> random genomes // - if( $this->gnr === 0 ) - $this->gnms[$this->gnm] = new Genome($this->numHid, $this->numNeu); + /* (1) Update generation & genome indexes */ + $this->gnr++; + $this->gnm = 0; - // {2.2} Others generations -> crossover + mutation // - else{ - $this->gnms[$this->gnm] = new Genome($best['father'], $best['mother']); - $this->gnms[$this->gnm]->mutation($this->mutThr); - } + /* (2) Fetch the whole generation fitness values */ + $ftRead = FileManager::read($this->storage['ft']['filename']); + $fitnesses = explode("\n", trim($ftRead) ); - /* (3) Calculate fitness */ - // ... blablabla + /* (3) Extract @mother & @father indexes */ + $iBest = $this->bestFitnesses($fitnesses); + + /* (4) Extract best 2 genomes */ + $sFather = FileManager::readline($this->storage['gn']['filename'], $iBest[0]); + $sMother = FileManager::readline($this->storage['gn']['filename'], $iBest[1]); + + /* (5) Unserializes them */ + $father = new Genome(2, 2, 2, 2); + $father->unserialize($sFather); + + $mother = new Genome(2, 2, 2, 2); + $mother->unserialize($sMother); + + /* (6) Create new generation */ + FileManager::write($this->storage['gn']['filename'], ''); + FileManager::write($this->storage['ft']['filename'], ''); + + for( $g = 0 ; $g < $this->maxGnm ; $g++ ){ + + // {6.1} Re-use father // + if( $g == 0 ) + FileManager::append($this->storage['gn']['filename'], $father->serialize()); + + // {6.2} Re-use mother // + else if( $g == 1 ) + FileManager::append($this->storage['gn']['filename'], $mother->serialize()); + + // {6.3} Do cross-over + mutation for the rest // + else{ + $gnm = new Genome($father, $mother); + $gnm->mutation($this->mutThr); + FileManager::append($this->storage['gn']['filename'], $gnm->serialize()); } } - // TODO: Select best genomes based on fitness - $best = null; + /* (3) If end of process + ---------------------------------------------------------*/ + }else{ + $this->gnr = null; + $this->gnm = null; + } } + /************************************************ + **** Utility **** + ************************************************/ + + /* RETURNS THE 2 BEST FITNESSES FROM A LIST + * + * @fitnesses List of indexes fitnesses + * + * @return best List of the 2 indexes of the best fitnesses + * + */ + private static function bestFitnesses($fitnesses=null){ + /* (1) Checks @fitnesses argument */ + if( !is_array($fitnesses) ) + throw new \Exception('Fitness list format error.'); + + /* (1) Find father (best) + ---------------------------------------------------------*/ + /* (1) Select greatest fitness value */ + arsort($fitnesses); + + /* (2) Attributes @father & @mother indexes */ + $iFather = null; + $iMother = null; + $c = 0; + foreach($fitnesses as $k=>$v){ + if( $c == 0 ) $iFather = $k; + else if( $c == 1 ) $iMother = $k; + else break; + + $c++; + } + + return [ $iFather, $iMother ]; + } /************************************************ **** Serialization Methods **** @@ -340,11 +498,12 @@ /* (2) Adding attributes */ $json['maxGnr'] = $this->maxGnr; $json['maxGnm'] = $this->maxGnm; - $json['kptGnm'] = $this->kptGnm; $json['mutThr'] = $this->mutThr; $json['fitEnd'] = $this->fitEnd; $json['numHid'] = $this->numHid; $json['numNeu'] = $this->numNeu; + $json['inpNeu'] = $this->inpNeu; + $json['outNeu'] = $this->outNeu; $json['storage'] = $this->storage; @@ -368,11 +527,12 @@ /* (3) Attributing json attributes */ $this->maxGnr = $json['maxGnr']; $this->maxGnm = $json['maxGnm']; - $this->kptGnm = $json['kptGnm']; $this->mutThr = $json['mutThr']; $this->fitEnd = $json['fitEnd']; $this->numHid = $json['numHid']; $this->numNeu = $json['numNeu']; + $this->inpNeu = $json['inpNeu']; + $this->outNeu = $json['outNeu']; $this->storage = $json['storage']; } diff --git a/build/neuralnetwork/storage/_buffer.ex b/build/neuralnetwork/storage/_buffer.ex index 6eee4ae..e69de29 100644 --- a/build/neuralnetwork/storage/_buffer.ex +++ b/build/neuralnetwork/storage/_buffer.ex @@ -1,8 +0,0 @@ -0,0,0;0,0 -0,0,1;0,1 -0,1,0;0,1 -0,1,1;0,1 -1,0,0;0,0 -1,0,1;0,1 -1,1,0;1,1 -1,1,1;1,1 diff --git a/build/neuralnetwork/storage/_buffer.ln b/build/neuralnetwork/storage/_buffer.ft similarity index 100% rename from build/neuralnetwork/storage/_buffer.ln rename to build/neuralnetwork/storage/_buffer.ft diff --git a/build/neuralnetwork/storage/test/test1.ln b/build/neuralnetwork/storage/_buffer.gn similarity index 100% rename from build/neuralnetwork/storage/test/test1.ln rename to build/neuralnetwork/storage/_buffer.gn diff --git a/build/neuralnetwork/storage/test/test1.ex b/build/neuralnetwork/storage/test/test1.ex index 6eee4ae..ff00d08 100644 --- a/build/neuralnetwork/storage/test/test1.ex +++ b/build/neuralnetwork/storage/test/test1.ex @@ -6,3 +6,11 @@ 1,0,1;0,1 1,1,0;1,1 1,1,1;1,1 +0,0,0;0,0 +0,0,2;0,2 +0,2,0;0,2 +0,2,2;0,2 +2,0,0;0,0 +2,0,2;0,2 +2,2,0;2,2 +2,2,2;2,2 diff --git a/build/neuralnetwork/storage/test/test1.ft b/build/neuralnetwork/storage/test/test1.ft new file mode 100644 index 0000000..518816c --- /dev/null +++ b/build/neuralnetwork/storage/test/test1.ft @@ -0,0 +1,520 @@ +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +2 +0 +0 +0 +0 +2 +0 +0 +0 +2 +0 +0 +0 +0 +0 +2 +2 +2 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +2 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +2 +0 +2 +0 +0 +2 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +2 +0 +0 +0 +2 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +2 +0 +0 +0 +0 +0 +2 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 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+2,3,3,3;0.489367723,0.373852628,0.239922459,0.672568113,0.74743934,0.49451507,0.293227933,0.27147136,0.320482195,0.378596779,0.675956641,0.342882078,0.746073832,0.55932817,0.672437548,0.071564074,0.626241537,0.258591118,0.759008232,0.137727608,0.261560443,0.549053744,0.945607863,0.497516644,0.05312679,0.682280646,0.094376912,0.855278267,0.266248062,0.567149395,0.284875234,0.402556257,0.953890443 diff --git a/build/neuralnetwork/storage/test/test1.nn b/build/neuralnetwork/storage/test/test1.nn index 850bff2..05d45af 100644 --- a/build/neuralnetwork/storage/test/test1.nn +++ b/build/neuralnetwork/storage/test/test1.nn @@ -1 +1 @@ -{"maxGnr":50,"maxGnm":100,"kptGnm":2,"mutThr":0.3,"fitEnd":1,"numHid":2,"numNeu":3,"max":{"input":[1,1,1],"output":[1,1]},"storage":[{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.nn","exists":false},{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ex","exists":false},{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ln","exists":false}]} \ No newline at end of file +{"maxGnr":50,"maxGnm":1000,"kptGnm":2,"mutThr":0.3,"fitEnd":1,"numHid":2,"numNeu":3,"inpNeu":3,"outNeu":2,"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}}} \ No newline at end of file diff --git a/config/neural-network.json b/config/neural-network.json index 1e02176..e420d7a 100644 --- a/config/neural-network.json +++ b/config/neural-network.json @@ -2,7 +2,6 @@ "storage_parent": "/build/neuralnetwork/storage", "default": { - "genomes_kept": 2, "mutation_threshold": 0.3, "fitness_end": 1, "storage": "_buffer", diff --git a/public/main.php b/public/main.php index ff22ac0..c48068e 100644 --- a/public/main.php +++ b/public/main.php @@ -10,38 +10,103 @@ return [($abc[0] & $abc[1]), $abc[1] | $abc[2]]; } - if( false && 'test_creating_dataset' ){ + if( true && 'test_creating_dataset' ){ + + $part = 1; echo "Welcome to neural-network.php\n"; - echo "-----------------------------\n"; + echo "-----------------------------\n\n"; - $nn = NeuralNetwork::create(50, 100); + /* [1] Trying to load neural network + =========================================================*/ + try{ - $nn->setHiddenLayersCount(2); - $nn->setHiddenLayerNeuronsCount(3); + $nn = NeuralNetwork::load('test/test1'); + echo "$part. NeuralNetwork loaded from 'test/test1'\n"; $part++; - $d = [0, 0, 0]; $nn->addSample($d, behaviour($d)); - $d = [0, 0, 1]; $nn->addSample($d, behaviour($d)); - $d = [0, 1, 0]; $nn->addSample($d, behaviour($d)); - $d = [0, 1, 1]; $nn->addSample($d, behaviour($d)); - $d = [1, 0, 0]; $nn->addSample($d, behaviour($d)); - $d = [1, 0, 1]; $nn->addSample($d, behaviour($d)); - $d = [1, 1, 0]; $nn->addSample($d, behaviour($d)); - $d = [1, 1, 1]; $nn->addSample($d, behaviour($d)); - $d = [0, 0, 0]; $nn->addSample($d, behaviour($d)); - $d = [0, 0, 2]; $nn->addSample($d, behaviour($d)); - $d = [0, 2, 0]; $nn->addSample($d, behaviour($d)); - $d = [0, 2, 2]; $nn->addSample($d, behaviour($d)); - $d = [2, 0, 0]; $nn->addSample($d, behaviour($d)); - $d = [2, 0, 2]; $nn->addSample($d, behaviour($d)); - $d = [2, 2, 0]; $nn->addSample($d, behaviour($d)); - $d = [2, 2, 2]; $nn->addSample($d, behaviour($d)); + /* [2] Else, creates it + =========================================================*/ + }catch(\Exception $e){ + + $nn = NeuralNetwork::create(50, 1000); + + $nn->setHiddenLayersCount(4); + $nn->setHiddenLayerNeuronsCount(3); + $nn->setInputLayerCount(3); + $nn->setOutputLayerCount(2); + + echo "$part. NeuralNetwork configured\n"; $part++; + + $d = [0, 0, 0]; $nn->addSample($d, behaviour($d)); + $d = [0, 0, 1]; $nn->addSample($d, behaviour($d)); + $d = [0, 1, 0]; $nn->addSample($d, behaviour($d)); + $d = [0, 1, 1]; $nn->addSample($d, behaviour($d)); + $d = [1, 0, 0]; $nn->addSample($d, behaviour($d)); + $d = [1, 0, 1]; $nn->addSample($d, behaviour($d)); + $d = [1, 1, 0]; $nn->addSample($d, behaviour($d)); + $d = [1, 1, 1]; $nn->addSample($d, behaviour($d)); + $d = [0, 0, 0]; $nn->addSample($d, behaviour($d)); + $d = [0, 0, 2]; $nn->addSample($d, behaviour($d)); + $d = [0, 2, 0]; $nn->addSample($d, behaviour($d)); + $d = [0, 2, 2]; $nn->addSample($d, behaviour($d)); + $d = [2, 0, 0]; $nn->addSample($d, behaviour($d)); + $d = [2, 0, 2]; $nn->addSample($d, behaviour($d)); + $d = [2, 2, 0]; $nn->addSample($d, behaviour($d)); + $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++; + + } + + + /* [2] Initializing learning routine + =========================================================*/ + $fitness = 0; + $max_fit = 0; + $nn->initLearningRoutine(function($input, $output){ + global $fitness; + if( $output[0] == behaviour($input)[0] ) $fitness++; + if( $output[1] == behaviour($input)[1] ) $fitness++; + }); + echo "$part. Learning routine initialized.\n"; $part++; + + + /* [3] Learning through generations and genomes + =========================================================*/ + /* (1) For each generation */ + for( $gnr = 0 ; $gnr < 50 ; $gnr++ ){ + + /* (2) For each genome */ + for( $gnm = 0 ; $gnm < 1000 ; $gnm++ ){ + $fitness = 0; + + /* (2.1) Get current genome */ + $g = $nn->getGenome(); + echo "\r[x] genome ".($nn->gnm+1)."/1000 on generation ".($nn->gnr+1)."/50 - max fitness: $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)]); + + /* (2.3) Set fitness & go to next genome */ + if( $fitness > $max_fit ) $max_fit = $fitness; + + $g->setFitness($fitness); + $nn->nextGenome(); + } + + } - $nn->store('test/test1', true); } + + + + if( false && 'load_neural_network' ){ $nn = NeuralNetwork::load('test/test1'); @@ -50,7 +115,7 @@ if( false && 'test_genomes' ){ /* (1) Basic Creation */ - $a = new Genome(2, 3); // 2 layers of 3 neurons each -> randomly filled + $a = new Genome(2, 3, 3, 2); // 2 layers of 3 neurons each -> randomly filled echo "A : ".$a->serialize()."\n"; @@ -72,7 +137,7 @@ } - if( true ){ + if( false ){ $g = new Genome(2, 3, 3, 2); $fitness = 0;