Differences Between: [Versions 310 and 400] [Versions 311 and 400] [Versions 39 and 400]
1 <?php 2 3 declare(strict_types=1); 4 5 namespace Phpml\NeuralNetwork\Training; 6 7 use Phpml\NeuralNetwork\Node\Neuron; 8 use Phpml\NeuralNetwork\Training\Backpropagation\Sigma; 9 10 class Backpropagation 11 { 12 /** 13 * @var float 14 */ 15 private $learningRate; 16 17 /** 18 * @var array 19 */ 20 private $sigmas = []; 21 22 /** 23 * @var array 24 */ 25 private $prevSigmas = []; 26 27 public function __construct(float $learningRate) 28 { 29 $this->setLearningRate($learningRate); 30 } 31 32 public function setLearningRate(float $learningRate): void 33 { 34 $this->learningRate = $learningRate; 35 } 36 37 public function getLearningRate(): float 38 { 39 return $this->learningRate; 40 } 41 42 /** 43 * @param mixed $targetClass 44 */ 45 public function backpropagate(array $layers, $targetClass): void 46 { 47 $layersNumber = count($layers); 48 49 // Backpropagation. 50 for ($i = $layersNumber; $i > 1; --$i) { 51 $this->sigmas = []; 52 foreach ($layers[$i - 1]->getNodes() as $key => $neuron) { 53 if ($neuron instanceof Neuron) { 54 $sigma = $this->getSigma($neuron, $targetClass, $key, $i == $layersNumber); 55 foreach ($neuron->getSynapses() as $synapse) { 56 $synapse->changeWeight($this->learningRate * $sigma * $synapse->getNode()->getOutput()); 57 } 58 } 59 } 60 61 $this->prevSigmas = $this->sigmas; 62 } 63 64 // Clean some memory (also it helps make MLP persistency & children more maintainable). 65 $this->sigmas = []; 66 $this->prevSigmas = []; 67 } 68 69 private function getSigma(Neuron $neuron, int $targetClass, int $key, bool $lastLayer): float 70 { 71 $neuronOutput = $neuron->getOutput(); 72 $sigma = $neuron->getDerivative(); 73 74 if ($lastLayer) { 75 $value = 0; 76 if ($targetClass === $key) { 77 $value = 1; 78 } 79 80 $sigma *= ($value - $neuronOutput); 81 } else { 82 $sigma *= $this->getPrevSigma($neuron); 83 } 84 85 $this->sigmas[] = new Sigma($neuron, $sigma); 86 87 return $sigma; 88 } 89 90 private function getPrevSigma(Neuron $neuron): float 91 { 92 $sigma = 0.0; 93 94 foreach ($this->prevSigmas as $neuronSigma) { 95 $sigma += $neuronSigma->getSigmaForNeuron($neuron); 96 } 97 98 return $sigma; 99 } 100 }
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