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<?php |
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declare(strict_types=1); |
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namespace Phpml\NeuralNetwork; |
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use Phpml\Exception\InvalidArgumentException; |
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use Phpml\NeuralNetwork\Node\Neuron; |
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class Layer |
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{ |
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/** |
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* @var Node[] |
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*/ |
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private $nodes = []; |
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/** |
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* @throws InvalidArgumentException |
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*/ |
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public function __construct(int $nodesNumber = 0, string $nodeClass = Neuron::class, ?ActivationFunction $activationFunction = null) |
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{ |
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if (!in_array(Node::class, class_implements($nodeClass), true)) { |
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throw new InvalidArgumentException('Layer node class must implement Node interface'); |
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} |
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for ($i = 0; $i < $nodesNumber; ++$i) { |
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$this->nodes[] = $this->createNode($nodeClass, $activationFunction); |
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} |
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} |
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public function addNode(Node $node): void |
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{ |
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$this->nodes[] = $node; |
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} |
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/** |
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* @return Node[] |
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*/ |
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public function getNodes(): array |
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{ |
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return $this->nodes; |
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} |
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public function getTrainedCharacteristics(): array |
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{ |
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$result = []; |
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foreach ($this->nodes as $node) { |
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if ($node instanceof Neuron) { |
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$result[] = $node->getTrainedCharacteristics(); |
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} |
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} |
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return $result; |
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} |
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public function setTrainedCharacteristics(array $characteristics): void |
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{ |
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// iterate over the node instances |
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$iNode = -1; |
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for ($i = 0; $i < count($this->nodes); $i++) { |
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$node = $this->nodes[$i]; |
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if ($node instanceof Neuron) { |
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$iNode ++; |
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if (count($characteristics) < $iNode + 1) { |
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throw new InvalidArgumentException('Loaded weights should match the layer structure '); |
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} |
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$node->setTrainedCharacteristics($characteristics[$iNode]); |
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} |
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} |
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} |
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private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null): Node |
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{ |
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if ($nodeClass === Neuron::class) { |
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return new Neuron($activationFunction); |
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} |
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return new $nodeClass(); |
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} |
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} |
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php-ai /
php-ml
If the size of the collection does not change during the iteration, it is generally a good practice to compute it beforehand, and not on each iteration: