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1 | <?php |
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2 | |||
3 | declare(strict_types=1); |
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4 | |||
5 | namespace Phpml\NeuralNetwork\Node; |
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6 | |||
7 | use Phpml\NeuralNetwork\ActivationFunction; |
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8 | use Phpml\NeuralNetwork\ActivationFunction\Sigmoid; |
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9 | use Phpml\NeuralNetwork\Node; |
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10 | use Phpml\NeuralNetwork\Node\Neuron\Synapse; |
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11 | |||
12 | class Neuron implements Node |
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13 | { |
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14 | /** |
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15 | * @var Synapse[] |
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16 | */ |
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17 | protected $synapses = []; |
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18 | |||
19 | /** |
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20 | * @var ActivationFunction |
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21 | */ |
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22 | protected $activationFunction; |
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23 | |||
24 | /** |
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25 | * @var float |
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26 | */ |
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27 | protected $output = 0.0; |
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28 | |||
29 | /** |
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30 | * @var float |
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31 | */ |
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32 | protected $z = 0.0; |
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33 | |||
34 | public function __construct(?ActivationFunction $activationFunction = null) |
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35 | { |
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36 | $this->activationFunction = $activationFunction ?: new Sigmoid(); |
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37 | } |
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38 | |||
39 | public function addSynapse(Synapse $synapse): void |
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40 | { |
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41 | $this->synapses[] = $synapse; |
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42 | } |
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43 | |||
44 | /** |
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45 | * @return Synapse[] |
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46 | */ |
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47 | public function getSynapses() |
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48 | { |
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49 | return $this->synapses; |
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50 | } |
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51 | |||
52 | public function getOutput(): float |
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53 | { |
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54 | if ($this->output === 0.0) { |
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55 | $this->z = 0; |
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0 ignored issues
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56 | foreach ($this->synapses as $synapse) { |
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57 | $this->z += $synapse->getOutput(); |
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58 | } |
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59 | |||
60 | $this->output = $this->activationFunction->compute($this->z); |
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61 | } |
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62 | |||
63 | return $this->output; |
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64 | } |
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65 | |||
66 | public function getDerivative(): float |
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67 | { |
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68 | return $this->activationFunction->differentiate($this->z, $this->output); |
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69 | } |
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70 | |||
71 | public function reset(): void |
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72 | { |
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73 | $this->output = 0.0; |
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74 | $this->z = 0.0; |
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75 | } |
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76 | } |
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77 |
This check looks for assignments to scalar types that may be of the wrong type.
To ensure the code behaves as expected, it may be a good idea to add an explicit type cast.