85 lines
3.1 KiB
PHP
85 lines
3.1 KiB
PHP
<?php
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namespace App\Models;
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use App\Events\PerceptronTrainingEnded;
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use App\Services\DataSetReader;
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use App\Services\IPerceptronIterationEventBuffer;
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use App\Services\ISynapticWeightsProvider;
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class SimpleBinaryPerceptronTraining extends NetworkTraining
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{
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private Perceptron $perceptron;
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private int $iterationErrorCounter = 0;
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public ActivationsFunctions $activationFunction = ActivationsFunctions::STEP;
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public const MIN_ERROR = 0;
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public function __construct(
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DataSetReader $datasetReader,
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protected float $learningRate,
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int $maxEpochs,
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protected ISynapticWeightsProvider $synapticWeightsProvider,
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IPerceptronIterationEventBuffer $iterationEventBuffer,
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string $sessionId,
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string $trainingId,
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) {
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parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
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$this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
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}
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public function start(): void
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{
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$this->epoch = 0;
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$error = 0;
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do {
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$this->iterationErrorCounter = 0;
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$this->epoch++;
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while ($nextRow = $this->datasetReader->getNextLine()) {
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$inputs = array_slice($nextRow, 0, -1);
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$correctOutput = (float) end($nextRow);
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$correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets
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$error = $this->iterationFunction($inputs, $correctOutput);
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// Broadcast the training iteration event
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$this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]);
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}
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$this->datasetReader->reset(); // Reset the dataset for the next iteration
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} while ($this->epoch < $this->maxEpochs && !$this->stopCondition());
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$this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
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$this->checkPassedMaxIterations(null);
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}
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protected function stopCondition(): bool
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{
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$condition = $this->iterationErrorCounter == 0;
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if ($condition === true) {
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event(new PerceptronTrainingEnded('Le perceptron ne commet plus d\'erreurs sur aucune des données', $this->sessionId, $this->trainingId));
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}
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return $this->iterationErrorCounter == 0;
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}
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private function iterationFunction(array $inputs, int $correctOutput)
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{
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$output = $this->perceptron->test($inputs);
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$error = $correctOutput - $output;
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if (abs($error) > $this::MIN_ERROR) {
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$this->iterationErrorCounter++;
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}
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if ($error !== 0) { // Update synaptic weights if needed
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$synaptic_weights = $this->perceptron->getSynapticWeights();
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$inputs_with_bias = array_merge([1], $inputs); // Add bias input
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$new_weights = array_map(fn($weight, $input) => $weight + $this->learningRate * $error * $input, $synaptic_weights, $inputs_with_bias);
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$this->perceptron->setSynapticWeights($new_weights);
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}
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return $error;
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}
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}
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