Use correct naming for iteration and epoch
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This commit is contained in:
2026-03-21 09:46:35 +01:00
parent 6abb417430
commit a70b7670e7
8 changed files with 38 additions and 37 deletions

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@@ -7,7 +7,6 @@ use Illuminate\Broadcasting\InteractsWithSockets;
use Illuminate\Contracts\Broadcasting\ShouldBroadcast; use Illuminate\Contracts\Broadcasting\ShouldBroadcast;
use Illuminate\Foundation\Events\Dispatchable; use Illuminate\Foundation\Events\Dispatchable;
use Illuminate\Queue\SerializesModels; use Illuminate\Queue\SerializesModels;
use Illuminate\Support\Facades\Log;
class PerceptronTrainingIteration implements ShouldBroadcast class PerceptronTrainingIteration implements ShouldBroadcast
{ {
@@ -17,7 +16,7 @@ class PerceptronTrainingIteration implements ShouldBroadcast
* Create a new event instance. * Create a new event instance.
*/ */
public function __construct( public function __construct(
public array $iterations, // ["iteration" => int, "exampleIndex" => int, "error" => float, "synaptic_weights" => array] public array $iterations, // ["epoch" => int, "exampleIndex" => int, "error" => float, "synaptic_weights" => array]
public string $sessionId, public string $sessionId,
public string $trainingId, public string $trainingId,
) )

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@@ -4,6 +4,7 @@ namespace App\Models;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Services\DataSetReader;
use App\Services\IPerceptronIterationEventBuffer;
use App\Services\ISynapticWeightsProvider; use App\Services\ISynapticWeightsProvider;
use App\Services\PerceptronIterationEventBuffer; use App\Services\PerceptronIterationEventBuffer;
@@ -18,36 +19,36 @@ class GradientDescentPerceptronTraining extends NetworkTraining
public function __construct( public function __construct(
DataSetReader $datasetReader, DataSetReader $datasetReader,
protected float $learningRate, protected float $learningRate,
int $maxIterations, int $maxEpochs,
protected ISynapticWeightsProvider $synapticWeightsProvider, protected ISynapticWeightsProvider $synapticWeightsProvider,
PerceptronIterationEventBuffer $iterationEventBuffer, IPerceptronIterationEventBuffer $iterationEventBuffer,
string $sessionId, string $sessionId,
string $trainingId, string $trainingId,
private float $minError, private float $minError,
) { ) {
parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId); parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
$this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize())); $this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
} }
public function start(): void public function start(): void
{ {
$this->iteration = 0; $this->epoch = 0;
do { do {
$this->epochError = 0; $this->epochError = 0;
$iterationErrorPerWeight = []; $epochCorrectorPerWeight = [];
$this->iteration++; $this->epoch++;
while ($nextRow = $this->datasetReader->getRandomLine()) { while ($nextRow = $this->datasetReader->getRandomLine()) {
$inputs = array_slice($nextRow, 0, -1); $inputs = array_slice($nextRow, 0, -1);
$correctOutput = (float) end($nextRow); $correctOutput = (float) end($nextRow);
$iterationError = $this->iterationFunction($inputs, $correctOutput); $iterationError = $this->iterationFunction($inputs, $correctOutput);
$this->epochError += (1 / 2) * (abs($iterationError) ** 2); // TDDO REMOVEME abs() $this->epochError += ($iterationError ** 2) / 2;
// Store the iteration error for each weight // Store the iteration error for each weight
$inputs_with_bias = array_merge([1], $inputs); // Add bias input $inputs_with_bias = array_merge([1], $inputs); // Add bias input
foreach ($inputs_with_bias as $index => $input) { foreach ($inputs_with_bias as $index => $input) {
$iterationErrorPerWeight[$index][] = $iterationError * $input; $epochCorrectorPerWeight[$index][] = $iterationError * $input;
} }
// Broadcast the training iteration event // Broadcast the training iteration event
@@ -57,14 +58,14 @@ class GradientDescentPerceptronTraining extends NetworkTraining
// Synaptic weights correction after each epoch // Synaptic weights correction after each epoch
$synaptic_weights = $this->perceptron->getSynapticWeights(); $synaptic_weights = $this->perceptron->getSynapticWeights();
$new_weights = array_map( $new_weights = array_map(
fn($weight, $weightIndex) => $weight + $this->learningRate * array_sum($iterationErrorPerWeight[$weightIndex]), fn($weight, $weightIndex) => $weight + $this->learningRate * array_sum($epochCorrectorPerWeight[$weightIndex]),
$synaptic_weights, $synaptic_weights,
array_keys($synaptic_weights) array_keys($synaptic_weights)
); );
$this->perceptron->setSynapticWeights($new_weights); $this->perceptron->setSynapticWeights($new_weights);
$this->datasetReader->reset(); // Reset the dataset for the next iteration $this->datasetReader->reset(); // Reset the dataset for the next iteration
} while ($this->iteration < $this->maxIterations && !$this->stopCondition()); } while ($this->epoch < $this->maxEpochs && !$this->stopCondition());
$this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend

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@@ -4,11 +4,11 @@ namespace App\Models;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Services\DataSetReader;
use App\Services\PerceptronIterationEventBuffer; use App\Services\IPerceptronIterationEventBuffer;
abstract class NetworkTraining abstract class NetworkTraining
{ {
protected int $iteration = 0; protected int $epoch = 0;
/** /**
* @abstract * @abstract
@@ -18,8 +18,8 @@ abstract class NetworkTraining
public function __construct( public function __construct(
protected DataSetReader $datasetReader, protected DataSetReader $datasetReader,
protected int $maxIterations, protected int $maxEpochs,
protected PerceptronIterationEventBuffer $iterationEventBuffer, protected IPerceptronIterationEventBuffer $iterationEventBuffer,
protected string $sessionId, protected string $sessionId,
protected string $trainingId, protected string $trainingId,
) { ) {
@@ -29,8 +29,8 @@ abstract class NetworkTraining
abstract protected function stopCondition(): bool; abstract protected function stopCondition(): bool;
protected function checkPassedMaxIterations(?float $finalError) { protected function checkPassedMaxIterations(?float $finalError) {
if ($this->iteration >= $this->maxIterations) { if ($this->epoch >= $this->maxEpochs) {
$message = 'Le nombre maximal d\'itérations a été atteint'; $message = 'Le nombre maximal d\'epoch a été atteint';
if ($finalError) { if ($finalError) {
$message .= " avec une erreur finale de $finalError"; $message .= " avec une erreur finale de $finalError";
} }
@@ -40,6 +40,6 @@ abstract class NetworkTraining
} }
protected function addIterationToBuffer(float $error, array $synapticWeights) { protected function addIterationToBuffer(float $error, array $synapticWeights) {
$this->iterationEventBuffer->addIteration($this->iteration, $this->datasetReader->getLastReadLineIndex(), $error, $synapticWeights); $this->iterationEventBuffer->addIteration($this->epoch, $this->datasetReader->getLastReadLineIndex(), $error, $synapticWeights);
} }
} }

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@@ -4,8 +4,8 @@ namespace App\Models;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Services\DataSetReader;
use App\Services\IPerceptronIterationEventBuffer;
use App\Services\ISynapticWeightsProvider; use App\Services\ISynapticWeightsProvider;
use App\Services\PerceptronIterationEventBuffer;
class SimpleBinaryPerceptronTraining extends NetworkTraining class SimpleBinaryPerceptronTraining extends NetworkTraining
{ {
@@ -19,25 +19,25 @@ class SimpleBinaryPerceptronTraining extends NetworkTraining
public function __construct( public function __construct(
DataSetReader $datasetReader, DataSetReader $datasetReader,
protected float $learningRate, protected float $learningRate,
int $maxIterations, int $maxEpochs,
protected ISynapticWeightsProvider $synapticWeightsProvider, protected ISynapticWeightsProvider $synapticWeightsProvider,
PerceptronIterationEventBuffer $iterationEventBuffer, IPerceptronIterationEventBuffer $iterationEventBuffer,
string $sessionId, string $sessionId,
string $trainingId, string $trainingId,
) { ) {
parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId); parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
$this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize())); $this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
} }
public function start(): void public function start(): void
{ {
$this->iteration = 0; $this->epoch = 0;
$error = 0; $error = 0;
do { do {
$this->iterationErrorCounter = 0; $this->iterationErrorCounter = 0;
$this->iteration++; $this->epoch++;
while ($nextRow = $this->datasetReader->getRandomLine()) { while ($nextRow = $this->datasetReader->getNextLine()) {
$inputs = array_slice($nextRow, 0, -1); $inputs = array_slice($nextRow, 0, -1);
$correctOutput = (float) end($nextRow); $correctOutput = (float) end($nextRow);
$correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets $correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets
@@ -48,7 +48,7 @@ class SimpleBinaryPerceptronTraining extends NetworkTraining
$this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]); $this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]);
} }
$this->datasetReader->reset(); // Reset the dataset for the next iteration $this->datasetReader->reset(); // Reset the dataset for the next iteration
} while ($this->iteration < $this->maxIterations && !$this->stopCondition()); } while ($this->epoch < $this->maxEpochs && !$this->stopCondition());
$this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend

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@@ -39,8 +39,8 @@ function getPerceptronErrorsPerIteration(): ChartData<
dataset.data.push(iteration.error); dataset.data.push(iteration.error);
// Epoch error // Epoch error
epochAverageError[iteration.iteration - 1] = epochAverageError[iteration.epoch - 1] =
(epochAverageError[iteration.iteration - 1] || 0) + (epochAverageError[iteration.epoch - 1] || 0) +
iteration.error ** 2 / 2; iteration.error ** 2 / 2;
}); });
@@ -81,7 +81,7 @@ function getPerceptronErrorsPerIteration(): ChartData<
plugins: { plugins: {
title: { title: {
display: true, display: true,
text: 'Nombre d\'erreurs par itération', text: 'Nombre d\'erreurs par epoch',
}, },
}, },
scales: { scales: {
@@ -106,8 +106,8 @@ function getPerceptronErrorsPerIteration(): ChartData<
}" }"
:data="{ :data="{
labels: props.iterations.reduce((labels, iteration) => { labels: props.iterations.reduce((labels, iteration) => {
if (!labels.includes(`Itération ${iteration.iteration}`)) { if (!labels.includes(`Époch ${iteration.epoch}`)) {
labels.push(`Itération ${iteration.iteration}`); labels.push(`Époch ${iteration.epoch}`);
} }
return labels; return labels;
}, [] as string[]), }, [] as string[]),

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@@ -202,7 +202,7 @@ watch(selectedDatasetCopy, (newValue) => {
<!-- MAX ITERATIONS --> <!-- MAX ITERATIONS -->
<FormField name="max_iterations"> <FormField name="max_iterations">
<FormItem> <FormItem>
<FormLabel>Nombre maximum d'epoch</FormLabel> <FormLabel>Nombre maximum d'itérations</FormLabel>
<FormControl> <FormControl>
<Input <Input
type="number" type="number"

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@@ -1,7 +1,7 @@
import type { Point } from "chart.js"; import type { Point } from "chart.js";
export type Iteration = { export type Iteration = {
iteration: number; epoch: number;
exampleIndex: number; exampleIndex: number;
weights: number[][][]; weights: number[][][];
error: number; error: number;
@@ -10,7 +10,8 @@ export type Iteration = {
export type Dataset = { export type Dataset = {
label: string; label: string;
data: DatasetPoint[]; data: DatasetPoint[];
defaultLearningRate: number | undefined; defaultLearningRate?: number;
defaultMinError?: number;
}; };
export type DatasetPoint = { export type DatasetPoint = {