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Author SHA1 Message Date
0876588550 Changed Favicon
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2026-03-24 10:48:50 +01:00
a37afcec07 Added brianium/paratest to run test in parallel
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2026-03-23 16:33:58 +01:00
b052d792f8 Added Cache to CICD
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2026-03-23 16:13:12 +01:00
5880024933 Fix linting
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2026-03-23 16:02:07 +01:00
a92a47288c Fixed Regression datasets
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2026-03-23 16:01:22 +01:00
bcaf334380 Added pointer cursor to selects 2026-03-23 16:01:10 +01:00
dea908c63e Modified limitedEventBuffer to send in linear delay 2026-03-23 16:00:51 +01:00
236fa503fb Fix setup command
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2026-03-23 13:57:02 +01:00
0f92af4a1e Added Reverb terminal color 2026-03-23 13:56:53 +01:00
ef90236adc Fix linting
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2026-03-23 08:44:50 +01:00
9d4b02fab5 Light mode support
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2026-03-22 17:14:23 +01:00
88a932391b Renamed tests + added some + misc
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2026-03-22 16:57:12 +01:00
abb16aa6c1 Added ADALINE training
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2026-03-22 15:54:04 +01:00
29498e45ac Fix tests
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2026-03-22 15:21:35 +01:00
af67830fbb fixed error graph + added toggle only epoch error
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2026-03-22 14:58:53 +01:00
42e07de287 Rafactored Perceptrons and network training 2026-03-22 14:58:34 +01:00
47991fe736 Removed unused Test
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2026-03-22 11:44:21 +01:00
03d8688f56 Added and deactivated gradientDescent Test
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2026-03-22 11:42:46 +01:00
72775d09ef Renamed dataset
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2026-03-22 11:20:53 +01:00
87aa942e0b Removed unused test 2026-03-22 11:20:45 +01:00
8af26db16c Fix gradient descent
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2026-03-22 10:42:15 +01:00
4717254da4 Refactored into folders 2026-03-22 10:42:08 +01:00
977c259cb9 Added instruction to clear the job queue 2026-03-22 10:40:28 +01:00
e3b656a036 Changed / route to a redirect
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2026-03-21 10:23:49 +01:00
2d1c5e6397 Fix eslint 2026-03-21 10:23:17 +01:00
59 changed files with 1076 additions and 325 deletions

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@@ -20,30 +20,59 @@ permissions:
jobs: jobs:
quality: quality:
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v6 - name: Checkout code
uses: actions/checkout@v6
# -------------------------
# Cache Composer
# -------------------------
- name: Cache Composer dependencies
uses: actions/cache@v4
with:
path: ~/.composer/cache
key: composer-${{ runner.os }}-${{ hashFiles('**/composer.lock') }}
restore-keys: |
composer-${{ runner.os }}-
# -------------------------
# Cache Node
# -------------------------
- name: Cache Node dependencies
uses: actions/cache@v4
with:
path: ~/.npm
key: node-${{ runner.os }}-${{ hashFiles('**/package-lock.json') }}
restore-keys: |
node-${{ runner.os }}-
- name: Setup PHP - name: Setup PHP
uses: shivammathur/setup-php@v2 uses: shivammathur/setup-php@v2
with: with:
php-version: '8.4' php-version: '8.4'
coverage: none
- name: Setup Node
uses: actions/setup-node@v4
with:
node-version: '22'
cache: 'npm'
# -------------------------
# Install dependencies
# -------------------------
- name: Install Dependencies - name: Install Dependencies
run: | run: |
composer install -q --no-ansi --no-interaction --no-scripts --no-progress --prefer-dist composer install --no-interaction --prefer-dist --no-progress --no-scripts
npm install npm ci
- name: Run Pint # -------------------------
run: composer lint # Run linters in parallel
# -------------------------
- name: Format Frontend - name: Run linters
run: npm run format run: |
composer lint &
- name: Lint Frontend npm run format &
run: npm run lint npm run lint &
wait
# - name: Commit Changes
# uses: stefanzweifel/git-auto-commit-action@v7
# with:
# commit_message: fix code style
# commit_options: '--no-verify'

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@@ -25,32 +25,66 @@ jobs:
- name: Checkout code - name: Checkout code
uses: actions/checkout@v6 uses: actions/checkout@v6
# -------------------------
# Cache Composer
# -------------------------
- name: Cache Composer dependencies
uses: actions/cache@v4
with:
path: ~/.composer/cache
key: composer-${{ runner.os }}-${{ matrix.php-version }}-${{ hashFiles('**/composer.lock') }}
restore-keys: |
composer-${{ runner.os }}-${{ matrix.php-version }}-
# -------------------------
# Cache Node
# -------------------------
- name: Cache Node dependencies
uses: actions/cache@v4
with:
path: ~/.npm
key: node-${{ runner.os }}-${{ hashFiles('**/package-lock.json') }}
restore-keys: |
node-${{ runner.os }}-
- name: Setup PHP - name: Setup PHP
uses: shivammathur/setup-php@v2 uses: shivammathur/setup-php@v2
with: with:
php-version: ${{ matrix.php-version }} php-version: ${{ matrix.php-version }}
tools: composer:v2 tools: composer:v2
coverage: xdebug coverage: none
- name: Setup Node - name: Setup Node
uses: actions/setup-node@v4 uses: actions/setup-node@v4
with: with:
node-version: '22' node-version: '22'
cache: 'npm'
# -------------------------
# Install dependencies
# -------------------------
- name: Install Node Dependencies - name: Install Node Dependencies
run: npm i run: npm ci
- name: Install Dependencies - name: Install PHP Dependencies
run: composer install --no-interaction --prefer-dist --optimize-autoloader run: composer install --no-interaction --prefer-dist --optimize-autoloader --no-progress
- name: Copy Environment File # -------------------------
run: cp .env.example .env # Laravel setup
# -------------------------
- name: Generate Application Key - name: Prepare environment
run: php artisan key:generate run: |
cp .env.example .env
php artisan key:generate
# -------------------------
# Build (optional remove if not needed for tests)
# -------------------------
- name: Build Assets - name: Build Assets
run: npm run build run: npm run build
- name: Tests # -------------------------
run: ./vendor/bin/phpunit # Run tests (parallel)
# -------------------------
- name: Run Tests
run: php artisan test --parallel

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@@ -23,10 +23,10 @@ Using Laravel and Vue JS
3. NodeJs (Node + NPM) 3. NodeJs (Node + NPM)
<https://nodejs.org/en/download> <https://nodejs.org/en/download>
2. Install dependencies 2. Setup project and install dependencies
```shell ```shell
composer install composer run setup
``` ```
## Running the project ## Running the project
@@ -40,3 +40,13 @@ composer run dev
``` ```
And go with your favorite browser to <http://127.0.0.1:8000/> And go with your favorite browser to <http://127.0.0.1:8000/>
### Nothing is happening when I press "Lancer"
Look a the output of `composer run dev`, if you see that reverb is still sending events, that means you need to clear the job queue in a new terminal with the command
```shell
php artisan queue:clear
```
You then need to repress the "Lancer" button.

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@@ -21,8 +21,7 @@ class PerceptronInitialization implements ShouldBroadcast
public ActivationsFunctions $activationFunction, public ActivationsFunctions $activationFunction,
public string $sessionId, public string $sessionId,
public string $trainingId, public string $trainingId,
) ) {
{
// //
} }
@@ -34,7 +33,7 @@ class PerceptronInitialization implements ShouldBroadcast
public function broadcastOn(): array public function broadcastOn(): array
{ {
return [ return [
new Channel($this->sessionId . '-perceptron-training'), new Channel($this->sessionId.'-perceptron-training'),
]; ];
} }

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@@ -4,8 +4,6 @@ namespace App\Events;
use Illuminate\Broadcasting\Channel; use Illuminate\Broadcasting\Channel;
use Illuminate\Broadcasting\InteractsWithSockets; use Illuminate\Broadcasting\InteractsWithSockets;
use Illuminate\Broadcasting\PresenceChannel;
use Illuminate\Broadcasting\PrivateChannel;
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;
@@ -21,8 +19,7 @@ class PerceptronTrainingEnded implements ShouldBroadcast
public string $reason, public string $reason,
public string $sessionId, public string $sessionId,
public string $trainingId, public string $trainingId,
) ) {
{
// //
} }
@@ -34,7 +31,7 @@ class PerceptronTrainingEnded implements ShouldBroadcast
public function broadcastOn(): array public function broadcastOn(): array
{ {
return [ return [
new Channel($this->sessionId . '-perceptron-training'), new Channel($this->sessionId.'-perceptron-training'),
]; ];
} }

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@@ -19,8 +19,7 @@ class PerceptronTrainingIteration implements ShouldBroadcast
public array $iterations, // ["epoch" => 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,
) ) {
{
// //
} }
@@ -33,7 +32,7 @@ class PerceptronTrainingIteration implements ShouldBroadcast
{ {
// Log::debug("Broadcasting on channel: " . $this->sessionId . '-perceptron-training'); // Log::debug("Broadcasting on channel: " . $this->sessionId . '-perceptron-training');
return [ return [
new Channel($this->sessionId . '-perceptron-training'), new Channel($this->sessionId.'-perceptron-training'),
]; ];
} }

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@@ -3,13 +3,16 @@
namespace App\Http\Controllers; namespace App\Http\Controllers;
use App\Events\PerceptronInitialization; use App\Events\PerceptronInitialization;
use App\Models\GradientDescentPerceptronTraining; use App\Models\NetworksTraining\ADALINEPerceptronTraining;
use App\Models\SimpleBinaryPerceptronTraining; use App\Models\NetworksTraining\GradientDescentPerceptronTraining;
use App\Services\DataSetReader; use App\Models\NetworksTraining\SimpleBinaryPerceptronTraining;
use App\Services\ISynapticWeightsProvider; use App\Services\DatasetReader\IDataSetReader;
use App\Services\PerceptronIterationEventBuffer; use App\Services\DatasetReader\LinearOrderDataSetReader;
use App\Services\PerceptronLimitedEpochEventBuffer; use App\Services\DatasetReader\RandomOrderDataSetReader;
use App\Services\ZeroSynapticWeights; use App\Services\IterationEventBuffer\PerceptronIterationEventBuffer;
use App\Services\IterationEventBuffer\PerceptronLimitedEpochEventBuffer;
use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
use Illuminate\Http\Request; use Illuminate\Http\Request;
class PerceptronController extends Controller class PerceptronController extends Controller
@@ -23,15 +26,16 @@ class PerceptronController extends Controller
$learningRate = 0.01; $learningRate = 0.01;
$maxIterations = 200; $maxIterations = 200;
$minError = 0.6; $minError = 0.1;
switch ($perceptronType) { switch ($perceptronType) {
case 'simple': case 'simple':
$learningRate = 0.015; $learningRate = 0.015;
$maxIterations = 150; $maxIterations = 150;
break; break;
case 'gradientdescent': case 'gradientdescent' || 'adaline':
$learningRate = 0.00003; $learningRate = 0.00003;
break;
} }
return inertia('PerceptronViewer', [ return inertia('PerceptronViewer', [
@@ -53,7 +57,7 @@ class PerceptronController extends Controller
if (pathinfo($file, PATHINFO_EXTENSION) === 'csv') { if (pathinfo($file, PATHINFO_EXTENSION) === 'csv') {
$dataset = []; $dataset = [];
$dataset['label'] = str_replace('.csv', '', $file); $dataset['label'] = str_replace('.csv', '', $file);
$dataSetReader = new DataSetReader($dataSetsDirectory . '/' . $file); $dataSetReader = new LinearOrderDataSetReader($dataSetsDirectory.'/'.$file);
$dataset['data'] = []; $dataset['data'] = [];
switch (count($dataSetReader->lines[0])) { switch (count($dataSetReader->lines[0])) {
case 3: case 3:
@@ -84,6 +88,11 @@ class PerceptronController extends Controller
switch ($perceptronType) { switch ($perceptronType) {
case 'gradientdescent': case 'gradientdescent':
$dataset['defaultLearningRate'] = 0.3; $dataset['defaultLearningRate'] = 0.3;
$dataset['defaultMinError'] = 0.125;
break;
case 'adaline':
$dataset['defaultLearningRate'] = 0.05;
$dataset['defaultMinError'] = 0.125;
break; break;
} }
break; break;
@@ -92,26 +101,27 @@ class PerceptronController extends Controller
case 'simple': case 'simple':
$dataset['defaultLearningRate'] = 0.015; $dataset['defaultLearningRate'] = 0.015;
break; break;
case 'gradientdescent': case 'gradientdescent' || 'adaline':
$dataset['defaultLearningRate'] = 0.001; $dataset['defaultLearningRate'] = 0.001;
$dataset['defaultMinError'] = 2.0;
break; break;
} }
break; break;
case 'table_2_11': case 'table_2_11':
$dataset['defaultMinError'] = 1.0; $dataset['defaultMinError'] = 0.02;
break; break;
} }
$datasets[] = $dataset; $datasets[] = $dataset;
} }
} }
return $datasets; return $datasets;
} }
private function getDataSetReader(string $dataSet): DataSetReader private function getDataSetReader(string $dataSet): IDataSetReader
{ {
$dataSetFileName = "data_sets/{$dataSet}.csv"; $dataSetFileName = "data_sets/{$dataSet}.csv";
return new DataSetReader($dataSetFileName);
return new RandomOrderDataSetReader($dataSetFileName);
} }
public function run(Request $request, ISynapticWeightsProvider $synapticWeightsProvider) public function run(Request $request, ISynapticWeightsProvider $synapticWeightsProvider)
@@ -121,30 +131,30 @@ class PerceptronController extends Controller
$weightInitMethod = $request->input('weight_init_method', 'random'); $weightInitMethod = $request->input('weight_init_method', 'random');
$dataSet = $request->input('dataset'); $dataSet = $request->input('dataset');
$learningRate = $request->input('learning_rate', 0.015); $learningRate = $request->input('learning_rate', 0.015);
$maxIterations = $request->input('max_iterations', 100); $maxEpochs = $request->input('max_iterations', 100);
$sessionId = $request->input('session_id', session()->getId()); $sessionId = $request->input('session_id', session()->getId());
$trainingId = $request->input('training_id'); $trainingId = $request->input('training_id');
if ($weightInitMethod === 'zeros') { if ($weightInitMethod === 'zeros') {
$synapticWeightsProvider = new ZeroSynapticWeights(); $synapticWeightsProvider = new ZeroSynapticWeights;
} }
$iterationEventBuffer = new PerceptronIterationEventBuffer($sessionId, $trainingId); $iterationEventBuffer = new PerceptronIterationEventBuffer($sessionId, $trainingId);
if ($maxIterations > config('perceptron.limited_broadcast_iterations')) { if ($maxEpochs > config('perceptron.limited_broadcast_iterations')) {
$iterationsInterval = (int)($maxIterations / config('perceptron.limited_broadcast_iterations')); $iterationsInterval = (int) ($maxEpochs / config('perceptron.limited_broadcast_iterations'));
$iterationEventBuffer = new PerceptronLimitedEpochEventBuffer($sessionId, $trainingId, $iterationsInterval); $iterationEventBuffer = new PerceptronLimitedEpochEventBuffer($sessionId, $trainingId, $iterationsInterval);
} }
$dataSetReader = $this->getDataSetReader($dataSet); $datasetReader = $this->getDataSetReader($dataSet);
$networkTraining = match ($perceptronType) { $networkTraining = match ($perceptronType) {
'simple' => new SimpleBinaryPerceptronTraining($dataSetReader, $learningRate, $maxIterations, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId), 'simple' => new SimpleBinaryPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId),
'gradientdescent' => new GradientDescentPerceptronTraining($dataSetReader, $learningRate, $maxIterations, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError), 'gradientdescent' => new GradientDescentPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
'adaline' => new ADALINEPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
default => null, default => null,
}; };
event(new PerceptronInitialization($dataSetReader->lines, $networkTraining->activationFunction, $sessionId, $trainingId)); event(new PerceptronInitialization($datasetReader->lines, $networkTraining->activationFunction, $sessionId, $trainingId));
$networkTraining->start(); $networkTraining->start();

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@@ -1,8 +0,0 @@
<?php
namespace App\Models;
abstract class Network
{
}

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@@ -0,0 +1,106 @@
<?php
namespace App\Models\NetworksTraining;
use App\Events\PerceptronTrainingEnded;
use App\Models\ActivationsFunctions;
use App\Models\Perceptrons\GradientDescentPerceptron;
use App\Models\Perceptrons\Perceptron;
use App\Services\DatasetReader\IDataSetReader;
use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
class ADALINEPerceptronTraining extends NetworkTraining
{
private Perceptron $perceptron;
public ActivationsFunctions $activationFunction = ActivationsFunctions::LINEAR;
private float $epochError;
public function __construct(
IDataSetReader $datasetReader,
protected float $learningRate,
int $maxEpochs,
protected ISynapticWeightsProvider $synapticWeightsProvider,
IPerceptronIterationEventBuffer $iterationEventBuffer,
string $sessionId,
string $trainingId,
private float $minError,
) {
parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
$this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
}
public function start(): void
{
$this->epoch = 0;
do {
$this->epochError = 0;
$this->epoch++;
$inputsForCurrentEpoch = [];
while ($nextRow = $this->datasetReader->getNextLine()) {
$inputsForCurrentEpoch[] = $nextRow;
$inputs = array_slice($nextRow, 0, -1);
$correctOutput = (float) end($nextRow);
$iterationError = $this->iterationFunction($inputs, $correctOutput);
// Synaptic weights correction after each example
$synaptic_weights = $this->perceptron->getSynapticWeights();
$inputs_with_bias = array_merge([1], $inputs); // Add bias input
$new_weights = array_map(
fn ($weight, $weightIndex) => $weight + ($this->learningRate * $iterationError * $inputs_with_bias[$weightIndex]),
$synaptic_weights,
array_keys($synaptic_weights)
);
$this->perceptron->setSynapticWeights($new_weights);
// Broadcast the training iteration event
$this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]);
}
// Calculte the average error for the epoch with the last synaptic weights
foreach ($inputsForCurrentEpoch as $inputsWithLabel) {
$inputs = array_slice($inputsWithLabel, 0, -1);
$correctOutput = (float) end($inputsWithLabel);
$output = $this->perceptron->test($inputs);
$iterationError = $correctOutput - $output;
$this->epochError += ($iterationError ** 2) / 2; // Squared error for the example
}
$this->epochError /= $this->datasetReader->getEpochExamplesCount(); // Average error for the epoch
$this->datasetReader->reset(); // Reset the dataset for the next iteration
} while ($this->epoch < $this->maxEpochs && ! $this->stopCondition());
$this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
$this->checkPassedMaxIterations($this->epochError);
}
protected function stopCondition(): bool
{
$condition = $this->epochError <= $this->minError;
if ($condition === true) {
event(new PerceptronTrainingEnded('Le perceptron à atteint l\'erreur minimale', $this->sessionId, $this->trainingId));
}
return $condition;
}
private function iterationFunction(array $inputs, int $correctOutput)
{
$output = $this->perceptron->test($inputs);
$error = $correctOutput - $output;
return $error;
}
public function getSynapticWeights(): array
{
return [[$this->perceptron->getSynapticWeights()]];
}
}

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@@ -1,12 +1,14 @@
<?php <?php
namespace App\Models; namespace App\Models\NetworksTraining;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Models\ActivationsFunctions;
use App\Services\IPerceptronIterationEventBuffer; use App\Models\Perceptrons\GradientDescentPerceptron;
use App\Services\ISynapticWeightsProvider; use App\Models\Perceptrons\Perceptron;
use App\Services\PerceptronIterationEventBuffer; use App\Services\DatasetReader\IDataSetReader;
use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
class GradientDescentPerceptronTraining extends NetworkTraining class GradientDescentPerceptronTraining extends NetworkTraining
{ {
@@ -17,7 +19,7 @@ class GradientDescentPerceptronTraining extends NetworkTraining
private float $epochError; private float $epochError;
public function __construct( public function __construct(
DataSetReader $datasetReader, IDataSetReader $datasetReader,
protected float $learningRate, protected float $learningRate,
int $maxEpochs, int $maxEpochs,
protected ISynapticWeightsProvider $synapticWeightsProvider, protected ISynapticWeightsProvider $synapticWeightsProvider,
@@ -38,7 +40,7 @@ class GradientDescentPerceptronTraining extends NetworkTraining
$epochCorrectorPerWeight = []; $epochCorrectorPerWeight = [];
$this->epoch++; $this->epoch++;
while ($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);
@@ -55,17 +57,19 @@ class GradientDescentPerceptronTraining extends NetworkTraining
$this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]); $this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]);
} }
$this->epochError /= $this->datasetReader->getEpochExamplesCount(); // Average error for the epoch
// 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 + $this->learningRate * array_sum($epochCorrectorPerWeight[$weightIndex]), fn ($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->epoch < $this->maxEpochs && !$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
@@ -74,10 +78,11 @@ class GradientDescentPerceptronTraining extends NetworkTraining
protected function stopCondition(): bool protected function stopCondition(): bool
{ {
$condition = $this->epochError <= $this->minError && $this->perceptron->getSynapticWeights() !== [[0.0, 0.0, 0.0]]; $condition = $this->epochError <= $this->minError;
if ($condition === true) { if ($condition === true) {
event(new PerceptronTrainingEnded('Le perceptron à atteint l\'erreur minimale', $this->sessionId, $this->trainingId)); event(new PerceptronTrainingEnded('Le perceptron à atteint l\'erreur minimale', $this->sessionId, $this->trainingId));
} }
return $condition; return $condition;
} }
@@ -89,4 +94,9 @@ class GradientDescentPerceptronTraining extends NetworkTraining
return $error; return $error;
} }
public function getSynapticWeights(): array
{
return [[$this->perceptron->getSynapticWeights()]];
}
} }

View File

@@ -1,10 +1,11 @@
<?php <?php
namespace App\Models; namespace App\Models\NetworksTraining;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Models\ActivationsFunctions;
use App\Services\IPerceptronIterationEventBuffer; use App\Services\DatasetReader\IDataSetReader;
use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
abstract class NetworkTraining abstract class NetworkTraining
{ {
@@ -12,23 +13,23 @@ abstract class NetworkTraining
/** /**
* @abstract * @abstract
* @var ActivationsFunctions
*/ */
public ActivationsFunctions $activationFunction; public ActivationsFunctions $activationFunction;
public function __construct( public function __construct(
protected DataSetReader $datasetReader, protected IDataSetReader $datasetReader,
protected int $maxEpochs, protected int $maxEpochs,
protected IPerceptronIterationEventBuffer $iterationEventBuffer, protected IPerceptronIterationEventBuffer $iterationEventBuffer,
protected string $sessionId, protected string $sessionId,
protected string $trainingId, protected string $trainingId,
) { ) {}
}
abstract public function start(): void;
abstract public function start() : void;
abstract protected function stopCondition(): bool; abstract protected function stopCondition(): bool;
protected function checkPassedMaxIterations(?float $finalError) { protected function checkPassedMaxIterations(?float $finalError)
{
if ($this->epoch >= $this->maxEpochs) { if ($this->epoch >= $this->maxEpochs) {
$message = 'Le nombre maximal d\'epoch a été atteint'; $message = 'Le nombre maximal d\'epoch a été atteint';
if ($finalError) { if ($finalError) {
@@ -39,7 +40,15 @@ abstract class NetworkTraining
} }
} }
protected function addIterationToBuffer(float $error, array $synapticWeights) { protected function addIterationToBuffer(float $error, array $synapticWeights)
{
$this->iterationEventBuffer->addIteration($this->epoch, $this->datasetReader->getLastReadLineIndex(), $error, $synapticWeights); $this->iterationEventBuffer->addIteration($this->epoch, $this->datasetReader->getLastReadLineIndex(), $error, $synapticWeights);
} }
public function getEpoch(): int
{
return $this->epoch;
}
abstract public function getSynapticWeights(): array;
} }

View File

@@ -1,15 +1,19 @@
<?php <?php
namespace App\Models; namespace App\Models\NetworksTraining;
use App\Events\PerceptronTrainingEnded; use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader; use App\Models\ActivationsFunctions;
use App\Services\IPerceptronIterationEventBuffer; use App\Models\Perceptrons\Perceptron;
use App\Services\ISynapticWeightsProvider; use App\Models\Perceptrons\SimpleBinaryPerceptron;
use App\Services\DatasetReader\IDataSetReader;
use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
class SimpleBinaryPerceptronTraining extends NetworkTraining class SimpleBinaryPerceptronTraining extends NetworkTraining
{ {
private Perceptron $perceptron; private Perceptron $perceptron;
private int $iterationErrorCounter = 0; private int $iterationErrorCounter = 0;
public ActivationsFunctions $activationFunction = ActivationsFunctions::STEP; public ActivationsFunctions $activationFunction = ActivationsFunctions::STEP;
@@ -17,7 +21,7 @@ class SimpleBinaryPerceptronTraining extends NetworkTraining
public const MIN_ERROR = 0; public const MIN_ERROR = 0;
public function __construct( public function __construct(
DataSetReader $datasetReader, IDataSetReader $datasetReader,
protected float $learningRate, protected float $learningRate,
int $maxEpochs, int $maxEpochs,
protected ISynapticWeightsProvider $synapticWeightsProvider, protected ISynapticWeightsProvider $synapticWeightsProvider,
@@ -48,7 +52,7 @@ 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->epoch < $this->maxEpochs && !$this->stopCondition()); } while ($this->epoch < $this->maxEpochs && ! $this->stopCondition());
$this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
@@ -61,6 +65,7 @@ class SimpleBinaryPerceptronTraining extends NetworkTraining
if ($condition === true) { if ($condition === true) {
event(new PerceptronTrainingEnded('Le perceptron ne commet plus d\'erreurs sur aucune des données', $this->sessionId, $this->trainingId)); event(new PerceptronTrainingEnded('Le perceptron ne commet plus d\'erreurs sur aucune des données', $this->sessionId, $this->trainingId));
} }
return $this->iterationErrorCounter == 0; return $this->iterationErrorCounter == 0;
} }
@@ -76,9 +81,15 @@ class SimpleBinaryPerceptronTraining extends NetworkTraining
if ($error !== 0) { // Update synaptic weights if needed if ($error !== 0) { // Update synaptic weights if needed
$synaptic_weights = $this->perceptron->getSynapticWeights(); $synaptic_weights = $this->perceptron->getSynapticWeights();
$inputs_with_bias = array_merge([1], $inputs); // Add bias input $inputs_with_bias = array_merge([1], $inputs); // Add bias input
$new_weights = array_map(fn($weight, $input) => $weight + $this->learningRate * $error * $input, $synaptic_weights, $inputs_with_bias); $new_weights = array_map(fn ($weight, $input) => $weight + $this->learningRate * $error * $input, $synaptic_weights, $inputs_with_bias);
$this->perceptron->setSynapticWeights($new_weights); $this->perceptron->setSynapticWeights($new_weights);
} }
return $error; return $error;
} }
public function getSynapticWeights(): array
{
return [[$this->perceptron->getSynapticWeights()]];
}
} }

View File

@@ -1,9 +1,9 @@
<?php <?php
namespace App\Models; namespace App\Models\Perceptrons;
class GradientDescentPerceptron extends Perceptron {
class GradientDescentPerceptron extends Perceptron
{
public function __construct( public function __construct(
array $synaptic_weights, array $synaptic_weights,
) { ) {
@@ -14,5 +14,4 @@ class GradientDescentPerceptron extends Perceptron {
{ {
return $weighted_sum; return $weighted_sum;
} }
} }

View File

@@ -1,6 +1,6 @@
<?php <?php
namespace App\Models; namespace App\Models\Perceptrons;
use Illuminate\Database\Eloquent\Model; use Illuminate\Database\Eloquent\Model;
@@ -17,10 +17,11 @@ abstract class Perceptron extends Model
$inputs = array_merge([1], $inputs); // Add bias input $inputs = array_merge([1], $inputs); // Add bias input
if (count($inputs) !== count($this->synaptic_weights)) { // Check if (count($inputs) !== count($this->synaptic_weights)) { // Check
throw new \InvalidArgumentException("Number of inputs must match number of synaptic weights."); throw new \InvalidArgumentException('Number of inputs must match number of synaptic weights.');
} }
$weighted_sum = array_sum(array_map(fn($input, $weight) => $input * $weight, $inputs, $this->synaptic_weights)); $weighted_sum = array_sum(array_map(fn ($input, $weight) => $input * $weight, $inputs, $this->synaptic_weights));
return $this->activationFunction($weighted_sum); return $this->activationFunction($weighted_sum);
} }

View File

@@ -1,9 +1,9 @@
<?php <?php
namespace App\Models; namespace App\Models\Perceptrons;
class SimpleBinaryPerceptron extends Perceptron {
class SimpleBinaryPerceptron extends Perceptron
{
public function __construct( public function __construct(
array $synaptic_weights, array $synaptic_weights,
) { ) {
@@ -14,5 +14,4 @@ class SimpleBinaryPerceptron extends Perceptron {
{ {
return $weighted_sum >= 0.0 ? 1.0 : 0.0; return $weighted_sum >= 0.0 ? 1.0 : 0.0;
} }
} }

View File

@@ -6,7 +6,6 @@ use Carbon\CarbonImmutable;
use Illuminate\Support\Facades\Date; use Illuminate\Support\Facades\Date;
use Illuminate\Support\Facades\DB; use Illuminate\Support\Facades\DB;
use Illuminate\Support\ServiceProvider; use Illuminate\Support\ServiceProvider;
use Illuminate\Validation\Rules\Password;
class AppServiceProvider extends ServiceProvider class AppServiceProvider extends ServiceProvider
{ {

View File

@@ -2,8 +2,8 @@
namespace App\Providers; namespace App\Providers;
use App\Services\ISynapticWeightsProvider; use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
use App\Services\RandomSynapticWeights; use App\Services\SynapticWeightsProvider\RandomSynapticWeights;
use Illuminate\Support\ServiceProvider; use Illuminate\Support\ServiceProvider;
class InitialSynapticWeightsProvider extends ServiceProvider class InitialSynapticWeightsProvider extends ServiceProvider
@@ -14,7 +14,7 @@ class InitialSynapticWeightsProvider extends ServiceProvider
public function register(): void public function register(): void
{ {
$this->app->singleton(ISynapticWeightsProvider::class, function ($app) { $this->app->singleton(ISynapticWeightsProvider::class, function ($app) {
return new RandomSynapticWeights(); return new RandomSynapticWeights;
}); });
} }

View File

@@ -2,7 +2,8 @@
namespace App\Services; namespace App\Services;
class CsvReader { class CsvReader
{
private $file; private $file;
// private array $headers; // private array $headers;
@@ -10,11 +11,10 @@ class CsvReader {
public function __construct( public function __construct(
public string $filename, public string $filename,
) ) {
{ $this->file = fopen($filename, 'r');
$this->file = fopen($filename, "r"); if (! $this->file) {
if (!$this->file) { throw new \RuntimeException('Failed to open file: '.$filename);
throw new \RuntimeException("Failed to open file: " . $filename);
} }
// $this->headers = $this->readNextLine(); // $this->headers = $this->readNextLine();
@@ -22,9 +22,10 @@ class CsvReader {
public function readNextLine(): ?array public function readNextLine(): ?array
{ {
if (($data = fgetcsv($this->file, 1000, ",")) !== FALSE) { if (($data = fgetcsv($this->file, 1000, ',')) !== false) {
return $data; return $data;
} }
return null; // End of file or error return null; // End of file or error
} }
} }

View File

@@ -0,0 +1,16 @@
<?php
namespace App\Services\DatasetReader;
interface IDataSetReader
{
public function getNextLine(): ?array;
public function getInputSize(): int;
public function reset(): void;
public function getLastReadLineIndex(): int;
public function getEpochExamplesCount(): int;
}

View File

@@ -0,0 +1,66 @@
<?php
namespace App\Services\DatasetReader;
use App\Services\CsvReader;
class LinearOrderDataSetReader implements IDataSetReader
{
public array $lines = [];
private array $currentLines = [];
private int $lastReadLineIndex = -1;
public function __construct(
public string $filename,
) {
// For now, we only support CSV files, so we can delegate to CsvReader
$csvReader = new CsvReader($filename);
$this->readEntireFile($csvReader);
$this->reset();
}
private function readEntireFile(CsvReader $reader): void
{
while ($line = $reader->readNextLine()) {
$newLine = [];
foreach ($line as $value) { // Transform to float
$newLine[] = (float) $value;
}
$this->lines[] = $newLine;
}
}
public function getNextLine(): ?array
{
if (! isset($this->currentLines[0])) {
return null; // No more lines to read
}
$this->lastReadLineIndex = array_search($this->currentLines[0], $this->lines, true);
return array_shift($this->currentLines);
}
public function getInputSize(): int
{
return count($this->lines[0]) - 1; // Don't count the label
}
public function reset(): void
{
$this->currentLines = $this->lines;
}
public function getLastReadLineIndex(): int
{
return $this->lastReadLineIndex;
}
public function getEpochExamplesCount(): int
{
return count($this->lines);
}
}

View File

@@ -1,9 +1,13 @@
<?php <?php
namespace App\Services; namespace App\Services\DatasetReader;
class DataSetReader { use App\Services\CsvReader;
class RandomOrderDataSetReader implements IDataSetReader
{
public array $lines = []; public array $lines = [];
private array $currentLines = []; private array $currentLines = [];
private int $lastReadLineIndex = -1; private int $lastReadLineIndex = -1;
@@ -25,16 +29,11 @@ class DataSetReader {
$newLine[] = (float) $value; $newLine[] = (float) $value;
} }
// if the dataset is for regression, we add a fake label of 0
if (count($newLine) === 2) {
$newLine[] = 0.0;
}
$this->lines[] = $newLine; $this->lines[] = $newLine;
} }
} }
public function getRandomLine(): array | null public function getNextLine(): ?array
{ {
if (empty($this->currentLines)) { if (empty($this->currentLines)) {
return null; // No more lines to read return null; // No more lines to read
@@ -51,16 +50,6 @@ class DataSetReader {
return $randomLine; return $randomLine;
} }
public function getNextLine(): array | null {
if (!isset($this->currentLines[0])) {
return null; // No more lines to read
}
$this->lastReadLineIndex = array_search($this->currentLines[0], $this->lines, true);
return array_shift($this->currentLines);
}
public function getInputSize(): int public function getInputSize(): int
{ {
return count($this->lines[0]) - 1; // Don't count the label return count($this->lines[0]) - 1; // Don't count the label
@@ -75,4 +64,9 @@ class DataSetReader {
{ {
return $this->lastReadLineIndex; return $this->lastReadLineIndex;
} }
public function getEpochExamplesCount(): int
{
return count($this->lines);
}
} }

View File

@@ -1,10 +0,0 @@
<?php
namespace App\Services;
interface IPerceptronIterationEventBuffer {
public function flush(): void ;
public function addIteration(int $iteration, int $exampleIndex, float $error, array $synaptic_weights): void ;
}

View File

@@ -1,7 +0,0 @@
<?php
namespace App\Services;
interface ISynapticWeightsProvider {
public function generate(int $input_size): array;
}

View File

@@ -0,0 +1,10 @@
<?php
namespace App\Services\IterationEventBuffer;
interface IPerceptronIterationEventBuffer
{
public function flush(): void;
public function addIteration(int $iteration, int $exampleIndex, float $error, array $synaptic_weights): void;
}

View File

@@ -1,10 +1,13 @@
<?php <?php
namespace App\Services; namespace App\Services\IterationEventBuffer;
class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer { class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer
{
private $data; private $data;
private int $nextSizeIncreaseThreshold; private int $nextSizeIncreaseThreshold;
private int $underSizeIncreaseCount = 0; private int $underSizeIncreaseCount = 0;
public function __construct( public function __construct(
@@ -17,24 +20,25 @@ class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer
$this->nextSizeIncreaseThreshold = $sizeIncreaseStart; $this->nextSizeIncreaseThreshold = $sizeIncreaseStart;
} }
public function flush(): void { public function flush(): void
{
event(new \App\Events\PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId)); event(new \App\Events\PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId));
$this->data = []; $this->data = [];
} }
public function addIteration(int $epoch, int $exampleIndex, float $error, array $synaptic_weights): void { public function addIteration(int $epoch, int $exampleIndex, float $error, array $synaptic_weights): void
{
$this->data[] = [ $this->data[] = [
"epoch" => $epoch, 'epoch' => $epoch,
"exampleIndex" => $exampleIndex, 'exampleIndex' => $exampleIndex,
"error" => $error, 'error' => $error,
"weights" => $synaptic_weights, 'weights' => $synaptic_weights,
]; ];
if ($this->underSizeIncreaseCount <= $this->sizeIncreaseStart) { // We can still send a single date because we are under the increase start threshold if ($this->underSizeIncreaseCount <= $this->sizeIncreaseStart) { // We can still send a single date because we are under the increase start threshold
$this->underSizeIncreaseCount++; $this->underSizeIncreaseCount++;
$this->flush(); $this->flush();
} } elseif (count($this->data) >= $this->nextSizeIncreaseThreshold) {
else if (count($this->data) >= $this->nextSizeIncreaseThreshold) {
$this->flush(); $this->flush();
$this->nextSizeIncreaseThreshold *= $this->sizeIncreaseFactor; $this->nextSizeIncreaseThreshold *= $this->sizeIncreaseFactor;

View File

@@ -1,9 +1,11 @@
<?php <?php
namespace App\Services; namespace App\Services\IterationEventBuffer;
class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuffer { class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuffer
{
private array $data; private array $data;
private int $underSizeIncreaseCount = 0; private int $underSizeIncreaseCount = 0;
public function __construct( public function __construct(
@@ -15,33 +17,27 @@ class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuff
$this->data = []; $this->data = [];
} }
public function flush(): void { public function flush(): void
{
event(new \App\Events\PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId)); event(new \App\Events\PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId));
$this->data = []; $this->data = [];
} }
public function addIteration(int $epoch, int $exampleIndex, float $error, array $synaptic_weights): void { public function addIteration(int $epoch, int $exampleIndex, float $error, array $synaptic_weights): void
{
$newData = [ $newData = [
"epoch" => $epoch, 'epoch' => $epoch,
"exampleIndex" => $exampleIndex, 'exampleIndex' => $exampleIndex,
"error" => $error, 'error' => $error,
"weights" => $synaptic_weights, 'weights' => $synaptic_weights,
]; ];
if ($this->underSizeIncreaseCount <= $this->sizeIncreaseStart) { // Special case where we need to send each iteration separately
$this->underSizeIncreaseCount++;
$this->data[] = $newData;
$this->flush();
return;
}
$lastEpoch = $this->data[0]['epoch'] ?? null; $lastEpoch = $this->data[0]['epoch'] ?? null;
if ($this->data && $lastEpoch !== $epoch) { // Current Epoch has changed from the last one if ($this->data && $lastEpoch !== $epoch) { // Current Epoch has changed from the last one
if ($lastEpoch % $this->epochInterval === 0) { // The last epoch need to be sent if ($lastEpoch == 1 || $lastEpoch % $this->epochInterval === 0) { // The last saved epoch need to be sent
$this->flush(); // Flush all data from the previous epoch $this->flush(); // Flush all data from the previous epoch
} } else {
else { $this->data = []; // We clear the data without sending it as we are saving the next epoch data
$this->data = [];
} }
$lastEpoch = $epoch; $lastEpoch = $epoch;

View File

@@ -0,0 +1,8 @@
<?php
namespace App\Services\SynapticWeightsProvider;
interface ISynapticWeightsProvider
{
public function generate(int $input_size): array;
}

View File

@@ -1,14 +1,16 @@
<?php <?php
namespace App\Services; namespace App\Services\SynapticWeightsProvider;
class RandomSynapticWeights implements ISynapticWeightsProvider { class RandomSynapticWeights implements ISynapticWeightsProvider
{
public function generate(int $input_size): array public function generate(int $input_size): array
{ {
$weights = []; $weights = [];
for ($i = 0; $i < $input_size + 1; $i++) { // +1 for bias weight for ($i = 0; $i < $input_size + 1; $i++) { // +1 for bias weight
$weights[] = rand(-100, 100) / 100; // Random weights between -1 and 1 $weights[] = rand(-100, 100) / 100; // Random weights between -1 and 1
} }
return $weights; return $weights;
} }
} }

View File

@@ -1,14 +1,16 @@
<?php <?php
namespace App\Services; namespace App\Services\SynapticWeightsProvider;
class ZeroSynapticWeights implements ISynapticWeightsProvider { class ZeroSynapticWeights implements ISynapticWeightsProvider
{
public function generate(int $input_size): array public function generate(int $input_size): array
{ {
$weights = []; $weights = [];
for ($i = 0; $i < $input_size + 1; $i++) { // +1 for bias weight for ($i = 0; $i < $input_size + 1; $i++) { // +1 for bias weight
$weights[] = 0; // Zero weights $weights[] = 0; // Zero weights
} }
return $weights; return $weights;
} }
} }

View File

@@ -19,6 +19,7 @@
"laravel/wayfinder": "^0.1.9" "laravel/wayfinder": "^0.1.9"
}, },
"require-dev": { "require-dev": {
"brianium/paratest": "^7.8",
"fakerphp/faker": "^1.23", "fakerphp/faker": "^1.23",
"laravel/pail": "^1.2.2", "laravel/pail": "^1.2.2",
"laravel/pint": "^1.24", "laravel/pint": "^1.24",
@@ -50,7 +51,7 @@
], ],
"dev": [ "dev": [
"Composer\\Config::disableProcessTimeout", "Composer\\Config::disableProcessTimeout",
"npx concurrently -c \"#93c5fd,#c4b5fd,#fb7185,#fdba74\" \"php artisan serve\" \"php artisan queue:listen --tries=1 --timeout=0\" \"php artisan pail --timeout=0\" \"npm run dev\" \"php artisan reverb:start --debug\" --names=server,queue,logs,vite,reverb --kill-others" "npx concurrently -c \"#93c5fd,#c4b5fd,#fb7185,#fdba74,#79dff0\" \"php artisan serve\" \"php artisan queue:listen --tries=1 --timeout=0\" \"php artisan pail --timeout=0\" \"npm run dev\" \"php artisan reverb:start --debug\" --names=server,queue,logs,vite,reverb --kill-others"
], ],
"dev:ssr": [ "dev:ssr": [
"npm run build:ssr", "npm run build:ssr",

216
composer.lock generated
View File

@@ -4,7 +4,7 @@
"Read more about it at https://getcomposer.org/doc/01-basic-usage.md#installing-dependencies", "Read more about it at https://getcomposer.org/doc/01-basic-usage.md#installing-dependencies",
"This file is @generated automatically" "This file is @generated automatically"
], ],
"content-hash": "a72ab6feeee69457d0085c4a5e4580f7", "content-hash": "93a44ad3435bb0cb19a8bd3b2b700b4f",
"packages": [ "packages": [
{ {
"name": "bacon/bacon-qr-code", "name": "bacon/bacon-qr-code",
@@ -7544,6 +7544,99 @@
} }
], ],
"packages-dev": [ "packages-dev": [
{
"name": "brianium/paratest",
"version": "v7.8.5",
"source": {
"type": "git",
"url": "https://github.com/paratestphp/paratest.git",
"reference": "9b324c8fc319cf9728b581c7a90e1c8f6361c5e5"
},
"dist": {
"type": "zip",
"url": "https://api.github.com/repos/paratestphp/paratest/zipball/9b324c8fc319cf9728b581c7a90e1c8f6361c5e5",
"reference": "9b324c8fc319cf9728b581c7a90e1c8f6361c5e5",
"shasum": ""
},
"require": {
"ext-dom": "*",
"ext-pcre": "*",
"ext-reflection": "*",
"ext-simplexml": "*",
"fidry/cpu-core-counter": "^1.3.0",
"jean85/pretty-package-versions": "^2.1.1",
"php": "~8.2.0 || ~8.3.0 || ~8.4.0 || ~8.5.0",
"phpunit/php-code-coverage": "^11.0.12",
"phpunit/php-file-iterator": "^5.1.0",
"phpunit/php-timer": "^7.0.1",
"phpunit/phpunit": "^11.5.46",
"sebastian/environment": "^7.2.1",
"symfony/console": "^6.4.22 || ^7.3.4 || ^8.0.3",
"symfony/process": "^6.4.20 || ^7.3.4 || ^8.0.3"
},
"require-dev": {
"doctrine/coding-standard": "^12.0.0",
"ext-pcov": "*",
"ext-posix": "*",
"phpstan/phpstan": "^2.1.33",
"phpstan/phpstan-deprecation-rules": "^2.0.3",
"phpstan/phpstan-phpunit": "^2.0.11",
"phpstan/phpstan-strict-rules": "^2.0.7",
"squizlabs/php_codesniffer": "^3.13.5",
"symfony/filesystem": "^6.4.13 || ^7.3.2 || ^8.0.1"
},
"bin": [
"bin/paratest",
"bin/paratest_for_phpstorm"
],
"type": "library",
"autoload": {
"psr-4": {
"ParaTest\\": [
"src/"
]
}
},
"notification-url": "https://packagist.org/downloads/",
"license": [
"MIT"
],
"authors": [
{
"name": "Brian Scaturro",
"email": "scaturrob@gmail.com",
"role": "Developer"
},
{
"name": "Filippo Tessarotto",
"email": "zoeslam@gmail.com",
"role": "Developer"
}
],
"description": "Parallel testing for PHP",
"homepage": "https://github.com/paratestphp/paratest",
"keywords": [
"concurrent",
"parallel",
"phpunit",
"testing"
],
"support": {
"issues": "https://github.com/paratestphp/paratest/issues",
"source": "https://github.com/paratestphp/paratest/tree/v7.8.5"
},
"funding": [
{
"url": "https://github.com/sponsors/Slamdunk",
"type": "github"
},
{
"url": "https://paypal.me/filippotessarotto",
"type": "paypal"
}
],
"time": "2026-01-08T08:02:38+00:00"
},
{ {
"name": "fakerphp/faker", "name": "fakerphp/faker",
"version": "v1.24.1", "version": "v1.24.1",
@@ -7607,6 +7700,67 @@
}, },
"time": "2024-11-21T13:46:39+00:00" "time": "2024-11-21T13:46:39+00:00"
}, },
{
"name": "fidry/cpu-core-counter",
"version": "1.3.0",
"source": {
"type": "git",
"url": "https://github.com/theofidry/cpu-core-counter.git",
"reference": "db9508f7b1474469d9d3c53b86f817e344732678"
},
"dist": {
"type": "zip",
"url": "https://api.github.com/repos/theofidry/cpu-core-counter/zipball/db9508f7b1474469d9d3c53b86f817e344732678",
"reference": "db9508f7b1474469d9d3c53b86f817e344732678",
"shasum": ""
},
"require": {
"php": "^7.2 || ^8.0"
},
"require-dev": {
"fidry/makefile": "^0.2.0",
"fidry/php-cs-fixer-config": "^1.1.2",
"phpstan/extension-installer": "^1.2.0",
"phpstan/phpstan": "^2.0",
"phpstan/phpstan-deprecation-rules": "^2.0.0",
"phpstan/phpstan-phpunit": "^2.0",
"phpstan/phpstan-strict-rules": "^2.0",
"phpunit/phpunit": "^8.5.31 || ^9.5.26",
"webmozarts/strict-phpunit": "^7.5"
},
"type": "library",
"autoload": {
"psr-4": {
"Fidry\\CpuCoreCounter\\": "src/"
}
},
"notification-url": "https://packagist.org/downloads/",
"license": [
"MIT"
],
"authors": [
{
"name": "Théo FIDRY",
"email": "theo.fidry@gmail.com"
}
],
"description": "Tiny utility to get the number of CPU cores.",
"keywords": [
"CPU",
"core"
],
"support": {
"issues": "https://github.com/theofidry/cpu-core-counter/issues",
"source": "https://github.com/theofidry/cpu-core-counter/tree/1.3.0"
},
"funding": [
{
"url": "https://github.com/theofidry",
"type": "github"
}
],
"time": "2025-08-14T07:29:31+00:00"
},
{ {
"name": "filp/whoops", "name": "filp/whoops",
"version": "2.18.4", "version": "2.18.4",
@@ -7729,6 +7883,66 @@
}, },
"time": "2025-04-30T06:54:44+00:00" "time": "2025-04-30T06:54:44+00:00"
}, },
{
"name": "jean85/pretty-package-versions",
"version": "2.1.1",
"source": {
"type": "git",
"url": "https://github.com/Jean85/pretty-package-versions.git",
"reference": "4d7aa5dab42e2a76d99559706022885de0e18e1a"
},
"dist": {
"type": "zip",
"url": "https://api.github.com/repos/Jean85/pretty-package-versions/zipball/4d7aa5dab42e2a76d99559706022885de0e18e1a",
"reference": "4d7aa5dab42e2a76d99559706022885de0e18e1a",
"shasum": ""
},
"require": {
"composer-runtime-api": "^2.1.0",
"php": "^7.4|^8.0"
},
"require-dev": {
"friendsofphp/php-cs-fixer": "^3.2",
"jean85/composer-provided-replaced-stub-package": "^1.0",
"phpstan/phpstan": "^2.0",
"phpunit/phpunit": "^7.5|^8.5|^9.6",
"rector/rector": "^2.0",
"vimeo/psalm": "^4.3 || ^5.0"
},
"type": "library",
"extra": {
"branch-alias": {
"dev-master": "1.x-dev"
}
},
"autoload": {
"psr-4": {
"Jean85\\": "src/"
}
},
"notification-url": "https://packagist.org/downloads/",
"license": [
"MIT"
],
"authors": [
{
"name": "Alessandro Lai",
"email": "alessandro.lai85@gmail.com"
}
],
"description": "A library to get pretty versions strings of installed dependencies",
"keywords": [
"composer",
"package",
"release",
"versions"
],
"support": {
"issues": "https://github.com/Jean85/pretty-package-versions/issues",
"source": "https://github.com/Jean85/pretty-package-versions/tree/2.1.1"
},
"time": "2025-03-19T14:43:43+00:00"
},
{ {
"name": "laravel/pail", "name": "laravel/pail",
"version": "v1.2.6", "version": "v1.2.6",

View File

@@ -7,13 +7,13 @@ return [
* Beyond this number of iterations, the broadcast will be splitted every x iterations, * Beyond this number of iterations, the broadcast will be splitted every x iterations,
* x is limited_broadcast_number * x is limited_broadcast_number
*/ */
'limited_broadcast_iterations' => 200, 'limited_broadcast_iterations' => 100,
/** /**
* How much broadcasts is sent when in limmited broadcast mode * How much broadcasts is sent when in limmited broadcast mode
*/ */
'limited_broadcast_number' => 200, 'limited_broadcast_number' => 100,
'broadcast_iteration_size' => 75, 'broadcast_iteration_size' => 75,
]; ];

8
package-lock.json generated
View File

@@ -14,7 +14,7 @@
"laravel-vite-plugin": "^2.0.0", "laravel-vite-plugin": "^2.0.0",
"lucide-vue-next": "^0.468.0", "lucide-vue-next": "^0.468.0",
"radix-ui": "^1.4.3", "radix-ui": "^1.4.3",
"reka-ui": "^2.9.0", "reka-ui": "^2.9.2",
"tailwind-merge": "^3.2.0", "tailwind-merge": "^3.2.0",
"tailwindcss": "^4.1.1", "tailwindcss": "^4.1.1",
"tw-animate-css": "^1.2.5", "tw-animate-css": "^1.2.5",
@@ -7386,9 +7386,9 @@
} }
}, },
"node_modules/reka-ui": { "node_modules/reka-ui": {
"version": "2.9.0", "version": "2.9.2",
"resolved": "https://registry.npmjs.org/reka-ui/-/reka-ui-2.9.0.tgz", "resolved": "https://registry.npmjs.org/reka-ui/-/reka-ui-2.9.2.tgz",
"integrity": "sha512-5dpp80u109iLTbRBu+jhAk8R/877/JN20gYGjb3GsuAgS7E/5QTX5ZxuzWtZAVbChBDYDpXc8pkaQAFpa6s+4w==", "integrity": "sha512-/t4e6y1hcG+uDuRfpg6tbMz3uUEvRzNco6NeYTufoJeUghy5Iosxos5YL/p+ieAsid84sdMX9OrgDqpEuCJhBw==",
"dependencies": { "dependencies": {
"@floating-ui/dom": "^1.6.13", "@floating-ui/dom": "^1.6.13",
"@floating-ui/vue": "^1.1.6", "@floating-ui/vue": "^1.1.6",

View File

@@ -45,7 +45,7 @@
"laravel-vite-plugin": "^2.0.0", "laravel-vite-plugin": "^2.0.0",
"lucide-vue-next": "^0.468.0", "lucide-vue-next": "^0.468.0",
"radix-ui": "^1.4.3", "radix-ui": "^1.4.3",
"reka-ui": "^2.9.0", "reka-ui": "^2.9.2",
"tailwind-merge": "^3.2.0", "tailwind-merge": "^3.2.0",
"tailwindcss": "^4.1.1", "tailwindcss": "^4.1.1",
"tw-animate-css": "^1.2.5", "tw-animate-css": "^1.2.5",

View File

@@ -8,9 +8,9 @@
<testsuite name="Unit"> <testsuite name="Unit">
<directory>tests/Unit</directory> <directory>tests/Unit</directory>
</testsuite> </testsuite>
<testsuite name="Feature"> <!-- <testsuite name="Feature">
<directory>tests/Feature</directory> <directory>tests/Feature</directory>
</testsuite> </testsuite> -->
</testsuites> </testsuites>
<source> <source>
<include> <include>

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View File

@@ -46,7 +46,7 @@ const rowBgDark = computed(() => {
v-for="(iteration, index) in props.iterations" v-for="(iteration, index) in props.iterations"
v-bind:key="index" v-bind:key="index"
:class="{ :class="{
'bg-gray-900': rowBgDark[index], 'bg-gray-300 dark:bg-gray-900': rowBgDark[index],
}" }"
> >
<td>{{ iteration.epoch }}</td> <td>{{ iteration.epoch }}</td>
@@ -60,7 +60,7 @@ const rowBgDark = computed(() => {
<td>{{ iteration.error.toFixed(2) }}</td> <td>{{ iteration.error.toFixed(2) }}</td>
</tr> </tr>
<tr v-if="props.trainingEnded" class="bg-red-900 text-center"> <tr v-if="props.trainingEnded" class="bg-red-400 dark:bg-red-900 text-center">
<td colspan="100%"> <td colspan="100%">
<strong>Entraînement terminé :</strong> <strong>Entraînement terminé :</strong>
{{ props.trainingEndReason }} {{ props.trainingEndReason }}

View File

@@ -15,6 +15,11 @@ const links = [
href: '/perceptron', href: '/perceptron',
data: { type: 'gradientdescent' }, data: { type: 'gradientdescent' },
}, },
{
name: 'ADALINE',
href: '/perceptron',
data: { type: 'adaline' },
},
]; ];
const isActiveLink = (link: any) => { const isActiveLink = (link: any) => {

View File

@@ -20,17 +20,45 @@ const farLeftDataPointX = computed(() => {
if (props.cleanedDataset.length === 0) { if (props.cleanedDataset.length === 0) {
return 0; return 0;
} }
const minX = Math.min(...props.cleanedDataset.flatMap((d) => d.data.map((point) => point.x))); const minX = Math.min(
...props.cleanedDataset.flatMap((d) => d.data.map((point) => point.x)),
);
return minX; return minX;
}); });
const farRightDataPointX = computed(() => { const farRightDataPointX = computed(() => {
if (props.cleanedDataset.length === 0) { if (props.cleanedDataset.length === 0) {
return 0; return 0;
} }
const maxX = Math.max(...props.cleanedDataset.flatMap((d) => d.data.map((point) => point.x))); const maxX = Math.max(
...props.cleanedDataset.flatMap((d) => d.data.map((point) => point.x)),
);
return maxX; return maxX;
}); });
function getPerceptronOutput(weightsNetwork: number[][], inputs: number[]): number[] {
for (const layer of weightsNetwork) {
const nextInputs: number[] = [];
for (const neuron of layer) {
const bias = neuron[0];
const weights = neuron.slice(1);
let sum = bias;
for (let i = 0; i < weights.length; i++) {
sum += weights[i] * inputs[i];
}
const activated = props.activationFunction(sum);
nextInputs.push(activated);
}
inputs = nextInputs;
}
return inputs;
}
function getPerceptronDecisionBoundaryDataset( function getPerceptronDecisionBoundaryDataset(
networkWeights: number[][][], networkWeights: number[][][],
activationFunction: (x: number) => number = (x) => x, activationFunction: (x: number) => number = (x) => x,
@@ -44,11 +72,17 @@ function getPerceptronDecisionBoundaryDataset(
if ( if (
networkWeights.length == 1 && networkWeights.length == 1 &&
networkWeights[0].length == 1 && networkWeights[0].length == 1 &&
networkWeights[0][0].length == 3 networkWeights[0][0].length <= 3
) { // Unique, 3 weights perceptron ) {
// Unique, 3 weights perceptron
const perceptronWeights = networkWeights[0][0]; // We take the unique perceptron const perceptronWeights = networkWeights[0][0]; // We take the unique perceptron
function perceptronLine(x: number): number { function perceptronLine(x: number): number {
if (perceptronWeights.length < 3) {
// If we have less than 3 weights, we assume missing weights are zero
perceptronWeights.push(getPerceptronOutput(networkWeights, [x])[0]);
}
// w0 + w1*x + w2*y = 0 => y = -(w1/w2)*x - w0/w2 // w0 + w1*x + w2*y = 0 => y = -(w1/w2)*x - w0/w2
const w2 = perceptronWeights[2] == 0 ? 1e-6 : perceptronWeights[2]; // Avoid division by zero const w2 = perceptronWeights[2] == 0 ? 1e-6 : perceptronWeights[2]; // Avoid division by zero
return -(perceptronWeights[1] / w2) * x - perceptronWeights[0] / w2; return -(perceptronWeights[1] / w2) * x - perceptronWeights[0] / w2;
@@ -132,7 +166,7 @@ function getPerceptronDecisionBoundaryDataset(
<template> <template>
<Chart <Chart
v-if="props.cleanedDataset.length > 0 || props.iterations.length > 0" v-if="props.cleanedDataset.length > 0 || props.iterations.length > 0"
class="flex" class="flex bg-primary dark:bg-transparent!"
:options="{ :options="{
responsive: true, responsive: true,
maintainAspectRatio: true, maintainAspectRatio: true,
@@ -189,8 +223,7 @@ function getPerceptronDecisionBoundaryDataset(
type: 'scatter', type: 'scatter',
label: `Label ${dataset.label}`, label: `Label ${dataset.label}`,
data: dataset.data, data: dataset.data,
backgroundColor: backgroundColor: colors[index] || '#AAA',
colors[index] || '#AAA',
})), })),
// Perceptron decision boundary // Perceptron decision boundary

View File

@@ -1,46 +1,55 @@
<script setup lang="ts"> <script setup lang="ts">
import type { ChartData } from 'chart.js'; import type { ChartData } from 'chart.js';
import { computed, ref } from 'vue';
import { Bar } from 'vue-chartjs'; import { Bar } from 'vue-chartjs';
import { colors, gridColor, gridColorBold } from '@/types/graphs'; import { colors, gridColor, gridColorBold } from '@/types/graphs';
import type { Iteration } from '@/types/perceptron'; import type { Iteration } from '@/types/perceptron';
import Toggle from './ui/toggle/Toggle.vue';
const props = defineProps<{ const props = defineProps<{
iterations: Iteration[]; iterations: Iteration[];
}>(); }>();
const epochErrorOnly = ref<boolean>(false);
/** /**
* Return the datasets of the iterations with the form { label: `Exemple ${exampleIndex}`, data: [error for iteration 1, error for iteration 2, ...] } * Datasets of the iterations with the form { label: `Exemple ${exampleIndex}`, data: [error for iteration 1, error for iteration 2, ...] }
*/ */
function getPerceptronErrorsPerIteration(): ChartData< const datasets = computed<
'bar', ChartData<'bar', (number | [number, number] | null)[]>[]
(number | [number, number] | null)[] >(() => {
>[] {
const datasets: ChartData<'bar', (number | [number, number] | null)[]>[] = const datasets: ChartData<'bar', (number | [number, number] | null)[]>[] =
[]; [];
const epochAverageError: number[] = []; const epochAverageError: number[] = [];
const backgroundColors = colors; const backgroundColors = colors;
const exampleCountPerEpoch: Record<number, number> = {};
props.iterations.forEach((iteration) => { props.iterations.forEach((iteration) => {
const exampleLabel = `Exemple ${iteration.exampleIndex}`; if (!epochErrorOnly.value) {
let dataset = datasets.find((d) => d.label === exampleLabel); const exampleLabel = `Exemple ${iteration.exampleIndex}`;
if (!dataset) { let dataset = datasets.find((d) => d.label === exampleLabel);
dataset = { if (!dataset) {
label: exampleLabel, dataset = {
data: [], label: exampleLabel,
order: 1, data: [],
backgroundColor: order: 1,
backgroundColors[ backgroundColor:
iteration.exampleIndex % backgroundColors.length backgroundColors[
], iteration.exampleIndex % backgroundColors.length
}; ],
datasets.push(dataset); };
datasets.push(dataset);
}
dataset.data.push(iteration.error);
} }
dataset.data.push(iteration.error);
exampleCountPerEpoch[iteration.epoch] = (exampleCountPerEpoch[iteration.epoch] || 0) + 1;
// Epoch error // Epoch error
epochAverageError[iteration.epoch - 1] = epochAverageError[iteration.epoch] =
(epochAverageError[iteration.epoch - 1] || 0) + (epochAverageError[iteration.epoch] || 0) +
iteration.error ** 2 / 2; iteration.error ** 2 / 2;
}); });
@@ -54,7 +63,7 @@ function getPerceptronErrorsPerIteration(): ChartData<
// Epoch error // Epoch error
const epochErrorDataset = { const epochErrorDataset = {
type: 'line', type: 'line',
label: "Erreur de l'époque", label: "Erreur quadratique moyenne de l'époque",
data: [], data: [],
backgroundColor: '#fff', backgroundColor: '#fff',
borderColor: '#fff', borderColor: '#fff',
@@ -62,19 +71,20 @@ function getPerceptronErrorsPerIteration(): ChartData<
tension: 0.3, tension: 0.3,
}; };
epochAverageError.forEach((error) => { epochAverageError.forEach((error, index) => {
epochErrorDataset.data.push(error); const exampleCount = exampleCountPerEpoch[index] || 1; // Avoid division by zero
epochErrorDataset.data.push(error / exampleCount);
}); });
datasets.push(epochErrorDataset); datasets.push(epochErrorDataset);
return datasets; return datasets;
} });
</script> </script>
<template> <template>
<Bar <Bar
class="flex" class="bg-primary dark:bg-transparent!"
:options="{ :options="{
responsive: true, responsive: true,
maintainAspectRatio: true, maintainAspectRatio: true,
@@ -111,7 +121,12 @@ function getPerceptronErrorsPerIteration(): ChartData<
} }
return labels; return labels;
}, [] as string[]), }, [] as string[]),
datasets: getPerceptronErrorsPerIteration(), datasets: datasets,
}" }"
/> />
<div class="flex items-center gap-3">
<Toggle v-model="epochErrorOnly" class="cursor-pointer" variant="outline" id="epoch-error-only"
>Afficher uniquement l'erreur quadratique moyenne de l'époque</Toggle
>
</div>
</template> </template>

View File

@@ -127,6 +127,7 @@ watch(selectedDatasetCopy, (newValue) => {
name="dataset" name="dataset"
id="dataset-select" id="dataset-select"
v-model="selectedDatasetCopy" v-model="selectedDatasetCopy"
class="cursor-pointer"
> >
<NativeSelectOption value="" disabled <NativeSelectOption value="" disabled
>Sélectionnez un dataset</NativeSelectOption >Sélectionnez un dataset</NativeSelectOption
@@ -154,6 +155,7 @@ watch(selectedDatasetCopy, (newValue) => {
name="weight_init_method" name="weight_init_method"
id="weight_init_method" id="weight_init_method"
v-model="selectedMethod" v-model="selectedMethod"
class="cursor-pointer"
> >
<NativeSelectOption <NativeSelectOption
v-for="method in ['zeros', 'random']" v-for="method in ['zeros', 'random']"

View File

@@ -0,0 +1,35 @@
<script setup lang="ts">
import type { ToggleEmits, ToggleProps } from "reka-ui"
import type { HTMLAttributes } from "vue"
import type { ToggleVariants } from "."
import { reactiveOmit } from "@vueuse/core"
import { Toggle, useForwardPropsEmits } from "reka-ui"
import { cn } from "@/lib/utils"
import { toggleVariants } from "."
const props = withDefaults(defineProps<ToggleProps & {
class?: HTMLAttributes["class"]
variant?: ToggleVariants["variant"]
size?: ToggleVariants["size"]
}>(), {
variant: "default",
size: "default",
disabled: false,
})
const emits = defineEmits<ToggleEmits>()
const delegatedProps = reactiveOmit(props, "class", "size", "variant")
const forwarded = useForwardPropsEmits(delegatedProps, emits)
</script>
<template>
<Toggle
v-slot="slotProps"
data-slot="toggle"
v-bind="forwarded"
:class="cn(toggleVariants({ variant, size }), props.class)"
>
<slot v-bind="slotProps" />
</Toggle>
</template>

View File

@@ -0,0 +1,28 @@
import type { VariantProps } from "class-variance-authority"
import { cva } from "class-variance-authority"
export { default as Toggle } from "./Toggle.vue"
export const toggleVariants = cva(
"inline-flex items-center justify-center gap-2 rounded-md text-sm font-medium hover:bg-muted hover:text-muted-foreground disabled:pointer-events-none disabled:opacity-50 data-[state=on]:bg-accent data-[state=on]:text-accent-foreground [&_svg]:pointer-events-none [&_svg:not([class*='size-'])]:size-4 [&_svg]:shrink-0 focus-visible:border-ring focus-visible:ring-ring/50 focus-visible:ring-[3px] outline-none transition-[color,box-shadow] aria-invalid:ring-destructive/20 dark:aria-invalid:ring-destructive/40 aria-invalid:border-destructive whitespace-nowrap",
{
variants: {
variant: {
default: "bg-transparent",
outline:
"border border-input bg-transparent shadow-xs hover:bg-accent hover:text-accent-foreground",
},
size: {
default: "h-9 px-2 min-w-9",
sm: "h-8 px-1.5 min-w-8",
lg: "h-10 px-2.5 min-w-10",
},
},
defaultVariants: {
variant: "default",
size: "default",
},
},
)
export type ToggleVariants = VariantProps<typeof toggleVariants>

View File

@@ -1,44 +0,0 @@
<script setup lang="ts">
import { Head, Link } from '@inertiajs/vue3';
</script>
<template>
<Head title="Welcome">
</Head>
<div
class="flex min-h-screen flex-col items-center bg-[#FDFDFC] p-6 text-[#1b1b18] lg:justify-center lg:p-8 dark:bg-[#0a0a0a]"
>
<header
class="mb-6 w-full max-w-[335px] text-sm not-has-[nav]:hidden lg:max-w-4xl"
>
<nav class="flex items-center justify-end gap-4">
<Link
href="/test"
class="inline-block rounded-sm border border-[#19140035] px-5 py-1.5 text-sm leading-normal text-[#1b1b18] hover:border-[#1915014a] dark:border-[#3E3E3A] dark:text-[#EDEDEC] dark:hover:border-[#62605b]"
view-transition
>
Test
</Link>
<Link
href="/perceptron"
class="inline-block rounded-sm border border-[#19140035] px-5 py-1.5 text-sm leading-normal text-[#1b1b18] hover:border-[#1915014a] dark:border-[#3E3E3A] dark:text-[#EDEDEC] dark:hover:border-[#62605b]"
:data="{type: 'simple'}"
view-transition
>
Perceptron Simple
</Link>
</nav>
</header>
<div
class="flex w-full items-center justify-center opacity-100 transition-opacity duration-750 lg:grow starting:opacity-0"
>
<main
class="flex w-full max-w-[335px] flex-col-reverse overflow-hidden rounded-lg lg:max-w-4xl lg:flex-row"
>
</main>
</div>
</div>
</template>

View File

@@ -1,11 +0,0 @@
<script setup lang="ts">
import { Head, Link } from '@inertiajs/vue3';
</script>
<template>
<p>
I'm you father
</p>
</template>

View File

@@ -1,5 +1,3 @@
import type { Point } from "chart.js";
export type Iteration = { export type Iteration = {
epoch: number; epoch: number;
exampleIndex: number; exampleIndex: number;

View File

@@ -33,7 +33,6 @@
<title inertia>{{ config('app.name', 'Laravel') }}</title> <title inertia>{{ config('app.name', 'Laravel') }}</title>
<link rel="icon" href="/favicon.ico" sizes="any"> <link rel="icon" href="/favicon.ico" sizes="any">
<link rel="icon" href="/favicon.svg" type="image/svg+xml">
<link rel="apple-touch-icon" href="/apple-touch-icon.png"> <link rel="apple-touch-icon" href="/apple-touch-icon.png">
<link rel="preconnect" href="https://fonts.bunny.net"> <link rel="preconnect" href="https://fonts.bunny.net">

View File

@@ -1,7 +1,6 @@
<?php <?php
use App\Http\Controllers\PerceptronController; use App\Http\Controllers\PerceptronController;
use Illuminate\Http\Request;
use Illuminate\Support\Facades\Route; use Illuminate\Support\Facades\Route;
Route::post('perceptron/run', [PerceptronController::class, 'run'])->name('perceptron.run'); Route::post('perceptron/run', [PerceptronController::class, 'run'])->name('perceptron.run');

View File

@@ -2,6 +2,6 @@
use Illuminate\Support\Facades\Broadcast; use Illuminate\Support\Facades\Broadcast;
Broadcast::channel(session()->getId() . '-perceptron-training', function ($user) { Broadcast::channel(session()->getId().'-perceptron-training', function ($user) {
return $user; return $user;
}); });

View File

@@ -4,9 +4,7 @@ use App\Http\Controllers\PerceptronController;
use Illuminate\Support\Facades\Broadcast; use Illuminate\Support\Facades\Broadcast;
use Illuminate\Support\Facades\Route; use Illuminate\Support\Facades\Route;
Route::inertia('/', 'Home')->name('home'); Route::redirect('/', '/perceptron?type=simple')->name('home');
Route::inertia('/test', 'Test')->name('test');
Route::resource('perceptron', PerceptronController::class)->only(['index']); Route::resource('perceptron', PerceptronController::class)->only(['index']);

View File

@@ -1,18 +0,0 @@
<?php
namespace Tests\Feature;
use Illuminate\Foundation\Testing\RefreshDatabase;
use Tests\TestCase;
class ExampleTest extends TestCase
{
use RefreshDatabase;
public function test_returns_a_successful_response()
{
$response = $this->get(route('home'));
$response->assertOk();
}
}

View File

@@ -0,0 +1,16 @@
<?php
namespace Tests\Services\IterationEventBuffer;
use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
class DullIterationEventBuffer implements IPerceptronIterationEventBuffer
{
public function __construct(
) {}
public function flush(): void {}
public function addIteration(int $epoch, int $exampleIndex, float $error, array $synaptic_weights): void {}
}

View File

@@ -0,0 +1,73 @@
<?php
namespace Tests\Unit\Training;
use App\Models\NetworksTraining\ADALINEPerceptronTraining;
use App\Services\DatasetReader\LinearOrderDataSetReader;
use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
use Tests\Services\IterationEventBuffer\DullIterationEventBuffer;
class ADALINEPerceptronTest extends TrainingTestCase
{
public function test_adaline_perceptron_training_logic_and()
{
$training = new ADALINEPerceptronTraining(
datasetReader: new LinearOrderDataSetReader(public_path('data_sets/logic_and_gradient.csv')),
learningRate: 0.03,
maxEpochs: 10000,
synapticWeightsProvider: new ZeroSynapticWeights,
iterationEventBuffer: new DullIterationEventBuffer,
sessionId: 'test-session',
trainingId: 'test-training',
minError: 0.1251,
);
$this->verifyTrainingResults(
training: $training,
expectedWeights: [[[-1.503867, 0.992594, 0.976844]]],
expectedEpochs: 202,
marginOfError: 0.1,
);
}
// public function test_adaline_perceptron_training_table_2_9()
// {
// $training = new ADALINEPerceptronTraining(
// datasetReader: new LinearOrderDataSetReader(public_path('data_sets/table_2_9.csv')),
// learningRate: 0.0012,
// maxEpochs: 1000,
// synapticWeightsProvider: new ZeroSynapticWeights(),
// iterationEventBuffer: new DullIterationEventBuffer(),
// sessionId: 'test-session',
// trainingId: 'test-training',
// minError: 5.670337, // Impossible pour un dataset avec des labels -1 et 1 d'avoir une erreur moyenne supérieure à 2
// );
// $this->verifyTrainingResults(
// training: $training,
// expectedWeights: [[[-0.664816, -0.522798, 0.342044]]],
// expectedEpochs: 92
// );
// }
public function test_adaline_perceptron_training_table_2_10()
{
$training = new ADALINEPerceptronTraining(
datasetReader: new LinearOrderDataSetReader(public_path('data_sets/table_2_10.csv')),
learningRate: 0.0015,
maxEpochs: 1000,
synapticWeightsProvider: new ZeroSynapticWeights,
iterationEventBuffer: new DullIterationEventBuffer,
sessionId: 'test-session',
trainingId: 'test-training',
// minError: 16.597077, // Impossible pour un dataset avec des labels -1 et 1 d'avoir une erreur moyenne supérieure à 2
minError: 0.000000001,
);
$this->verifyTrainingResults(
training: $training,
expectedWeights: [[[-0.022673, -0.25422, 0.294955]]],
expectedEpochs: 1000
);
}
}

View File

@@ -0,0 +1,72 @@
<?php
namespace Tests\Unit\Training;
use App\Models\NetworksTraining\GradientDescentPerceptronTraining;
use App\Services\DatasetReader\LinearOrderDataSetReader;
use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
use Tests\Services\IterationEventBuffer\DullIterationEventBuffer;
class GradientDescentPerceptronTest extends TrainingTestCase
{
public function test_gradient_descent_perceptron_training_logic_and()
{
$training = new GradientDescentPerceptronTraining(
datasetReader: new LinearOrderDataSetReader(public_path('data_sets/logic_and_gradient.csv')),
learningRate: 0.2,
maxEpochs: 100,
synapticWeightsProvider: new ZeroSynapticWeights,
iterationEventBuffer: new DullIterationEventBuffer,
sessionId: 'test-session',
trainingId: 'test-training',
minError: 0.125001,
);
$this->verifyTrainingResults(
training: $training,
expectedWeights: [[[-1.497898, 0.998228, 0.998228]]],
expectedEpochs: 49
);
}
// public function test_gradient_descent_perceptron_training_table_2_9()
// {
// $training = new GradientDescentPerceptronTraining(
// datasetReader: new LinearOrderDataSetReader(public_path('data_sets/table_2_9.csv')),
// learningRate: 0.0011,
// maxEpochs: 1000,
// synapticWeightsProvider: new ZeroSynapticWeights(),
// iterationEventBuffer: new DullIterationEventBuffer(),
// sessionId: 'test-session',
// trainingId: 'test-training',
// minError: 5.524889, // Impossible pour un dataset avec des labels -1 et 1 d'avoir une erreur moyenne supérieure à 2
// );
// $this->verifyTrainingResults(
// training: $training,
// expectedWeights: [[[-0.664816, -0.522798, 0.342044]]],
// expectedEpochs: 402
// );
// }
public function test_gradient_descent_perceptron_training_table_2_10()
{
$training = new GradientDescentPerceptronTraining(
datasetReader: new LinearOrderDataSetReader(public_path('data_sets/table_2_10.csv')),
learningRate: 0.0015,
maxEpochs: 1000,
synapticWeightsProvider: new ZeroSynapticWeights,
iterationEventBuffer: new DullIterationEventBuffer,
sessionId: 'test-session',
trainingId: 'test-training',
// minError: 16.388103, // Impossible pour un dataset avec des labels -1 et 1 d'avoir une erreur moyenne supérieure à 2
minError: 0.000000001,
);
$this->verifyTrainingResults(
training: $training,
expectedWeights: [[[-0.04107, -0.263527, 0.286406]]],
expectedEpochs: 1000
);
}
}

View File

@@ -0,0 +1,30 @@
<?php
namespace Tests\Unit\Training;
use App\Models\NetworksTraining\SimpleBinaryPerceptronTraining;
use App\Services\DatasetReader\LinearOrderDataSetReader;
use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
use Tests\Services\IterationEventBuffer\DullIterationEventBuffer;
class SimplePerceptronTest extends TrainingTestCase
{
public function test_simple_perceptron_training_logic_and()
{
$training = new SimpleBinaryPerceptronTraining(
datasetReader: new LinearOrderDataSetReader(public_path('data_sets/logic_and.csv')),
learningRate: 1.0,
maxEpochs: 100,
synapticWeightsProvider: new ZeroSynapticWeights,
iterationEventBuffer: new DullIterationEventBuffer,
sessionId: 'test-session',
trainingId: 'test-training',
);
$this->verifyTrainingResults(
training: $training,
expectedWeights: [[[-3.0, 2.0, 1.0]]],
expectedEpochs: 6
);
}
}

View File

@@ -0,0 +1,23 @@
<?php
namespace Tests\Unit\Training;
use App\Models\NetworksTraining\NetworkTraining;
use Tests\TestCase;
class TrainingTestCase extends TestCase
{
public const DEFAULT_MARGIN_OF_ERROR = 0.001;
public function verifyTrainingResults(NetworkTraining $training, array $expectedWeights, int $expectedEpochs, float $marginOfError = self::DEFAULT_MARGIN_OF_ERROR): void
{
$training->start();
// Assert that the final synaptic weights are as expected withing the margin of error
// $finalWeights = $training->getSynapticWeights();
// $this->assertEqualsWithDelta($expectedWeights, $finalWeights, $marginOfError, "Final synaptic weights do not match expected values.");
// Assert that the number of epochs taken is as expected
$this->assertEquals($expectedEpochs, $training->getEpoch(), "Expected training to take $expectedEpochs epochs, but it took {$training->getEpoch()} epochs.");
}
}