Some bugfixes and misc

app/Events/PerceptronInitialization.php

@@ -5,11 +5,11 @@ namespace App\Events;
 use App\Models\ActivationsFunctions;
 use Illuminate\Broadcasting\Channel;
 use Illuminate\Broadcasting\InteractsWithSockets;
-use Illuminate\Contracts\Broadcasting\ShouldBroadcast;
+use Illuminate\Contracts\Broadcasting\ShouldBroadcastNow;
 use Illuminate\Foundation\Events\Dispatchable;
 use Illuminate\Queue\SerializesModels;
 
-class PerceptronInitialization implements ShouldBroadcast
+class PerceptronInitialization implements ShouldBroadcastNow
 {
     use Dispatchable, InteractsWithSockets, SerializesModels;
 

app/Events/PerceptronTrainingEnded.php

@@ -4,11 +4,11 @@ namespace App\Events;
 
 use Illuminate\Broadcasting\Channel;
 use Illuminate\Broadcasting\InteractsWithSockets;
-use Illuminate\Contracts\Broadcasting\ShouldBroadcast;
+use Illuminate\Contracts\Broadcasting\ShouldBroadcastNow;
 use Illuminate\Foundation\Events\Dispatchable;
 use Illuminate\Queue\SerializesModels;
 
-class PerceptronTrainingEnded implements ShouldBroadcast
+class PerceptronTrainingEnded implements ShouldBroadcastNow
 {
     use Dispatchable, InteractsWithSockets, SerializesModels;
 

app/Events/PerceptronTrainingIteration.php

@@ -4,12 +4,12 @@ namespace App\Events;
 
 use Illuminate\Broadcasting\Channel;
 use Illuminate\Broadcasting\InteractsWithSockets;
-use Illuminate\Contracts\Broadcasting\ShouldBroadcast;
+use Illuminate\Contracts\Broadcasting\ShouldBroadcastNow;
 use Illuminate\Foundation\Events\Dispatchable;
-use Illuminate\Support\Arr;
 use Illuminate\Queue\SerializesModels;
+use Illuminate\Support\Arr;
 
-class PerceptronTrainingIteration implements ShouldBroadcast
+class PerceptronTrainingIteration implements ShouldBroadcastNow
 {
     use Dispatchable, InteractsWithSockets, SerializesModels;
 
@@ -39,19 +39,20 @@ class PerceptronTrainingIteration implements ShouldBroadcast
 
     public function broadcastWith(): array
     {
-        $weights = collect($this->iterations)
+        $iterations = self::normalizeForJson($this->iterations);
+        $weights = collect($iterations)
             ->pluck('weights')
             ->first(fn (array $weights): bool => $weights !== []);
         $shouldBroadcastAllWeights = $weights !== null
             && count(Arr::flatten($weights)) <= config('perceptron.max_displayed_weights');
 
-        $lastIterationIndex = count($this->iterations) - 1;
+        $lastIterationIndex = count($iterations) - 1;
         $iterations = array_map(
             fn (array $iteration, int $index): array => $shouldBroadcastAllWeights || $index === $lastIterationIndex
                 ? $iteration
                 : [...$iteration, 'weights' => []],
-            $this->iterations,
-            array_keys($this->iterations),
+            $iterations,
+            array_keys($iterations),
         );
 
         return [
@@ -59,4 +60,20 @@ class PerceptronTrainingIteration implements ShouldBroadcast
             'trainingId' => $this->trainingId,
         ];
     }
+
+    public static function normalizeForJson(mixed $value): mixed
+    {
+        if (is_float($value) && ! is_finite($value)) {
+            return null;
+        }
+
+        if (! is_array($value)) {
+            return $value;
+        }
+
+        return array_map(
+            fn (mixed $item): mixed => self::normalizeForJson($item),
+            $value,
+        );
+    }
 }

app/Http/Controllers/PerceptronController.php

@@ -18,7 +18,6 @@ use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
 use App\Services\SynapticWeightsProvider\RandomSynapticWeights;
 use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
 use Illuminate\Http\Request;
-use Illuminate\Support\Facades\DB;
 
 class PerceptronController extends Controller
 {
@@ -134,6 +133,11 @@ class PerceptronController extends Controller
                         break;
                     case 'table_2_11':
                         $dataset['defaultMinError'] = 0.02;
+                        switch ($perceptronType) {
+                            case 'monolayer':
+                                $dataset['defaultLearningRate'] = 0.0015;
+                                break;
+                        }
                         break;
                     case 'table_4_12':
                         switch ($perceptronType) {
@@ -145,11 +149,13 @@ class PerceptronController extends Controller
                         }
                         break;
                     case 'table_4_17':
+                        $dataset['defaultMinError'] = 0.055;
                         switch ($perceptronType) {
                             case 'multilayer':
-                                $dataset['defaultLearningRate'] = 0.5;
-                                $dataset['defaultMinError'] = 0.08;
+                                $dataset['defaultLearningRate'] = 0.3;
                                 $dataset['defaultMaxIterations'] = 400;
+                                $dataset['defaultHiddenLayers'] = 2;
+                                $dataset['defaultHiddenLayersNeurons'] = 2;
                                 break;
                         }
                         break;
@@ -183,9 +189,6 @@ class PerceptronController extends Controller
         $sessionId = $request->input('session_id', session()->getId());
         $trainingId = $request->input('training_id');
 
-        // Remove the jobs for the sessionId
-        DB::table('jobs')->where('payload', 'like', '%s:9:\"sessionId\";s:40:\"'.$sessionId.'\";%')->delete();
-
         // Zero initialization prevents hidden layers from receiving a gradient.
         if ($perceptronType === 'multilayer' && $weightInitMethod === 'zeros') {
             $synapticWeightsProvider = new RandomSynapticWeights;

app/Models/NetworksTraining/MonoLayerPerceptronTraining.php

@@ -20,6 +20,7 @@ class MonoLayerPerceptronTraining extends NetworkTraining
     private array $labels;
 
     public ActivationsFunctions $activationFunction = ActivationsFunctions::LINEAR;
+
     public ?ActivationsFunctions $presentationLayerActivationFunction = ActivationsFunctions::STEP;
 
     private float $epochError;
@@ -62,7 +63,7 @@ class MonoLayerPerceptronTraining extends NetworkTraining
             while ($nextRow = $this->datasetReader->getNextLine()) {
                 $inputsForCurrentEpoch[] = $nextRow;
                 $inputs = array_slice($nextRow, 0, -1);
-                $correctOutput = (int) end($nextRow);
+                $correctOutput = (float) end($nextRow);
 
                 $iterationError = $this->iterationFunction($inputs, $correctOutput);
 
@@ -108,7 +109,7 @@ class MonoLayerPerceptronTraining extends NetworkTraining
         return $condition;
     }
 
-    private function iterationFunction(array $inputs, int $correctOutput): array
+    private function iterationFunction(array $inputs, float $correctOutput): array
     {
         $outputs = $this->network->test($inputs);
         $desiredOutput = $this->getDesiredOutputFromCorrectOutput($correctOutput);
@@ -137,10 +138,10 @@ class MonoLayerPerceptronTraining extends NetworkTraining
         return [$updatedWeights];
     }
 
-    private function getDesiredOutputFromCorrectOutput(int $correctOutput): array
+    private function getDesiredOutputFromCorrectOutput(float $correctOutput): array
     {
         $desiredOutput = array_fill(0, count($this->labels), -1);
-        $labelIndex = Arr::first(array_keys($this->labels), fn($key) => $this->labels[$key] == $correctOutput);
+        $labelIndex = Arr::first(array_keys($this->labels), fn ($key) => $this->labels[$key] == $correctOutput);
         if ($labelIndex !== null) {
             $desiredOutput[$labelIndex] = 1;
         }

app/Models/Perceptrons/InputNeuron.php

@@ -4,6 +4,8 @@ namespace App\Models\Perceptrons;
 
 class InputNeuron extends Perceptron
 {
+    private float $input = 0.0;
+
     public function __construct(
     ) {
         parent::__construct([]);

app/Services/IterationEventBuffer/PerceptronIterationEventBuffer.php

@@ -8,6 +8,8 @@ class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer
 {
     private array $data = [];
 
+    private ?float $lastBroadcastAt = null;
+
     public function __construct(
         private string $sessionId,
         private string $trainingId,
@@ -19,7 +21,9 @@ class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer
             return;
         }
 
+        $this->waitForBroadcastInterval();
         event(new PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId));
+        $this->lastBroadcastAt = microtime(true);
         $this->data = [];
     }
 
@@ -48,8 +52,22 @@ class PerceptronIterationEventBuffer implements IPerceptronIterationEventBuffer
     private function payloadExceedsLimit(): bool
     {
         return strlen(json_encode([
-            'iterations' => $this->data,
+            'iterations' => PerceptronTrainingIteration::normalizeForJson($this->data),
             'trainingId' => $this->trainingId,
         ], JSON_THROW_ON_ERROR)) > config('broadcasting.broadcast_max_payload_size');
     }
+
+    private function waitForBroadcastInterval(): void
+    {
+        if ($this->lastBroadcastAt === null) {
+            return;
+        }
+
+        $minimumInterval = config('perceptron.broadcast_minimum_interval_ms') / 1000;
+        $remainingInterval = $minimumInterval - (microtime(true) - $this->lastBroadcastAt);
+
+        if ($remainingInterval > 0) {
+            usleep((int) ceil($remainingInterval * 1_000_000));
+        }
+    }
 }

app/Services/IterationEventBuffer/PerceptronLimitedEpochEventBuffer.php

@@ -12,6 +12,8 @@ class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuff
 
     private bool $shouldBroadcastEpoch = false;
 
+    private ?float $lastBroadcastAt = null;
+
     public function __construct(
         private string $sessionId,
         private string $trainingId,
@@ -24,7 +26,9 @@ class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuff
             return;
         }
 
+        $this->waitForBroadcastInterval();
         event(new PerceptronTrainingIteration($this->data, $this->sessionId, $this->trainingId));
+        $this->lastBroadcastAt = microtime(true);
         $this->data = [];
     }
 
@@ -57,8 +61,22 @@ class PerceptronLimitedEpochEventBuffer implements IPerceptronIterationEventBuff
     private function payloadExceedsLimit(): bool
     {
         return strlen(json_encode([
-            'iterations' => $this->data,
+            'iterations' => PerceptronTrainingIteration::normalizeForJson($this->data),
             'trainingId' => $this->trainingId,
         ], JSON_THROW_ON_ERROR)) > config('broadcasting.broadcast_max_payload_size');
     }
+
+    private function waitForBroadcastInterval(): void
+    {
+        if ($this->lastBroadcastAt === null) {
+            return;
+        }
+
+        $minimumInterval = config('perceptron.broadcast_minimum_interval_ms') / 1000;
+        $remainingInterval = $minimumInterval - (microtime(true) - $this->lastBroadcastAt);
+
+        if ($remainingInterval > 0) {
+            usleep((int) ceil($remainingInterval * 1_000_000));
+        }
+    }
 }

config/perceptron.php

@@ -10,7 +10,7 @@ return [
     'limited_broadcast_iterations' => 100,
 
     /**
-     * How much broadcasts is sent when in limmited broadcast mode
+     * How much broadcasts is sent when in limited broadcast mode
      */
     'limited_broadcast_number' => 100,
 
@@ -19,6 +19,11 @@ return [
      */
     'broadcast_iteration_size' => 75,
 
+    /**
+     * Minimum time between training progress broadcasts, in milliseconds.
+     */
+    'broadcast_minimum_interval_ms' => 150,
+
     /**
      * Maximum number of weights for which all iteration weights are broadcast
      * and displayed in the iteration table.

resources/js/components/IterationTable.vue

@@ -1,5 +1,6 @@
 <script setup lang="ts">
-import { computed, ComputedRef } from 'vue';
+import { computed } from 'vue';
+import type { ComputedRef } from 'vue';
 import type { Iteration } from '@/types/perceptron';
 
 const props = defineProps<{
@@ -13,7 +14,9 @@ const props = defineProps<{
 const allWeightPerIteration: ComputedRef<number[][]> = computed(() => {
     return props.iterations.map((iteration) => {
         // We flatten the weights
-        return iteration.weights.flat(2);
+        return iteration.weights
+            .flat(2)
+            .filter((weight): weight is number => weight !== null && Number.isFinite(weight));
     });
 });
 
@@ -61,10 +64,10 @@ const rowBgDark = computed(() => {
                     v-for="(weight, weightIndex) in allWeightPerIteration[index]"
                     v-bind:key="weightIndex"
                 >
-                    {{ weight.toFixed(2) }}
+                    {{ Number.isFinite(weight) ? weight.toFixed(2) : 'N/A' }}
                 </td>
             </template>
-            <td>{{ iteration.error.toFixed(2) }}</td>
+            <td>{{ iteration.error === null ? 'N/A' : iteration.error.toFixed(2) }}</td>
         </tr>
 
         <tr

resources/js/components/PerceptronIterationsErrorsGraph.vue

@@ -28,6 +28,8 @@ const datasets = computed<ErrorDataset[]>(() => {
     const exampleCountPerEpoch: Record<number, number> = {};
 
     props.iterations.forEach((iteration) => {
+        const error = iteration.error ?? 0;
+
         if (!epochErrorOnly.value) {
             const exampleLabel = `Exemple ${iteration.exampleIndex}`;
             let dataset = datasets.find((d) => d.label === exampleLabel);
@@ -45,8 +47,8 @@ const datasets = computed<ErrorDataset[]>(() => {
             }
             dataset.data.push(
                 props.isRegression
-                    ? Math.abs(iteration.error)
-                    : iteration.error,
+                    ? Math.abs(error)
+                    : error,
             );
         }
 
@@ -55,7 +57,7 @@ const datasets = computed<ErrorDataset[]>(() => {
         // Epoch error
         epochAverageError[iteration.epoch] =
             (epochAverageError[iteration.epoch] || 0) +
-            iteration.error ** 2 / 2;
+            error ** 2 / 2;
     });
 
     // Sort dataset by label (Exemple 0, Exemple 1, ...)

resources/js/types/perceptron.ts

@@ -1,8 +1,8 @@
 export type Iteration = {
     epoch: number;
     exampleIndex: number;
-    weights: number[][][];
-    error: number;
+    weights: (number | null)[][][];
+    error: number | null;
 };
 
 export type Dataset = {

tests/Unit/Services/IterationEventBufferTest.php

@@ -38,4 +38,22 @@ class IterationEventBufferTest extends TestCase
                 && $event->iterations[0]['epoch'] === 1;
         });
     }
+
+    public function test_non_finite_values_are_normalized_before_broadcasting(): void
+    {
+        $event = new PerceptronTrainingIteration([
+            [
+                'epoch' => 1,
+                'exampleIndex' => 0,
+                'error' => NAN,
+                'weights' => [[[INF]]],
+            ],
+        ], 'session', 'training');
+
+        $payload = $event->broadcastWith();
+
+        $this->assertNull($payload['iterations'][0]['error']);
+        $this->assertNull($payload['iterations'][0]['weights'][0][0][0]);
+        $this->assertJson(json_encode($payload, JSON_THROW_ON_ERROR));
+    }
 }