Multilayer neuron network

app/Http/Controllers/PerceptronController.php

@@ -6,6 +6,7 @@ use App\Events\PerceptronInitialization;
 use App\Models\NetworksTraining\ADALINEPerceptronTraining;
 use App\Models\NetworksTraining\GradientDescentPerceptronTraining;
 use App\Models\NetworksTraining\MonoLayerPerceptronTraining;
+use App\Models\NetworksTraining\MultiLayerPerceptronTraining;
 use App\Models\NetworksTraining\SimpleBinaryPerceptronTraining;
 use App\Services\DatasetReader\IDataSetReader;
 use App\Services\DatasetReader\LinearOrderDataSetReader;
@@ -13,12 +14,11 @@ use App\Services\DatasetReader\RandomOrderDataSetReader;
 use App\Services\IterationEventBuffer\PerceptronIterationEventBuffer;
 use App\Services\IterationEventBuffer\PerceptronLimitedEpochEventBuffer;
 use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
+use App\Services\SynapticWeightsProvider\RandomSynapticWeights;
 use App\Services\SynapticWeightsProvider\ZeroSynapticWeights;
-use Illuminate\Contracts\Queue\Job;
 use Illuminate\Http\Request;
 use Illuminate\Support\Facades\DB;
-use Symfony\Contracts\EventDispatcher\Event;
-use Tests\Services\IterationEventBuffer\DullIterationEventBuffer;
+use Illuminate\Support\Facades\Validator;
 
 class PerceptronController extends Controller
 {
@@ -38,9 +38,16 @@ class PerceptronController extends Controller
                 $learningRate = 0.015;
                 $maxIterations = 150;
                 break;
-            case 'gradientdescent' || 'adaline':
+            case 'gradientdescent':
+            case 'adaline':
                 $learningRate = 0.00003;
                 break;
+            case 'monolayer':
+                $learningRate = 0.03;
+                break;
+            case 'multilayer':
+                $learningRate = 0.8;
+                break;
         }
 
         return inertia('PerceptronViewer', [
@@ -50,6 +57,7 @@ class PerceptronController extends Controller
             'minError' => $minError,
             'learningRate' => $learningRate,
             'maxIterations' => $maxIterations,
+            'maxDisplayedWeights' => config('perceptron.max_displayed_weights'),
         ]);
     }
 
@@ -106,7 +114,8 @@ class PerceptronController extends Controller
                             case 'simple':
                                 $dataset['defaultLearningRate'] = 0.015;
                                 break;
-                            case 'gradientdescent' || 'adaline':
+                            case 'gradientdescent':
+                            case 'adaline':
                                 $dataset['defaultLearningRate'] = 0.001;
                                 break;
                         }
@@ -114,6 +123,15 @@ class PerceptronController extends Controller
                     case 'table_2_11':
                         $dataset['defaultMinError'] = 0.02;
                         break;
+                    case 'table_4_12':
+                        switch ($perceptronType) {
+                            case 'multilayer':
+                                $dataset['defaultLearningRate'] = 0.8;
+                                $dataset['defaultMinError'] = 0.001;
+                                $dataset['defaultMaxIterations'] = 2000;
+                                break;
+                        }
+                        break;
                 }
                 $datasets[] = $dataset;
             }
@@ -133,7 +151,19 @@ class PerceptronController extends Controller
     {
         $startTime = microtime(true);
 
+        // Verifications
+        $validator = Validator::make($request->all(), config('perceptron.run_inputs_validation'));
+
+        if ($validator->fails()) {
+            return response()->json([
+                'message' => 'Invalid input parameters',
+                'errors' => $validator->errors(),
+            ], 400);
+        }
+
         $perceptronType = $request->input('type');
+        $hiddenLayers = $request->input('hidden_layers', 2);
+        $hiddenLayersNeurons = $request->input('hidden_layers_neurons', 3);
         $minError = $request->input('min_error', 0.01);
         $weightInitMethod = $request->input('weight_init_method', 'random');
         $dataSet = $request->input('dataset');
@@ -145,7 +175,11 @@ class PerceptronController extends Controller
         // Remove the jobs for the sessionId
         DB::table('jobs')->where('payload', 'like', '%s:9:\"sessionId\";s:40:\"'. $sessionId .'\";%')->delete();
 
-        if ($weightInitMethod === 'zeros') {
+        // Zero initialization prevents hidden layers from receiving a gradient.
+        if ($perceptronType === 'multilayer' && $weightInitMethod === 'zeros') {
+            $synapticWeightsProvider = new RandomSynapticWeights;
+        }
+        else if ($weightInitMethod === 'zeros') {
             $synapticWeightsProvider = new ZeroSynapticWeights;
         }
 
@@ -162,6 +196,7 @@ class PerceptronController extends Controller
             'gradientdescent' => new GradientDescentPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
             'adaline' => new ADALINEPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
             'monolayer' => new MonoLayerPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
+            'multilayer' => new MultiLayerPerceptronTraining($datasetReader, $learningRate, $maxEpochs, $hiddenLayers, $hiddenLayersNeurons, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
             default => null,
         };